Miracle-dz/UniFAR-FTUs huggingface dataset:
Geometry-based static hand gesture recognition using support vector machine

Static hand gesture recognition plays an important role in developing a system for human-computer interaction. Besides, such systems can be also used by the deaf community in order to convey information through gestures instead of words. A vision-based processing of hand gesture recognition consists of three main stages: preprocessing, feature extraction and identification. In this paper, the first stage involves following two sub-stages: segmentation which locates hand using color information and extracts its silhouette; separation that separates arm, the part with less information, based on geometrical properties. In the second stage, features which extracted from hand-without-arm are general (ratio of width to height, wrist angle and number of fingers) and detailed (calculated based on fingertips and cross sections) characteristics. Finally, support vector machine model with "max-wins" voting strategy is used to classify the hand gestures. The experiment is conducted on color image dataset of Polish Ministry of Science and Higher Education, with 89.5% classification accuracy.
Investigating the Change-Proneness of Service Patterns and Antipatterns

Like any other software systems, service-based systems (SBSs) evolve frequently to accommodate new user requirements. This evolution may degrade their design and implementation and may cause the introduction of common bad practice solutions -- antipatterns -- in opposition to patterns which are good solutions to common recurring design problems. We believe that the degradation of the design of SBSs does not only affect the clients of the SBSs but also the maintenance and evolution of the SBSs themselves. This paper presents the results of an empirical study that aimed to quantify the impact of service patterns and antipatterns on the maintenance and evolution of SBSs. We measure the maintenance effort of a service implementation in terms of the number of changes and the size of changes (i.e., Code churns) performed by developers to maintain and evolve the service, two effort metrics that have been widely used in software engineering studies. Using data collected from the evolutionary history of the SBS FraSCAti, we investigate if (1) services involved in patterns require less maintenance effort, (2) services detected as antipatterns require more maintenance effort than other services, and (3) if some particular service antipatterns are more change-prone than others. Results show that (1) services involved in patterns require less maintenance effort, but not at statistically significant level, (2) services detected as antipatterns require significantly more maintenance effort than non-antipattern services, and (3) services detected as God Component, Multi Service, and Service Chain antipatterns are more change-prone (i.e., Require more maintenance effort) than the services involved in other antipatterns. We also analysed the relation between object-oriented code smells and service patterns/antipatterns and found a significant difference in the proportion of code smells contained in the implementations of service patterns and antipatterns.
International student networks as transnational social capital: illustrations from Japan

ABSTRACT This paper examines how social isolation in a non-Anglophone context where English is not the main language of instruction for local students but is for international students, has unintended consequences for social capital formation among the latter. What factors influence international student network formation in such places where linguistic barriers are institutionalised and what are their consequences not only during college but beyond, in shaping students’ career plans? Using qualitative interview data with 67 international (originating from Asian countries) and domestic students in Japanese universities, we find that such institutional barriers negatively promote greater isolation of international students but positively encourage the formation of diverse multinational ties – a process through which international students gain ideas, confidence and direction regarding their post-graduation career plans to work transnationally.
Wildfire Outreach and Citizen Entrepreneurs in the Wildland–Urban Interface: A Cross-Case Analysis in Colorado

Due to rapid growth in the wildland-urban interface (WUI), the risk to lives and property from wildfires is increasing in the western United States. While previous studies have identified factors that influence residents’ perceptions of wildfire risk and responsibility for mitigation, less research has been conducted on how mitigation information is disseminated to residents or the most effective strategies for doing so. During an examination of two case studies of catastrophic wildfires in Colorado, an important actor involved in wildfire outreach emerged that we label the citizen entrepreneur. Citizen entrepreneurs are highly motivated community members who can help resource-constrained wildfire agencies encourage mitigation on private property by directly engaging with WUI residents. Using data from interviews with wildfire professionals and focus groups with residents, this research note introduces the concept of citizen entrepreneurs and provides an initial examination of the important role they can play in wildfire outreach.
Cosmological Evolution on Self-Tuned Branes and the Cosmological Constant

Weconsiderthecosmologicalevolutionofabulkscalareldandordinary matterlivingonthebraneworldinthelightoftheconstraintsimposedbythematter dominated cosmological evolution and a small cosmological constant now. We rule outmodelswithaself-tunedminimumofthefourdimensionalpotentialastheywould lead to rapid oscillations of the Hubble parameter now. A more natural framework is provided by supergravity in singular spaces where the brane coupling and the bulkpotentialarerelatedbysupersymmetry, leadingtoafourdimensionalrun-away potential. For late times we obtain an accelerating universe due to the breaking of supersymmetry on the brane with an acceleration parameter of q0 = 4=7and associated equation of state ! = 5=7.
Research on Default Probability of Emerging Technology Firms

