Miracle-dz/UniFAR-FTUs huggingface dataset:
A STUDY ON USING THE MELLIN TRANSFORM FOR VOWEL RECOGNITION

In this paper we discuss the applicability of the Mellin transform for vowels recognition, focusing on spectral envelope scale distribution. The hypothesis used is that same vowels produced same spectral envelope shapes (same curves with different compression factor), so an energy, time and scale normalization can be used to map same vowels to same distributions. So, using fast algorithms, we study the applicability of this idea to build a realtime or quasi-realtime system capable of making vowel discrimination in a relatively straightforward way.
Big Data Analysis Using Hadoop and MapReduce

In the last few years, the advancement of technology has been growing at a rapid rate. This trend is expected to continue to grow over the next few years due to the amount of data and information being created daily. Eventually, it is going to be difficult to manage various aspects of our information. As a result of this, it is essential to acquire the necessary tools or software to help us organize our information and use it to acquire as well as filter certain pieces of data we consider important. Specifically, Apache Hadoop is designed to perform such tasks. Its software library incorporated internally allows users to work with hundreds of nodes and petabytes of data. In addition, it allows analysis to be done among interactive queries at a very fast rate. One application in Hadoop, MapReduce, is used to filter and analyze activity log files recorded by computers at a fundamental level to help us increase awareness of the level of security in our systems and monitor any strange activities occurring in a network. With the use of the Linux operating system, we can determine the number of instances of certain activity within our system by creating commands that help parse log files without having to open up the files to manually count them.
Readability evolution of the narratives in the annual report . A longitudinal study on two Spanish companies

Previous research on the readability of annual reports is based mainly on English narratives and has found them difficult to read. Although the results of such research cannot be generalized to different contexts, accounting narratives written in non-English languages have seldom been analyzed in this respect. More important, few studies have longitudinally examined the evolution in readability of such narratives. This study focuses on the readability evolution of annual report narratives written in Spanish, applying an adapted version of the Flesch readability formula to two sets of documents from different companies over most of the years of the 20th century. The results confirm that the reports are indeed difficult to read but show an improvement in readability over the years. The study tested several variables that might influence readability, including profitability.
KOSZUL DUALITY FOR REPRESENTATIONS OF AN A-INFINITY ALGEBRA DEFINED OVER A COMMUTATIVE RING (PRELIMINARY VERSION)

We generalize the Koszul duality of Lefévre-Hasegawa and Positselski to A∞-algebras and modules defined over an arbitrary commutative ring. This is formulated in terms of generalized twisting cochains. Much of the theory we present has not previously appeared, even for objects defined over a field. We show that a projective resolution of the complex underlying an A∞-algebra has an A∞-algebra structure that makes the augmentation map a strict morphism. This gives both motivating examples and an important tool in generalizing results from a field to an arbitrary ring. One of the main results is a characterization of acyclic twisting cochains, which we show can considerably reduce the complexity of representations of an A∞-algebra. As applications of the theory, we give a change of rings theorem for projective resolutions, and generalize the classical BGG correspondence between the exterior and symmetric algebras to a correspondence between a Koszul complex and a curved symmetric algebra. This recovers much of the classical theory of homological algebra over a complete intersection ring and provides a path to a generalization to noncommutative versions, in particular to modular representations of finite dimensional p-restricted Lie algebras.
Adaptive Consensus Voting Algorithm

Fault-tolerant technologies have been applied in many high reliability fields.N-version programming techno-logy is one of those Fault-tolerant technologies.In the software system,voting algorithm can mask the error outputs,redundant technology can prevent false results from propagating to the next sub-module in the software system,and enhance the reliability of the system.Many voting algorithms are widely used in fault-tolerant technology,in which Consensus Voting Algorithm are also widely applied,but the consensus voting strategy is particularly effective in small output spaces because it automatically adjusts the voting to the changes in the effective output space cardinality.But the consensus voting algorithm is more prone to cause identical-and-wrong(IAW) results in this case.Therefore,to resolve this problem,this paper proposed an adaptive consensus voting algorithm.The history records information of modules are used to improve the power of consensus voting algorithm,the proposed algorithm reduces the probability of the incorrect results passing the voter and improves the system safety and reliability.Experiments demonstrate the power of our proposed algorithm.
RESPONSE Sloughing ontology

