Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of a Distributed Integrative Architecture for Robotics

The eld of robotics employs a vast amount of coupled sub-systems. These need to interact cooperatively and concurrently in order to yield the desired results. Some hybrid algorithms also require intensive cooperative interactions internally. The architecture proposed lends itself amenable to problem domains that require rigorous calculations that are usually impeded by the capacity of a single machine, and incompatibility issues between software computing elements. Implementations are abstracted away from the physical hardware for ease of development and competition in simulation leagues. Monolithic developments are complex, and the desire for decoupled architectures arises. Decoupling also lowers the threshold for using distributed and parallel resources. The ability to re-use and re-combine components on demand, therefore is essential, while maintaining the necessary degree of interaction. For this reason we propose to build software components on top of a Service Oriented Architecture (SOA) using Web Services. An additional benet is platform independence regarding both the operating system and the implementation language. The robot soccer platform as well as the associated simulation leagues are the target domain for the development. Furthermore are machine vision and remote process control related portions of the architecture currently in development and testing for industrial environments. We provide numerical data based on the Python frameworks ZSI and SOAPpy undermining the suitability of this approach for the eld of robotics. Response times of signicantly
Concept Disambiguation for Improved Subject Access Using Multiple Knowledge Sources

We address the problem of mining text for relevant image metadata. Our work is situated in the art and architecture domain, where highly specialized technical vocabulary presents challenges for NLP techniques. To extract high quality metadata, the problem of word sense disambiguation must be addressed in order to avoid leading the searcher to the wrong image as a result of ambiguous — and thus faulty — metadata. In this paper, we present a disambiguation algorithm that attempts to select the correct sense of nouns in textual descriptions of art objects, with respect to a rich domain-specific thesaurus, the Art and Architecture Thesaurus (AAT). We performed a series of intrinsic evaluations using a data set of 600 subject terms extracted from an online National Gallery of Art (NGA) collection of images and text. Our results showed that the use of external knowledge sources shows an improvement over a baseline.
Minimum Energy Reliable Information Gathering Using Data Fusion Tree in WSNs

Data fusion is widely used in wireless sensor networks. In this paper, we explore the problem of minimum energy reliable information gathering (MERIG) in wireless sensor networks under data fusion tree model. From the perspective of information value, two algorithms, the optimal algorithm and the distributed approximate algorithm are proposed. The optimal algorithm is the optimal solution for MERIG while the distributed algorithm can approximate the optimal well. Using these two schemes, the information reliability can be guaranteed with high energy efficient manner under unreliable wireless environment.
THE EMERGING JVT / H . 26 L VIDEO CODING STANDARD

JVT/H.26L is a current project of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Motion Picture Experts Group (MPEG). The main goals of the new JVT/H.26L standardization effort are a simple and straight forward video coding design to achieve enhanced compression performance and provision of a "network-friendly" video representation addressing "conversational" (video telephony) and "non-conversational" (storage, broadcast, or streaming) applications. Hence, the JVT/H.26L design covers a Video Coding Layer (VCL), which provides the core high-compression representation of the video picture content, and a Network Adaptation Layer (NAL), which packages that representation for delivery over a particular type of network. The JVT/H.26L VCL has achieved a significant improvement in rate-distortion efficiency – providing nearly a factor of two in bit-rate savings against existing standards.
Designing the human-machine interface for highly automated cars — Challenges, exemplary concepts and studies

During the last years, intensive research has been conducted to make high degrees of automation available in cars. However, driver assistance systems today still need the driver to monitor the system. This will most probably change in near future, as highly automated driving becomes available. With the driver out of the control loop, this driving mode has beneficial aspects for the driver and could improve traffic safety as a high portion of traffic accidents are due to human error. On the other hand, high degrees of automation can have detrimental effects which are well known from other domains like aviation. These effects have led to fatal accidents in the past. The authors investigate various aspects of this topic and the corresponding challenges for the human-machine interface in future cars. In this paper, we present three of our research areas: the take-over process, trust in automation and utilization of drivetime. For each area, we explain theoretical background, current challenges and studies we conducted.
Let's stay together: Towards traffic aware virtual machine placement in data centers

