title: Smart Supervisory Control for Optimized Power Management System of hybrid Micro-Grid

text: Micro grid have been accepted concept widely for the better interconnection of distributed generators (DGs). Corresponding to the conventional power system ac microgrid have been proposed, particularly increasing the use of renewable energy sources generate dc power which is need a dc link for the purpose of grid connection and as a result of increasing modern dc loads. Dc micro grid has been recently emerged for their benefits in terms of efficiency cost and no of conversion stages.. During the islanding operation of the hybrid ac/dc microgrid, the IC is intended to take the role of supplier to one microgrid and at the same time acts as a load to the other microgrid and the power management system should be able to share the power demand between the exiting ac and dc sources in both the microgrids. This paper considers the power flow control and management issues amongst multiple sources distributed throughout both ac and dc microgrids. The paper proposes a decentralized power sharing method in order to eliminate the need for communication between DGs or microgrids. The performance of the proposed power control strategy is validated for different operating conditions, using MATLAB/SIMULATION environment. Keyword: Mixed integer linear programming, hybrid ac/dc microgrid, interlinking ac/dc converter, power management. Introduction Nowadays, electrical grids are more distributed, intelligent and flexible. They are not only driven by the growing environmental concern and the energy security, but also by the ornamenting of the electricity market. Over 100 years the three phase AC power systems existing due to its different operating voltage levels and over long distance. Newly more renewable power conversion systems are connected in ac distribution systems due to environmental issues caused by fueled power plants. Nowadays, more DC loads like LED and Electric vehicles are connected to AC power systems to save energy and to reduce the pollution caused by the fossil fueled power plants. The rising rate of consumption of nuclear and fossil fuels, and the community demand for reducing pollutant emission in electricity generation field are the most significant reasons for worldwide attention to the renewable energy resources. In generally micro grids are defined as a cluster of loads, distributed energy sources, and storage devices. It is accepted that for excellent operation of the micro-grid, a PMS is essential to manage power flow in the micro-grid. It is noteworthy that the power flow means the determination of the output of the electricity generation facilities to meet the demanded power. There are two general approaches to develop PMSs: 1) rule based and 2) optimization-based. In contrast, the latter approach supervises power flow in a micro-grid by minimizing a cost function, which is derived based on performance expectations of the micro-grid, and considering some operational constraints. Recently, a robust PMS for a grid-connected system is presented in [1], in which uncertainty in the generation prediction is considered in the design procedure. On the other hand, hybrid ac/dc micro-grid is a new concept, which decouples dc sources with dc loads and ac sources with ac loads, while power is exchanged between both sides using a bidirectional converter/inverter [2], [3]. In [4]-[6], a droop-based controller is introduced to manage power sharing between the ac and dc micro-grids. In this paper, the ac and dc micro-grids are treated as two separate entities with individual droop representations, where the information from these two droop characteristics is merged to decide the amount of power to exchange between the microgrids. In [7], a hybrid ac/dc micro-grid consisting a WG as an ac source and a PV array as a dc source is International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3980-3986 © Research India Publications. http://www.ripublication.com 3981 presented, where a rule-based system is proposed to manage the power flow in the hybrid ac/dcmicro-grid. In [8] and [9], the amount of power which should be exchanged between the micro-grids is determined through arule-based management system with four predefined operating modes. Finally, a rulebased PMS for a hybrid ac/dc microgrid is presented in [10], where more distinct operation modes are considered. Hence, microgrids [12] are becoming a reality to cope with a new scenario in which renewable energy, distributed generation (DG) and distributed energy-storage systems have to be integrated together. This new concept makes the final user not to be a passive element in the grid, but an entity able to generate, storage, control and manage part of the energy that he/she will consume. Besides, a reduction in cost and an increment in reliability and transparency are achieved. The radial transformation of the electrical grid entails deeply challenges not only on the architecture of the power system, but also in the control system. There are many control techniques in the literature based on the droop control method whose aim is to avoid communication between DG units [13][18]. Although this method achieves good reliability and flexibility, it presents several drawbacks [19], [20]: 1) it is not suitable when parallel DG units share nonlinear loads, it must take into account harmonic currents; 2) the output impedance of DG units and the line impedances affect the power sharing accuracy; 3)it is dependent of the load frequency deviations, which implies a phase deviation between DG units and grid/load. To cope with this problem, two additional control loops have been defined in [21] and [22]: Secondary control, which restores the nominal values of the frequency and voltage in the MG; and Tertiary control, which sets the reference of the frequency and voltage in the MG. This paper is organized as follows. Section II gives a brief overview of the typical hybrid ac/dc micro grid modeling In section III gives the overview of renewable power source models and their corresponding converters, where the models of PV and DG as the sources of the ac micro-grid are given in Section III-A, the model of battery as the source of the dc micro-gridis given in Section III-B, and the model of Generator as the source of dc micro grid in section III-C. In Section IV, a PMS to coordinating between the ac and dc micro-grids is proposed. Section IV-Apresents, Grid Connected Mode. In Section IV-B, minimum and maximum charge/discharge power of the battery banks, and minimum allowable power exchange between the ac and dc micro-grids in isolated mode computation are presented. The simulation results obtained with the proposed PMS are also reported in Section V. Finally, Section VI summarizes the main outcome of this paper. Microgrid Modelling MicroGrid design begins by understanding the load profile needed to be served by the system. Often, the load is adjusted in the system design by applying energy efficiency measures such as demand response controls, equipment upgrades, and other system adjustments to reduce the overall generation needs. What does not typically happen, however, is a closer look at those loads to determine how much can be served natively by DC power sources. This is a fundamental flaw in optimizing the use of renewable energy resources that supply DC electricity-like photovoltaic, battery, and fuel cell technologies. Instead, the entire load is considered and the resulting power generation requirements are sized accordingly. With some additional thought and separation of the DC loads from the AC loads, the amount of renewable generation required can be dramatically reduced to only supply dc power for the dc equipment in the building. In other words, by designing separate DC and AC networks, a building MicroGrid could be developed that minimizes power losses due to transformation or conversion by simply supplying the equipment with the native electricity it requires. So, instead of using 50 rooftop solar panels to supply a building, you might only need 10, driving down system costs and increasing efficiencies by utilizing the best type of power for each piece of equipment being served. The conceptual architecture described in this article proposes a building MicroGrid using a hybrid approach of DC renewable generation resources for DC equipment and the utility grid for AC equipment. An “energy router” acts as the hub that manages electricity across the AC and DC buses and minimizes the need for lossy DC-AC and AC-DC electricity transformations. Figure 2.1: Architecture of Microgrid Figure 2. 1, above, shows the overall building level DC MicroGrid architecture. Because of the power losses incurred with DC power over long distances, this concept is best used in a building level MicroGrid with short runs for the circuits on the system. In reality, calling it a hybrid MicroGrid is probably more apropos, but for the purposes of this discussion, we’ll use the DC MicroGrid terminology to keep it short. The Green Lines represent the DC part of the system, while the Orange Lines represent the AC portion. In typical office buildings, the amount of DC power equipment ranges from 20-30% of the overall load, with those numbers steadily rising as LED lights, computers, more electronics, and electric International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3980-3986 © Research India Publications. http://www.ripublication.com 3982 vehicles enter the equation. The architectural rendering in Figure 1 may not be complete as some DC equipment will require DC-DC transformations from the DC network’s supply voltage, but these transformations are less lossy than AC-DC transformations and also produce much less heat. DC Network The building’s DC electricity generation needs can be met through renewable energy technologies:  Solar (Photovoltaic)


title: BDO-SD: An efficient scheme for big data outsourcing with secure deduplication

text: In the big data era, duplicated copies of data may be generated by various smart devices. Although convergent encryption has been extensively adopted for secure deduplication, it is still very challenging to efficiently and reliably manage the convergent keys and support keyword search over encrypted data. This paper addresses this problem by presenting an efficient scheme for big data outsourcing with secure deduplication, named BDO-SD. Specifically, with the convergent encryption technique, data owners can outsource their data to the cloud server with data deduplication; with the idea of public key encryption and keywords search, a data user can query encrypted data while preserving its privacy. Security analysis demonstrates that our proposed BDO-SD scheme can achieve the data confidentiality, query privacy and key security. Simulation results show that compared with other schemes, our scheme can achieve better efficiency than the existing data deduplication schemes.


title: Protocol Oblivious Forwarding (POF): Software-Defined Networking with Enhanced Programmability

text: Software-defined networking separates the control and forwarding planes of a network to make it more programmable and application- aware. As one of the initial implementations of SDN, OpenFlow abstracts a forwarding device as a flow table and realizes flow processing by applying the "match-and-act" principle. However, the protocol-dependent nature of OpenFlow still limits the programmability of the forwarding plane. Hence, in this article, we discuss how to leverage protocol-oblivious forwarding (POF) to further enhance the network programmability such that the forwarding plane becomes protocol-independent and can be dynamically reprogrammed to support new protocol stacks seamlessly. We first review the development of OpenFlow and explain the motivations for introducing POF. Then we explain the working principle of POF, discuss our efforts on realizing the POF development ecosystem, and show our implementation of POF-based source routing as a novel use case. Finally, we elaborate on the first WAN-based POF network testbed that includes POF switches located in two cities in China.


