Miracle-dz/UniFAR-FTUs huggingface dataset:
An effective algorithm of tracking multiple objects in occlusion scenes

In the field of Computer Vision (CV), multiple object tracking has been one of the hot issues, and it is especially one of difficulties to effectively track multiple objects in occlusion scenes. In this paper, we propose an effective algorithm to dissolve the occlusion issue in tracking multiple objects, combining the feature of overlap region with the feature of RGB-based dominant color histogram (DCH). Firstly, occlusion can be judged by computing the size of overlap region. Secondly, if occlusion takes place, RGB-based DCH can be used to estimate the likelihood of occluded objects. And then, the occluded objects are tracked effectively. Additionally, RGB-based DCH is only computed when merging and splitting, and the computational complexity is effectively reduced. From the experimental results, the proposed algorithm can improve the validity and robustness of tracking multiple objects.
Firm size, technological intensity of sector and relational competencies to innovate: Evidence from French industrial innovating firms

This article stresses the importance of competencies, specifically relational competencies, in the innovation process. Innovation output is not only produced by R&D but also often supported by networks and interfirm relations that differ according to the size of the firm. We perform an empirical analysis of the relationship between French industrial firms’ relational competencies and their sizes. Our results show that the size and the technological intensity of their sector are strongly correlated with relational competencies. We give also some statistical results concerning the relationship between tacit and codified procedures and external versus internal sources of the competencies.
The Infusion of Inquiry-Based Learning into School-Based Agricultural Education: A Review of Literature.

Demands for increases in student achievement have led education professionals to incorporate various and rigorous teaching strategies into classrooms across the United States. Within schoolbased agricultural education (SBAE), agriculture teachers have responded to these challenges quite well. SBAE incorporates a wide variety of teaching and learning strategies, theories, and ideas into its conceptual framework. One such teaching and learning strategy is referred to as inquiry-based learning, commonly known in SBAE as problem-based learning. This method emphasizes cognitive development, critical thinking, and intellectual growth in students. The purpose of this study was to develop an understanding of the emergence and current utilization of inquiry-based learning in SBAE. We found that inquiry-based learning has been a long-standing staple in SBAE, particularly in terms of increasing the achievement of agricultural students. As a result, a model of the use of inquiry-based learning in SBAE programs was developed. Recommendations, discussion, and implications for research and classroom practice were included in this study.
A hybrid reactive routing protocol for Mobile Ad-hoc Networks

A lot of research effort has been put by researchers in developing routing protocols for Mobile Ad-hoc Networks (MANETs). Each protocol proposed and designed so far has its own merits and demerits. Researchers around the world continue to develop novel, advanced routing protocols that can route messages towards their destination in an efficient way while consuming minimum amounts of resources. In this work we take two well known MANET routing protocols, namely, the Ad-hoc On-demand Distance Vector routing protocol and the Epidemic routing protocol, and combine their preferred properties to formulate a new Hybrid routing protocol. We propose this routing protocol again as a reactive protocol with the objective of increasing the message delivery ratio while utilizing minimum mobile device resources. Our extensive simulation based experimental studies show that the newly proposed Hybrid protocol outperforms the other two protocols in many aspects under various testing scenarios.
From user to character: an investigation into user-descriptions in scenarios

When I ﬁrst read the script of Thelma andLouise I was drawn into the story. I immedi-ately imagined the characters as realpersons and I was so interested in whathappened to them that I continued readinguntil the end. As I read I tried to ﬁgure out inmy imagination why Thelma and Louiseacted as they did and what did motivatethem, a long time before the script gave meany clues. This script is what, in movieterms, is called a good read.
Dynamics of Industry and Innovation: Organizations, Networks and Systems Strategic Organization: a Field in Search of Micro- Foundations Strategic Organization: a Field in Search of Micro-foundations

Organizations are made up of individuals, and there is no organization without individuals. There is nothing quite as elementary; yet, this elementary truth seems to have been lost in the increasing focus on structure, routines, capabilities, culture, institutions, and various other collective conceptualizations in much of recent strategic organization research. It is not overstating the matter too much to say that " organization " has generally entered the field of strategy in the form of various aggregate concepts. Steve Tallman for helpful comments. A version of this essay was presented at the 2004 Academy of Management conference in the BPS symposium (organized by Teppo Felin and Jamal Shamsie) – " The Role of Individual Stakeholders in Value Creation and Appropriation, " and at seminars at Copenhagen Business School and Bristol University Business School. Thanks to participants for helpful comments. The usual disclaimer applies.
A Novel Mixture of Experts Model Based on Cooperative Coevolution

