Miracle-dz/UniFAR-FTUs huggingface dataset:
Brand New K-FACs: Speeding up K-FAC with Online Decomposition Updates

K-FAC (arXiv:1503.05671, arXiv:1602.01407) is a tractable implementation of Natural Gradient (NG) for Deep Learning (DL), whose bottleneck is computing the inverses of the so-called ``Kronecker-Factors'' (K-factors). RS-KFAC (arXiv:2206.15397) is a K-FAC improvement which provides a cheap way of estimating the K-factors inverses. In this paper, we exploit the exponential-average construction paradigm of the K-factors, and use online numerical linear algebra techniques to propose an even cheaper (but less accurate) way of estimating the K-factors inverses. In particular, we propose a K-factor inverse update which scales linearly in layer size. We also propose an inverse application procedure which scales linearly as well (the one of K-FAC scales cubically and the one of RS-KFAC scales quadratically). Overall, our proposed algorithm gives an approximate K-FAC implementation whose preconditioning part scales linearly in layer size (compare to cubic for K-FAC and quadratic for RS-KFAC). Importantly however, this update is only applicable in some circumstances (typically for all FC layers), unlike the RS-KFAC approach (arXiv:2206.15397). Numerical results show RS-KFAC's inversion error can be reduced with minimal CPU overhead by adding our proposed update to it. Based on the proposed procedure, a correction to it, and RS-KFAC, we propose three practical algorithms for optimizing generic Deep Neural Nets. Numerical results show that two of these outperform RS-KFAC for any target test accuracy on CIFAR10 classification with a slightly modified version of VGG16_bn. Our proposed algorithms achieve 91$\%$ test accuracy faster than SENG (the state of art implementation of empirical NG for DL; arXiv:2006.05924) but underperform it for higher test-accuracy.
A Survey On Hand Gesture Recognition System For Human Computer Interaction(HCI)

As Computers turn out to be more unavoidable in the public eye, encouraging characteristic human– Computer Interaction (HCI) will positively affect their utilization. Subsequently, there has been developing enthusiasm for the advancement of new methodologies and innovations for crossing over the human computer hindrance. A definitive point is to convey HCI to an administration where associations with PCs will be as normal as a connection between humans, and to this end, incorporating gestures in HCI is a crucial research area. Gestures have for some time been considered as a collaboration strategy that can conceivably convey more innovative, pure and natural strategies for speaking with our computers. This paper gives an examination of provisional surveys done in this area. The adoption of hand gestures as a characteristic interface fills in as a spurring power for look into in gesture anatomy, its portrayals and recognition strategies, programming stages and structures which are examined in this paper. It centre’s around the three principle periods of hand gesture recognition i.e. discovery, tracking and recognition. This paper likewise gives an examination of existing writing identified with gesture recognition frameworks for human PC cooperation by classifying it under various key parameters. The primary objective of this review is to give analysts in the field of gesture based HCI with an outline of advance accomplished to date.
The Relations Between Anxiety Symptoms and Friendships in Adolescence

Anxiety symptoms can often be experienced as a silent struggle in adolescence, as many anxious adolescents do not exhibit outward symptoms. Identifying adolescents who are struggling with subthreshold anxiety symptoms can be even more difficult. As adolescence is a time where friendships become primary sources for emotional support, youth who experience anxiety symptoms and associated distress may have trouble navigating close relationships with peers. The current study aims to investigate the relations between adolescents’ anxiety symptoms and their friendship functioning, as well as the impact of their anxiety symptoms on friends’ emotional adjustment. Data were taken from a larger project on adolescent friendships and emotional adjustment, approved by the University of Maine Institutional Review Board (IRB). Participants (N = 186) were nested within 93 same-gender friendship dyads and were between 13 and 19 years of age. Dyads’ emotional adjustment and friendship functioning were assessed concurrently and after 3 months. Self-report measures of anxiety symptoms, friendship quality, and depressive symptoms were gathered. Descriptive statistics, mean-level gender differences, and correlations among study variables were computed, and dyadic data analyses tested primary hypotheses of interest. Results indicated that anxiety symptoms were not associated with lower levels of positive friendship quality. Additionally, although friends were similar to one another in terms of anxiety symptoms, results did not support evidence of anxiety contagion over 3 months. Future research should test for anxiety contagion across a longer period of time (e.g., 1 year), and studies of adolescent anxiety should continue to control for depressive symptoms to account for the overlap in symptomatology between depressive and anxiety symptoms. This study contributes to the existing literature on the impact of adolescents’ internalizing symptoms on friendships and the emotional adjustment of friends.
UML MARTE Time Model and Its Clock Constraint Specification Language