title: Digital Game-Based Learning in high school Computer Science education: Impact on educational effectiveness and student motivation

text: 0360-1315/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.compedu.2008.06.004 * Tel.: +3


title: The 'digital natives' debate: A critical review of the evidence

text: The idea that a new generation of students is entering the education system has excited recent attention among educators and education commentators. Termed ‘digital natives’ or the ‘Net generation’, these young people are said to have been immersed in technology all their lives, imbuing them with sophisticated technical skills and learning preferences for which traditional education is unprepared. Grand claims are being made about the nature of this generational change and about the urgent necessity for educational reform in response. A sense of impending crisis pervades this debate. However, the actual situation is far from clear. In this paper, the authors draw on the fields of education and sociology to analyse the digital natives debate. The paper presents and questions the main claims made about digital natives and analyses the nature of the debate itself. We argue that rather than being empirically and theoretically informed, the debate can be likened to an academic form of a ‘moral panic’. We propose that a more measured and disinterested approach is now required to investigate ‘digital natives’ and their implications for education. The one thing that does not change is that at any and every time it appears that there have been ‘great changes’. Marcel Proust, Within a Budding Grove


title: Forecasting emerging technologies : Use of bibliometrics and patent analysis

text: It is rather difficult to forecast emerging technologies as there is no historical data available. In such cases, the use of bibliometrics and patent analysis have provided useful data. This paper presents the forecasts for three emerging technology areas by integrating the use of bibliometrics and patent analysis into well-known technology forecasting tools such as scenario planning, growth curves and analogies. System dynamics is also used to be able to model the dynamic ecosystem of the technologies and their diffusion. Technologies being forecasted are fuel cell, food safety and optical storage technologies. Results from these three applications help us to validate the proposed methods as appropriate tools to forecast emerging technologies. © 2006 Elsevier Inc. All rights reserved.


title: Food-related illness and death in the United States.

text: Letters Letters Letters Letters Letters correctly identified E. faecium and E. faecalis to the species level, most (4 of 5) did not correctly identify E. gallinarum (three misidentified it as E. casseliflavus and one as E. faecalis). The results of this study are consistent with those of previous studies in the United States (4,5), South America (6), Spain (7), and Mexico (8). Although in countries like Chile, disk diffusion is practical and reliable for most susceptibility testing, detecting low-level vanco-mycin resistance in enterocci is difficult without supplementary testing. In Chile, as in other countries, strategies should be implemented to improve detection of these strains, including improvement of phenotypical and genotypical methods for VRE detection and species identification. Documentation of proficiency in detecting VRE is important for improving laboratory performance, detecting clinical isolates, and accurate and reliable reporting to local, national, and international surveillance systems. A, Febre N, et al. Epidemiologic analysis for acquisition of vancomycin-resistant enterococcus (VRE) in an intensive care unit in Brazil. Altschuler M, et al. Study to determine the ability of clinical laboratories to detect antimicrobial-resistant To the Editor: Dr. Mead and colleagues should be commended for attempting to estimate the prevalence of foodborne disease in the United States (1). Their study provides more complete estimates than previous studies in terms of the number of foodborne pathogens included; for example, it includes the first realistic estimate of the number of cases of disease due to Norwalk-like caliciviruses. However, the publication of these estimates raises some important issues. Even though " accurate estimates of disease burden are the foundation of sound public health policy " (2), most of these estimates (in particular, the assumption that unknown agents are transmitted by food in the same proportion as known agents) were derived from assumptions rather than data. Known foodborne agents clearly cannot account for most gastrointestinal illnesses (1). However, illnesses from unknown agents may be as likely to have the transmission characteristics of rotavirus (1% foodborne) or Cryptosporidium (10% foodborne) as those of the Norwalk-like viruses (40% foodborne). Furthermore , it was assumed that detecting outbreaks or cases of toxin-mediated illnesses (e.g., due to Bacillus cereus, Staphylococcus aureus, or Clostridium perfringens) follows the model of Salmonella. In the authors' entire list of known foodborne agents, data are presented for cases identified both from outbreaks and active surveillance for only three agents: Salmonella, Shigella, and Campylobacter. Salmonella is clearly the most …


title: What makes things fun to learn? heuristics for designing instructional computer games

text:
In this paper, I will describe my intuitions about what makes computer games fun. More detailed descriptions of the experiments and the theory on which this paper is based are given by Malone (1980a, 1980b). My primary goal here is to provide a set of heuristics or guidelines for designers of instructional computer games. I have articulated and organized common sense principles to spark the creativity of instructional designers (see Banet, 1979, for an unstructured list of similar principles). To demonstrate the usefulness of these principles, I have included several applications to actual or proposed instructional games. Throughout the paper I emphasize games with educational uses, but I focus on what makes the games fun, not on what makes them educational.
 Though I will not emphasize the point in this paper, these same ideas can be applied to other educational environments and life situations. In a sense, the categories I will describe constitute a general taxonomy of intrinsic motivation—of what makes an activity fun or rewarding for its own sake rather than for the sake of some external reward (See Lepper and Greene, 1979).
 I think the essential characteristics of good computer games and other intrinsically enjoyable situations can be organized into three categories: challenge, fantasy, and curiosity.


title: Code and tell: assessing young children's learning of computational thinking using peer video interviews with ScratchJr

text: In this paper, we present a novel technique for assessing the learning of computational thinking in the early childhood classroom. Students in three second grade classrooms learned foundational computational thinking concepts using ScratchJr and applied what they learned to creating animated collages, stories, and games. They then conducted artifact-based video interviews with each other in pairs using their iPad cameras. As discussed in the results, this technique can show a broad range of what young children learn about computational thinking in classroom interventions using ScratchJr than more traditional assessment techniques. It simultaneously provides a developmentally appropriate educational activity (i.e. peer interviews) for early childhood classrooms.


title: Tadalafil therapy for pulmonary arterial hypertension.

text:
BACKGROUND
Treatment options for pulmonary arterial hypertension target the prostacyclin, endothelin, or nitric oxide pathways. Tadalafil, a phosphodiesterase type-5 inhibitor, increases cGMP, the final mediator in the nitric oxide pathway.

METHODS AND RESULTS
In this 16-week, double-blind, placebo-controlled study, 405 patients with pulmonary arterial hypertension (idiopathic or associated), either treatment-naive or on background therapy with the endothelin receptor antagonist bosentan, were randomized to placebo or tadalafil 2.5, 10, 20, or 40 mg orally once daily. The primary end point was the change from baseline to week 16 in the distance walked in 6 minutes. Changes in World Health Organization functional class, clinical worsening, and health-related quality of life were also assessed. Patients completing the 16-week study could enter a long-term extension study. Tadalafil increased the distance walked in 6 minutes in a dose-dependent manner; only the 40-mg dose met the prespecified level of statistical significance (P<0.01). Overall, the mean placebo-corrected treatment effect was 33 m (95% confidence interval, 15 to 50 m). In the bosentan-naive group, the treatment effect was 44 m (95% confidence interval, 20 to 69 m) compared with 23 m (95% confidence interval, -2 to 48 m) in patients on background bosentan therapy. Tadalafil 40 mg improved the time to clinical worsening (P=0.041), incidence of clinical worsening (68% relative risk reduction; P=0.038), and health-related quality of life. The changes in World Health Organization functional class were not statistically significant. The most common treatment-related adverse events reported with tadalafil were headache, myalgia, and flushing.

CONCLUSIONS
In patients with pulmonary arterial hypertension, tadalafil 40 mg was well tolerated and improved exercise capacity and quality of life measures and reduced clinical worsening.


title: Classification of rice grain varieties using two artificial neural networks (MLP and neuro-fuzzy).

text: Artificial neural networks (ANNs) have many applications in various scientific areas such as identification, prediction and image processing. This research was done at the Islamic Azad University, Shahr-e-Rey Branch, during 2011 for classification of 5 main rice grain varieties grown in different environments in Iran. Classification was made in terms of 24 color features, 11 morphological features and 4 shape factors that were extracted from color images of each grain of rice. The rice grains were then classified according to variety by multi layer perceptron (MLP) and neuro-fuzzy neural networks. The topological structure of the MLP model contained 39 neurons in the input layer, 5 neurons (Khazar, Gharib, Ghasrdashti, Gerdeh and Mohammadi) in the output layer and two hidden layers; neuro-fuzzy classifier applied the same structure in input and output layers with 60 rules. Average accuracy amounts for classification of rice grain varieties computed 99.46% and 99.73% by MLP and neuro-fuzzy classifiers alternatively. The accuracy of MLP and neuro-fuzzy networks changed after feature selections were 98.40% and 99.73 % alternatively.


title: Skin force sensor using piezoresistive PEDOT:PSS with arabitol on flexible PDMS

text: In this paper, a flexible conducting polymer based force sensor array has been developed. A conducting polymer, namely poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) with additive arabitol, was utilized as the piezoresistive layer on a flexible polydimethylsiloxane (PDMS) substrate owing to its high conductivity and stretchability. A simplified strain sensor has been developed to demonstrate the properties of the arabitol-PEDOT:PSS. Suitable curing conditions and arabitol concentration have been established with design of experiment. The arabitol-PEDOT:PSS can be stretched up to 20% and it shows a significant gauge factor of 11.5. A flexible interdigital force sensor array has been developed to demonstrate the effectiveness of arabitol-PEDOT:PSS on PDMS as a force sensor.


title: Electrostatic adhesive brakes for high spatial resolution refreshable 2.5D tactile shape displays

text: We investigate the mechanism, design, modeling and fabrication of a scalable high resolution, low cost and lightweight refreshable 2.5D tactile pin array controlled by electrostatic adhesive brakes. By replacing linear actuators in motorized shape displays with a high voltage solid-state circuit that can be fabricated with printable electronics techniques, we can decrease the cost and complexity of such devices. Electrostatic adhesive brakes, made by patterning interdigital electrodes on high dielectric constant thin films, are used to hold metal pins' positions and provide contact force to the user's fingertip. We present designs of two high resolution brake modules which are 1.7 mm pitch with 0.8 mm width pins and 4 mm pitch with 1.58 mm width pins with a maximum measured dynamic loading force of 76.3 gf and static loading force of 28 gf on an individual pin (for the later size). A small demonstration of 4 × 2 pin array with a 4 mm pitch size within a row and 2.5 mm pitch size between the rows, using 1.58 mm width pins, was created. We also characterized the refresh time to be 37.5 ms for each brake, which enables refreshable actuated pin displays.