Combining several suitable neural networks can enhance the generalization performance of the group when compared to a single network alone. However it remains a largely open question, how best to build a suitable combination of individuals. Jacobs and his colleagues proposed the Mixture of Experts (ME) model, in which a set of neural networks are trained together with a gate network. This tight coupling mechanism enables the system to (i) encourage diversity between the individual neural networks by specializing them in different regions of the input space, and (ii) allow for a “good” combination weights of the ensemble members to emerge by training the gate, which computes the dynamic weights together with the classifiers. In this paper, we have wrapped a Cooperative Coevolutionary (CC) algorithm around the basic ME model. This CC layer allows better exploration of the weight space, and hence, an ensemble with better performance. The results show that CC-ME is better on average than the original ME on a number of classification problems. We have also introduced a novel mechanism for visualizing the modular structures that emerged from the model.
A Vision Approach for Expiry Date Recognition using Stretched Gabor Features

Product"expiry date represent important information for products consumption. They must contain clear information in the label. The expiry date information stamped on the cover of product faced some challenges due to their writing in pencil and distorted characters. In this paper, an automated vision approach for recognizing expiry date numerals of industrial product is presented. The system consists of four stages namely, numeral string pre"proc essing, numerals string segmentation, features extraction and numeral recognition. In pre"processing module, we convert the im age to binary image based on threshold. A vertical projection process is adopted to isolate numerals, in the segmentation module. In the features extraction module, Fourier Magnitude (FM), Local Energy (LE) and Complex Moments (CM) derived from Stretched Gabor (S"Gabor) filters outputs are extracted at various filter orientations. Also, the mean and the variance of each feature map are extracted. The recognition process is achieved by classifying the extracted features, which represent the numeral image, with trained Multilayer Neural Network (MNN) using k"fol d cross validation procedure. Through experiments, we demonstrate the richness of the S"Gabor features of information is highlighted. Consequently, the set of features shows its usefulness for practical usage. Keyword : Computer vision, FM, CM, LE, numeral recognition, NN, S"Gabor filters.
Trajectories of physical activity in Montreal adolescents from age 12 to 17 years.

BACKGROUND Despite the benefits of physical activity, many Canadian adolescents are inactive and rates of inactivity increase with age. Few studies describe the pattern of change in physical activity as a function of age during adolescence. METHODS Data were drawn from the Nicotine Dependence in Teens Study. The analytic sample included 1206 adolescents who completed a 7-day physical activity recall up to 4 times per year over 5 years. Individual growth models, analyzed using multilevel models for change, were developed separately by sex controlling for season. RESULTS Physical activity levels through adolescence were best described by a cubic function. Levels increased from age 12 to a peak at approximately age 13.5, decreased to age 16.5, and increased again to age 17. Activity participation was highest in the spring and lowest during fall and winter. Substantial within- and between-subject heterogeneity in the trajectories was evident. CONCLUSION Adolescent physical activity follows a complex, curvilinear pattern in both males and females, with considerable variation within- and between-persons.
DECOMPOSING LORENZ AND CONCENTRATION CURVES *

We decompose the Lorenz curve and its associated concentration curve by population subgroups. To illustrate these decompositions, we examine changes in earnings inequality among West Germans, East Germans, and foreign guest workers during the recent German unification. We show that East German earnings have become less concentrated in the lower deciles of the overall German earnings distribution, while the earnings of West Germans and foreign guest workers have become more concentrated in the lower deciles. * The authors would like to thank two anonymous referees for their helpful comments.
Multiplex picoliter-droplet digital PCR for quantitative assessment of DNA integrity in clinical samples.

BACKGROUND Assessment of DNA integrity and quantity remains a bottleneck for high-throughput molecular genotyping technologies, including next-generation sequencing. In particular, DNA extracted from paraffin-embedded tissues, a major potential source of tumor DNA, varies widely in quality, leading to unpredictable sequencing data. We describe a picoliter droplet-based digital PCR method that enables simultaneous detection of DNA integrity and the quantity of amplifiable DNA. METHODS Using a multiplex assay, we detected 4 different target lengths (78, 159, 197, and 550 bp). Assays were validated with human genomic DNA fragmented to sizes of 170 bp to 3000 bp. The technique was validated with DNA quantities as low as 1 ng. We evaluated 12 DNA samples extracted from paraffin-embedded lung adenocarcinoma tissues. RESULTS One sample contained no amplifiable DNA. The fractions of amplifiable DNA for the 11 other samples were between 0.05% and 10.1% for 78-bp fragments and ≤1% for longer fragments. Four samples were chosen for enrichment and next-generation sequencing. The quality of the sequencing data was in agreement with the results of the DNA-integrity test. Specifically, DNA with low integrity yielded sequencing results with lower levels of coverage and uniformity and had higher levels of false-positive variants. CONCLUSIONS The development of DNA-quality assays will enable researchers to downselect samples or process more DNA to achieve reliable genome sequencing with the highest possible efficiency of cost and effort, as well as minimize the waste of precious samples.
Emerging understandings of mindfulness through experiential awareness

