Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Method for Image Color Constancy by Using 2 nd Order Gray Edge Algorithm with Bilateral Filter

The methodology is proposed to extension of existing method applying local color constancy to image patches, rather than on entire image globally. Many algorithms have to estimating the color constancy of the light sources are developed, but all existing methods are applied on single light source i.e they are consider an image is effected only single uniform illumination, this case is not every time, because images are effected more than one illuminations. The illumination of single light source is violated by illumination of multiple sources of light. Here we will discuss a new methodology it considers an image is affected by various light sources, without any information about the color of light sources. The technique grid based sampling and keypoint based sampling along with grey edge algorithm can be used to estimate the color of multiple lights. Finally the color correction gives the most promising and also it has to provide consistency of these algorithms over various types of images taken from different datasets. This proposed method gives better results than previous methods for color constancy.
Task-Based Learning in Task-Based Teaching: Training Teachers of Chinese as a Foreign Language

ABSTRACT Task-based language teaching (TBLT) is increasingly becoming known for its distinct edge in developing learners’ functional competence. Although its potential in promoting content learning has yet to be realized and explored, it should be high, given TBLT's primary attention to meaning. To what extent does the potential play out in foreign language teacher education, a domain involving much content learning, is both an intellectually stimulating and practically meaningful question. This article reports on a semester-long study investigating task-based learning in a Chinese language teacher-training program that promotes TBLT. The participants were three Chinese-speaking trainees, who, while being exposed to TBLT, performed ongoing tasks. Data from one task—writing weekly reading journals—were analyzed for both content and language, quantitatively (using robust automated tools) and qualitatively. The results show tangible gains on both counts—understanding TBLT (content) and the ability to articulate it (language). The conceptual and methodological implications of the findings are discussed for future research.
Reliability modeling of distributed generation in conventional distribution systems planning and analysis

The primary objective of any electric utility company in the new competitive environment is to increase the market value of the services by providing the right amount of reliability, and at the same time, lower its costs for operation, maintenance and construction of new facilities in order to provide lower rates for customers. The electric utility company will strive to achieve this objective via many different means, one of which is to defer the capital distribution facility requirements in favor of a distributed generation (DG) solution by an independent power producer (IPP) to meet the growing customer load demand. In this case, the distribution capital investment deferral credit received by the IPP will be dependent on the incremental system reliability improvement rendered by the DG solution. In other words, the size, location and the reliability of the DG will be based on the comparable incremental reliability provided by the distribution solution under considerations. This paper presents a reliability model for determining the DG equivalence to a distribution facility for use in distribution system planning studies in the new competitive environment.
A State Equivalence and Confluence Checker for CHR

Analyzing confluence of CHR programs manually can be an impractical and time consuming task. Based on a new theorem for state equivalence, this work presents the first tool for testing equivalence of CHR states. As state equivalence is an essential component of confluence analysis, we apply this tool in the development of a confluence checker that overcomes limitations of existing checkers. We further provide evaluation results for both tools and detail their modular design, which allows for extensions and reuse in future implementations of CHR tools.
A Study of Solder Joint Failure Criteria

One of the challenges in an experimental study of solder joint reliability is to determine when cracks occur in a solder joint or when a solder joint fails. Cracks in a real solder joint are difficult to identify using an X-Ray system. Cross-sectioning and scanning electron microscopy (SEM) is a destructive method. A common non-destructive test method is to monitor resistance increase in a solder joint or a daisy-chain. However, no scientific research has been done in establishing the relationship between the crack area of an interconnection and the change in resistance of the interconnection. This paper proposes a method of defining failure criteria as the resistance increase in a solder joint exceeding a threshold. The threshold is determined by k times the range over the natural variation in resistance measured by a measurement system. The natural variation by random cause is judged using X-bar and R charts. The principles of defining failure criteria are to be able to detect failure of solder joints a.
Control of Mobile Robots Through Wireless Sensor Networks

A trend in today’s mobile robotics is to perform the control of mobile robots in a distributed fashion. This control scheme requires a wireless communication network connecting the robot to the other existing devices in the environment. WiFi and Bluetooth are examples of such networks. Ad-hoc networks such as wireless sensor networks (WSN) can be deployed instantly and offer a wide coverage by employing a large number of communicating nodes. In addition to provide a communication link to the robots, a WSN can aid the robot’s navigation, localization, and also enhance its sensory capabilities. This paper presents a network architecture for supporting the control and communication of mobile robots through WSNs.
Teacher–child relational conflict in Head Start – exploring the roles of child behaviour, teacher stress, and bias, and classroom environment