The UML Profile for MARTE extends the UML with constructs dedicated to the modeling and analysis of real-time and embedded systems. Its time profile provides a rich model of time based on the notion of logical clocks that can be used consistently through all modeling elements/diagrams. The MARTE time profile comes with a companion language, called CCSL. CCSL is a formal declarative language used to handle the MARTE logical clocks and schedule the execution of the different parts of a model. This chapter gives a snapshot on modeling and analysis facilities that have been developed specifically around the time profile of MARTE and CCSL. A second objective is to show how MARTE can be combined with other profiles such as EAST-ADL. The last objective is the use of CCSL as a common language for specifying the semantics of models to allow their execution in a common framework. The MARTE and EAST-ADL constructs are illustrated on an example of a simplified cruise control. The example starts with a description of functional and timing requirements captured using a specific profile called EAST-ADL dedicated to the automotive domain. Then some of the requirements are refined with UML state machines and activities adorned with MARTE stereotypes. All these models rely on MARTE clocks. The semantics of these diagrams is given by a CCSL description that is automatically derived from the models. The resulting CCSL specification can be used to execute the UML/EAST-ADL specification, to animate the model, or to perform various kinds of analyses.
A Novel Optimization Strategy Based Cost Differential Evolution Algorithm for Training Neural Network

Abstract – A new heuristic variant of the differential evolution algorithm is presented in this paper to choose mutant vector strategy. Our proposed algorithm called Based cost Differential Evolution (Bc-DE), generated the mutant vector by adding a weighted difference of two cost function multiplied by a vector selected randomly to the best individual vector. The performance of the Bc-DE algorithm is broadly evaluated on several bound-constrained nonlinear and non-differentiable continuous numerical optimization problems and compares with the conventional DE and several others DE variants. It is demonstrated that the new method converges faster and with more certainty than many other acclaimed global optimization methods. Finally, we will try to improve our proposed method by applying the Bc-DE such as a learning algorithm to train neural network for non linear system identification. Simulation results demonstrate that the new tuning method using Based cost Differential Evolution has a better control system performance compared with the others approaches.
A Low-Complexity Floor Determination Method Based on WiFi for Multi-Floor Buildings

—Floor determination has become an extremely urgent issue to resolve because many applications require accurate information on floor numbers to provide better localization services. This paper presents a Wi-Fi based, low-complexity floor determination method for multi-floor buildings. In this paper, the Multi-Wall-Floor (MWF) model is used in the simulation and the analysis. Simulation results show that the floor determination accuracy is nearly 100% if the deployment density of Wireless Access Points (WAPs) is sufficiently high on each floor. It is also shown that the proposed method provides a good estimation of floor determination even when only a few WAPs are implemented on each floor. In our scheme, detailed information on the WAP coordinates is not needed, except floor ID and Received Signal Strength (RSS) of each WAP. The novelty of the proposed method is that it can work in extreme conditions, where there are no WAPs on the floor.
Toward Optimal FPGA Implementation of Deep Convolutional Neural Networks for Handwritten Hangul Character Recognition

Deep convolutional neural network (DCNN) is an advanced technology in image recognition. Because of extreme computing resource requirements, DCNN implementation with software alone cannot achieve real-time requirement. Therefore, the need to implement DCNN accelerator hardware is increasing. In this paper, we present a field programmable gate array (FPGA)-based hardware accelerator design of DCNN targeting handwritten Hangul character recognition application. Also, we present design optimization techniques in SDAccel environments for searching the optimal FPGA design space. The techniques we used include memory access optimization and computing unit parallelism, and data conversion. We achieved about 11.19 ms recognition time per character with Xilinx FPGA accelerator. Our design optimization was performed with Xilinx HLS and SDAccel environment targeting Kintex XCKU115 FPGA from Xilinx. Our design outperforms CPU in terms of energy efficiency (the number of samples per unit energy) by 5.88 times, and GPGPU in terms of energy efficiency by 5 times. We expect the research results will be an alternative to GPGPU solution for real-time applications, especially in data centers or server farms where energy consumption is a critical problem. Category: Artificial Intelligence
A multidimensional Ramsey Theorem