Fuzzy Passive-Aggressive classification: A robust and efficient algorithm for online classification problems


title: Electric field effect in atomically thin carbon films.

text: We describe monocrystalline graphitic films, which are a few atoms thick but are nonetheless stable under ambient conditions, metallic, and of remarkably high quality. The films are found to be a two-dimensional semimetal with a tiny overlap between valence and conductance bands, and they exhibit a strong ambipolar electric field effect such that electrons and holes in concentrations up to 10(13) per square centimeter and with room-temperature mobilities of approximately 10,000 square centimeters per volt-second can be induced by applying gate voltage.


title: Quality Traits of “Cannabidiol Oils”: Cannabinoids Content, Terpene Fingerprint and Oxidation Stability of European Commercially Available Preparations

text: Cannabidiol (CBD)-based oil preparations are becoming extremely popular, as CBD has been shown to have beneficial effects on human health. CBD-based oil preparations are not unambiguously regulated under the European legislation, as CBD is not considered as a controlled substance. This means that companies can produce and distribute CBD products derived from non-psychoactive hemp varieties, providing an easy access to this extremely advantageous cannabinoid. This leaves consumers with no legal quality guarantees. The objective of this project was to assess the quality of 14 CBD oils commercially available in European countries. An in-depth chemical profiling of cannabinoids, terpenes and oxidation products was conducted by means of GC-MS and HPLC-Q-Exactive-Orbitrap-MS in order to improve knowledge regarding the characteristics of CBD oils. Nine out of the 14 samples studied had concentrations that differed notably from the declared amount, while the remaining five preserved CBD within optimal limits. Our results highlighted a wide variability in cannabinoids profile that justifies the need for strict and standardized regulations. In addition, the terpenes fingerprint may serve as an indicator of the quality of hemp varieties, while the lipid oxidation products profile could contribute in evaluation of the stability of the oil used as milieu for CBD rich extracts.


title: Hybrid BFOA-PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems

text: In the Bacteria Foraging Optimization Algorithm (BFAO), the chemotactic process is randomly set, imposing that the bacteria swarm together and keep a safe distance from each other. In hybrid bacteria foraging optimization algorithm and particle swarm optimization (hBFOA-PSO) algorithm the principle of swarming is introduced in the framework of BFAO. The hBFOA-PSO algorithm is based on the adjustment of each bacterium position according to the neighborhood environment. In this paper, the effectiveness of the hBFOA-PSO algorithm has been tested for Automatic Generation Control (AGC) of an interconnected power system. A widely used linear model of two area non-reheat thermal system equipped with Proportional-Integral (PI) controller is considered initially for the design and analysis purpose. At first, a conventional Integral Time multiply Absolute Error (ITAE) based objective function is considered and the performance of hBFOA-PSO algorithm is compared with PSO, BFOA and GA. Further a modified objective function using ITAE, damping ratio of dominant eigenvalues and settling time with appropriate weight coefficients is proposed to increase the performance of the controller. Further, robustness analysis is carried out by varying the operating load condition and time constants of speed governor, turbine, tieline power in the range of +50% to -50% as well as size and position of step load perturbation to demonstrate the robustness of the proposed hBFOA-PSO optimized PI controller. The proposed approach is also extended to a nonlinear power system model by considering the effect of governor dead band non-linearity and the superiority of the proposed approach is shown by comparing the results of Craziness based Particle Swarm Optimization (CRAZYPSO) approach for the identical interconnected power system. Finally, the study is extended to a three area system considering both thermal and hydro units with different PI coefficients and comparison between ANFIS and proposed approach has been provided.


title: miRNAs and apoptosis: RNAs to die for

text: MicroRNAs (miRNAs) are small non-coding RNAs of about 18–24 nucleotides in length that negatively regulate gene expression. Discovered only recently, it has become clear that they are involved in many biological processes such as developmental timing, differentiation and cell death. Data that connect miRNAs to various kinds of diseases, particularly cancer, are accumulating. miRNAs can influence cancer development in many ways, including the regulation of cell proliferation, cell transformation, and cell death. In this review, we focus on miRNAs that have been shown to play a role in the regulation of apoptosis. We first describe in detail how Drosophila has been utilized as a model organism to connect several miRNAs with the cell death machinery. We discuss the genetic approaches that led to the identification of those miRNAs and subsequent work that helped to establish their function. In the second part of the review article, we focus on the involvement of miRNAs in apoptosis regulation in mammals. Intriguingly, many of the miRNAs that regulate apoptosis have been shown to affect cancer development. In the end, we discuss a virally encoded miRNA that influences the cell death response in the mammalian host cell. In summary, the data gathered over the recent years clearly show the potential and important role of miRNAs to regulate apoptosis at various levels and in several organisms.


title: DOES THE BALANCED SCORECARD WORK : AN EMPIRICAL INVESTIGATION Professor

text: Commentators suggest that between 30 and 60% of large US firms have adopted the Balanced Scorecard, first described by Bob Kaplan and David Norton in their seminal Harvard Business Review paper of 1992 (Kaplan and Norton, 1992; Marr et al, 2004). Empirical evidence that explores the performance impact of the balanced scorecard, however, is extremely rare and much that is available is anecdotal at best. This paper reports a study that set out to explore the performance impact of the balanced scorecard by employing a quasi-experimental design. Up to three years worth of financial data were collected from two sister divisions of an electrical wholesale chain based in the UK, one of which had implemented the balanced scorecard and one of which had not. The relative performance improvements of geographically matched pairs of branches were compared to establish what, if any, performance differentials existed between the branches that had implemented the balanced scorecard and those that had not. The key findings of the study are that while the Electrical division – the division that implemented the balanced scorecard – sees improvements in sales and gross profit; similar performance improvements are also observed in the sister division. Hence the performance impact of the balanced scorecard has to be questioned. Clearly further work on this important topic is required in similar settings where natural experiments occur.


title: A flexible architecture integrating monitoring and analytics for managing large-scale data centers

text: To effectively manage large-scale data centers and utility clouds, operators must understand current system and application behaviors. This requires continuous, real-time monitoring along with on-line analysis of the data captured by the monitoring system, i.e., integrated monitoring and analytics -- Monalytics [28]. A key challenge with such integration is to balance the costs incurred and associated delays, against the benefits attained from identifying and reacting to, in a timely fashion, undesirable or non-performing system states. This paper presents a novel, flexible architecture for Monalytics in which such trade-offs are easily made by dynamically constructing software overlays called Distributed Computation Graphs (DCGs) to implement desired analytics functions. The prototype of Monalytics implementing this flexible architecture is evaluated with motivating use cases in small scale data center experiments, and a series of analytical models is used to understand the above trade-offs at large scales. Results show that the approach provides the flexibility needed to meet the demands of autonomic management at large scale with considerably better performance/cost than traditional and brute force solutions.


title: Learning Automata as a Basis for Multi Agent Reinforcement Learning

text: Learning Automata (LA) are adaptive decision making devices suited for operation in unknown environments [12]. Originally they were developed in the area of mathematical psychology and used for modeling observed behavior. In its current form, LA are closely related to Reinforcement Learning (RL) approaches and most popular in the area of engineering. LA combine fast and accurate convergence with low computational complexity, and have been applied to a broad range of modeling and control problems. However, the intuitive, yet analytically tractable concept of learning automata makes them also very suitable as a theoretical framework for Multi agent Reinforcement Learning (MARL). Reinforcement Learning (RL) is already an established and profound theoretical framework for learning in stand-alone or single-agent systems. Yet, extending RL to multi-agent systems (MAS) does not guarantee the same theoretical grounding. As long as the environment an agent is experiencing is Markov, and the agent can experiment sufficiently, RL guarantees convergence to the optimal strategy. In a MAS however, the reinforcement an agent receives, may depend on the actions taken by the other agents acting in the same environment. Hence, the Markov property no longer holds. And as such, guarantees of convergence are lost. In the light of the above problem it is important to fully understand the dynamics of multi-agent reinforcement learning. Although, they are not fully recognized as such, LA are valuable tools for current MARL research. LA are updated strictly on the basis of the response of the environment, and not on the basis of any knowledge regarding other automata, i.e. nor their strategies, nor their feedback. As such LA agents are very simple. Moreover, LA can be treated analytically. Convergence proofs do exist for a variety of settings ranging from a single automaton model acting in a simple stationary random environment to a distributed automata model interacting in a complex environment. In this paper we argue that LA are very interesting building blocks for learning in multi agent systems. The LA can be viewed as policy iterators, who update their action probabilities based on private information only. This is a very attractive property in applications where communication is expensive. LA are in particular appealing in games with stochastic payoffs. Then we move to collections of learning automata, that can independently converge to interesting solution concepts. We study the single stage setting, including the analytical results. Then we generalize to interconnected learning automata, that can deal with multi agent multi-stage problems. We also show how Ant Colony Optimization can be mapped to the interconnected Learning Automata setting. This extended abstract is a summary of an article published earlier [14].