As tenants take networked virtual machines (VMs) as their requirements, effective placement of VMs is needed to reduce the network cost in cloud data centers. The cost is one of the major concerns for the cloud providers. In addition to the cost caused by network traffics (N-cost), the cost caused by the utilization of physical machines (PM-cost) is also non-negligible. In this paper, we focus on the optimized placement of VMs to minimize the cost, the combination of N-cost and PM-cost. We define N-cost by various functions, according to different communication models. We formulate the placement problem, and prove it to be NP-hard. We investigate the problem from two aspects. Firstly, we put a special emphasis on minimizing the N-cost with fixed PM-cost. For the case that tenants request the same amount of VMs, we present optimal algorithms under various definitions of N-cost. For the case that tenants require different numbers of VMs, we propose an approximation algorithm. Also, a greedy algorithm is implemented as the baseline to evaluate the performance. Secondly, we study the general case of the VM placement problem, in which both N-cost and PM-cost are taken into account. We present an effective binary-search-based algorithm to determine how many PMs should be used, which makes a tradeoff between PM-cost and N-cost. For all of the algorithms, we conduct theoretical analysis and extensive simulations to evaluate their performance and efficiency.
Hydrothermal systems and mineralization of volcanic arcs : Comparison of West Pacific and Mediterranean arcs

Introduction Hydrothermal systems and their associated metal deposits have been studied at oceanic spreading centers since the late 1970s when they were first discovered. More recently, those studies have been extended to subduction zone hydrothermal systems including active volcanic arcs and back-arc environments. Oceanic spreading centers compose a global ridge system where new ocean crust is formed (divergent boundary) and extends for about 64,000 kilometres (km). Volcanic arc hydrothermal systems form where ocean crust is consumed by subduction (convergent boundary) which creates a chain of volcanoes, both submarine and subaerial, and back-arc spreading in some arc systems (Fig. 1); these two together add another 25,000 km to the zone of global volcanism and hydrothermal activity. Back-arc basins generally form via seafloor spreading, similar to that at oceanic ridges. Recent studies have concentrated on hydrothermal systems in West Pacific and Mediterranean Sea volcanic arc and back-arc basin subduction systems and associated mineral deposits, which range from high-temperature sulphide-sulphate deposits, lowtointermediate temperature sulfur and silica deposits, and low-temperature iron-oxide and manganese-oxide deposits (e.g., Alfieris et al., 2013; Dando et al., 1999; Hein et al., 2000, 2008, 2013; Kilias et al., 2001; Petersen et al., 2013). Here we provide a brief background on hydrothermal systems and then compare Pacific and Mediterranean hydrothermal volcanic arc deposits.
The Global Impact of Quotas

Quotas have become an important mechanism through which women today are entering legislatures worldwide. This study shows that the introduction of quotas has helped overcome constraints on women's representation posed by economic underdevelopment, cultural influences, and even electoral systems. This study also demonstrates that the introduction of quotas offers the most explanatory power for women's representation today, together with electoral systems that allow for greater candidate turnover (i.e., party-list proportional representation systems). The majority of studies explaining women's legislative representation prior to 2000 focused on electoral systems, cultural considerations, and the strength of leftist political parties. Since the mid-1990s, however, an increasing number of countries have introduced gender quotas, which this article incorporates into older models in cross-national multivariate analysis.
Control strategies for multi-frequency power transfer in a smart-transformer-fed low-voltage grid

Smart grids have attracted the attention of the scientific community for years, since the ability to better manage distributed resources in a dynamic grid scenario is of paramount importance. Among the solutions that have been investigated, there is the smart transformer (ST) distribution concept, where an AC/AC power converter substitutes the traditional distribution transformer while enabling additional services. Considering that the ST can generate arbitrary voltage waveforms, power distribution is not restricted anymore to the fundamental frequency, but additional harmonics can be used. This paper analyzes different control possibilities for multi-frequency converters, comparing the results in terms of dynamic performance, control complexity, and communication requirements.
Log-new weibull extension regression models: sensitivity and residual analysis

Standard lifetime distributions usually very place strong restrictions on the data as is well illustrated by their inability to produce bathtub curves, and thus to adequately interpret data with this character. Mudholkar et al. (1995) introduced the exponentiated-Weibull distribution and Xie et al. (2002) proposed the new Weibull extension distribution. The new Weibull extension distribution with parameters λ, α and τ considers that life time T has a density function given by
Human Endogenous Retrovirus (HERVK9) Structural Polymorphism With Haplotypic HLA-A Allelic Associations