Many emerging technology firms (ETF) are usually indebted and on deficit at the early stage due to the market or technology factors. In this research, we use stochastic integral techniques to measure the default probability of these ETF before the maturity date of debt. By measuring default probability, the credit risk of the ETF can be predicted and assessed.
A texture and curvature bimodal leaf recognition model for identification of Costa Rican plant species

In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap's underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant.
A Multiscale Approach to Emerging Market Pricing

Market risk measurement has a long tradition in finance and it has been drawing the attention of many academic studies since Markowitz (1952). But the CAPM model (and derived models) assumptions have been targets of much criticism, in the sense that beta estimation may be imprecise. The supposition of investor's homogenous expectations is one of its problems, knowing that investors have different profiles concerning risk exposure and time horizon. Thus, this article aims to verify the scale differences of emerging markets risk pricing based on the international CAPM model. To perform this analysis, it was used wavelet decomposition and panel regressions. The results confirm some literature trends regarding the beta tendency to increase at lower frequencies, as well as the best fit(R2). Additionally, we bring a unique contribution in relation to the long term leverage effect, showing that this form of risk affects only the long-term investors, causing a risk exposure not verified in the short term.
Elderly humans exposed to concentrated air pollution particles have decreased heart rate variability

Air pollution particles are thought to kill >500,000 people worldwide each year. The population most at risk appears to be elderly people with respiratory and cardiovascular disease. As yet, no commonly accepted mechanism has been proposed which can explain the cause of these deaths. Heart rate variability (HRV) was assessed in healthy elderly adults between the ages of 60 and 80 who were exposed twice for 2 h: once to clean air and once to concentrated ambient air pollution particles (CAPS). Changes in HRV were measured immediately before, immediately following, and 24 h after exposure. Elderly subjects experienced significant decreases in HRV in both time and frequency domains immediately following exposure. Some of these changes persisted for at least 24 h. These data were compared with HRV data collected from young healthy volunteers exposed to CAPS in a previous study, in which no CAPS-induced changes in HRV were found. These concentrated ambient air pollution particle-induced changes in heart rate variability in a controlled human exposure study extend similar findings reported in recent panel studies and suggest potential mechanisms by which particulate matter may induce adverse cardiovascular events.
Role of Emotions and Aesthetics in ICT Usage for Underserved Communities: A NeuroIS Investigation

Usability and efficiency has received lot of attention in terms of ICT usage and attitude however non instrumental factors like emotions and aesthetics and their impact on ICT usage attitude and performance has not been extensively tested. Further underserved communities are focused communities that have limitations in terms of formal and functional literacy and technology experience. Aesthetics have been shown to be an important predictor of usage but this has not been tested in underserved communities. Also positive emotions have been linked to greater ICT usage as well as aesthetic experience. The measurement of factors like emotions, aesthetic preferences and ICT usage has so far been restricted to questionnaires however we propose to use objective measures like brain imaging technique (EEG) to supplement existing methodologies. The current paper is a research in progress that addresses potential role of aesthetics and emotions for understanding aesthetic preferences and ICT usages in underserved communities.
Fitting Convolutions of Exponential Distributions to Daily Realized Volatility Data

Convolutions of exponential distributions have widely used in stochastic process and queuing network. In this paper, the closed-form of the probability density function of the sum of exponential random variables is obtained. And we fit convolutions of exponential distributions to the daily realized volatility data of the SSE Composite Index. Further, some proposals to model the log of the asset price by stochastic volatility models are given.
Optimal mesh design for the finite element approximation of reaction–diffusion problems

We consider the numerical approximation of singularly perturbed problems, and in particular reaction–diffusion problems, by the h version of the finite element method. We present guidelines on how to design non‐uniform meshes both in one and two dimensions that are asymptotically optimal as the meshwidth tends to zero. We also present the results of numerical computations showing that robust, optimal rates can be achieved even in the pre‐asymptotic range. Copyright © 2001 John Wiley & Sons, Ltd.
Further studies of a FFT-based auditory spectrum with application in audio classification