title: A New Approach of copy move Forgery Detection using Rigorous Preprocessing and Feature Extraction

text: these days, advanced pictures are being used in an extensive variety of uses and for numerous reasons. They additionally assume an imperative part in the capacity and exchange of visual data, particularly the mystery ones. With this far reaching utilization of advanced pictures, notwithstanding the expanding number of devices and programming of computerized pictures altering, it has turned out to be anything but difficult to control and change the real data of the picture. In this way, it has turned out to be important to check the credibility and the respectability of the picture by utilizing present day and advanced methods, which add to examination and comprehension of the pictures’ substance, and after that ensure their trustworthiness. There are many sorts of picture imitation, the most critical and prominent sort is called duplicate glue fabrication, which utilizes a similar picture during the time spent falsification. This sort of fraud is utilized for one of two things, first to cover a protest or scene by replicating the region of the picture and gluing it on another zone of a similar picture. In this paper we have presented a new approach of copy move forgery detection. proposed scheme uses Oriented FAST and rotated BRIEF(ORB) alternative of scale invariant feature transform (SIFT) technique which is integrated with modified local contrast modification-contrast limited adaptive histogram equalization(LCM-CLAHE). Experimental results shows that proposed scheme is more promising in terms of false positive rate(FPR) and true positive rate(TPR) compare to state of the art techniques. Keywords— Image Processing, Image Enhancement, Histogram Equalization, SIFT, TPR, FPR, Copy move forgery, ORB


title: An Ontology-based Summarization System for Arabic Documents (OSSAD)

text: With the problem of increased web resources and the huge amount of information available, the necessity of having automatic summarization systems appeared. Since summarization is needed the most in the process of searching for information on the web, where the user aims at a certain domain of interest according to his query, domain-based summaries would serve the best. Despite the existence of plenty of research work in the domain-based summarization in English, there is lack of them in Arabic due to the shortage of existing knowledge bases. In this paper an Ontology-based Summarization System for Arabic Documents, OSSAD, is introduced. Domain knowledge is extracted from an Arabic corpus and represented by topic related concepts/keywords and the lexical relations among them. The user’s query is first expanded by using the Arabic WordNet and then by adding the domain-specific knowledge base to the expansion. For summarization, decision tree algorithm (C4.5) is used, which was trained by a set of features extracted from the original documents. For the testing dataset, Essex Arabic Summaries Corpus (EASC) was used. Recall Oriented Understudy for Gisting Evaluation (ROUGE) was used to compare OSSAD summaries with the human summaries along with other automatic summarization systems, showing that the proposed approach demonstrated promising results.


title: Adult hippocampal neurogenesis is involved in anxiety-related behaviors

text: Adult hippocampal neurogenesis is a unique example of structural plasticity, the functional role of which has been a matter of intense debate. New transgenic models have recently shown that neurogenesis participates in hippocampus-mediated learning. Here, we show that transgenic animals, in which adult hippocampal neurogenesis has been specifically impaired, exhibit a striking increase in anxiety-related behaviors. Our results indicate that neurogenesis plays an important role in the regulation of affective states and could be the target of new treatments for anxiety disorders.


title: A quasi fixed frequency constant on time controlled boost converter

text: Continuous conduction mode (CCM) boost converter is difficult to compensate due to the right half plane (RHP) zero. This paper presents a quasi fixed frequency constant on time (COT) controlled boost converter, it has no loop compensation requirement. With the proposed COT control, pulse frequency modulation (PFM) comes free at light load, which improves the light load efficiency compared with traditional PWM control. A compact on-time generator that controls the operation frequency is proposed. And a current sink based feedback circuit is used to improve the quality of feedback signal.The COT controller is designed with 1.5 mum BCD process. Simulation results demonstrate that the COT boost converter has fast load transient response and quasi fixed frequency operation.


title: Credit decision tool using mobile application data for microfinance in agriculture

text: Smallholder agriculture is vital for food security and poverty reduction. Poor, unbanked smallholder farmers face challenges in obtaining loans for agriculture due to missing financial credit history. Although credit decisions tools with alternatives such as big data from mobile phones currently exist, these are mainly targeted towards consumer credit solutions. There is need for research focused on applying such data to credit decisions in agriculture, considering the unique challenges of the field. This research proposes a credit decision tool using alternative data from a mobile phone application used for reporting agricultural activities. 213 users submitted 41613 reports of farm activity by 11336 farmers over a 5-year period. Users were classified groups based on personal information, association with farmers, and reports. Three methods are applied for analysis: multiple logistic regression, a support vector machine with a linear kernel, and a support vector machine with a radial basis function kernel. Three sets of features, selected with different methods, are used. The results are evaluated by accuracy, and Area Under the Receiver operating curve (AUC). The support vector machine with a radial basis function kernel shows the best performance on the original data set with an Area Under the Receiver operating curve (AUC) value of 0.983. Feasibility of applying each method in agricultural microfinance is considered. Finally, further development of the models using Geographic Information System analysis of geospatial data which affects agricultural productivity, such as soil type and water resources, is suggested to incorporate the ability of the borrower to repay loans from farm activity.


title: A robot's spatial perception communicated via human touch

text: A robot perceives space in order to navigate, map, search and investigate its surroundings. One application area where humans interact with robots is search and rescue. The robot may have unique capabilities such as seeing outside the visible spectrum and being able to navigate in tight and hazardous spaces. In such an operation, the human may also be an effective search agent. Thus, it would be beneficial if the robot’s spatial perception was conveyed to the human via a secondary peripheral modality. We have worked on developing a visual to tactile substitution.device for people who are visually impaired or blind. We propose to use this similar technique to the remote robot in order that it convey its spatial perception to the human operator or co-worker.


title: A Structured Vector Space Model for Word Meaning in Context

text: We address the task of computing vector space representations for the meaning of word occurrences, which can vary widely according to context. This task is a crucial step towards a robust, vector-based compositional account of sentence meaning. We argue that existing models for this task do not take syntactic structure sufficiently into account. We present a novel structured vector space model that addresses these issues by incorporating the selectional preferences for words’ argument positions. This makes it possible to integrate syntax into the computation of word meaning in context. In addition, the model performs at and above the state of the art for modeling the contextual adequacy of paraphrases.


title: Phrase-Based Statistical Machine Translation

text: This paper is based on the work carried out in the framework of the Verbmobil project, which is a limited-domain speech translation task (German-English). In the final evaluation, the statistical approach was found to perform best among five competing approaches. In this paper, we will further investigate the used statistical translation models. A shortcoming of the single-word based model is that it does not take contextual information into account for the translation decisions. We will present a translation model that is based on bilingual phrases to explicitly model the local context. We will show that this model performs better than the single-word based model. We will compare monotone and non-monotone search for this model and we will investigate the benefit of using the sum criterion instead of the maximum approximation.


title: Mining the Web for Bilingual Text

text: STRAND (Resnik, 1998) is a languageindependent system for automatic discovery of text in parallel translation on the World Wide Web. This paper extends the preliminary STRAND results by adding automatic language identification, scaling up by orders of magnitude, and formally evaluating performance. The most recent end-product is an automatically acquired parallel corpus comprising 2491 English-French document pairs, approximately 1.5 million words per language. 1 I n t r o d u c t i o n Text in parallel translation is a valuable resource in natural language processing. Statistical methods in machine translation (e.g. (Brown et al., 1990)) typically rely on large quantities of bilingual text aligned at the document or sentence level, and a number of approaches in the burgeoning field of crosslanguage information retrieval exploit parallel corpora either in place of or in addition to mappings between languages based on information from bilingual dictionaries (Davis and Dunning, 1995; Landauer and Littman, 1990; Hull and Oard, 1997; Oard, 1997). Despite the utility of such data, however, sources of bilingual text are subject to such limitations as licensing restrictions, usage fees, restricted domains or genres, and dated text (such as 1980's Canadian politics); or such sources simply may not exist for * This work was supported by Department of Defense contract MDA90496C1250, DARPA/ITO Contract N66001-97-C-8540, and a research grant from Sun Microsystems Laboratories. The author gratefully acknowledges the comments of the anonymous reviewers, helpful discussions with Dan Melamed and Doug Oard, and the assistance of Jeff Allen in the French-English experimental evaluation. language pairs of interest. Although the majority of Web content is in English, it also shows great promise as a source of multilingual content. Using figures from the Babel survey of multilinguality on the Web (h tZp : / /www. i s o c . o r g / ) , it is possible to estimate that as of June, 1997, there were on the order of 63000 primarily non-English Web servers, ranging over 14 languages. Moreover, a followup investigation of the non-English servers suggests that nearly a third contain some useful cross-language data, such as parallel English on the page or links to parallel English pages the follow-up also found pages in five languages not identified by the Babel study (Catalan, Chinese, Hungarian, Icelandic, and Arabic; Michael Littman, personal communication). Given the continued explosive increase in the size of the Web, the trend toward business organizations that cross national boundaries, and high levels of competition for consumers in a global marketplace, it seems impossible not to view multilingual content on the Web as an expanding resource. Moreover, it is a dynamic resource, changing in content as the world changes. For example, Diekema et al., in a presentation at the 1998 TREC-7 conference (Voorhees and Harman, 1998), observed that the performance of their cross-language information retrieval was hurt by lexical gaps such as Bosnia/Bosniethis illustrates a highly topical missing pair in their static lexical resource (which was based on WordNet 1.5). And Gey et al., also at TREC-7, observed that in doing cross-language retrieval using commercial machine translation systems, gaps in the lexicon (their example was acupuncture/Akupunktur) could make the difference between precision of 0.08 and precision of 0.83 on individual queries. ttesnik (1998) presented an algorithm called


title: "I don't believe in word senses"

text: Word sense disambiguation assumes word senses. Within the lexicography and linguistics literature, they are known to be very slippery entities. The paper looks at problems with existing accounts of ‘word sense’ and describes the various kinds of ways in which a word’s meaning can deviate from its core meaning. An analysis is presented in which word senses are abstractions from clusters of corpus citations, in accordance with current lexicographic practice. The corpus citations, not the word senses, are the basic objects in the ontology. The corpus citations will be clustered into senses according to the purposes of whoever or whatever does the clustering. In the absence of such purposes, word senses do not exist. Word sense disambiguation also needs a set of word senses to disambiguate between. In most recent work, the set has been taken from a general-purpose lexical resource, with the assumption that the lexical resource describes the word senses of English/French/: : : , between which NLP applications will need to disambiguate. The implication of the paper is, by contrast, that word senses exist only relative to a task.


