Miracle-dz/UniFAR-FTUs huggingface dataset:
ROUTING PROTOCOL FOR SDN-CLUSTER BASED MANET

Mobile Ad hoc NETwork (MANET) is a network of mobile nodes that connect with each other through the wireless interfaces without infrastructures. These nodes have limited energy and move freely from one location to another. Software Defined Networking (SDN) is a new architecture consists of data and control parts. It was discovered to increase the possibilities of traditional network architecture. Moreover, it plays a big role in saving the energy by selecting the optimal path with minimum energy consumption or the path included intermediates node with highest remaining energy. The mobility of MANET nodes makes the routing process very difficult and needs in sometimes that all nodes participate in this process, which leads to high overhead and energy consumption. Therefore, there is need to a special routing protocol to resolve the above troubles. The aim of this work is to design a routing protocol called SDN-Cluster Based Routing Protocol (S-CBRP) to enhance the route building/rebuilding process and increase the lifetime of MANET by selecting the optimal path to the target node with minimum energy consumption and takes into account the node's remaining energy and delay constraints. The proposed architecture depends on implementing SDN agent in each cluster head node to work as a local SDN controller for managing one or more clusters. All the local controllers connect to the central SDN controller that manages the entire network. Also, the full dump and incremental transmission approaches are used to decrease the energy consumption and overhead of sending the cluster information to the central SDN controller. The results demonstrated that SCBRP is better than FF-AOMDV in terms of energy consumption, network overhead, average source-todestination delay and packet delivery ratio.
Suuremahuliste andmete analüüs Apache Spark hajussüsteemi näitel. Data analytics on the example of cluster computing framework Apache Spark

This master’s thesis is about implementing Apache top level project Spark cluster computing framework in Amazon cloud. The aim of the implementation is to elaborate Spark cluster implementation method for small and medium size enterprises (SME). This is necessary for SMEs to whom the traditional relational data warehouse (DW) solutions are too expensive and meets scaling limits when processing big data. Nowadays Hadoop Distributed File System (HDFS) and MapReduce (MR) parallel processing framework are used as alternatives. This paradigm is efficient in big data processing, but suffers under high latency, which is not acceptable for data querying and analysis. The aim of using the Spark cluster implementation is derived from Spark’s low latency, high scalability and fault tolerance. The first goal of this master’s thesis is to use a distributed system that offers low latency and fast response time to analyse data in ad-hoc querying manner. After researching various Hadoop compliant platforms, the author of the thesis decided to continue with analysis of Apache Spark cluster computing framework and introduce a method for implementing it on Amazon Elastic Cloud. Apache Spark stack is suitable for interactive ad-hoc data analysis, iterative machine learning, graph processing, data mining in logs and all kinds of batch processes, i.e. MapReduce. The thesis is focused on interactive ad-hoc data analysis and therefore describes the Apache Shark Command Line Interface and Shark Scala Shell. Both of the mentioned Shark user interfaces enable the end user to query data on Hadoop Distributed File System in an SQL compatible environment. Amazon Simple Storage is used for data storing. Spark cluster implementation is a precondition for launching data profiling tests. The second goal of this master’s thesis is to analyse the outcomes of performance tests of data profiling. Spark on traditional Hadoop cluster should be 10 to100 times faster than Hive. Spark’s outstanding performance is achieved by memory and Resilient Distributed Dataset usage. As a result it appears that ten node Spark cluster on AWS platform is capable of processing 10 gigabytes and 470 million rows of data within seconds. This outcome is comparable to Massively Parallel Processing (MPP) databases and therefore it can be said that Spark cluster is suitable for big data ad-hoc analysis. The current implementations of the traditional Hadoop MapReduce systems are outdated and not suitable for interactive data analysis. The thesis is in English and contains 64 pages of text, 6 chapters, 14 figures, 5 tables.
Extraction and Optimization of chitosan from edible mushroom using for food coating and water treatment

Chitosan being the second most abundant polysaccharide available on earth. In the present investigation extraction and optimization on Chitosan from mushroom as a source was carried out. The confirmation for the Chitosan was done using TBA Assay, DNS test and confirmed by FTIR analysis. Food coating was carried out and efficacy was tested comparing with that of non coated one. The firmness of control fruit during the red stage on the 20 th day was 31.65N where as for the coated fruit on the same day it was 46.79N. Coating was the most effective treatment for retardation of softening of harvested fruits and vegetables. The titratable acidity of control at the time of red stage on the 20th day was 0.611% whereas for coated fruit on the same day it was 0.559%. Biopolymer as an edible coating with 2% solid percentage remains a viable alternative to delay the ripening of tomato. By optimizing the solid percentage, it could be applicable to other fruits and vegetables.
1 Functional Improvements and Neurological Recovery Table 6 . 1 Studies on functional improvement and neurological recovery

ed from medical records. The PoCs reflected aspects of care received within 24 hours of admission, documentation and general management, and included CT scan, swallowing assessment, allied health assessment, documentation of premorbid functioning and discharge needs, measures to avoid aspiration, deep vein thrombosis and use of antiplatelet Adherence to key PoC was higher in SUs than in other models. For all patients, adherence to PoC was associated with improved mortality at discharge and trends found with independence at home.468 of 1701 eligible patients participated. (28%) Overall PoC adherence rates for individual care models were SU 75%, mobile service 65%, and conventional care 52% (P<0.001). The adjusted odds of participants being alive at discharge if adhering to all or all but 1 PoC was significant (OR 3.63; 95% CI: 1.04 to 12.66; P=0.043). Important trends at 28 weeks were found for being at home (aOR 3.09; 95% CI: 0.96 to 9.87;
Design and simulation of Neutral Point Clamped multilevel inverter using HSVM algorithm

In this paper Neutral Point Clamped Multi-Level Inverter is controlled by Hysteresis Space Vector Modulation algorithm which helps to reduce the Total Harmonic Distortion (THD) factor in the output. Neutral Point Clamped Multi-Level Inverter (NPC-MLI) is suitable for transformer-less Photovoltaic (PV) grid connected system. PV source forms the input of the system and output can be synchronized with a grid connected system. Further, the use of a split inductor helps to avoid the use of a transformer, hence, reducing the size, leakage current and the voltage stress in the inverter. The proposed system simulation results were verified using MATLAB/ SIMULINK. Keywords— Maximum Power Point Tracking ( MPPT), Multilevel inverter, Hysteresis Space Vector Modulation (HSVM), Neutral Point Clamping (NPC).
Sea turtle stranding events along the Mauritanian coast

Despite Mauritania’s proximity to globally recognized sea turtle nesting hotspots, the Bijagos Archipelago in Guinea-Bissau and Boavista Island within the Cabo Verde Archipelago, data on the status of sea turtle species in Mauritania remain scant. To address this, we conducted an extensive 6-year field study with the aim of gathering data about sea turtle stranding events along the Mauritanian coast. Between 2009 and 2016, our team recorded 1787 stranded sea turtles in various stages of decomposition (fresh to advanced), including dry sea turtle carapaces in or near coastal villages. Individuals comprised green turtle (Chelonia mydas, 93%; N=1654), loggerhead turtle (Caretta caretta, 5%; N=90), leatherback turtle (Dermochelys coriacea, 2%; N=28), and olive Ridley turtle (Lepidochelys olivacea, 1%; N=15). Curved carapace length measurements taken from all recorded sea turtles indicated a dominant presence of immature individuals for C. mydas and C. caretta. Fishing lines, net entanglements, hooks, traces of knife cuts, and the remains of slaughtered individuals found in coastal villages indicated anthropogenic threats and poaching. Our results testify to the need to reinforce better fishing regulations and to combat poaching activities, which pose direct threats to sea turtles inhabiting/visiting the Mauritanian sea and beaches from other well-protected areas. The current status of sea turtles in Mauritania is of regional and global concern, because marine turtles are migratory species and the dangers they are exposed to in this area may directly impact on populations in the West Africa region.
HOW ORGANIZATIONAL INNOVATIONS HELP MANAGERS TO IMPROVE QUALITY OF THEIR WORK : AN EMPIRICAL STUDY

The paper identifies the influence of organizational innovations in work of managers by means of empirical research. Four sets were identified in the paper and they present the basis for reviewing the influence of organizational innovations. The set V1, . Vi,. Vn defines types of organizational innovations, the set X1, . Xj, . Xm managerial activities, the set Y1, . Yk, . Yo types of changes which can be caused by organizational innovations and the set Z1, . Zl, . Zp determines hierarchical levels of management. The goal of the paper is to identify which types of organizational changes cause particular changes at individual level of management and how they influence work of managers at these hierarchical managerial levels. The research was carried out in a selected basic set of companies consisting of Slovak medium sized and large companies performing in the area of industrial production. The basic method which is used is sociological interrogation. We find that the implementation of organizational innovations demonstrable influence managerial work at all levels of management. We identified the most frequently implemented organizational innovations in Slovak medium sized and large companies, innovations with the highest intensity of changes and managerial activities in which was the impact of organizational innovations is mostly seen.
Predictive Associative Search Models in Variable Structure Control Systems

Predictive associative search models found a wide application in advanced control systems, decision making systems, play a fundamental role in any activity concerned with the signal processing process. In the paper, associative search identification models in variable structure control systems are considered. The application of this approach is especially effective whilst compensating for insufficient lab data for model development. In such a case, fuzzy specification of certain process variables using process knowledge base is practiced. A methodology of the synthesis of a variable structure control system is presented, as well issues of the stability of a model built by use of the associative search are considered, in the aspect of the spectrum analysis of the multi-scale wavelet expansion. Key-Words: system identification, control system, information model, virtual model, associative search, fuzzy model, knowledge base, wavelets
Accelerating Machine Learning Applications on Graphics Processors

Recent developments in programmable, highly parallel Graphics Processing Units (GPUs) have enabled high performance implementations of machine learning algorithms. We describe a solver for Support Vector Machine training running on a GPU, using Platt’s Sequential Minimal Optimization algorithm and an adaptive first and second order working set selection heuristic, which achieves speedups of 9-35× over LIBSVM running on a traditional processor. We also present a GPU-based system for SVM classification which achieves speedups of 63-133× over LIBSVM.
Notation of Discontinuous Combined Volume and Hodge – Deligne

Generalizing up the renowned Bernstein– Kushnirenko hypothesis, Khovansk ̆ıi demonstrated in 1978 a combinatorial recipe for the number juggling variety of the compactification of a conventional complete crossing point related to a group of grid polytopes. As of late, an undifferentiated from combinatorial recipe, called the discrete blended volume, was acquainted by Bihan and appeared with be nonnegative. By making a commentary of Khovansk ̆ıi in his paper unequivocal, we translate this invariant as the (motivic) number-crunching class of the non-minimal nonexclusive complete between areas related to the group of cross section polytopes.
An Efficient Deep Neural Network Classifier in Banking System

Huge amounts of data had been stored in various repositories and the amount of data to be stored is growing rapidly. To extract hidden information from the data, there is a need for data mining techniques. Classification is the process of analyzing the input data by categorizing the records into one of the predefined class labels. Banking system is a fast growing area which collects large number of records associated with customer transactions. This work deals with the analysis of Bank Marketing dataset belonging to a Portuguese bank containing 1000 instances of different clients by building a Deep Neural Network classifier to predict whether a client subscribe for a term deposit. Experiments are conducted on the Bank marketing dataset by applying the Deep Neural network classifier along with four existing classifiers. Our results show that the proposed Deep neural net classifier outperforms the existing classifiers in terms of accuracy.
DECISION-MAKING OF MANUFACTURING SYSTEM FUNCTIONAL OBJECTIVES

We study the relationship among customer demand, competitive strategy and manufacturing system functional objectives based on manufacturing enterprises in the northeast of China. The results show that customer demands have a significant positive effect on competitive strategy. Enhancing customer demand is beneficial to improve the level of competitive strategy of enterprises; competitive strategy have a remarkable positive influence on manufacturing system functional objectives; customer demand directly affect manufacturing system functional objectives, which is indirectly impacted by customer demand through competitive strategy. In addition, both competitive strategy and manufacturing system functional objectives are notably influenced through satisfactions of customer demand. The conclusion of the research can provide theoretical guidance for enterprises which implement manufacturing system functional objectives.
RENEWABLE POWER HARVESTING MECHANISM : SURVEY

Energy harvesting techniques is a technology to generate electrical energy from natural energy resources. Today’s world goes faster with their fast developing technology. Whole world depend upon their technology. The main base of technology depends on availability energy resources. Nowadays, important is the need to develop new energy resources. Many countries have started to install facilities that use renewable energy sources for power generation. This paper surveys about the power generation and harvesting. Index term: Hydro power, Wind power, Solar power, CO2, Energy harvesting.
Resolving loop based path explosion during Symbolic Execution

Symbolic execution is a widely used method for testing device drivers and achieving high code coverage. One problem in exploring code using symbolic execution is loop based path explosion. First, trying all paths using dynamic techniques does not guarantee additional code coverage. Second, large formulas to reach new branch using static analysis do not scale well due to constraint solver limitations.This paper describes challenger deep, a static analysis tool that precomputes a sequence of sub-paths within the loop body so that a specified branch of code can be reached. We use Z3 constraint solver for small queries. For larger queries where Z3 takes exceedingly large time, we switch to a genetic algorithm. Our tool is generic and can be used in both functional testing or whole program testing when a loop construct is encountered.
Traitements complémentaires et parallèles du diabète Comité d’experts des Lignes directrices de pratique clinique de Diabète Canada

• Entre 25 et 57 % des personnes atteintes de diabète disent avoir recours à la médecine complémentaire et parallèle. • Lors d’études cliniques d’une durée d’au moins 3 mois réalisées auprès d’adultes atteints de diabète de type 2, il a été démontré que certains produits de santé naturels réduisent le taux d’HbA1C de 0,5 % et plus; cependant, comme la plupart de ces études étaient uniques et de petite envergure, des évaluations à plus grande échelle sont nécessaires avant que l’emploi répandu de ces produits puisse être recommandé. • Quelques autres produits de santé naturels fréquemment utilisés contre le diabète ont été évalués dans le cadre d’études contrôlées avec répartition aléatoire de plus grande envergure et/ou de méta-analyses qui ont réfuté les croyances populaires attribuant des bienfaits à ces composés. • Les professionnels de la santé doivent toujours demander à leurs patients s’ils ont recours à des approches complémentaires et parallèles, car certaines d’entre elles peuvent causer des effets indésirables inattendus et/ou des interactions avec les pharmacothérapies classiques.
Cimetidine as a model drug

Crystal polymorphism of active ingredients is relevant to the pharmaceutical industry, since polymorphic changes taking place during manufacture or storage of pharmaceutical formulations can affect critical properties of the products. Cimetidine (CIM) has several relevant solid state forms, including four polymorphs (A, B, C and D), an amorphous form (AM) and a monohydrate (M1). Dehydration of M1 has been reported to yield mixtures of polymorphs A, B and C or just a single form. Standards of the solid forms of CIM were prepared and unequivocally characterized by FTIR spectroscopy, digital microscopy, differential scanning calorimetry and solid state 13C NMR spectroscopy. Multivariate curve resolution with alternating least squares (MCR-ALS) was coupled to variable temperature attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) to dynamically characterize the behavior of form M1 of CIM over a temperature range from ambient to 160 ◦C, without sample pretreatment. MCR-ALS analysis of ATR-FTIR spectra obtained from the tested solid under variable temperature conditions unveiled the pure spectra of the species involved in the polymorphic transitions. This allowed the simultaneous observation of thermochemical and thermophysical events associated to the changes involved in the solid forms, enabling their unequivocal identification and improving the understanding of their thermal behavior. It was demonstrated that under the experimental conditions, dehydration of M1 initially results in the formation of polymorph B; after melting and upon cooling, the latter yields an amorphous solid (AM). It was concluded that the ATR-FTIR/MCR association is a promising and useful technique for monitoring solid-state phase transformations. © 2014 Elsevier B.V. All rights reserved.
Capacity Utilization , Productivity and Production Function : Results on Public Sector Unit ( BVFCL , Namrup )

This paper analyses the relation between capacity utilization and productivity of BVFCL, Namrup for the period 20032013. The results point out that both in short run and long run the factors are related to each other. However, it is capacity utilization that granger cause productivity. Specification and estimation of CD (CobbDouglas), CES (Constant Elasticity of Substitution) and VES (Variable Elasticity of Substitution) production function indicates that BVFCL follows CD production function.
A Tier Metaphor for Describing R , D & E

We seek to understand how the use of Research, Development, and Engineering (R,D&E) metrics can lead to more effective management of R,D&E. This paper combines qualitative and quantitative research to understand and improve the use of R,D&E metrics. Our research begins with interviews of 43 representative Chief Technical Officers, Chief Executive Offices, and researchers at 10 research-intensive international organizations. These interviews, and an extensive review of the literature, provide qualitative insights. Formal mathematical models attempt to explore these qualitative insights based on more general principles. Our research suggests that metrics-based evaluation and management vary according to the characteristics of the R,D&E activity. For applied projects, we find that project selection can be based on market-outcome metrics when firms use central subsidies to account for short-termism, risk aversion, and scope. With an efficient form of subsidies known as ‘‘tin-cupping,’’ the business units have the incentives to choose the projects that are in the firm’s best long-term interests. For core-technological development, longer time delays and more risky programs imply that popular R,D&E effectiveness metrics lead researchers to select programs that are not in the firm’s long-term interest. Our analyses suggest that firms moderate such market-outcome metrics by placing a larger weight on metrics that attempt to measure research effort more directly. These metrics include standard measures such as publications, citations, patents, citations to patents, and peer review. For basic research, the issues shift to getting the right people and encouraging a breadth of ideas. Unfortunately, metrics that identify the ‘‘best people’’ based on research success lead directly to ‘‘not-invented-here’’ behaviors. Such behaviors result in research empires that are larger than necessary, but lead to fewer ideas. We suggest that firms use ‘‘research tourism’’ metrics, which encourage researchers to take advantage of research spillovers from universities, other industries, and, even, competitors. (Marketing; Research and Development; Product Development; Incentives)
Chapter 9 VideoClipQuests as a New Setup for Learning

VideoClipQuests (VCQs) are a teaching–learning approach focused on the learners self-activity while information is collected by searching the Internet, similar to the well-established concept of WebQuests. VCQs can be one element to sensibly integrate the possibilities and advantages of the virtual world into teaching. Some of the advantages of VCQs are that they allow the teachers great latitude, they can be created very easily, they are compatible with a multitude of learning platforms, and they can be used both in e-learning and traditional lectures. Moreover, they appear to inherently motivate the learners and thus become highly accepted. In this chapter, we present the concept of a VCQ as well as first evaluation results of their influence in learning.