In this paper, the noise-robustness of a recently proposed fast Fourier transform (FFT)-based auditory spectrum (FFT-AS) is further evaluated through speech/music/noise classification experiments wherein mismatched test cases are considered. The features obtained from the FFT-AS show more robust performance as compared to the conventional mel-frequency cepstral coefficient (MFCC) features. To further explore the FFT-AS from a perspective of practical audio classification, an audio classification algorithm using features derived from the FFT-AS is implemented on the floating-point DSP platform TMS320C6713. Through various optimization approaches, a significant reduction in the computational complexity is achieved wherein the implemented system demonstrates the ability to classify among speech, music and noise under the constraint of real-time processing.
Locating Peaks in Proteomic Mass Spectral Data Using the Morel-Helmholtz Principle

Proteomics is a rapidly emerging field of research that will help identify and characterize the complex proteins that are responsible for the function of complex biological systems. For detection and identification of separated components, mass spectrometry is evolving to be the method-of-choice because of its high sensitivity and its ability to characterize the individual components. Analysis of biological sample will typically generate a protein mass fingerprint of the various constitutive components, with the component mass expressed as mass-to-charge (m/z) ratios and the relative abundance of each component as the peak height. However, reliably finding protein peaks with small relative abundance has been a difficult signal processing task, and many of the currently used techniques require many arbitrary parameters. This paper investigates the application of the Morel-Helmholtz principle, a single parameter method, to mass spectrometry signal processing. A comparison of the Morel-Helmholtz peak finding method with a thresholding method demonstrates that using the false alarm rate of one per interval will detect peaks that can optimally classify mass spectrometry data equally well as a well chosen threshold
Comparison of Transportation Network Optimization with Different Equity Measures Using Bilevel Programming Approach

Equity issues in the transportation field recently deserve much discussion on various aspects involving accessibility distribution and environmental pollution among different social groups in case of the introduction of policies such as tax, road pricing, network improvement, etc. A variety of equity measures have been proposed in non-transportation fields, however, none of existing studies in transportation has attempted to clarify their different performances within a same context. Therefore, this paper intends to make a comparative analysis on six representative equity measures, including Gini coefficient, Theil index, mean log deviation, relative mean deviation, coefficient of variation, and Atkinson index, given the policy assumption of continuous road network design. An equity optimization model is developed based on the bi-level programming approach, where the upper level is to optimize the equity which is defined with respect to zonal accessibility. The lower level problem is a standard user equilibrium model to represent traffic variations induced by network improvement. A sensitivity analysis is conducted using the artificial network data of Sioux Falls. It is found that the six equity measures result in similar variation patterns of accessibility and average inter-zonal travel time on one hand, but lead to different efficiencies of road investment on the other. The findings of this study are expected to be able to provide a meaningful reference on the evaluation of equity-related studies, and the methodologies could be used to measure other equity issues in transportation.
The Impacts of Governance and Institution on Financial Inclusion: Evidence from Muslim Countries and Developing Economies

Using the data of more than 100,000 individuals’ characteristics in the Global Findex database, this paper examines the links between financial inclusion, institutions, and governance using panel data analysis from Muslim and developing countries. This paper argues that strong economic governance and institutions are important elements in improving financial inclusion especially for the poor segment of the society because markets, economic activity, and transactions more generally, cannot function well in their absence. The results suggest that governance positively influences financial inclusion by increasing the number of bank accounts and saving in formal financial institutions, but negatively impacts on borrowing behavior. There are also significant differences across countries and regions in explaining financial inclusion. The study suggests that removing corruption, increasing transparent legal framework, fair judicial proceedings and good administration are essential for development and raising financial inclusiveness prospects. باستخدام ما يزيد عن 100 ألف من البيانات المتعلقة بخصائص المستجيبين في قاعدة بيانات (فيندكس) العالمية، تدرس هذه الورقة بهدف استنطاق العلاقة التي تربط بين الشمول المالي والعمل المؤسسي والحوكمة في البلدان الإسلامية والنامية، وذلك باستخدام منهج تحليل البيانات اللوحي. وتناقش هذه الورقة أهمية الحوكمة الاقتصادية القوية والعمل المؤسسي المتين في تعزيز الشمول المالي، وخاصة بالنسبة للفئات الفقيرة من المجتمع. ذلك لأن الأسواق والنشاط الاقتصادي والمعاملات عامة لا يمكن أن تعمل بشكل جيد في غيابهما. وتشير نتائج الدراسة إلى أن الحوكمة تؤثر بشكل إيجابي على الشمول المالي من حيث زيادة عدد الحسابات المصرفية والادخار في المؤسسات المالية الرسمية، بينما تؤثر بشكل سلبي على سلوك الاقتراض. كما تشير هذه النتائج أيضا إلى وجود اختلافات كبيرة بين البلدان والأقاليم في تفسيرها للشمول المالي. وفي الأخير تعتبر هذه الدراسة أن إزالة الفساد، وتعزيز شفافية الإطار القانوني، والإجراءات القضائية العادلة، والإدارة الجيدة من العناصر الأساسية التي تساهم في تعزيز التنمية ورفع آفاق الشمول المالي.
Notice of Violation of IEEE Publication PrinciplesTowards a Unified Framework for Complexity Measurement in Aspect-Oriented Systems