title: FACE-CHANGE: Application-Driven Dynamic Kernel View Switching in a Virtual Machine

text: Kernel minimization has already been established as a practical approach to reducing the trusted computing base. Existing solutions have largely focused on whole-system profiling - generating a globally minimum kernel image that is being shared by all applications. However, since different applications use only part of the kernel's code base, the minimized kernel still includes an unnecessarily large attack surface. Furthermore, once the static minimized kernel is generated, it is not flexible enough to adapt to an altered execution environment (e.g., new workload). FACE-CHANGE is a virtualization-based system to facilitate dynamic switching at runtime among multiple minimized kernels, each customized for an individual application. Based on precedent profiling results, FACE-CHANGE transparently presents a customized kernel view for each application to confine its reach ability of kernel code. In the event that the application exceeds this boundary, FACE-CHANGE is able to recover the missing code and back trace its attack/exception provenance to analyze the anomalous behavior.


title: Lightweight application classification for network management

text: Traffic application classification is an essential step in the network management process to provide high availability of network services. However, network management has seen limited use of traffic classification because of the significant overheads of existing techniques. In this context we explore the feasibility and performance of lightweight traffic classification based on NetFlow records. In our experiments, the NetFlow records are created from packet-trace data and pre-tagged based upon packet content. This provides us with NetFlow records that are tagged with a high accuracy for ground-truth. Our experiments show that NetFlow records can be usefully employed for application classification. We demonstrate that our machine learning technique is able to provide an identification accuracy (≈ 91%) that, while a little lower than that based upon previous packet-based machine learning work (> 95%), is significantly higher than the commonly used port-based approach (50--70%). Trade-offs such as the complexity of feature selection and packet sampling are also studied. We conclude that a lightweight mechanism of classification can provide application information with a considerably high accuracy, and can be a useful practice towards more effective network management.


title: A Compact Ka-Band Planar Three-Way Power Divider

text: A Ka-band planar three-way power divider which uses the coupled line instead of the transmission line is proposed to reduce chip size. The proposed planar topology, different from the conventional Wilkinson power divider, is analyzed and can provide not only compact but also dc block characteristics, which are very suitable for monolithic microwave integrated circuit applications. The divider implemented by a pHEMT process shows an insertion loss less than 5.1 dB and an output isolation better than 17 dB. A return loss less than 18 dB and a phase difference of 4.2deg at 30 GHz can be achieved. Finally, good agreements between the simulation and experimental results are shown.


title: Optimal control of execution costs for portfolios

text: We derive dynamic optimal trading strategies that minimize the expected cost of trading blocks of securities over a xed time horizon. Given xed blocks si of shares of stock i to be traded within a nite number of periods T , i = 1; : : : ; n, and given price-impact functions that yield the execution price of an individual trade as a function of the shares of stock i traded and current market conditions, we obtain the optimal sequence of trades as a function of market conditions|closed-form expressions in some cases|that minimizes the expected cost of executing si within T periods. We also propose an approximation algorithm for incorporating constraints, a particularly important extension in practice. To illustrate the practical relevance of our methods, we apply them to a hypothetical portfolio of 25 stocks by estimating their price-impact functions using historical trade data from 1996 and deriving the optimal execution strategies for the portfolio, and by performing several Monte Carlo simulation experiments. This research is part of the MIT Laboratory for Financial Engineering's Transactions Costs Project. We are grateful to Investment Technology Group, the National Science Foundation (Grant Nos. DMI{9610486 and SBR{9709976), and the sponsors of the LFE for nancial support. We thank Dave Cushing, Chris Darnell, Robert Ferstenberg, Rohit D'Souza, John Heaton, Leonid Kogan, Bruce Lehmann, Greg Peterson, Jiang Wang, and seminar participants at Columbia, Harvard, London Business School, MIT, Northwestern, the NYSE Conference on Best Execution, the Society of Quantitative Analysts, and Yale for helpful comments and discussion. Boeing Professor of Operations Research, MIT Sloan School of Management and Operations Research Center, Massachusetts Institute of Technology, E53-359, Cambridge, MA 02142{1347. Portfolio Strategist, Long Term Capital Management, One East Weaver St., Greenwich, CT 06831. Harris & Harris Group Professor, MIT Sloan School of Management and Operations Research Center, Cambridge, MA 02142{1347.


title: Optimization of image description metrics using policy gradient methods

text: In this paper, we propose a novel training procedure for image captioning models based on policy gradient methods. This allows us to directly optimize for the metrics of interest, rather than just maximizing likelihood of human generated captions. We show that by optimizing for standard metrics such as BLEU, CIDEr, METEOR and ROUGE, we can develop a system that improve on the metrics and ranks first on the MSCOCO image captioning leader board, even though our CNN-RNN model is much simpler than state of the art models. We further show that by also optimizing for the recently introduced SPICE metric, which measures semantic quality of captions, we can produce a system that significantly outperforms other methods as measured by human evaluation. Finally, we show how we can leverage extra sources of information, such as pre-trained image tagging models, to further improve quality.


title: A Quasi-Passive Leg Exoskeleton for Load-Carrying Augmentation

text: A quasi-passive leg exoskeleton is presented for load-carrying augmentation during walking. The exoskeleton has no actuators, only ankle and hip springs and a knee variabledamper. Without a payload, the exoskeleton weighs 11.7kg and requires only 2 Watts of electrical power during loaded walking. For a 36 kg payload, we demonstrate that the quasi-passive exoskeleton transfers on average 80% of the load to the ground during the single support phase of walking. By measuring the rate of oxygen consumption on a study participant walking at a self-selected speed, we find that the exoskeleton slightly increases the walking metabolic cost of transport (COT) as compared to a standard loaded backpack (10% increase). However, a similar exoskeleton without joint springs or damping control (zero-impedance exoskeleton) is found to increase COT by 23% compared to the loaded backpack, highlighting the benefits of passive and quasi-passive joint mechanisms in the design of efficient, low-mass leg exoskeletons.


title: Face recognition using PCA-based method

text: The objective of this paper is to develop the image processing and recognize the faces using PCA-based face recognition technique. MATLAB based programs are implemented to identify the faces using Indian databases and the Face recognition data, University of Essex, UK. For matching unknown images with known images, different techniques like sum of absolute difference (SAD), sum of squared difference (SSD), normalized cross correlation (NCC) etc. can be used which has been shown in this paper. Finally, it has been shown that the performance of PCA-based face recognition system is quite satisfactory instead of having some shortcomings of the system. (Abstract)


title: Learning input correlations through nonlinear temporally asymmetric Hebbian plasticity.

text: Triggered by recent experimental results, temporally asymmetric Hebbian (TAH) plasticity is considered as a candidate model for the biological implementation of competitive synaptic learning, a key concept for the experience-based development of cortical circuitry. However, because of the well known positive feedback instability of correlation-based plasticity, the stability of the resulting learning process has remained a central problem. Plagued by either a runaway of the synaptic efficacies or a greatly reduced sensitivity to input correlations, the learning performance of current models is limited. Here we introduce a novel generalized nonlinear TAH learning rule that allows a balance between stability and sensitivity of learning. Using this rule, we study the capacity of the system to learn patterns of correlations between afferent spike trains. Specifically, we address the question of under which conditions learning induces spontaneous symmetry breaking and leads to inhomogeneous synaptic distributions that capture the structure of the input correlations. To study the efficiency of learning temporal relationships between afferent spike trains through TAH plasticity, we introduce a novel sensitivity measure that quantifies the amount of information about the correlation structure in the input, a learning rule capable of storing in the synaptic weights. We demonstrate that by adjusting the weight dependence of the synaptic changes in TAH plasticity, it is possible to enhance the synaptic representation of temporal input correlations while maintaining the system in a stable learning regime. Indeed, for a given distribution of inputs, the learning efficiency can be optimized.


