Miracle-dz/UniFAR-FTUs huggingface dataset:
Memory-based state estimation for handling occlusion during object tracking by Particle Filter

Particle Filter is one of the most widely used algorithm in object tracking, because it can handle the nonlinear and/or non-Gaussian problems. However it fails when the tracked object is occluded by other objects. In order to solve such problems, in this paper, a memory-based state estimation scheme is introduced into the particle filter to estimate the state of the occluded object. When occlusion occurs, the tracked object is located by the states stored in the memory space. And the tracked object can be correctly relocated when recovered from the occlusion. The experimental results show the effects of our proposed method.
Pocket-Based Drug Design: Exploring Pocket Space

The identification and application of druggable pockets of targets play a key role in in silico drug design, which is a fundamental step in structure-based drug design. Herein, some recent progresses and developments of the computational analysis of pockets have been covered. Also, the pockets at the protein–protein interfaces (PPI) have been considered to further explore the pocket space for drug discovery. We have presented two case studies targeting the kinetic pockets generated by normal mode analysis and molecular dynamics method, respectively, in which we focus upon incorporating the pocket flexibility into the two-dimensional virtual screening with both affinity and specificity. We applied the specificity and affinity (SPA) score to quantitatively estimate affinity and evaluate specificity using the intrinsic specificity ratio (ISR) as a quantitative criterion. In one of two cases, we also included some applications of pockets located at the dimer interfaces to emphasize the role of PPI in drug discovery. This review will attempt to summarize the current status of this pocket issue and will present some prospective avenues of further inquiry.
Output feedback variable structure-like control of nonlinear mechanical systems

In this paper, we develop a new output feedback, variable structure-like (discontinuous) tracking controller for a class of uncertain, nonlinear, multi-input multi-output, mechanical systems whose dynamics are first-order differentiable. A novel filter design and Lyapunov-type stability analysis are used to prove semi-global asymptotic tracking. As a by-product of the proposed framework, we also present the design of a new variable structure-like velocity observer that ensures global asymptotic velocity observation.
Design And Implementation of Low-Cost Power Efficient Embedded Control Systems in Domestic Induction Heating Appliances

The proposed modulation technique of power converter topology provides high reliability, excellent performance, minimum energy consumption which reduces switching loss. The Power converter features a full-bridge resonant converter operating with a switching frequency ( ) between 15 kHz and 40 kHz in order to improve efficiency and power density make a suitable solution for domestic induction heating appliances. The digital control systems of these appliances require performing accurate and smooth power control while assuring the safety of the power devices. In order to accomplish, it is necessary to provide the target output power and specific current parameters selected by the user. A/D converter subsystem digitizes the output current. ΣΔ ADCs combines oversampling and the shaping of the quantization noise to achieve high accuracy, which makes them a cost effective and power efficient solution.
A conceptual indexing approach for Arabic texts

Classical IR systems are often based on lexical matching using approaches that rely on purely statistical methods founded on distributions of keywords to calculate the similarity between the query and the documents of the corpus. The relevance of a document according to a query is based on the similarity of vocabulary and not according to the thematic similarity between both. Indeed, a document selected by the IRS relevant shares the same words with the query. Among the research that tried to overcome the limitations of conventional IR, there is an approach called (Concept-Based Information Retrieval) that is characterized by the notion of conceptual space in which documents and queries are represented by opposition to the space of simple words used in conventional IR. The use of external knowledge such as WordNet was the subject of several works in IR, often geared towards improving the precision (WSD: Word-Sense Disambiguation, Conceptual Indexing) and/or improving the recall (query expansion).
UNISM: Unified Scheduling and Mapping for General Networks on Chip

Task scheduling and core mapping have a significant impact on the overall performance of network on chip (NOC). In this paper, a unified task scheduling and core mapping algorithm called UNISM is proposed for different NOC architectures including regular mesh, irregular mesh and custom networks. First, a unified model combining scheduling and mapping is introduced using mixed integer linear programming (MILP). Then, a novel graph model is proposed to consider the network irregularity and estimate communication energy and latency, since the number of network hops is not accurate enough for irregular mesh and custom networks. To make the MILP-based UNISM scalable, a heuristic is employed to speed up our method. Compared with two previous state-of-the-art works, experimental results show that more than 15% and 11.5% improvement on the execution time is achieved with similar energy consumption on average for regular mesh NOC. For irregular and custom NOC, the improvement is 27.3% and 14.5% on the execution time with 24.3% and 18.5% lower energy. Moreover, our method is scalable for large benchmarks in terms of runtime.
The relationship of school-based parental involvement with student achievement: a comparison of principal and parent survey reports from PISA 2012