ABSTRACT Mindfulness practices are increasingly used in classrooms to enhance the well-being dimensions of learning environments. New Zealand policy documents draw on a bicultural perspective that promotes a holistic framing of well-being. This paper will consider the transformative possibilities of a mindfulness-based breathing intervention in two New Zealand classrooms of students aged between 10 and 12 years old. Operational definitions of mindfulness include awareness of emotional, cognitive, and physical experiences rather than a focus on a state of mind. Using authentic inquiry, we draw on multi-theoretical and multi-methodological perspectives to explore observing/noticing/attending to sensations/perceptions/thoughts/feelings associated with a classroom mindfulness intervention. Specifically, we examine students’ increased awareness and evolving understandings of mind | body connections that emerged during cogenerative dialoguing. We found that students puzzled over whether it is possible to separate physical, mental and emotional states. We consider the implications of the mindfulness-breathing intervention in generating participants’ insights into well-being and wellness.
New Results in Tropical Discrete Geometry

Following the recent work of Develin and Sturmfels and others (see, e.g., [10, 16, 2, 11]), we investigate discrete geometric questions over the tropical semiring (R, min, +). Specifically, we obtain the following tropical analogues of classical theorems in convex geometry: a separation theorem for a pair of disjoint tropical polytopes by tropical halfspaces and tropical versions of Radon’s lemma, Helly’s theorem, the Centerpoint theorem, and Tverberg’s theorem, including algorithms to find tropical centerpoints and Tverberg points. We also prove tropical analogues of the colored Carathéodory and colored Tverberg theorems. Furthermore, we study the tropical analogues of k-sets and levels in halfspace arrangements and obtain tight bounds of Θ(nd−1) for the number of tropical halving sets in any fixed dimension d.
Multiagent Distributed Ontology Learning

In this paper, we describe a framework for distributed ontology learning embedded in a multiagent environment. The objective of this framework is to improve communication and understanding among the agents while preserving agent autonomy. Each agent maintains a dictionary for its own experience and a translation table. The dictionary allows the agent to compare and discover relationships between a pair of words or concepts, while the translation table enables the agent to learn and record (a selected portion of) the vocabulary of its neighbors that is useful for the collaboration among the agents. The motivation for this distributed ontology learning is that each agent has its own experience and thus learns its own ontology depending on what it has been exposed to. As a result, different agents may use different words to represent the same experience. When two agents communicate, agent A may not understand what agent B and that hinders collaboration. However, equipped with the distributed ontology learning capabilities, agents are able to evolve independently their own ontological knowledge while maintaining translation tables through learning to help sustain the collaborative effort.
A Study of the Factors Influencing Forest Farmers Information Technology Adoption

Information technology is one of the most important factors that have been impacting the development of forestry construction, with forest farmers playing an increasingly crucialrole in promotion of information technology. Survey data in this paper, collected from Yongan County and Youxi County in Fujian Province, usescombinedRough Set Theory (RST) andSupport Vector Machine (SVM), applied for reduction of influential factors of information technology adoption behavior of forestry farmers. The result shows factors, i.e.age, education, highest degree of the family, average annual income, forestland area, average annual income of forestland, status of fixed phone, average spending on mobile phone per month, status of cable TV and connection to the Internet, are of key influential in forestry farmers’ decision of information technology adoption. Keyword:Influential factors; information technology adoption; rough set theory; support vector machine
Korean Version of the ABILOCO Questionnaire in the Assessment of Locomotion in Hemiplegic Stroke Patients

Objective To investigate the intra- and inter-rater reliability of the Korean version of the ABILOCO questionnaire (K-ABILOCO). Methods The original ABILOCO questionnaire was translated into Korean and back-translated into English. Stroke patients (n=30) with hemiplegia were evaluated using the K-ABILOCO at one week interval. At each visit, the physiatrist also evaluated patient performance of the activities described in the K-ABILOCO, and the total logit scores were recorded. The total scores were used to evaluate intraclass correlation (ICC). Test-retest scores and each test scores were compared to obtain the intra- and inter-rater reliability. Results The K-ABILOCO showed good intra-rater correlation at one week interval in both patient and physiatrist evaluations (ICC=0.81, 0.91), respectively. It also showed a high inter-rater correlation between the patient and physiatrist at both the first and second visits (ICC=0.76, 0.84), respectively. Conclusion The K-ABILOCO is a useful tool that may reliably evaluate the locomotion ability in hemiplegic stroke patients.
Orchestrator: Guarding Against Voltage Emergencies in Multithreaded Applications