title: Battery Charger for Electric Vehicle Traction Battery Switch Station with PV System

text: This paper presents the functionality of a commercialized fast charger for a lithium-ion electric vehicle propulsion battery. The device is intended to operate in a battery switch station, allowing an up-to 1-h recharge of a 25-kWh depleted battery, removed from a vehicle. The charger is designed as a dual-stage-controlled ac/dc converter. The input stage consists of a three-phase full-bridge diode rectifier combined with a reduced rating shunt active power filter. The input stage creates an uncontrolled pulsating dc bus while complying with the grid codes by regulating the total harmonic distortion and power factor according to the predetermined permissible limits. The output stage is formed by six interleaved groups of two parallel dc–dc converters, fed by the uncontrolled dc bus and performing the battery charging process. The charger is capable of operating in any of the three typical charging modes: constant current, constant voltage, and constant power. Simulation results are shown to demonstrate the functionality of the device with including of Photovoltaic system. I.INTRODUCTION The traction battery is undoubtedly the most critical component of an electric vehicle (EV), since the cost and weight as well as the reliability and driving range of the vehicle are strongly influenced by the battery characteristics. Modern rechargeable lithium batteries, which are, by far, the most power or energy dense among modern batteries, are commonly used in traction applications. The high energy/power content requires appropriate battery management to ensure safety and optimal performance. In particular, proper recharging is essential in order to utilize the full capacity of the battery pack and preserve its nominal lifetime there are two common types of vehicle battery chargers. The onboard (often referred to as slow or low power) charger is located on board. The propulsion battery is recharged via the slow charger, plugged into a charging spot, while the vehicle is at parking lot . The off board (so-called fast or high power) charger is located at the battery switch station (BSS). The battery must be removed from the vehicle to be recharged via the fast charger (FC). The slow charger usually operates at 0.15–0.25-C rates, while the FC rate may typically reach 2-C rates, i.e., while charging a 25-kWh battery; the slow charger supplies 3–4 kW, while the FC peak power is typically 30–50 kW. The typical concept of EV includes urban driving only, where the full battery charge is sufficient for mediumrange routes of 50–100 miles. Recharging is accomplished by plugging the car into charge spots placed at different city locations throughout the day and at driver’s home during the night. Recently, a paradigm shift toward closing the gap between EV and conventional vehicles has occurred, forcing the infrastructure to support EV intercity driving as well. The following concept of BSS was developed: When out of charge, the EV battery can be replaced at a BSS, allowing nearly uninterrupted long range driving. The replacement process takes 2–4 min, similar to the duration of conventional refuelling process . The near empty battery, removed from a vehicle at the BSS, is recharged by an FC to be available as quickly as possible for the next customer. The charging time is obviously crucial, affecting the battery stock. For example, assuming 4-min battery replacement time, 15 vehicles per hour may be processed by each service lane. If battery charging time is 1 h, the minimum stock of 15 batteries per lane should be present at the station. Reducing the charging time obviously reduces the stock as well. It is worth noting that, since there is no human involvement in the fast charging process, galvanic isolation is usually not required to be present in an FC. M.Deepthi et. al. / International Journal of New Technologies in Science and Engineering Vol. 2, Issue 6,Dec 2015, ISSN 2349-0780 Available online @ www.ijntse.com 225 The FC is basically a controlled ac/dc power supply, drawing the power from the three-phase ac utility grid, converting it to dc and injecting it into the traction battery. In order to create a feasible solution, the FC must both satisfy the grid code in terms of power factor (PF) and harmonic content from the utility side and support lithium-ion charging modes from the battery side. Since the BSS usually contains multiple FCs, its impact on the distribution grid is very significant, as shown by previous research. Therefore, the input stage of the FC usually performs PF correction (PFC) according to the regulation requirements in addition to rectification. It can be accomplished by employing either an active rectifier , or a diode rectifier combined with a PFC circuit. The wellknown single-phase PFC approach, utilizing an uncontrolled rectifier followed by a full-rating boost dc–dc converter, is unsuitable for the three-phase diode rectifier case. However, it can be modified by splitting the three-phase rectifier into either two single-phase legs followed by two independent PFC converters or three single-phase Δor Y-connected stages. Alternatively, a more elegant approach employs a shunt connected active power filter (APF) at the uncontrolled rectifier input, supplying the reactive current to the diode rectifier, thus achieving both near-unity PF and near-zero total harmonic distortion (THD) by letting the utility to supply the active current only, which is in phase with the utility voltage and of the same shape. The use of either one three-phase or three single-phase APF configurations is potentially feasible for implementing a three-phase PFC stage. The additional advantage of the approach is the fact that, because of the shunt connection, the APF rating is less than onethird of the bridge rectifier rating, since the APF supplies the reactive and harmonic power only, while the series-connected PFC converter rating is equal to the load kilo volt ampere rating. The resulting loss reduction is an extremely desirable feature for an FC since the dissipated heat must be removed from the BSS by means of a cumbersome ventilation system, whose complexity is proportional to the amount of the heat to be removed. From the battery side, a conventional lithium-ion battery charging is characterized by two main phases: constant current (CC) and constant voltage (CV). Recently, constant power (CP) charging became popular in large vehicle battery packs. Hence, the charger output stage (typically consisting of dc–dc converters) must be capable of operating as either a current or voltage source. Alternatively, it can be operated as a voltage supply with dynamic current limitation. CP mode is usually achieved by operating as a current source, constantly varying according to the power profile. Moreover, the charger output current ripple should be kept as low as possible in order to prevent undesired influence on the battery chemistry. The wellknown solution, allowing splitting the load power between multiple modules in order to reduce both the conduction losses and current ripple, is interleaving. Interleaving employs parallel operation of converters, whose output current is equally shifted with respect to others such that, when summed, the current ripples partially cancel each other, creating a low ripple total output current. In addition, interleaving also reduces the implementation challenge of designing a single fullrating converter by using several lower rating converters instead at the expense of somewhat increased hardware cost, volume/weight, and more complex control circuitry. M.Deepthi et. al. / International Journal of New Technologies in Science and Engineering Vol. 2, Issue 6,Dec 2015, ISSN 2349-0780 Available online @ www.ijntse.com 226 II.POWER QUALITY Electric power quality may be defined as a measure of how well electric power service can be utilized by customers. Power Quality problem is an occurrence manifested as a nonstandard voltage, current or frequency that results in a failure or a mis operation of end user equipment. To compensate harmonics conventional Passive Filters are used for specific number of harmonics. To compress total harmonic content Active Power Filters are used. For all types of power quality solutions at the distribution system voltage level DFACTS also called as Custom Power Devices are introduced to improve Power Quality. Power quality is certainly a major concern in the present era; it becomes of especially important with the introduction sophisticated devices, whose performance is very sensitive to the quality of power supply. Modern industrial processes are based on a large amount of electronic devices such as programmable logic controllers and adjustable speed drives. Electronic devices are very sensitive to disturbances and thus industrial loads become less tolerant to power quality problems. Power Quality has become an important issue since many loads at various distribution ends like adjustable speed drives, process industries, printers, domestic utilities; computers, microprocessor based equipments etc. have become intolerant to voltage fluctuations, harmonic content and interruptions. Power Quality mainly deals with issues like maintaining a fixed voltage at the Point of Common Coupling for various distribution voltage levels irrespective of voltage fluctuations, maintaining near unity power factor power drawn from the supply, blocking of voltage and current unbalance from passing upwards from various distribution levels, reduction of voltage and current harmonics in the system and suppression of excessive supply neutral current. Recently, the importance of power quality issues has increased due to various reasons. First of all, there have been changes in the nature of electrical loads. On one hand, the characteristics of load have become more complex due to the increased use of power electronic equipment, which results in a deviation of voltage and current from its sinusoidal wavefor


title: A stretchable PIFA antenna

text: This paper presents a stretchable Planar Inverted-F Antenna (PIFA) based on a new metallization technique of depositing nanoscale thin (50/100nm) Au film on elastomer Polydimethylsiloxane (PDMS). The thin metal films can be reversibly stretched up to 20% without losing electrical conduction. The PIFA antenna made of new materials can work under a 10% strain and return to its original state after removal of an applied stress. Simulation and measurement results for the antenna performance are given.


title: A secure triple level encryption method using cryptography and steganography

text: Cryptography is the practice for secure communication in the presence of third parties. Steganography is technique of writing hidden messages such that except the sender and receiver, no one even suspects the existence of the message. In today's hi-tech age, threats from intruders are very great such that usage of either of the above techniques separately may not be able to provide the intended protection. In order to increase the level of protection, both the techniques may be used in a combined manner. Multimedia techniques can also be used to hide the data. In this paper, we propose an encrypting system which combines techniques of cryptography and steganography with data hiding. Instead of using a single level of data encryption, the message is encrypted twice. Traditional techniques have been used for this purpose. Then the cipher is hidden inside the image in encrypted format for further use. It uses a reference matrix for selection of passwords depending on the properties of the image. The image with the hidden data is used for further purposes.


title: Achieving high navigation accuracy using inertial navigation systems in autonomous underwater vehicles

text: This paper presents a summary of the current state-of-the-art in INS-based navigation systems in AUVs manufactured by Bluefin Robotics Corporation. A detailed description of the successful integrations of the Kearfott T-24 Ring Laser Gyro and the IXSEA PHINS III Fiber Optic Gyro into recent Bluefin Robotics AUVs is presented. Both systems provide excellent navigation accuracy for high quality data acquisition. This paper provides a comprehensive assessment of the primary advantages and disadvantages of each INS, paying particular attention to navigation accuracy, power draw, physical size, and acoustic radiated noise. Additionally, a brief presentation of a recently integrated Synthetic Aperture Sonar system will be used to highlight how critical a high-performance INS is to hydrographic, mine countermeasures, and other SAS applications.