ABSTRACT Numerous studies have examined influential factors on teacher–child relational conflict; however, only a limited number of studies have presented in-depth portrayals of teachers’ conflict with children living in poverty at the preschool level. The purpose of this paper is to explore teacher, child, and contextual characteristics that influence teacher–child relational conflict in Head Start. Ten Head Start teachers from five centres across two counties were recruited. Each participant was interviewed twice and observed once for an entire school day. Interview and observation data were analysed through a grounded theory approach by using the qualitative data analysis software NVivo. Four themes emerged as teacher-perceived influences on conflictual relationships: children’s behaviour, teachers’ stress and biases, and the classroom environment. The results may have implications for teacher professional development and Head Start policies.
Evaluation of renal vascular lesions using circulating endothelial cells in patients with lupus nephritis.

OBJECTIVE Currently the detection of renal vascular lesions (VLS) mainly depends on biopsy examination, and lacks surrogate biomarkers for clinical dynamic evaluation. The aim of this study is to find the correlation between numbers of circulating endothelial cells (CECs) and renal VLS in lupus nephritis (LN). METHODS Thirty LN patients with VLS and 30 LN patients without VLS were recruited. Thirty age- and sex-matched healthy volunteers served as controls. CECs were isolated from peripheral blood with anti-CD-146-coated immunomagnetic Dynabeads and were counted under microscopy. Parameters of renal involvement, including blood urea nitrogen, serum creatinine, 24 h urine protein excretion and quantitative urine sedimentation were also measured. RESULTS The number of CECs showed no difference between LN patients without VLS and controls. In patients with VLS, the number of CECs was significantly higher than those without VLS (P < 0.01). A strong positive correlation was found between CECs and serum creatinine (r = 0.503, P < 0.01) and mean blood pressure (r = 0.423, P < 0.05). In all LN patients with VLS, CEC number of the patients with thrombotic microangiopathy (TMA) significantly increased compared with those without TMA (P < 0.01). CONCLUSION Numeration of CECs may serve as a potential and useful marker for vasculopathy in LN. Dynamic observations of CEC number can be used not only to provide evidence for monitoring disease severity and disease activity, but also to determine therapy efficacy in LN patients.
Autonomous compressive spectrum sensing approach for 3.5 GHz shared spectrum

The underutilized 3.5 GHz shared spectrum poses an excellent opportunity and potential for more intensive secondary usage by innovative applications/services. To find more spectral holes, a wide portion of spectrum must be sensed, which requires high sampling rates and a lot of measurements to be processed. Compressive sensing (CS) has recently become one of the promising techniques to deal with the sampling rate bottleneck of the wideband spectrum sensing. However, there are two significant challenges in the implementation of CS based wideband spectrum sensing: 1) no apriori knowledge of users activity statistics and 2) the varying bandwidth of channels and power levels. To address these issues, we proposed an autonomous compressive spectrum sensing approach that enables a secondary user to choose the number of measurements automatically, while the exact wideband signal reconstruction is guaranteed without assumption on spectral sparsity or channel characteristics. Specifically, the compressive measurements are collected block-by-block while the spectral is gradually reconstructed and the measurements collection process can be terminated once the variation of the Euclidean distance among the sequence of recovery solutions falls below a desired tolerance.
Parameterization of the duration of infection stages of serotype O foot-and-mouth disease virus: an analytical review and meta-analysis with application to simulation models

Foot-and-mouth disease (FMD) is considered one of the most important infectious diseases of livestock because of the devastating economic consequences that it inflicts in affected regions. The value of critical parameters, such as the duration of the latency or the duration of the infectious periods, which affect the transmission rate of the FMD virus (FMDV), are believed to be influenced by characteristics of the host and the virus. Disease control and surveillance strategies, as well as FMD simulation models, will benefit from improved parameter estimation. The objective of this study was to quantify the distributions of variables associated with the duration of the latency, subclinical, incubation, and infectiousness periods of FMDV transmission. A double independent, systematic review of 19 retrieved publications reporting results from experimental trials, using 295 animals in four reference laboratories, was performed to extract individual values related to FMDV transmission. Probability density functions were fitted to data and a set of regression models were used to identify factors associated with the assessed parameters. Latent, subclinical, incubation, and infectious periods ranged from 3.1 to 4.8, 2 to 2.3, 5.5 to 6.6, and 3.3 to 5.7 days, respectively. Durations were significantly (p < 0.05) associated independently with route of exposure, type of donor, animal species, strains, characteristics of sampling, and clinical signs. These results will contribute to the improvement of disease control and surveillance strategies and stochastic models used to simulate FMD spread and, ultimately, development of cost-effective plans to prevent and control the potential spread of the disease in FMD-free regions of the world.
Wrist Compression Feedback by Pneumatic Actuation