I am surprised to be replying to a series of commentaries that agree with the basic premise of pluralism. Two pairs of commentators were invited to offer evaluations of pluralism from contrasting positions. One pair, Dietrich and Markman, have previously identified ‘the importance of . representational pluralism in cognitive science’ (Dietrich and Markman 2003, p. 116) – but such statements are reserved for a modest paragraph at the very end of a long paper, with most of that paper centred around rather traditional notions of cognition (see Markman 1999, for a thorough treatment of multiple forms of representation). In this issue, in their separate commentaries, Markman and Dietrich enthusiastically endorse the pluralist view; I critique some specifics of their commentaries below. The most ‘fundamentalist’ perspective, that of Spivey and Anderson, espouses a family of frameworks rather than just one: ‘. a complex dynamical systems approach (fuelled also by ecological psychology, embodied cognition, and connectionism)’. (Spivey and Anderson, this issue, my emphasis). The frameworks they refer to are of course intimately inter-related, and this is one aspect of the integrative pluralism that I argue for in my article (Sections 4.1 and 4.4). So along with the endorsement of Van Orden (however reluctant), it seems that there is a unanimous recognition of the value of integrating diverse perspectives, rather than inflexibly arguing for one at the expense of all others. So, if I may be so bold, now that all contributors to the special issue agree that some form of pluralism is needed, we can work out further details. One concern for pluralism is how diverse the co-existing frameworks might be. I suggested in my article that symbolic and dynamical perspectives, though apparently inconsistent, could nevertheless co-exist as important schemes in cognitive science, contributing explanations to differing sub-domains of cognitive phenomena. But Spivey and Anderson wish to relegate all symbolic descriptions to ‘descriptive shortcuts’ in hopes of taking cognitive science closer and closer to the ‘ontic stream’ of cognition. Their clearly stated and direct challenge to pluralism is based on an ultimate perspective on cognition based in neural dynamics. If a true reductionism were adopted, as recommended in their commentary, then ‘neuron’ must itself be a descriptive shortcut:
Factors Affecting Classification Algorithms Recommendation: A Survey

A lot of classification algorithms are available in the area of data mining for solving the same kind of problem with a little guidance for recommending the most appropriate algorithm to use which gives best results for the dataset at hand. As a way of optimizing the chances of recommending the most appropriate classification algorithm for a dataset, this paper focuses on the different factors considered by data miners and researchers in different studies when selecting the classification algorithms that will yield desired knowledge for the dataset at hand. The paper divided the factors affecting classification algorithms recommendation into business and technical factors. The technical factors proposed are measurable and can be exploited by recommendation software tools.
Enhanced Data and Node Security Based Verifiable Top-k Query Scheme

we propose the system with our contribution of adding data security and node security by adding th e features of homomorphic encryption algorithm for data security and pairwise keying for node security. We propose an effici ent system for preventing location leaks in Sensor Networks and al so it ensures the privacy-preserving scheme against traffic analy sis and flow tracing. With the faster homomorphic encryption algorithm technique, the proposed scheme offers two significa nt privacy preserving features, packet flow untraceability and message content confidentiality, which can efficiently thwart traffic analysis/flow tracing attacks. Moreover, with homomorphic encryption, the proposed scheme keeps the essence o f random linear network coding, and each sink can recover th e source messages by inverting with a very high probability. The quantitative analysis and simulative evaluation on privacy enhancement and computational overhead demonstrate the effectiveness and efficiency of the proposed scheme . Mobile sinks (MSs) are vital in many wireless sensor network (WS N) applications for efficient data accumulation, local ized sensor reprogramming, and for distinguishing and revoking compromised sensors. However, in sensor networks th at make use of the existing key pre distribution schemes fo r pair-wise key establishment and authentication between sensor nod es and mobile sinks, the employment of mobile sinks for da t collection elevates a new security challenge. Thus introducing the data security and node security algorithm in SafeQ protocol makes the system more efficient and accurate.
de travail « Effects on competitiveness and innovation activity from the integration of strategic aspects with social and environmental management »

This paper analyses the nature and details of the impact which the integration of social and environmental considerations with business strategy has on different dimensions of competitiveness and innovation activity on the firm level. Its objective is to answer the question as to whether a positive link exists between integration and the effects of environmental and social performance on competitiveness and innovation activity. After presenting a theoretical framework based on extant work, the paper introduces the research methods and variables. Subsequently results are presented for four different dimensions of competitiveness, namely market-related, image-related, efficiency-related and risk-related advantage as well as for innovatory activity in terms of product and process innovation. These raise the possibility that the process of integration is more important for bringing about a positive link than a resulting integration type. Based on the results, implications are discussed and we shall draw the conclusions from the findings.
Cost Sensitive Semi-Supervised Laplacian Support Vector Machine