Abstract This paper explores parental involvement using principal and parent survey reports to examine whether parents’ involvement in their children’s schools predicts academic achievement. Survey data from principals and parents of seven countries from the PISA 2012 database and hierarchical linear modelling were used to analyse between- and within- school variance in students’ math achievement. Factor analysis of both principal and parent responses revealed three dimensions of parental involvement with schools: parent-initiated involvement, teacher-initiated involvement and parent volunteerism. Principal reports of parent-initiated involvement positively predicted between-school differences in student achievement. Within schools, parent reports of teacher-initiated involvement negatively predicted student achievement. The paper shows the importance of understanding the source of information for survey measures. Information on parental involvement from the parent surveys of the PISA study is suitable for describing within-school variation in student achievement, whereas principal reports can be used to predict variation between schools.
Implicit managerial theories about followers and customers

The purpose of this paper is to take a new look at an old idea: since McGregor’s work in the 1960s, it is common knowledge that managers’ implicit theories about their followers can have self-fulfilling consequences. Surprisingly, McGregor’s work has largely remained within the bounds of employee motivation and has not met with a wide response in related fields such as service management. Assuming that managers do not only hold implicit theories of their followers but also of their customers (i.e. implicit customer theories), this paper transfers McGregor’s Theory X and Theory Y to the service context. It further derives a framework of possible consistencies and inconsistencies between management styles and service strategies, depending on implicit managerial theories about the average employee and customer. ,This conceptual paper integrates a management classic, current empirical findings, and media reports into a new line of thought. ,This paper develops and undergirds the thesis that it is conducive to the development of trustful and productive relationships both with customers and followers if managers proceed from confident assumptions about them, thereby activating virtuous circles instead of vicious cycles. ,This paper links concepts from the organizational domain to the service domain. It implies a normative component in arguing for the productive potential of positive and the destructive potential of negative assumptions about both followers and customers. The value of this idea lies in the potential for positive relational dynamics and better customer and workplace relationships.
A metric for self-rightability and understanding its relationship to simple morphologies

To robustly operate in dynamic, unknown environments, robots should be able to autonomously recover from simple errors such as tip-over. Most efforts to date have introduced specific techniques applied as point solutions on simple terrain. For a more general solution, we previously introduced a framework for analyzing and generating solutions to the self-righting problem for a generic robot. In this paper, we turn our attention toward understanding how a robot's morphology affects its ability to self-right. We begin by briefly reviewing our framework, which is used to generate the results within the paper. We then introduce a self-rightability metric that can be used to evaluate a given robot design's potential for self-righting. It can also be used to compare disparate designs. Next, we show how the metric can be used to perform a parametric study covering multiple design variables for a simple robot class. In this way, we hope to enable designers to begin to understand how design parameters such as joint limits, limb length, limb to body mass ratio, limb mass location, and body aspect ratio will affect the robot's ability to self-right on a variety of ground angles. Finally, we show a case study of limb mass and validate results using a modular, 3 degree of freedom physical robot. Ultimately, we hope to enable the production of robots that are more capable of autonomously self-righting.
A Query-Based Summarization Service from Multiple News Sources

It can be time consuming to search Internet news, due to multiple sources reporting repetitive information. Given a query and a set of relevant text articles, query-focused multi-document summarization (QMDS) aims to generate a fluent, well-organized, and compact summary that answers the query. While QMDS helps to summarize search results, most top-performing systems for this purpose remain largely extractive. Extractive summarization extracts a group of sentences and concatenates them. In this paper, we propose a summarization service based on abstractive QMDS using multi-sentence compression (MSC). Our proposed service generates a novel summary representing the gist of the content of the source document(s). Experiments using popular summarization benchmark datasets demonstrate the effectiveness of the proposed service.
Modeling the effect of variable work piece hardness on surface roughness in an end milling using multiple regression and adaptive Neuro fuzzy inference system

Article history: Received July 2 2013 Received in revised format September 7 2013 Accepted November 23 2013 Available online November 26 2013 The aim of this study is to correlate work piece material hardness with surface roughness in prediction studies. The proposed model is for prediction of surface roughness of tool steel materials of hardness 55 HRC to 62 HRC (±2 HRC). The machining experiments are performed under various cutting conditions using work piece of different hardness. The surface roughness of these specimens is measured. The result showed that the influence of work piece material hardness on surface finish is significant for cutting speed and feed in CNC end milling operation. It is also observed that the surface roughness prediction accuracy of Adaptive neuro fuzzy inference system using triangular membership function is better than Gaussian, bell shape membership function and regression analysis. Surface roughness prediction accuracy with material hardness as input parameter is 97.61%. © 2014 Growing Science Ltd. All rights reserved
Hunger in Children in the United States: Potential Behavioral and Emotional Correlates