Ramsey theory is a central and active branch of combinatorics. Although Ramsey numbers for graphs have been extensively investigated since Ramsey's work in the 1930s, there is still an exponential gap between the best known lower and upper bounds. For $k$-uniform hypergraphs, the bounds are of tower-type, where the height grows with $k$. Here, we give a multidimensional generalisation of Ramsey's Theorem to Cartesian products of graphs, proving that a doubly exponential upper bound suffices in every dimension. More precisely, we prove that for every positive integers $r,n,d$, in any $r$-colouring of the edges of the Cartesian product $\square^{d} K_N$ of $d$ copies of $K_N$, there is a copy of $\square^{d} K_n$ such that the edges in each direction are monochromatic, provided that $N\geq 2^{2^{C_drn^{d}}}$. As an application of our approach we also obtain improvements on the multidimensional Erd\H{o}s-Szekeres Theorem proved by Fishburn and Graham $30$ years ago. Their bound was recently improved by Buci\'c, Sudakov, and Tran, who gave an upper bound that is triply exponential in four or more dimensions. We improve upon their results showing that a doubly expoenential upper bounds holds any number of dimensions.
An Approach to Generate 2-Dimensional AVK to Enhance Security of Shared Information

As the sharing of information through the communication channels increases, the indispensability of maintaining confidentiality of those shared information also increases proportionally. Providing reasonable security over the insecure channel is a challenging research. Due to the advancement of computational efficiency, confidentiality of the information cannot be assured with the help of a static key. Keeping this in mind, many researchers have proposed several time variant key generation techniques, out of which Automatic Variable Key (AVK) is a novel approach. In conventional AVK and in different variations of AVK; the key varies every time as new data is exchanged between sender and receiver while the key size remains constant throughout the data communication. Therefore, to increase the randomness among the successive keys that is the key for ensuring the greater security, we have proposed a 2-dimensional AVK in which the auto generated keys not only vary in bits sequence (i.e. session by session) but also in size.
Designing efficient and safe weak references in Eiffel with parametric types

In this paper, we present our work on the design and implementation of weak references within the SmartEiffel project. We introduce the known concept of weak references, reminding how this peculiar kind of references can be used to optimize and fine-tune the memory behavior of programs, thus potentially speeding up their execution. We show that genericity (parametric types in Eiffel) is the key to implementing weak references in a statically-checked hence safer and more efficient way. We compare our solution for weak references to similar notions in other languages and stress the advantages it offers.
Conceptions, practices and power plays around the notion of tenure security: examining the land policy development and implementation process in Madagascar

Land tenure is high on the international development agenda. A key notion in these policy debates is tenure security, which is portrayed crucial for economic growth, poverty reduction, social cohesion and governance. A gap exists, however, between conceptions of tenure security in critical development literature and its practice within land policies. With this research, I demonstrate the complexities of the notion and the ambiguities of policies established around it. Taking the example of Malagasy land policy process, I ask how tenure security has been conceived, practiced and maintained. I ‘study through’ the policy process (Wedel and Feldman 2005), relying on concepts of policy narratives (Roe 1991), assemblages (Li 2007) and power (Gaventa 2006). I adopt qualitative, temporal and nested research approaches. I combine research from global, national and local levels, drawing on observations, semi-structured interviews and document analysis, attending to the stories of social actors linked to the policy. The Malagasy land policy was structured around the conceptions and practices of recognition and registration of legitimate tenure rights by decentralised authorities. The policy has, however, faced institutional, operational and social challenges. By questioning the state authority and control over land, it has also become an arena for power plays. Hence, the policy has generated unintended consequences in terms of tenure security and failed to win widespread support. The research findings highlight the importance of considering tenure security in land policy from multiple perspectives throughout the process and by attending to its inherently political nature. I conclude that tenure security is an institutional matter influenced by authority, political, social, cultural, and power relations between actors at different levels. Consequently, policies should go beyond the blueprint solutions of recognition and registration of tenure rights. Key words: Land, tenure security, policy process, policy narratives, assemblage, power, Madagascar
Examining the Factors Underlining the Inflationary Phenomenon in Ghana – A Dynamic ARDL Analysis

The phenomenon of inflation is one of the most widely discussed economic issues across the world and for this reason has continued to remain very relevant and visible within the policy domain. This is because it affects the economic fortunes of the principal actors within the economy from the low to the high income. This study adds to the existing literature on inflation by identifying the short and long run factors which influence its trajectory in the Ghanaian economy. The study adopts the Autoregressive Distributed Lag approach to comprehensively establish the long and short run determinants of inflation based on the data set spanning from 1979 to 2016 and the empirical analysis shows that price level is in the long run significantly determined by food crop production, crude oil prices, population, output of goods and services and money supply but in the short run the only variable which does not impact significantly on the price level variable is the interest rate proxied by the policy rate. It is also established that the system is able to correct about 60% of the deviations from its equilibrium position in every quarter. The main recommendation that emanates from the study is that policy makers instead of dealing with inflation mainly from the orthodox monetary perspective must also begin to pay more attention to the supply side issues in the economy.
Estimation and testing for separable variance–covariance structures