The frequency and HLA-A allelic associations of a HERVK9 DNA structural polymorphism located in close proximity to the highly polymorphic HLA-A gene within the major histocompatibility complex (MHC) genomic region were determined in Japanese, African Americans, and Australian Caucasians to better understand its human population evolutionary history. The HERVK9 insertion or deletion was detected as a 3′ LTR or a solo LTR, respectively, by separate PCR assays. The average insertion frequency of the HERVK9.HG was significantly different (P < 1.083e−6) between the Japanese (0.59) and the African Americans (0.34) or Australian Caucasians (0.37). LD analysis predicted a highly significant (P < 1.0e−5) linkage between the HLA-A and HERVK9 alleles, probably as a result of hitchhiking (linkage). Evolutionary time estimates of the solo, 5′ and 3′ LTR nucleotide sequence divergences suggest that the HERVK9 was inserted 17.3 MYA with the first structural deletion occurring 15.1 MYA. The LTR/HLA-A haplotypes appear to have been formed mostly during the past 3.9 MY. The HERVK9 insertion and deletion, detected by a simple and economical PCR method, is an informative genetic and evolutionary marker for the study of HLA-A haplotype variations, human migration, the origins of contemporary populations, and the possibility of disease associations.
A stroke extraction method for multifont Chinese characters based on the reduced special interval graph

We describe a new method for representation of an image pattern, which we call the reduced special interval graph (RSIG). Any binary image pattern can be easily converted into a RSIG. Based on the RSIG, we can enlarge the scope of vision and process a much greater zone of the image. This helps us properly extract the feature of the image and identify the image pattern. We apply the RSIG to help us extract the strokes of Chinese characters by incorporating some knowledge about the structure of Chinese characters. We found this method can not only heuristically extract strokes but also heuristically eliminate noises including those added to strokes for the artistic sake. Experimental results reveal that the method based on the RSIG can extract the strokes of Chinese characters effectively and efficiently. Moreover, the RSIG can be applied to many other application areas, and it is an effective representation method in pattern recognition and image processing. >
Runtime optimisation in WSNs for load balancing using pheromone signalling

Wireless Sensor Networks (WSNs) consist of multiple, distributed nodes each with limited resources. With their strict resource constraints and application-specific characteristics, WSNs contain many challenging trade-offs. This paper proposes a bio-inspired load balancing approach, based on pheromone signalling mechanisms, to solve the trade-off between service availability and energy consumption. We explore the performance consequences of the pheromone-based load balancing approach using: 1) a system-level simulator; 2) deployment of real sensor testbeds to provide a competitive analysis of these evaluation methodologies. The effectiveness of the proposed algorithm is evaluated with different scenario parameters and the required performance evaluation techniques are investigated on case studies based on sound sensors.
Domain Specific Word Extraction from Hierarchical Web Documents: A First Step Toward Building Lexicon Trees from Web Corpora

Domain specific words and ontological information among words are important resources for general natural language applications. This paper proposes a statistical model for finding domain specific words (DSW s) in particular domains, and thus building the association among them. When applying this model to the hierarchical structure of the web directories node-by-node, the document tree can potentially be converted into a large semantically annotated lexicon tree. Some preliminary results show that the current approach is better than a conventional TF-IDF approach for measuring domain specificity. An average precision of 65.4% and an average recall of 36.3% are observed if the top-10% candidates are extracted as domain-specific words. 1 Domain Specific Words and Lexicon Trees as Important NLP Resources Domain specific words (DSW s) are important anchoring words for natural language processing applications that involve word sense disambiguation (WSD). It is appreciated that multi-sense words appearing in the same document tend to be tagged with the same word sense if they belong to the same common domain in the semantic hierarchy (Yarowsky, 1995). The existence of some DSW s in a document will therefore be a strong evidence of a specific sense for words within the document. For instance, the existence of basketball in a document would strongly suggest the sport sense of the word ( Pistons ), rather than its mechanics sense. It is also a personal belief that DSW-based sense disambiguation, document classification and many similar applications would be easier than sense-based models since sense-tagged documents are rare while domain-aware training documents are abundant on the Web. DSW identification is therefore an important issue. On the other hand, the semantics hierarchy among words (especially among sets of domain specific words) as well as the membership of domain specific words are also important resources for general natural language processing applications, since the hierarchy will provide semantic links and ontological information (such as is-A and part-of relationships) for words, and, domain specific words belonging to the same domain may have the synonym or antonym relationships. A hierarchical lexicon tree (or a network, in general) (Fellbaum, 1998; Jurafsky and Martin, 2000), indicative of sets of highly associated domain specific words and their hierarchy, is therefore invaluable for NLP applications. Manually constructing such a lexicon hierarchy and acquiring the associated words for each node in the hierarchy, however, is most likely unaffordable both in terms of time and cost. In addition, new words (or new usages of words) are dynamically produced day by day. For instance, the Chinese word (pistons) is more frequently used as the sport or basketball sense (referring to the Detroit
FACIAL EXPRESSION RECOGNITION INTELLIGENT SECURITY SYSTEM FOR REAL TIME SURVEILLANCE