Objective. Results from a recent series of surveys from 9 states and the District of Columbia by the Community Childhood Hunger Identification Project (CCHIP) provide an estimate that 4 million American children experience prolonged periodic food insufficiency and hunger each year, 8% of the children under the age of 12 in this country. The same studies show that an additional 10 million children are at risk for hunger. The current study examined the relationship between hunger as defined by the CCHIP measure (food insufficiency attributable to constrained resources) and variables reflecting the psychosocial functioning of low-income, school-aged children. Methods. The study group included 328 parents and children from a CCHIP study of families with at least 1 child under the age of 12 years living in the city of Pittsburgh and the surrounding Allegheny County. A two-stage area probability sampling design with standard cluster techniques was used. All parents whose child was between the ages of 6 and 12 years at the time of interview were asked to complete a Pediatric Symptom Checklist, a brief parent-report questionnaire that assesses children's emotional and behavioral symptoms. Hunger status was defined by parent responses to the standard 8 food-insufficiency questions from the CCHIP survey that are used to classify households and children as “hungry,” “at-risk for hunger,” or “not hungry. ” Results. In an area probability sample of low-income families, those defined as hungry on the CCHIP measure were significantly more likely to have clinical levels of psychosocial dysfunction on the Pediatric Symptom Checklist than children defined as at-risk for hunger or not hungry. Analysis of individual items and factor scores on the Pediatric Symptom Checklist showed that virtually all behavioral, emotional, and academic problems were more prevalent in hungry children, but that aggression and anxiety had the strongest degree of association with experiences of hunger. Conclusion. Children from families that report multiple experiences of food insufficiency and hunger are more likely to show behavioral, emotional, and academic problems on a standardized measure of psychosocial dysfunction than children from the same low-income communities whose families do not report experiences of hunger. Although causality cannot be determined from a cross-sectional design, the strength of these findings suggests the importance of greater awareness on the part of health care providers and public health officials of the role of food insufficiency and hunger in the lives of poor children.
A Computational Treatment of Korean Serial Verb Constructions

The so-called serial verb construction (SVC) is a complex predicate structure consisting of two or more verbal heads but denotes one single event. This paper first dis- cusses the grammatical properties of Korean SVCs and provides a lexicalist, construction- based analysis couched upon a typed-feature structure grammar. We also show the results of implementing the grammar in the LKB (Linguistics Knowledge Building) system couched upon the existing the KRG (Korean Resource Grammar) which has been developed since 2003. The implementation results provides us with a feasible direction of expanding the analysis to cover a wider range of relevant data.
An ungreedy Chinese deterministic dependency parser considering long-distance dependency

This paper presents a two-step dependency parser to parse Chinese deterministically. By dividing a sentence into two parts and parsing them separately, the error accumulation can be avoided effectively. Previous works on shift-reduce dependency parser may guarantee the greedy characteristic of deterministic parsing less. This paper improves on a kind of deterministic dependency parsing method to weaken the greedy characteristic of it. During parsing, both forward and backward parsing directions are chosen to decrease the unparsed rate. Support vector machines are utilized to determine the word dependency relations and in order to solve the problem of long distance dependency, a group of combined global features are presented in this paper. The proposed parser achieved significant improvement on dependency accuracy and root accuracy.
Reducing speech recognition costs: By compressing the input data

One of the key constraints of using embedded speech recognition modules is the required computational power. To decrease this requirement, we propose an algorithm that clusters the speech signal before passing it to the recognition units. The algorithm is based on agglomerative clustering and produces a sequence of compressed frames, optimized for recognition. Our experimental results indicate that the proposed method presents a frame rate with average 40 frames per second on medium to large vocabulary isolated word recognition tasks without loss of recognition accuracy which result in up to 60% faster recognition in compare to usual 100 fps fixed frame rate sampling. This value is quite close to the theoretically optimal value of 37.5 frames per second while the best result of former approaches is about 60 frames per second.
An analysis of synergy effects in an omnidirectional modular perception system

The increasing complexity of Advanced Driver Assistance Systems (ADAS) requires new design strategies in order to provide the necessary reliability for safety-related applications. In this paper, the connection of several perception modules to a modular ADAS is proposed. The benefits of such an approach are analyzed on the example of a vision and radar based vehicle & lane detection system. In particular, the effect of algorithmic synergies between the modules is investigated. The performance of the modular perception system is demonstrated using real-world data from the concept vehicle Carai. The results show that the performance and reliability of this approach surpasses the properties of the single modules.
MISSING FEATURE IMPUTATION OF LOG-SPECTRAL DATA FOR NOISE ROBUST ASR