Aspect-oriented programming (AOP) is an emerging technique that provides a mechanism to clearly encapsulate and implement concerns that crosscut other modules. It is claimed that this technique improves code modularization and therefore reduce complexity of object-oriented programs (OOP). Most of the proposed complexity measurement frameworks and metrics for AOP are for AspectJ programming language. In this paper we have defined a generic complexity measurement framework that takes into account three, the most well known families of available AOP languages, AspectJ, CaesarJ and Hyper/J. The proposed unified framework contributes to better understanding of complexity in AOP, which in turn help to (i) define new complexity metrics which permit the analysis and comparison of Java, AspectJ, CaesarJ and Hyper/J implementations, and (ii) integrating different existing measures and examine same concepts in different ways.
Effects of a functional COMT polymorphism on prefrontal cognitive function in patients with 22q11.2 deletion syndrome.

OBJECTIVE The 22q11.2 deletion syndrome (DiGeorge/velocardiofacial syndrome) is associated with attentional problems and executive dysfunction, and is one of the highest known risk factors for schizophrenia. These behavioral manifestations of 22q11.2 deletion syndrome could result from haploinsufficiency of the catechol O-methyltransferase (COMT) gene, located within the 22q11 region. The goal of the present study was to examine COMT genotype as a predictor of prefrontal cognitive function in patients with 22q11.2 deletion syndrome. METHOD Patients with confirmed 22q11.2 deletions (N=44) underwent neurocognitive testing following Val(158)Met genotyping (Met hemizygous: N=16; Val hemizygous: N=28). RESULTS Analyses of covariance revealed that Met-hemizygous patients performed significantly better on a composite measure of executive function (comprising set-shifting, verbal fluency, attention, and working memory) than did Val-hemizygous patients. CONCLUSIONS These data are consistent with those of previous studies in normal individuals, suggesting that a functional genetic polymorphism in the 22q11 region may influence prefrontal cognition in individuals with COMT haploinsufficiency.
Sensor location in feedback control of partial differential equation systems

The task of placing sensors for purposes of feedback control is vital in order to obtain information necessary for accurate state estimation. We present a method for optimal location of sensors which is motivated by the feedback control law for the distributed parameter system. In particular, we show how feedback functional gains reflect spatial regions over which accurate information is paramount for control. We use this information in an algorithm which computes centroidal Voronoi tesselations, yielding optimal locations for sensors. This placement is compared with three others to show that location can be more important than number of sensors.
Microenvironment and Immunology Natural Killer Cells Are Essential for the Ability of BRAF Inhibitors to Control BRAFV 600 E-Mutant Metastatic Melanoma

BRAF is a major oncogenic mutation found in approximately 50% of human melanoma that confers constitutive activation of the MAPK pathway and increased melanoma growth. Inhibition of BRAF by oncogene targeting therapy increases overall survival of patients with melanoma, but is unable to produce many durable responses. Adaptive drug resistance remains the main limitation to BRAF inhibitor clinical efficacy and immune-based strategies could be useful to overcome disease relapse. Tumor microenvironment greatly differs between visceral metastasis and primary cutaneous melanoma, and the mechanisms involved in the antimetastatic efficacy of BRAF inhibitors remain to be determined. To address this question, we developed a metastatic BRAF-mutant melanoma cell line and demonstrated that the antimetastatic properties of BRAF inhibitor PLX4720 (a research analogue of vemurafenib) require host natural killer (NK) cells and perforin. Indeed, PLX4720 not only directly limited BRAF-induced tumor cell proliferation, but also affected NK cell functions. We showed that PLX4720 increases the phosphorylation of ERK1/2, CD69 expression, and proliferation of mouse NK cells in vitro. NK cell frequencies were significantly enhanced by PLX4720 specifically in the lungs of mice with BRAF lung metastases. Furthermore, PLX4720 also increased human NK cell pERK1/2, CD69 expression, and IFNg release in the context of anti-NKp30 and IL2 stimulation. Overall, this study supports the idea that additional NK cell-based immunotherapy (by checkpoint blockade or agonists or cytokines) may combine well with BRAF inhibitor therapy to promote more durable responses in melanoma. Cancer Res; 74(24); 7298–308. 2014 AACR.