title: An empirical study of tokenization strategies for biomedical information retrieval

text: Due to the great variation of biological names in biomedical text, appropriate tokenization is an important preprocessing step for biomedical information retrieval. Despite its importance, there has been little study on the evaluation of various tokenization strategies for biomedical text. In this work, we conducted a careful, systematic evaluation of a set of tokenization heuristics on all the available TREC biomedical text collections for ad hoc document retrieval, using two representative retrieval methods and a pseudo-relevance feedback method. We also studied the effect of stemming and stop word removal on the retrieval performance. As expected, our experiment results show that tokenization can significantly affect the retrieval accuracy; appropriate tokenization can improve the performance by up to 96%, measured by mean average precision (MAP). In particular, it is shown that different query types require different tokenization heuristics, stemming is effective only for certain queries, and stop word removal in general does not improve the retrieval performance on biomedical text.


title: The new blocs on the block: using community forums to foster new neighbourhoods

text: Research has consistently shown that online tools increase social capital. In the context of neighbourhoods Hampton and Wellman have shown that in newly developed areas residents effectively used mailing lists to connect with each other, circulate information, and ask for help. The research question of whether similar findings would hold in the larger context of a city for a long period of time is still open. To tackle this research question, we have gathered the complete dataset of the most popular neighbourhood online forum in Dublin. In this dataset, we have people sharing a common purpose (blocs) who live in the same neighbourhood and interact online to ask for help, engage in local activities, and, more generally, have a better understanding of their physical community. Our analysis highlights the particularly concentrated usage in newly established developments where a pre-existing community may be absent. Additionally, these communications provide a valuable resource to understand local issues relevant to the community.


title: Learning MultiGoal Inverse Kinematics in Humanoid Robot

text: General Inverse Kinematic (IK) solvers may not guarantee real-time control of the end-effectors in external coordinates along with maintaining stability. This work addresses this problem by using Reinforcement Learning (RL) for learning an inverse kinematics solver for reachability tasks which ensures stability and self-collision avoidance while solving for end effectors. We propose an actor-critic based algorithm to learn joint space trajectories of stable configuration for solving inverse kinematics that can operate over continuous action spaces. Our approach is based on the idea of exploring the entire workspace and learning the best possible configurations. The proposed strategy was evaluated on the highly articulated upper body of a 27 degrees of freedom (DoF) humanoid for learning multi-goal reachability tasks of both hands along with maintaining stability in double support phase. We show that the trained model was able to solve inverse kinematics for both the hands, where the articulated torso contributed to both the tasks.


title: Park Here! a smart parking system based on smartphones' embedded sensors and short range Communication Technologies

text: Nowadays, the convergence of Internet of Things (IoT) networking and mobile applications is favoring the deployment of novel and advanced smart parking systems through which users can be informed in real-time about the presence of vacant parking spots close to their destinations. In this paper, we provide an example of such opportunity, by describing Park Here!, a novel mobile application that aims at mitigating the overhead caused by parking spot seeking operations in urban areas. Our solution targets common city environments, where no per-spot sensors are available, and there is no remote service allowing the reservation in-advance of a parking spot. For this scenario, we propose a novel algorithm for the automatic detection of parking actions performed by the user, through the analysis of smartphone embedded sensors' (accelerometer/gyroscope), and of the Bluetooth connectivity. Once a parking event has been detected, an adaptive strategy allows disseminating the information over the target scenario, using a combination of Internet connection to a remote server, and Device-to-Device (D2D) connections over WiFi Direct links. Preliminary experiments demonstrate the accuracy of the proposed algorithm in correctly identifying parking events in an automatic way, and hence in notifying information to other potentially interested users.


title: Prediction of Rainfall Time Series Using Modular Artificial Neural Networks Coupled with Data Preprocessing Techniques

text: 1 Dept. of Civil and Structural Engineering, Hong Kong Polytechnic University, 4 Hung Hom, Kowloon, Hong Kong, People’s Republic of China 5 6 2 Changjiang Institute of Survey, Planning, Design and Research, 7 Changjiang Water Resources Commission, 8 430010, Wuhan, HuBei, People’s Republic of China 9 10 3 Department of Civil Engineering, Ryerson University, 11 350 Victoria Street, Toronto, Ontario, Canada, M5B 2K3 12 13 *Email: cekwchau@polyu.edu.hk 14 15 ABSTRACT 16


title: INTEGRATION OF BIM AND GIS : THE DEVELOPMENT OF THE CITYGML GEOBIM EXTENSION

text: There is a growing interest in the integration of BIM and GIS. However, most of the research is focused on importing BIM data in GIS applications and vice versa. Real integration of BIM and GIS is using the strong parts of the GIS technology in BIM, and of course the strong parts from BIM technology in GIS. In this paper a mix of strong parts from both worlds is integrated in a single project. The paper describes the development of a CityGML extension called GeoBIM to get semantic IFC data into a GIS context. The conversion of IFC to CityGML (including the GeoBIM extension) is implemented in the open source Building Information Modelserver. This contribution was selected in a double blind review process to be published within the Lecture Notes in Geoinformation and Cartography series (Springer-Verlag, Heidelberg). Advances in 3D Geo-Information Sciences Kolbe, Thomas H.; König, Gerhard; Nagel, Claus (Eds.) 2011, X ISBN 978-3-642-12669-7, Hardcover Date of Publication: January 5, 2011 Series Editors: Cartwright, W., Gartner, G., Meng, L., Peterson, M.P. ISSN: 1863-2246 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXVIII-4/W15 5th International 3D GeoInfo Conference, November 3-4, 2010, Berlin, Germany 193


title: FLEXIBLE GENERATION OF SEMANTIC 3 D BUILDING MODELS

text: The paper presents a new 3D semantic building model dedicated to urban development. It provides the following special semantic features: storeys, passages, opening objects, and building variants, modelling different levels of detail and design respectively temporal variants. The model also includes a parametric part supporting easy generation of buildings and building variants in the urban design phase. In order to make the powerful tools of the CA(A)D world accessible to city modeling, a toolbox is being developed for transformation of IFC data. These extensions and addition facilitate multiple utilization of city models and thus enhance sustainability of modeling.


title: An investigation into the applicability of building information models in geospatial environment in support of site selection and fire response management processes

text: 1474-0346/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.aei.2008.06.001 * Corresponding author. Tel.: +90 312 266 00 5 (U. Isikdag); tel.: +44 161 295 62 90; fax: +44 016 tel.: +44 0161 295 4992; fax: +44 0161 295 3173 (G. E-mail addresses: egetera@superonline.com, uisik j.underwood@salford.ac.uk (J. Underwood), g.aoauad@ Some tasks in the construction industry and urban management field such as site selection and fire response management are usually managed by using a Geographical Information System (GIS), as the tasks in these processes require a high level and amount of integrated geospatial information. Recently, a key element of this integrated geospatial information to emerge is detailed geometrical and semantic information about buildings. In parallel, Building Information Models (BIMs) of today have the capacity for storing and representing such detailed geometrical and semantic information. In this context, the research aimed to investigate the applicability of BIMs in geospatial environment by focusing specifically on these two domains; site selection and fire response management. In the first phase of the research two use case scenarios were developed in order to understand the processes in these domains in a more detailed manner and to establish the scope of a possible software development for transferring information from BIMs into the geospatial environment. In the following phase of the research two data models were developed – a Schema-Level Model View and a geospatial data model. The Schema-Level Model View was used in simplifying the information acquired from the BIM, while the geospatial data model acted as the template for creating physical files and databases in the geospatial environment. Following this, three software components to transfer building information into the geospatial environment were designed, developed, and validated. The first component served for acquiring the building information from the BIM, while the latter two served for transforming the information into the geospatial environment. The overall research demonstrated that it is possible to transfer (high level of geometric and semantic) information acquired from BIMs into the geospatial environment. The results also demonstrated that BIMs provide a sufficient level and amount of (geometric and semantic) information (about the building) for the seamless automation of data management tasks in the site selection and fire response management processes. 2008 Elsevier Ltd. All rights reserved.


title: Credit Assignment Techniques in Stochastic Computation Graphs

text: Stochastic computation graphs (SCGs) provide a formalism to represent structured optimization problems arising in artificial intelligence, including supervised, unsupervised, and reinforcement learning. Previous work has shown that an unbiased estimator of the gradient of the expected loss of SCGs can be derived from a single principle. However, this estimator often has high variance and requires a full model evaluation per data point, making this algorithm costly in large graphs. In this work, we address these problems by generalizing concepts from the reinforcement learning literature. We introduce the concepts of value functions, baselines and critics for arbitrary SCGs, and show how to use them to derive lower-variance gradient estimates from partial model evaluations, paving the way towards general and efficient credit assignment for gradient-based optimization. In doing so, we demonstrate how our results unify recent advances in the probabilistic inference and reinforcement learning literature.


title: How to Play any Mental Game or A Completeness Theorem for Protocols with Honest Majority

text:
We present a polynomial-time algorithm that, given as a input the description of a game with incomplete information and any number of players, produces a protocol for playing the game that leaks no partial information, provided the majority of the players is honest.
Our algorithm automatically solves all the multi-party protocol problems addressed in complexity-based cryptography during the last 10 years. It actually is a completeness theorem for the class of distributed protocols with honest majority. Such completeness theorem is optimal in the sense that, if the majority of the players is not honest, some protocol problems have no efficient solution [C].


title: Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features.