Cost sensitive learning is the hot research area in machine learning.In practical real applications,the datasets are usually class-imbalanced,most of the samples are unlabeled,only a few of the samples are labeled,and noise samples are existed.Although some progress has been made in cost sensitive learning for such situation,it needs further solved.For that we propose a semi-supervised Laplacian support vector machine based on cost sensitive learning.On the basis of label propagation,the proposed model integrates the misclassification costs considering class-imbalance into the hinge loss and Laplacian regularization of the Laplacian support vector machine.At the same time,considering the effect on the decision hypersphere of the noise samples,we define an example-dependent cost which makes the weights of noise samples lower.The experimental results on 7 UCI,8 NASA datasets demonstrate the superiority of our proposed algorithm.
Can Modern Standard Arabic Approaches be used for Arabic Dialects? Sentiment Analysis as a Case Study

We present the Shami-Senti corpus, the ﬁrst Levantine corpus for Sentiment Analysis (SA), and investigate the usage of off-the-shelf models that have been built for Modern Standard Arabic (MSA) on this corpus of Dialectal Arabic (DA). We apply the models on DA data, showing that their accuracy does not exceed 60%. We then proceed to build our own models involving different feature combinations and machine learning methods for both MSA and DA and achieve an accuracy of 83% and 75% respectively.
Chapter 5 from : Methylotrophs and Methylotroph Communities

Lanthanides were previously thought to be biologically inert owing to their low solubility; however, they have recently been shown to strongly impact the metabolism of methylotrophic bacteria. Leading efforts in this emergent field have demonstrated far-reaching impacts of lanthanide metabolism in biology; from the identification of novel roles of enzymes and pathways dependent on lanthanide-chemistry to the control of transcriptional regulatory networks to the modification of microbial community interactions. Even further, the recent discovery of lanthanide-dependent enzymes associated with multi-carbon metabolism in both methylotrophs and non-methylotrophs alike suggests that lanthanide biochemistry may be more widespread than initially thought. Current efforts aim to understand how lanthanide chemistry and lanthanide-dependent enzymes affect numerous ecosystems and metabolic functions. These efforts are likely to have a profound impact on biotechnological processes involving methylotrophic communities and the biologically mediated recovery of these critical metals from a variety of waste streams while redefining our understanding of a fundamental set of metals in biology. Introduction: lanthanides in
Comparison on Privacy-Preserving Detection of Sensitive Data Exposure

Recently security firms, Government organizations and other research scholars identifies that data leakage is common in fields where sensitive data are stored and processed. And it is analyzed that data leakage is been growing rapidly, in which human errors are one of the main causes of data loss. The common approach in detecting data leak screens the content in storage and transmission that expose sensitive information. The approach usually requires the detection operation to conduct the secrecy. And there exists lot of techniques, algorithms to find data leakage and provide alerts to the organization. The data leak detection(DTD) privacy –preserving solution solves through the special set of sensitive data digest in the detection. The data leak detection systems were proposed to detect data in small scale and large scale organizations with fuzzy fingerprints. In this paper, we review the data leak detection mechanisms.
Day-ahead bidding on energy markets-a basic model and its extension to bidding curve

Wind resources energy production is highly influenced by uncertain weather conditions. We provide several simple models for bidding on day-ahead energy markets, which take into account the uncertainty. The obtained optimal bids and bidding curve are based not only on the point prediction, but also on the forecasted distribution of generated energy. We relate the resulting problems to two-stage stochastic programs with simple recourse.
Labeling Satellite Imagery with Atmospheric Conditions and Land Cover

In this project, we take on the Kaggle challenge “Planet: Understanding the Amazon from Space”. Our goal is to accurately label satellite images with atmospheric conditions, land use and land cover. We start with the background of the challenge and a brief overview of how we have modeled the problem. We then examine related work that is relevant to this project. In the methods section, we describe the main approach we use for getting to results. A description of the dataset we use comes next, followed by a description of our experiments. Finally, we close with conclusions and areas of future investigation.
Design of a Data Encryption Test-Bed Used to Analyze Encryption Processing Overhead