Most common forms of haptic feedback use vibration, which immediately captures the user's attention, yet is limited in the range of strengths it can achieve. Vibration feedback over extended periods also tends to be annoying. We present compression feedback, a form of haptic feedback that scales from very subtle to very strong and is able to provide sustained stimuli and pressure patterns. The demonstration may serve as an inspiration for further work in this area, applying compression feedback to generate subtle, intimate, as well as intense feedback.
Incidence of Type II CRISPR1-Cas Systems in Enterococcus Is Species-Dependent

CRISPR-Cas systems, which obstruct both viral infection and incorporation of mobile genetic elements by horizontal transfer, are a specific immune response common to prokaryotes. Antiviral protection by CRISPR-Cas comes at a cost, as horizontally-acquired genes may increase fitness and provide rapid adaptation to habitat change. To date, investigations into the prevalence of CRISPR have primarily focused on pathogenic and clinical bacteria, while less is known about CRISPR dynamics in commensal and environmental species. We designed PCR primers and coupled these with DNA sequencing of products to detect and characterize the presence of cas1, a universal CRISPR-associated gene and proxy for the Type II CRISPR1-Cas system, in environmental and non-clinical Enterococcus isolates. CRISPR1-cas1 was detected in approximately 33% of the 275 strains examined, and differences in CRISPR1 carriage between species was significant. Incidence of cas1 in E. hirae was 73%, nearly three times that of E. faecalis (23.6%) and 10 times more frequent than in E. durans (7.1%). Also, this is the first report of CRISPR1 presence in E. durans, as well as in the plant-associated species E. casseliflavus and E. sulfureus. Significant differences in CRISPR1-cas1 incidence among Enterococcus species support the hypothesis that there is a tradeoff between protection and adaptability. The differences in the habitats of enterococcal species may exert varying selective pressure that results in a species-dependent distribution of CRISPR-Cas systems.
The construction of masculinity in male facial care product advertisement

Many studies are done on gender bias on women, but a little on men. If one of women’s stereotypes is wearing makeup, then one of men is no need taking care of his face. However, the consumption of male facial products has shown an up going trend. Ironically, it is not commonly perceived as users of facial care products, since they would be labeled as gay. This study aims to show that gender bias does not only happen to women but also men. In addition, the media is supposed to be the means to liberate and empower marginalized groups and not present news by reinforcing stereotypes of the group. The research question is how ads construct a masculine figure by emphasizing on his needs for facial treatment? The theoretical concepts used in this research are social construction of reality, stereotypes and fetishism while the method of data collection is semiotic text analysis through purposive selection. The results show that masculinity represented in the advertisement figures defines the stereotypes that fit with consumptive urban society behavior. Construction of the advertised product is not for the purpose of selling it for its function, but rather to support the exclusive image and identity of the target buyers.
Simulation Platform for Coordinated Charging of Electric Vehicles

EMERALD is a project funded by the European Commission under the FP7 program focusing on energy use optimization on the integration of the electric vehicles into the transport and energy infrastructure. Between the objectives of EMERALD, enhanced power demand prediction and power flow support management system uses the power flow demand simulation platform considered in this paper. The power flow demand simulation platform is a software tool that defines the estimation of electric vehicles power demand according to different conditions as, arrival and departure curves, the estimation of power production based on renewable energy sources and the electricity cost. The tool coordinates scheduling for charging of electric vehicles in order to minimize the recharging cost, considering the energy balance between the generation and demand power.
Functional a posteriori error estimates for discontinuous Galerkin approximations of elliptic problems

In this article, we develop functional a posteriori error estimates for discontinuous Galerkin (DG) approximations of elliptic boundary‐value problems. These estimates are based on a certain projection of DG approximations to the respective energy space and functional a posteriori estimates for conforming approximations developed by S. Repin (see e.g., Math Comp 69 (2000) 481–500). On these grounds, we derive two‐sided guaranteed and computable bounds for the errors in “broken” energy norms. A series of numerical examples presented confirm the efficiency of the estimates. © 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2009
Teleoperation of a humanoid robot using full-body motion capture , example movements , and machine learning