The statistical analysis of data for a p‐variate response observed repeatedly on q occasions or of spatiotemporal data recorded at p locations by q times for n individuals may require that constraints be imposed on the modeling of the variance–covariance structure of the underlying process, not because of the repeated‐measures or spatiotemporal nature of the data but because there is not enough data otherwise to estimate the model parameters. Besides stationarity and isotropy, separability is an interesting option for that purpose because it reduces the number of variance‐covariance parameters to estimate, from pq(pq + 1)/2 to the Kronecker product of two matrices with p(p + 1)/2 and q(q + 1)/2 parameters. Originally, in the late 1980s, separability of the variance–covariance structure was assumed. Under this model, combined with the normality assumption on the underlying distribution, novel theoretical developments were thus made. The question of estimation of the parameters of a separable variance–covariance structure, more particularly by maximum likelihood, was raised from the early 1990s on, the question of testing for this structure being effectively addressed several years later. The existence and uniqueness of maximum likelihood estimators for the matrix normal distribution (i.e., the doubly multivariate normal distribution characterized by a simply separable variance–covariance structure) have been and remain questions of interest, as shown by recent results. Below, the reader is guided throughout the field of study of the separable variance–covariance structures as the author provides a fair treatment of the topic, its components, extensions (e.g., double separability), and future perspectives.
Odkrywanie wiedzy w wypowiedziach tekstowych. Metoda budowy słownika klasyfikacyjnego

semantics logic between elements of ex-pression attractive area in Data Mining and text analysis. of text use integrates in the following field: linguistics, NLP, logic, statistics in order to build a reliable analytical tool in CAQDAS environment; (b) the use of appli-cation available in CAQDAS solutions and developing them with new techniques for classification tools; (c) assessment of the adopted solution. The method for dictionary building requires a syn-thesis of many solutions. To build accurate classification dictionary one needs: the basics of the language content search, Thesaurus, synonym dictionary, lexical relations definitions. Authors describe a step-by-step process of building a classification dictionary, accentuate the pitfalls and important decisions, which appears to be important during the analysis process.
Brat2BioC: conversion tool between brat and BioC

NICTA Victoria Research Lab, Melbourne VIC 3010, Australia Department of Computing and Information Systems, University of Melbourne, Melbourne VIC 3010, Australia Humboldt-Universitat zu Berlin, WBI, Berlin, Germany Berlin Brandenburg Center for Regenerative Therapies, Charite, Berlin, Germany ! Introduction Interoperability between text mining solutions requires sharing information, specifically resources such as annotated corpora, in a common format. Several formats are available that have been used in the biomedical natural language processing (BioNLP) community, though no single standard has emerged. The BioC formalism [1] is intended to fill this gap, by providing tools to work with BioC, in addition to the proposed format itself. Translation of annotations of commonly used formats into BioC allows reusing existing annotated corpora with BioC solutions. The standoff brat (brat rapid annotation tool) format is one of the more commonly used formats. For instance it has been used in the BioNLP shared task series [2]. Several corpora have been made available in the brat format, including the Human Variome Project corpus and the CellFinder corpus[3]. We have prepared a software solution, named Brat2BioC, that translates annotations originally in brat format into BioC and vice versa. The Brat2BioC tool is available in bitbucket at https://bitbucket.org/nicta_biomed/brat2bioc.
Obstacles to Employability Skills Training Programs in Malaysia from the Perspectives of Employers’, Educators’ and Graduates’ Perspective

Over the last two decades, employability skills training programs initiated by the Malaysian government and agencies are an essential strategy to improve the skills of the workforce and minimize unemployment. However, stakeholders seem perplexed about the direction and attainment of the training programs. There are raising concerns whether employability skills training programs are designed and offered properly in improving workers’ skills and securing unemployed workers’ employment. Therefore, the purpose of this study was to examine the perceptions of educators, employers, and recent graduates regarding the contributing factors that impede the progress of employability skills training programs. The theoretical framework for this quantitative study was based on Human Capital Theory. A survey questionnaire contains qualitative component questions was developed to gather feedback from employers, educators, and graduates from the central economic region of the west coast of peninsular Malaysia. The findings of this study revealed the major obstacles to effective employability skills training programs in the workforce of Malaysia, such as unclear objectives and direction of training programs, negative attitudes of recent graduates, and inactive involvement of employers in local workforce education and training. These obstacles will be a key area to be assessed and improved in program evaluation.