Data security is one of the most pressing issues faced by the organizations today. Unauthorized access to confidential information corresponding to employees/customers like SSN (Social Security numbers), financial information, health records, birth dates can be compromised both to the individual customers involved and the company withholding the data. The problem has become immense, approximately 260 million records were compromised since 2005 and companies, states and countries have reacted by mandating that industries should stringently follow the best security practices, including encryption and decryption of data. Also, the costs associated with data threats are quite increasing (Whitfield & Susan, 2007). Businesses that use strong encryption methodologies in their mobile devices, computers, cloud systems, other locations might not gain 100 % protection from dangerous hackers, but they can decrease their vulnerability to such attacks and thereby the potential of financial losses. Data encryption is the method of converting data in a computer or any communication system making it unintelligible in a way that the data can be reversed only by the authorized people accessing the original data. The primary goal is to safeguard the confidentiality of data, but integrity checks are also provided by the technique in various forms of authentication message codes. For instance, digital signature schemes are also fundamentals of encryption. The purpose of it is to ensure the authenticity of the identity of the receiver and sender. With an increasing awareness of security threats, many of the current companies are using cryptographic techniques for ensuring data security. Many of the companies like Amazon, Apple, AT&T and Comcast are using encryption techniques for securing the information. While there are a many encryption and decryption techniques available today, there is an obvious requirement for the current companies to find and choose the best reliable cryptographic techniques for securing their data. A performance test of various algorithms is needed to bring up the best technique. This research paper deals with the implementation of different cryptographic algorithms with a programming language called JAVA. It involves designing a graphical user interface (GUI) where sample input can be entered, common algorithms used to encrypt and decrypt the input can be selected. A mechanism for building a test bed for comparing the performances of the implemented algorithms is designed to calculate the encryption processing overhead.
III . 28 Investigation of 14 th Century Byzantine and Serbian Fresco Painting

Representative samples of 14 century fresco paintings (renders and colour layers) from various Serbian monuments (Byzantine influence sphere) were examined, characterized and correlated with corresponding examples from the Byzantine area. In the present work samples from eight monuments (from frescoes created by Michael and Eutychios Astrapas or by the masters highly connected to their work) were examined, in order to achieve a comparison based on characterization and . For pigment analysis Scanning Electron Microscopy (SEM) with EDX and Fibre Optic Microscopy (FOM) was used. The mortar samples were examined by Fibre Optic Microscopy (FOM), X Ray Diffraction (XRD), FTIR Spectroscopy, Hg Porosimetry, Thermal Analysis (DT/TGA) and for their grain size distribution. All the mortars were lime mortars with aluminosilicates, calcite aggregates and organic additives like straw. The mortars from one monument displayed magnesian lime binder as well. All the identified pigments belong to the traditionally used natural pigments of the Byzantine iconography of the 14 century.
Modelling of a Small Unmanned Aerial Vehicle

Unmanned aircraft systems (UAS) are playing increasingly prominent roles in defense programs and defense strategies around the world. Technology advancements have enabled the development of it to do many excellent jobs as reconnaissance, surveillance, battle fighters, and communications relays. Simulating a small unmanned aerial vehicle (SUAV) dynamics and analyzing its behavior at the preflight stage is too important and more efficient. The first step in the UAV design is the mathematical modeling of the nonlinear equations of motion. A survey with a standard method to obtain the full non-linear equations of motion is utilized, and then the linearization of the equations according to a steady state flight condition (trimming) is derived. This modeling technique is applied to an Ultrastick-25e fixed wing UAV to obtain the valued linear longitudinal and lateral models. At the end, the behavior of the states of the non-linear UAV and the resulted linear model is compared by applying a doublet signals in the control surfaces to check the matching between them.
Live Transcoding and Streaming-asa-Service with Low Delay and High QoE

Multimedia content delivery and real-time streaming over the top of the existing infrastructure is nowadays part and parcel of every media ecosystem thanks to open standards and the adoption of the Hypertext Transfer Protocol (HTTP) as its primary mean for transportation. Hardware encoder manufacturers have adopted their product lines to support the dynamic adaptive streaming over HTTP but suffer from the inflexibility to provide scalability on demand, specifically for event-based live services that are only offered for a limited period of time. The cloud computing paradigm allows for this kind of flexibility and provide the necessary elasticity in order to easily scale with the demand required for such use case scenarios. In this paper we describe how to deploy a transcoding and streaming-as-a-service platform based on open standards (i.e., mainly MPEG-DASH) utilizing standard cloud and content delivery infrastructures to enable low-delay and high-quality streaming to heterogeneous clients. We describe how to deploy it for video on demand, 24/7 live, and event-based live services.