text: For a successful analysis of the relation between amino acid sequence and protein structure, an unambiguous and physically meaningful definition of secondary structure is essential. We have developed a set of simple and physically motivated criteria for secondary structure, programmed as a pattern-recognition process of hydrogen-bonded and geometrical features extracted from x-ray coordinates. Cooperative secondary structure is recognized as repeats of the elementary hydrogen-bonding patterns “turn” and “bridge.” Repeating turns are “helices,” repeating bridges are “ladders,” connected ladders are “sheets.” Geometric structure is defined in terms of the concepts torsion and curvature of differential geometry. Local chain “chirality” is the torsional handedness of four consecutive Ca positions and is positive for right-handed helices and negative for ideal twisted @-sheets. Curved pieces are defined as “bends.” Solvent “exposure” is given as the number of water molecules in possible contact with a residue. The end result is a compilation of the primary structure, including SS bonds, secondary structure, and solvent exposure of 62 different globular proteins. The presentation is in linear form: strip graphs for an overall view and strip tables for the details of each of 10,925 residues. The dictionary is also available in computer-readable form for protein structure prediction work.


title: Improved segmentation of abnormal cervical nuclei using a graph-search based approach

text: Reliable segmentation of abnormal nuclei in cervical cytology is of paramount importance in automation-assisted screening techniques. This paper presents a general method for improving the segmentation of abnormal nuclei using a graph-search based approach. More specifically, the proposed method focuses on the improvement of coarse (initial) segmentation. The improvement relies on a transform that maps round-like border in the Cartesian coordinate system into lines in the polar coordinate system. The costs consisting of nucleus-specific edge and region information are assigned to the nodes. The globally optimal path in the constructed graph is then identified by dynamic programming. We have tested the proposed method on abnormal nuclei from two cervical cell image datasets, Herlev and H&E stained liquid-based cytology (HELBC), and the comparative experiments with recent state-of-the-art approaches demonstrate the superior performance of the proposed method.


title: The inferior parietal lobule and temporoparietal junction: A network perspective

text: Information processing in specialized, spatially distributed brain networks underlies the diversity and complexity of our cognitive and behavioral repertoire. Networks converge at a small number of hubs - highly connected regions that are central for multimodal integration and higher-order cognition. We review one major network hub of the human brain: the inferior parietal lobule and the overlapping temporoparietal junction (IPL/TPJ). The IPL is greatly expanded in humans compared to other primates and matures late in human development, consistent with its importance in higher-order functions. Evidence from neuroimaging studies suggests that the IPL/TPJ participates in a broad range of behaviors and functions, from bottom-up perception to cognitive capacities that are uniquely human. The organization of the IPL/TPJ is challenging to study due to the complex anatomy and high inter-individual variability of this cortical region. In this review we aimed to synthesize findings from anatomical and functional studies of the IPL/TPJ that used neuroimaging at rest and during a wide range of tasks. The first half of the review describes subdivisions of the IPL/TPJ identified using cytoarchitectonics, resting-state functional connectivity analysis and structural connectivity methods. The second half of the article reviews IPL/TPJ activations and network participation in bottom-up attention, lower-order self-perception, undirected thinking, episodic memory and social cognition. The central theme of this review is to discuss how network nodes within the IPL/TPJ are organized and how they participate in human perception and cognition.


title: A Comparison of learning algorithms on the Arcade Learning Environment

text: Reinforcement learning agents have traditionally been evaluated on small toy problems. With advances in computing power and the advent of the Arcade Learning Environment, it is now possible to evaluate algorithms on diverse and difficult problems within a consistent framework. We discuss some challenges posed by the arcade learning environment which do not manifest in simpler environments. We then provide a comparison of model-free, linear learning algorithms on this challenging problem set.


title: Robust Face Recognition Using Symmetric Shape-from-Shading

text: Sensitivity to variations in illumination is a fundamental and challenging problem in face recognition. In this paper, we describe a new method based on symmetric shape-from-shading (SFS) to develop a face recognition system that is robust to changes in illumination. The basic idea of this approach is to use the symmetric SFS algorithm as a tool to obtain a prototype image which is illumination-normalized. Applying traditional SFS algorithms to real images of complex objects (in terms of their shape and albedo variations) such as faces is very challenging. It is shown that the symmetric SFS algorithm has a unique point-wise solution. In practice, given a single real face image with complex shape and varying albedo, even the symmetric SFS algorithm cannot guarantee the recovery of accurate and complete shape information. For the particular problem of face recognition, we utilize the fact that all faces share a similar shape making the direct computation of the prototype image from a given face image feasible. The symmetry property has been used to develop a new model-based source-from-shading algorithm which is more accurate than existing algorithms. Using the symmetric property, we are also able to gain insight into how changes in illumination a ect eigen-subspace based face recognition systems. Finally, to demonstrate the e cacy of our method, we have applied it to several publicly available face databases. We rst compare a new illumination-invariant measure to the measure proposed in (Jacobs et al., 1998), and then demonstrate signi cant performance improvement over existing face recognition systems using PCA and/or LDA for images acquired under variable lighting conditions.


title: Real-time lane detection and forward collision warning system based on stereo vision

text: This paper presents a real-time and robust lane detection and forward collision warning technique based on stereo cameras. First, obstacles image is obtained through stereo matching and UV-disparity segmentation algorithm. Then, Inverse Perspective Mapping(IPM) and Sobel filtering are conducted to generate a low-noise top view of the road by fusing the obstacles image and the original image. Next, Hough Transformation for the top view map is completed and the extreme points(poles) are calculated as the detected lanes according to the traffic lanes model. Besides, the host lane is selected or supplemented among all the detected lanes and the nearest obstacle in this host lane is detected for the forward collision warning. Experimental results on the public data set indicate that our method can work effectively and real-timely in the normal structured environment.


title: DSP Implementation in the Loop of the Vector Control Drive of a Permanent Magnet Synchronous Machine

text:
The aim of this work is to design and implement the FOC (Field Oriented Control) of the permanent magnet synchronous machine (PMSM) on DSP in Hardware In the Loop (HIL). The MATLAB /Simulink, the IDE Code Composer Studio and the DSP TMS320F28335 platform will be used to perform the simulation, the code generation and the HIL.
 The obtained performances of this command (a speed response time of 10 ms and a zero static error vis-à-vis the setpoint and disruption) converge to those obtained with conventional simulation on SIMULINK


title: Automatic Vehicle Accident Detection and Messaging System Using GSM and GPS Modem

text: The Rapid growth of technology and infrastructure has made our lives easier. The advent of technology has also increased the traffic hazards and the road accidents take place frequently which causes huge loss of life and property because of the poor emergency facilities. Our project will provide an optimum solution to this draw back. An accelerometer can be used in a car alarm application so that dangerous driving can be detected. It can be used as a crash or rollover detector of the vehicle during and after a crash. With signals from an accelerometer, a severe accident can be recognized. According to this project when a vehicle meets with an accident immediately Vibration sensor will detect the signal or if a car rolls over, and Micro electro mechanical system (MEMS) sensor will detects the signal and sends it to ARM controller. Microcontroller sends the alert message through the GSM MODEM including the location to police control room or a rescue team. So the police can immediately trace the location through the GPS MODEM, after receiving the information. Then after conforming the location necessary action will be taken. If the person meets with a small accident or if there is no serious threat to anyone`s life, then the alert message can be terminated by the driver by a switch provided in order to avoid wasting the valuable time of the medical rescue team. This paper is useful in detecting the accident precisely by means of both vibration sensor and Micro electro Mechanical system (MEMS) or accelerometer. As there is a scope for improvement and as a future implementation we can add a wireless webcam for capturing the images which will help in providing driver`s assistance.


title: Counting Graphlets: Space vs Time

text: Counting graphlets is a well-studied problem in graph mining and social network analysis. Recently, several papers explored very simple and natural approaches based on Monte Carlo sampling of Markov Chains (MC), and reported encouraging results. We show, perhaps surprisingly, that this approach is outperformed by a carefully engineered version of color coding (CC) [1], a sophisticated algorithmic technique that we extend to the case of graphlet sampling and for which we prove strong statistical guarantees. Our computational experiments on graphs with millions of nodes show CC to be more accurate than MC. Furthermore, we formally show that the mixing time of the MC approach is too high in general, even when the input graph has high conductance. All this comes at a price however. While MC is very efficient in terms of space, CC's memory requirements become demanding when the size of the input graph and that of the graphlets grow. And yet, our experiments show that a careful implementation of CC can push the limits of the state of the art, both in terms of the size of the input graph and of that of the graphlets.


title: CommonSense: Collaborative learning of scene semantics by robots and humans

text: The recent introduction of robots to everyday scenarios has revealed new opportunities for collaboration and social interaction between robots and people. However, high level interaction will require semantic understanding of the environment. In this paper, we advocate that co-existence of assistive robots and humans can be leveraged to enhance the semantic understanding of the shared environment, and improve situation awareness. We propose a probabilistic framework that combines human activity sensor data generated by smart wearables with low level localisation data generated by robots. Based on this low level information and leveraging colocation events between a user and a robot, it can reason about semantic information and track humans and robots across different rooms. The proposed system relies on two-way sharing of information between the robot and the user. In the first phase, user activities indicative of room utility are inferred from consumer wearable devices and shared with the robot, enabling it to gradually build a semantic map of the environment. This will enable natural language interaction and high-level tasks for both assistive and co-working robots. In a second phase, via colocation events, the robot is able to share semantic information with the user, by labelling raw user data with semantic information about room type. Over time, the labelled data is used for training an Hidden Markov Model for room-level localisation, effectively making the user independent from the robot.