In this paper, we present a missing feature (MF) imputation algorithm for log-spectral data with applications to noise robust ASR. Drawing from previous work [1], we adapt the previously proposed spectrographic reconstruction solution to the liftered log-spectral domain by introducing log-spectral flooring (LS-FLR). LS-FLR is shown to be an efficient and effective noise robust feature extraction technique. When LSFLR is integrated in deriving the novel log-spectral data imputation framework, the overall system is shown to provide significant improvements in noise robust speech recognition.
Adaptation to Speed in Macaque Middle Temporal and Medial Superior Temporal Areas

The response of a sensory neuron to an unchanging stimulus typically adapts, showing decreases in response gain that are accompanied by changes in the shape of tuning curves. It remains unclear whether these changes arise purely due to spike rate adaptation within single neurons or whether they are dependent on network interactions between neurons. Further, it is unclear how the timescales of neural and perceptual adaptation are related. To examine this issue, we compared speed tuning of middle temporal (MT) and medial superior temporal neurons in macaque visual cortex after adaptation to two different reference speeds. For 75% of speed-tuned units, adaptation caused significant changes in tuning that could be explained equally well as lateral shifts, vertical gain changes, or both. These tuning changes occurred rapidly, as both neuronal firing rate and Fano factor showed no evidence of changing beyond the first 500 ms after motion onset, and the magnitude of tuning curve changes showed no difference between trials with adaptation durations shorter or longer than 1 s. Importantly, the magnitude of tuning shifts was correlated with the transient-sustained index, which measures a well characterized form of rapid response adaptation in MT, and is likely associated with changes at the level of neuronal networks. Tuning curves changed in a manner that increased neuronal sensitivity around the adapting speed, consistent with improvements in human and macaque psychophysical performance that we observed over the first several hundred ms of adaptation.
Getting the Mix Right Again: An Updated and Theoretical Rationale for Interaction

No topic raises more contentious debate among educators than the role of interaction as a crucial component of the education process. This debate is fueled by surface problems of definition and vested interests of professional educators, but is more deeply marked by epistemological assumptions relative to the role of humans and human interaction in education and learning. The seminal article by Daniel and Marquis (1979) challenged distance educators to get the mixture right between independent study and interactive learning strategies and activities. They quite rightly pointed out that these two primary forms of education have differing economic, pedagogical, and social characteristics, and that we are unlikely to find a “perfect” mix that meets all learner and institutional needs across all curricula and content. Nonetheless, hard decisions have to be made. Even more than in 1979, the development of newer, cost effective technologies and the nearly ubiquitous (in developed countries) Net-based telecommunications system is transforming, at least, the cost and access implications of getting the mix right. Further, developments in social cognitive based learning theories are providing increased evidence of the importance of collaborative activity as a component of all forms of education – including those delivered at a distance. Finally, the context in which distance education is developed and delivered is changing in response to the capacity of the semantic Web (Berners-Lee, 1999) to support interaction, not only amongst humans, but also between and among autonomous agents and human beings. Thus, the landscape and challenges of “getting the mix right” have not lessened in the past 25 years, and, in fact, have become even more complicated. This paper attempts to provide a theoretical rationale and guide for instructional designers and teachers interested in developing distance education systems that are both effective and efficient in meeting diverse student learning needs.
The Genetic Basis for Variation in Olfactory Behavior in Drosophila melanogaster

The genetic underpinnings that contribute to variation in olfactory perception are not fully understood. To explore the genetic basis of variation in olfactory perception, we measured behavioral responses to 14 chemically diverse naturally occurring odorants in 260400 flies from 186 lines of the Drosophila melanogaster Genetic Reference Panel, a population of inbred wild-derived lines with sequenced genomes. We observed variation in olfactory behavior for all odorants. Low to moderate broad-sense heritabilities and the large number of tests for genotype–olfactory phenotype association performed precluded any individual variant from reaching formal significance. However, the top variants (nominal P < 5×10−5) were highly enriched for genes involved in nervous system development and function, as expected for a behavioral trait. Further, pathway enrichment analyses showed that genes tagged by the top variants included components of networks centered on cyclic guanosine monophosphate and inositol triphosphate signaling, growth factor signaling, Rho signaling, axon guidance, and regulation of neural connectivity. Functional validation with RNAi and mutations showed that 15 out of 17 genes tested indeed affect olfactory behavior. Our results show that in addition to chemoreceptors, variation in olfactory perception depends on polymorphisms that can result in subtle variations in synaptic connectivity within the nervous system.