Search results for: Candidate Sets

Authors: J.R. Quevedo, E. Montañés, J. Ranilla, A. Bahamonde

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The new framework the Higher Education is immersed in involves a complete change in the way lecturers must teach and students must learn. Whereas the lecturer was the main character in traditional education, the essential goal now is to increase the students' participation in the process. Thus, one of the main tasks of lecturers in this new context is to design activities of different nature in order to encourage such participation. Seminars are one of the activities included in this environment. They are active sessions that enable going in depth into specific topics as support of other activities. They are characterized by some features such as favoring interaction between students and lecturers or improving their communication skills. Hence, planning and organizing strategic seminars is indeed a great challenge for lecturers with the aim of acquiring knowledge and abilities. This paper proposes a method using Artificial Intelligence techniques to obtain student profiles from their marks and preferences. The goal of building such profiles is twofold. First, it facilitates the task of splitting the students into different groups, each group with similar preferences and learning difficulties. Second, it makes it easy to select adequate topics to be a candidate for the seminars. The results obtained can be either a guarantee of what the lecturers could observe during the development of the course or a clue to reconsider new methodological strategies in certain topics.

Keywords: artificial intelligence, clustering, organizingseminars, student profile

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Authors: Nagmani Lnu

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Often, quality engineering refers to testing the applications that either have a User Interface (UI) or an Application Programming Interface (API). We often find mature test practices, standards, and automation regarding UI or API testing. However, another kind is present in almost all types of industries that deal with data in bulk and often get handled through something called a batch application. This is primarily an offline application companies develop to process large data sets that often deal with multiple business rules. The challenge gets more prominent when we try to automate batch testing. This paper describes the approaches taken to test a batch application from a financial industry to test the payment settlement process (a critical use case in all kinds of FinTech companies), resulting in 100% test automation in test creation and test execution. One can follow this approach for any other batch use cases to achieve a higher efficiency in their testing process.

Keywords: Batch testing, batch test automation, batch test strategy, payments testing, payments settlement testing.

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Authors: Chee Peng Lim, Wei Yee Goh

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In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.

Keywords: AdaBoost, Elman network, neural network ensemble, time series regression.

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Authors: María-Dolores Cubiles-de-la-Vega, Rafael Pino-Mejías, Esther-Lydia Silva-Ramírez

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A dissimilarity measure between the empiric characteristic functions of the subsamples associated to the different classes in a multivariate data set is proposed. This measure can be efficiently computed, and it depends on all the cases of each class. It may be used to find groups of similar classes, which could be joined for further analysis, or it could be employed to perform an agglomerative hierarchical cluster analysis of the set of classes. The final tree can serve to build a family of binary classification models, offering an alternative approach to the multi-class SVM problem. We have tested this dendrogram based SVM approach with the oneagainst- one SVM approach over four publicly available data sets, three of them being microarray data. Both performances have been found equivalent, but the first solution requires a smaller number of binary SVM models.

Keywords: Cluster Analysis, Empiric Characteristic Function, Multi-class SVM, R.

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Authors: C. Ardil

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This article presents a multiple criteria evaluation approach to uncertainty, vagueness, and imprecision analysis for ranking alternatives with fuzzy data for decision making using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The fighter aircraft evaluation and selection decision making problem is modeled in a fuzzy environment with triangular fuzzy numbers. The fuzzy decision information related to the fighter aircraft selection problem is taken into account in ordering the alternatives and selecting the best candidate. The basic fuzzy TOPSIS procedure steps transform fuzzy decision matrices into matrices of alternatives evaluated according to all decision criteria. A practical numerical example illustrates the proposed approach to the fighter aircraft selection problem.

Keywords: triangular fuzzy number (TFN), multiple criteria decision making analysis, decision making, aircraft selection, MCDMA, fuzzy TOPSIS

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Authors: Sarantos Psycharis

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Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

Keywords: STEM, computational thinking, physical computing, Arduino, Labview, self-efficacy.

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Authors: Zhihan Li

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Nowadays, most universities use the course enrollment system considering students’ registration orders. However, the students’ preference level to certain courses is also one important factor to consider. In this research, the possibility of applying a preference-first system has been discussed and analyzed compared to the order-first system. A bipartite graph is applied to resemble the relationship between students and courses they tend to register. With the graph set up, we apply Ford-Fulkerson (F.F.) