Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Music Auto-Tagging with Convolutional Neural Networks

Technology is revolutionizing the way in which music is distributed and consumed. As a result, millions of songs are instantly available to millions of people, on the Internet. This has created the need for novel music search and discovery services. Music is often searched using descriptive keywords, or tags, based on the content of the song. Hence, one very important task in achieving a great music search engine is automatic tagging of music. Currently, deep learning techniques using convolutional neural networks produce state- of-the-art results for this task. Several deep learning algorithms are able to achieve good results but at the cost of efficiency. As neural networks get deeper, the cost of computation grows exponentially. In this paper, we present a deep learning-based ensemble method that achieves near state-of-the-art performance on the music auto-tagging task. Our method is significantly more efficient in terms of computation time and disk space. This opens up the option of using our proposed model directly on a mobile device.
Improving Search Engines by Demoting Non-Relevant Documents

A good search engine aims to have more relevant documents on the top of the list. This paper describes a new technique called ? Improving search engines by demoting non-relevant documents? (DNR) that improves the precision by detecting and demoting non-relevant documents. DNR generates a new set of queries that are composed of the terms of the original query combined in different ways. The documents retrieved from those new queries are evaluated using a heuristic algorithm to detect the non-relevant ones. These non-relevant documents are moved down the list which will consequently improve the precision. The new technique is tested on WT2g test collection. The testing of the new technique is done using variant retrieval models, which are the vector model based on the TFIDF weighing measure, the probabilistic models based on the BM25, and DFR-BM25 weighing measures. The recall and precision ratios are used to compare the performance of the new technique against the performance of the original query.
Molecular detection of Begomovirus ( family : Geminiviridae ) infecting Glycine max ( L . ) Merr . and associated weed Vigna trilobata

Plant virus detection and diagnosis play major role in ascertaining the crop losses and to devise efficient disease control strategies. Yellow mosaic viruses (genus: Begomovirus; family: Geminiviridae) are serious pathogens of grain legumes and leguminous weeds. In this study, we report PCR based diagnosis of legume yellow mosaic viruses infecting soybean and associated weed species Vigna trilobata in soybean crop ecosystem. Simple and efficient PCR based detection designed for studying begomoviruses infecting soybean was utilized in identifying yellow mosaic virus infection in weed Vigna trilobata. Initial PCR detection demonstrated yellow mosaic symptoms in Vigna and soybean are due to legume begomovirus infection. Further PCR assay in Vigna and soybean revealed infection was due to Mungbean yellow mosaic India virus (MYMIV) which is prevalent in soybean grown regions of central India. Implications of MYMIV infection in perennial weed species like Vigna for disease management strategies are also discussed.
ArgumentAtion And reflexivity

The aim of this chapter is to explore the way in which discursive and argumentative analyses may facilitate the emergence of participants’ reflexive practices during social interactions. As we consider reflexivity embedded in the practices of argumentation, we intend to analyze how the participation framework and the argumentative practices of adults and children can elicit the emergence of the capacity to be active thinkers in different settings of interaction. In our perspective, participants constitute their model of rationality interactively, as inner logic emerging in the course of different interactions. In particular, we focus on argumentative discussions in which people are concerned with showing and clarifying the rationality of their conducts for themselves and for the others as well. This need for accountability is considered the core of the reflexive practices continuously accomplished by social actors during interactions.
A comparison of soil sampling and direct search in malacological field inventories

We compared quadrate based soil sampling and time restricted direct search methods in order to evaluate their use in land snail diversity assessment. The study was conducted in a riparian alder forest in Hungary. By each of the methods, we compared the observed and estimated number of land snail species, the nature of biases due to the variation in species catchability, and the incidence based complementarity of the two methods. We tested the effect of collectors’ identity on the sampling results in case of the time restricted search. Based on our results, we suggest simultaneous use of the two methods, and the use of species accumulation curves to define sampling efficiency in field inventories for exploring terrestrial mollusc faunas.
inteliScaler Workload and Resource Aware , Proactive Autoscaler for PaaS Cloud Frameworks Group Members

Cloud systems rely on virtualization techniques to provide computing resources on demand. Elasticity is a key feature where provisioning and de-provisioning of resources is done via autoscaling. Reactive auto-scaling, in which the scaling actions take place just after meeting the triggering thresholds, suffers from several issues like risk of under provisioning at peak loads and over provisioning during other times. For example, in most of the Platform-as-a-Service (PaaS) frameworks, auto-scaling solutions are based on reactive, threshold-driven approaches. Such systems are incapable of catering to rapidly varying workloads, unless the associated thresholds are sufficiently low; however, maintaining low thresholds introduces the problem of over-provisioning under relatively stable workloads. Determining an optimum threshold, which solves these issues while minimizing the costs and meeting QoS demands is not a trivial task for a regular PaaS user. Alternatively, thresholds are not a good indication of QoS compliance, which is a key performance indicator of most cloud applications. Proactive auto scaling solutions, where future resource demands can be forecasted and necessary scaling actions enacted beforehand, can overcome these issues. Nevertheless, the effectiveness of such proactive scaling solutions depends on the accuracy of the prediction method(s) adopted. We propose inteliScaler, a proactive and cost-aware auto-scaling solution to address the above issues by combining a predictive model, cost model, and a smart killing feature. First, we evaluated several forecasting models for their applicability in forecasting different workload patterns. Second, we introduce an ensemble workload prediction mechanism based on time series and machine learning techniques for making more accurate predictions on drastically different workload patterns. Simulation results using the RUBiS application and several empirical workload traces show significant cost savings by inteliScaler compared to a typical PaaS auto-scaler. Moreover, our ensemble method produces significantly lower forecast errors compared to the use of individual forecasting models and the prediction technique employed in Apache Stratos, an open source PaaS framework. We further evaluated the proposed approach by implementing it on Apache Stratos PaaS framework, and then deploying and testing it on AWS EC2. Results show significant QoS improvements and cost reductions relative to a typical reactive and threshold-based PaaS auto-scaling solution.
A WEB-BASED OPERATED EXPERIMENT FOR UNDERGRADUATE ENGINEERING LABORATORY

An undergraduate experiment in the Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, has been developed for on-line operation over the Internet. By adopting rapidly changing Internet and object component technologies, we developed a novel approach combining the Internet and regular laboratory equipment. The client–server applications use a Visual Basic and Labtech programming environment, which includes remote access of control and data acquisition. The details of the architecture design and the experiment are discussed to provide enhanced understanding of the technical issues involved and the solutions chosen.
High-performance PMSM servo-drive with constrained state feedback position controller

This paper describes high-performance permanent magnet synchronous motor (PMSM) servo-drive with constrained state feedback (SFC) position controller. Superior behavior of the control system has been achieved by applying SFC with constraints handling method based on a posteriori model predictive approach (MPAC). The concept utilizes predictive equations obtained from discrete-time model of the PMSM to compute control signals which generate admissible values of the future state variables. The novelty of the proposed solution lies in the limitation of several state-space variables in servo-drive control system. Since MPAC has firstly been applied to limit more than one state-space variable of the plant, necessary conditions for introducing constraints into multivariable control system with SFC are depicted. Due to the low complexity of proposed algorithm, a low cost microprocessor, STM32F4, is employed to execute the state feedback position control with model predictive approach to constraints handling. Experimental results show that the proposed control method provides superior performance of PMSM servodrive with modern SiC based voltage source inverter (VSI).
Characterising Passengers ’ Travel Patterns in London Public Transit

Since the invention of the Smart Card in the late 1960s, this technology itself and its derivative applications have been increasingly benefiting and maturing in several industrial sectors, such as healthcare, banking, and government. In the public transit field, extensive researches that adopt data from the SCAFC system have been conducting accordingly, most of which are popularly categorised in the strategic-level study that aims primarily to understanding passengers’ travel pattern via characterisation and classification (Pelletier, Trépanier, and Morency, 2011). Understanding transit patterns can be beneficial to assess the performance of the transit network, more accurately forecast travel demand, adjust service arrangement which copes with the ridership varying from both space and time.
CoolSPICE : SPICE for Extreme Temperature Range Integrated Circuit Design and Modeling

We developed a compact modeling methodology as well as a niche SPICE design suite to enable integrated circuit design for extreme environment operation. This new design suite, CoolSPICE, with its low temperature models is expected to significantly improve reliability, performance and lifetime of electronics that are used for space or low temperature niche applications. CoolSPICE with its graphical user interface including schematics editor and plotter, as shown in Fig. 1, offer a convenient and accurate way to design wide temperature range integrated circuits.
5-15-2019 MORAL SENSITIVITY IN INFORMATION SECURITY DILEMMAS

Activities that undermine information security such as noncompliance with information security policies raise moral concerns since they can expose valuable information assets. Existing research shows that moral reflection could play an inhibitory role in one’s decision to undermine information security. However, it is not clear whether users interpret such decisions from a moral standpoint to engage in moral reflection in the first place. Users have to be morally sensitive before they engage in moral reflection. Moral sensitivity involves perceiving a situation as morally relevant, identifying the parties involved and perceiving possible courses of action. We examine moral sensitivity in security dilemmas in a Finnish university setting. We develop audio records of conversations about two policy compliance scenarios, each involving moral concerns. After playing back these audio records to participants, we pose probing questions to examine their moral sensitivity. Our preliminary results indicate that users may not be sensitive towards the moral concerns raised by security dilemmas. Based on our findings, we suggest providing users with information regarding those affected by security decisions, IT capabilities in an organization and the possible consequences of different courses of action in security education programs rather than directives about morally right or wrong behavior.
Do Individuals in Developing Countries Care about Personal Health Information Privacy? An Empirical Investigation

As developing countries migrate to electronic healthcare (e-health) systems, emerging case studies suggest concerns are being raised about the privacy and security of personal health information (PHI) (e.g., Bedeley & Palvia, 2014; Willyard, 2010). However, there is lack of consideration of PHI privacy in the development of e-health systems in these countries as developers and policy makers assume that individuals are in greater need of healthcare and may not care about issues such as privacy (Policy Engagement Network [PEN], 2010). To better understand these assumptions and concerns individuals may have about the digitization of their PHI, this study examined individuals’ privacy concerns regarding the use of electronic health record (EHR) systems by hospitals for storing and managing PHI. A survey was conducted on a sample of 276 individuals in Ghana, a Sub-Saharan African country. We analysed the dataset using t-test and analysis of variance (ANOVA). Contradicting the assumption underlying e-health systems development, the results demonstrated that whilst individuals are less concerned about the collection of their PHI by hospitals, they are highly concerned about unauthorised secondary use, errors, and unauthorize access regarding their PHI stored in EHR systems. These concerns are especially greater for individuals with high computer experience and those who are extremely concerned about their health. Furthermore, compared with women and older individuals (35 years or older), men and younger individuals (aged 18-24) are more concerned about the collection of their PHI by hospitals. Implications for research and practice are discussed.
A Survey on Value Based Plagiarism Detection to Identify Similar Code

The reused code in software field will degrade the efficiency in development and in execution phases. To Identifying similar code fragments is more challenging in case of code theft. In case of code theft many automated obfuscation code transformations are used to hide the stolen code. To handle such obfuscated code with a strong evidence of a suspicious program some methods are used based on the runtime values of the program during its execution. The runtime values are core values dynamic characterization of program executables, this technique is resilient in data and control obfuscation techniques. The dynamic taint analyzer will extract and refine the runtime executables of the core values. The value based plagiarism detection method (VaPD) is used to measure the two code fragments by using longest common subsequent method. The similarity measuring algorithms are used to check codes which belong to same ancestry.
U NEMPLOYMENT DURATION AND THE ROLE OF JOB RELATED CONCESSIONS FOR LEAVING WELFARE

Unemployment strongly influences an individual’s economic resources and life chances and thus being unemployed is also an important predictor of his or her position in the inequality structure. Especially for those among the unemployed who have to rely on means tested benefits, episodes of unemployment often go along with substantial material restrictions. Therefore, measures or regulations that might lead to a shortening of unemployment episodes might also be useful for reducing inequalities. In our paper, we focus on a particular regulation in Germany that aims at shortening unemployment episodes—namely the obligation of unemployed recipients of means tested benefits to make concessions regarding the characteristics of the job they are searching for. Doing so, we ask the question, whether making such concessions will indeed shorten unemployment episodes. Our results indicate that there is no positive effect of making concessions on the chances of reemployment. In contrast to that, searching for a different job (that does not necessarily imply a concession) has a substantial and positive effect. Thus, it appears that being generally flexible regarding one’s future occupation might be more important for reemployment chances than accepting less qualified or lower-status employment.
Sedentarism and Metabolic Syndrome: Broadening the measurement of sedentarism

The metabolic syndrome (MS) is a combination of cardiovascular risk factors, including visceral obesity, low HDL cholesterol level, increased triglycerides, hyperglycemia and high blood pressure. This sequence of risk factors contributes towards the development of atherosclerotic cardiovascular disease (ACVD) and diabetes mellitus.
Macroeconometric evaluation of active labour-market policy – a case study for Germany

Most evaluation studies of active labour-market policies (ALMPs) focus on the microeconometric evaluation approach using individual data. However, as the microeconometric approach usually ignores impacts on non-participants, it should be seen only as a first step to a complete evaluation to be followed by analysis at macroeconomic level. Our study evaluates the impact of active labour-market programmes in Germany on the whole economy. The evaluation focuses on vocational training and additionally on subsidised employment programmes in order to compare them to vocational training. To do this we outline the institutional structure of ALMPs in Germany and conduct a theoretical discussion that enables us see how ALMP might influence the whole economy. This framework serves as a starting point for the empirical analysis, which uses regional data from 175 German labour office districts and a dynamic panel data estimator to evaluate the impacts of ALMP in Germany from 1999 to 2001. The empirical analysis relies on the Beveridge curve relationship, explaining total unemployment as a function of vacancies and ALMP activity. With this empirical model we are able to estimate the overall effect of ALMP on the economy. We use a dynamic specification that enables us to control for the highly persistent pattern of German unemployment. Since the usual estimation methods are not appropriate in dynamic panel data models, we use a system generalised method of moments (GMM) estimator that was found to perform well in the case of highly persistent data. Within the system GMM framework we account for the inherent simultaneity problem resulting from the fact that ALMP would normally be determined by a policy reaction function, i.e. the decision on how much is spent on ALMP is driven by the economic situation. This would result in a causal link from the dependent variable (unemployment or employment) to the ALMP measures which would result in misleading estimates. Our results indicate different pictures in East and West Germany. Whereas in West Germany we find a positive result for vocational training, the results in East Germany do not look favourable. The results for East Germany should be treated with caution since adequate estimators cannot be implemented due to a too small number of regional units. Comparing vocational training programmes in West Germany with job creation schemes (Arbeitsbeschaffungsmaßnahmen, JCS), we additionally find that vocational training is the more efficient measure in reducing unemployment. 1. Executive summary 182
NUMERICAL SIMULATION OF NONCLASSICAL AILERON BUZZ OVER 3 D UNSTRUCTURED ADAPTIVE MESHES

Abstract. Aileron buzz refers to the self–sustained oscillations of an aileron flapping behind an aircraft wing. Nonclassical buzz occurs in transonic flow regimes, and it is characterized by the oscillation of the shock wave location on and off the aileron surface. In order to simulate this phenomenon, we couple the rigid aileron dynamics with the finite volume ALE compressible flow solver Flowmesh. Dynamic grid adaptation is performed through the MMG remeshing library; a local conservative procedure tracks each mesh modification in time, thus avoiding any explicit solution interpolation step, while complying with the moving boundaries and performing solution–driven adaptation. We simulate a simplified test case, consisting of a straight wing between two walls, with a finite–span aileron. Simulations of different aileron spans highlight the 3D flow effects on the frequency of the aileron oscillations. Simulations over an alternative 2D setup, in which the aileron is still connected to the main wing by means of two flexible elements, show the influence of the air gap between aileron and wing on the shock wave movement and on the development of self–sustained aileron oscillations.
A STUDY ON INVENTORY MANAGEMENT OF INDIAN PHARMACEUTICAL INDUSTRY AND ITS IMPACT ON PROFITABILITY

The creation of firms‟ value is been positively expected by a well-designed and implemented working capital management. The purpose of this paper is to examine the trends in inventory management and its impact on firms‟ performance and to examine significant difference between the profitability of firms and industries. Here we consider the return on total assets as dependent variable, which is used as a measure of profitability and relation between inventory management and their profitability. For this purpose here, we have taken a sample of ten Indian Pharmaceuticals firms (NSE listed) and the period of 2000-2014. In this study, we used panel data regression for the investigation of the results. The panel data regression shows that the highly investments in inventories are associated with less profitability. In previous empirical work, a strong significant relationship between WCM and profitability has been found. In this way the final analysis of the operational efficiency, liquidity and profitability of the Indian Pharmaceuticals firms have shown a significant changes and it also shows how best practices are prevailing in the Cipla Ltd. and others, which are contributing to performance.
The Simulation of a Force in Microscale Sensing Employing an Optical Double Ring Resonator System

This paper presents an optical double-ring resonator system of which the design and analytical model are demonstrated to be useful as a novel force in micro-Newton measurement-sensing devices based on optical sensors. The sensing application can be accomplished by changing the optical filtering characteristic of an optical resonance structure such as the ring resonator system. Together with the concept of stress/strain and the elastic modulus of the waveguide material, the relationship between a slightly different value in the exerted force acting on the sensing unit and a difference in the waveguide length can be evaluated. Indeed, changing the optical path length (the waveguide length) causes the difference in peak spectrum of the filtering signals obtained from a ring resonator system. Hence, by measuring the spacing shift between the sensing and setting peak signal in the considered channel, the measurement of a slightly different value in the exerted forces on the sensing unit can be achieved. From the simulation results, an exerted force in small-scale ranges from 10 μN to 50 μN have been evaluated by measuring a spacing shift between the peak signals ranging from 35 pm to 225 pm. In this study, the potential of using such a double-ring resonator device for a force in micro-Newton sensing application is studied and discussed.