Facial Expression Recognition is a part of biometric authentication that focuses on uniquely recognizing human facial appearance based upon one or more intrinsic physical or behavioral traits and inside emotions portrayed on one’s face. This paper explains on research based on improving current surveillance systems by adding facial expression recognition to make a system that will detect a person’s expression (who has intentions of causing harm) and report to the securities before the person can commit any prohibited work. The system captures ones feeling/expressions through a camera and send the footage for preprocessing before it can be extracted to see if the emotion/expression captured has the intentions of causing harm.
On the co-existence of distributed and centralized routing control-planes

Network operators can and do deploy multiple routing control-planes, e.g., by running different protocols or instances of the same protocol. With the rise of SDN, multiple control-planes are likely to become even more popular, e.g., to enable hybrid SDN or multi-controller deployments. Unfortunately, previous works do not apply to arbitrary combinations of centralized and distributed control-planes. In this paper, we develop a general theory for coexisting control-planes. We provide a novel, exhaustive classification of existing and future control-planes (e.g., OSPF, EIGRP, and Open-Flow) based on fundamental control-plane properties that we identify. Our properties are general enough to study centralized and distributed control-planes under a common framework. We show that multiple uncoordinated control-planes can cause forwarding anomalies whose type solely depends on the identified properties. To show the wide applicability of our framework, we leverage our theoretical insight to (i) provide sufficient conditions to avoid anomalies, (ii) propose configuration guidelines, and (iii) define a provably-safe procedure for reconfigurations from any (combination of) control-planes to any other. Finally, we discuss prominent consequences of our findings on the deployment of new paradigms (notably, SDN) and previous research works.
An Algorithm to Construct FP-Tree on VODCA

To construct FP-Tree in mining frequent pattern, we propose a parallel algorithm CFPV (Construct FP-Tree on VODCA) for construct FP-Tree. This method is based on a new parallel computing environment on the distributed shared memory, called View-Oriented, Distributed, Cluster-based Approach to parallel computing (VODCA). It discusses the fact of views division and the results when generate FP-Tree on VODCA, and discusses the dynamic task allocation strategy of the algorithm. The experimental results prove the correctness and effectiveness of CFPV algorithm.
Analysis and Design of a Transverse-Flux Dual Rotor Machine for Power-Split Hybrid Electric Vehicle Applications

A novel compound-structure transverse-flux permanent-magnet synchronous machine (CS-TFPMSM) is proposed in this paper, which is used in hybrid electric vehicles (HEVs) to fulfill the power-split function. The key component of the CS-TFPMSM is a brushless transverse-flux dual rotor machine (TFDRM). The TFDRM originates from the transverse-flux machines, and is capable of speed adjustment between the transverse-flux rotor and the permanent-magnet rotor without using any brushes. The structure and principle of the TFDRM are described. The torque equations of the TFDRM are deduced, which are different from those of traditional machines. Based on the investigation, the TFDRM tends to have high leakage and a poor power factor. The method to obtain high power factor is discussed. The back electromotive force (BEMF) and torque of the TFDRM are simulated with the variation of parameters, such as pole-pair number, width of the permanent magnets (PMs), and so on. A prototype of a 10kW TFDRM is designed.
White-tailed deer attacking humans during the fawning season: a unique human–wildlife conflict on a university campus

Human-wildlife confl icts associated with suburban white-tailed deer (Odocoileus virginianus) populations have increased in the last 20 years. Primary threats to human health and safety associated with overabundant deer populations include deer-vehicle collisions, attacks on humans, disease, and damage to native and ornamental vegetation. During the fawning seasons (May-June) of 2005 and 2006, 13 confi rmed incidences of white-tailed deer attacking humans occurred on the campus of Southern Illinois University-Carbondale. To our knowledge, no report exists that documents free-ranging does attacking humans during the fawning season. The attacks occurred at multiple locations on campus, with injuries to humans, including minor scrapes, bruises, broken bones, and skin lacerations requiring stitches. Wildlife managers may face the increased likelihood of aggressive behavior from deer directed towards humans as deer and human populations increase and come into closer contact with each other.
A Phenomic Algorithm for Reconstruction of Gene Networks

Abstract — The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.
Doing innovation in the wild

Doing research 'in the wild is becoming an increasingly popular approach towards developing innovative computing systems and applications. This paper reflects upon a research project conducted in the wild, and key aspects of the work involved in making the project work, to examine current tropes about the approach. It suggests that doing research in the wild is rather more complicated than is reflected in current understandings, and that even greater involvement of ethnographers, computer scientists, software engineers and other disciplines operating within systems design is needed if innovation is to be effectively driven within and by real world contexts of use.