In this paper we present and evaluate a novel method for teleoperating a humanoid robot via a full-body motion capture suit. Our method does not use any a priori analytical or mathematical modeling (e.g. forward or inverse kinematics) of the robot, and thus this approach could be applied to the calibration of any human-robot pairing, regardless of differences in physical embodiment. Our approach involves training a feed-forward neural network for each DOF on the robot to learn a mapping between sensor data from the motion capture suit and the angular position of the robot actuator to which each neural network is allocated. To collect data for the learning process, the robot leads the human operator through a series of paired synchronised movements which capture both the operator’s motion capture data and the robot’s actuator data. Particle swarm optimisation is then used to train each of the neural networks. The results of our experiments demonstrate that this approach provides a fast, effective and flexible method for teleoperation of a humanoid robot.
Modelling Organisational Information Processing - Implications from Organisational Learning, Organisational Psychology and Sociology, Organisational Memory and Knowledge Management -

This paper presents a model for organisational information processing (OIP model) which is used to introduce a theoretical frame for the analysis of the potentials of information and communication technologies, tools and systems to support organisations in organisational information processing. Apart from the well known analysis of individual information processing in the categories of information acquisition, storing and retrieval, additional processes have to be taken into account. These are social interaction and group memory on the group level, information sharing, knowledge acquisition and learning on the organisational level. These processes can be supported by information systems especially designed for these tasks: organisational memory systems. The OIP model is based on theories of organisational psychology and sociology, approaches of organisational learning as well as on the conceptualisation of the tasks information, data and knowledge on the organisational level as used in German business informatics. These are briefly reviewed and characterised according to their contribution to the OIP model. The paper concludes with an outlook on further research on organisational memory systems as planned by the author in order to show some applications of the model.
Social networking and context management for the future 3D Internet

Current trends in 3D visualization merged with internet applications and sensor technologies will soon break the barriers to the widespread acceptance of 3D Internet, and they will enable a full user immersion in the virtual world. However this evolution will impact dramatically on the existing infrastructures since the fruition of 3D content in real time by a huge number of people poses new issues related to the system responsiveness and to the ability of managing context information. In this paper we observe that actions related to the acquisition of context from the physical and from the virtual worlds, as well as actuation in both worlds can be considered as a special case of context management and actuation. For this reason we propose an architecture for the management of such aspects within a unique framework, and an experimental testbed that validates the architecture.
Strong-Cyclic Planning when Fairness is Not a Valid Assumption

We address the class of fully-observable nondeterministic (FOND) planning problems where non-deterministic actions are not guaranteed to display fair behaviour. Typical solutions to FOND planning problems either guarantee goal reachability with a bounded number of transitions (so-called strong acyclic solutions), or are predicated on a fairness assumption that presumes each action effect occurs infinitely often when the action is applied infinite times in the same state (so-called strongcyclic solutions). We introduce the FOND planning model, that extends the FOND model with a more informed description of the action transitions. Solutions to FOND problems guarantee goal reachability, even when the classical fairness assumption is not valid. We characterize different topologies, or classes, of solutions showing that typical strong acyclic, and fair strong-cyclic planning are particular cases. Moreover, we characterize a class of FOND solutions that also solve 1primary normative fault-tolerant problems, and are robust to any finite number of faults during execution. We present algorithms to solve each class of problems. Finally, we present the results of one of our algorithms in the search for so-called normative solutions for a selection of blocksworld problems where the classical fairness assumption is not valid.
Artery : A Data-Centric Architecture for Wireless Sensor Networks

Sensor networks, composed of large amount of micro-sensors, are considered promising, both in academic research and in real life applications. To ensure highly efficient communications between event observers and sensor network users, new infrastructures and algorithms are being developed. This paper describes Artery, a novel architecture that delivers queries and data between multiple observers and multiple mobile users. Simulation results show that Artery outperforms some major data dissemination algorithms.
Context cues for classification of competitive and collaborative overlaps

Being able to respond appropriately to users’ overlaps should be seen as one of the core competencies of incremental dialogue systems. At the same time identifying whether an interlocutor wants to support or grab the turn is a task which comes natu- rally to humans, but has not yet been implemented in such sys- tems. Motivated by this we first investigate whether prosodic characteristics of speech in the vicinity of overlaps are signifi- cantly different from prosodic characteristics in the vicinity of non-overlapping speech. We then test the suitability of differ- ent context sizes, both preceding and following but excluding features of the overlap, for the automatic classification of col- laborative and competitive overlaps. We also test whether the fusion of preceding and succeeding contexts improves the clas- sification. Preliminary results indicate that the optimal context for classification of overlap lies at 0.2 seconds preceding the overlap and up to 0.3 seconds following it. We demonstrate that we are able to classify collaborative and competitive overlap with a median accuracy of 63%.