Voltage emergency (VE) has become a critical challenge with decreasing feature size and increasing power capacity. Destructive core interference is one main source of VE in multicore processors. We observed that the applications following single program and multiple data programming model tend to spark domain-wide destructive core interference because multiple threads exhibit similar power activity. We analyze and quantify this effect and propose one low-cost solution, Orchestrator, to avoid voltage droop synergy among cores. Orchestrator leverages the thread diversity to smooth voltage droops in multicore architectures based on thread scheduling. The thread migration impact on performance is also considered. Experimental results show that Orchestrator can significantly reduce VEs, thereby improving performance.
Federal Reserve Bank of New York Staff Reports Housing Busts and Household Mobility: an Update Housing Busts and Household Mobility: an Update

This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in this paper are those of the authors and are not necessarily reflective of views at the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. Abstract This paper provides updated estimates of the impact of three financial frictions—negative equity, mortgage lock-in, and property tax lock-in—on household mobility. We add the 2009 wave of the American Housing Survey (AHS) to our sample and also create an improved measure of permanent moves in response to Schulhofer-Wohl's (2011) critique of our earlier work (2010). Our updated estimates corroborate our previous results: Negative equity reduces household mobility by 30 percent, and $1,000 of additional mortgage or property tax costs reduces household mobility by 10 to 16 percent. Schulhofer-Wohl's finding of a slight positive correlation between mobility and negative equity appears due to a large fraction of false positives, as his coding methodology has the propensity to misclassify almost half of the additional moves it identifies relative to our measure of permanent moves. This also makes his mobility measure dynamically inconsistent, as many transitions originally classified as a move are reclassified as a nonmove when additional AHS panels become available. We conclude with directions for future research, including potential improvements to measures of household mobility. The views expressed in this paper are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System.
Speech recognition techniques for a sign language recognition system

One of the most significant differences between automatic sign language recognition (ASLR) and automatic speech recognition (ASR) is due to the computer vision problems, whereas the corresponding problems in speech signal processing have been solved due to intensive research in the last 30 years. We present our approach where we start from a large vocabulary speech recognition system to profit from the insights that have been obtained in ASR research. The system developed is able to recognize sentences of continuous sign language independent of the speaker. The features used are obtained from standard video cameras without any special data acquisition devices. In particular, we focus on feature and model combination techniques applied in ASR, and the usage of pronunciation and language models (LM) in sign language. These techniques can be used for all kind of sign language recognition systems, and for many video analysis problems where the temporal context is important, e.g. for action or gesture recognition. On a publicly available benchmark database consisting of 201 sentences and 3 signers, we can achieve a 17% WER.
Tachyon condensation in the D 0 / D 4 system

The D0/D4 system with a Neveu-Schwarz B-field in the spatial directions of the D4-brane has a tachyon in the spectrum of the (0,4) strings. The tachyon signals the instability of the system to form a bound state of the D0-brane with the D4-brane. We use the Wess-Zumino-Witten like open superstring field theory formulated by Berkovits to study the tachyon potential for this system. The tachyon potential lies outside the universality class of the D-brane anti-D-brane system. It is a function of the B-field. We calculate the tachyon potential at the zeroth level approximation. The minimum of the tachyon potential in this case is expected to reproduce the mass defect involved in the formation of the D0/D4 bound state. We compare the minimum of the tachyon potential with the mass defect in three cases. For small values of the B-field we obtain 70% of the expected mass defect. For large values of the B-field with Pf(2παB) > 0 the potential reduces to that of the D-brane anti-D-brane reproducing 62% of the expected mass defect. For large values of the B-field with Pf(2παB) < 0 the minimum of the tachyon potential gives 25% of the expected mass defect. At the tachyon condensate we show that the (0,4) strings decouple from the low energy dynamics.
Long-term cooperative tracking using multiple unmanned aerial vehicles

In this paper, we study the long-term cooperative tracking in large areas using multiple unmanned aerial vehicles (UAVs). Firstly, a hybrid tracking algorithm, which switches between a correlation filters based tracker and a cascaded detector, is developed for the robust long-term tracking using a single UAV. Then, a centralized cooperation strategy is proposed to achieve cooperative tracking using multiple UAVs. Finally, the developed algorithms are demonstrated using both a public database and a laboratory mock-up.
Real-time GPS receiver based on a radiation tolerant microprocessor

This paper describes the design and implementation of a prototype GPS receiver for space applications using a radiation tolerant microprocessor. The special characteristics of space environment were considered during design. All the modules necessary for basic functionality were implemented: signal acquisition, synchronization, tracking, ephemeris decodification, and navigation solution calculation. All of these modules were separately validated using actual satellite signals. The presented results show that the receiver achieves reliable performance.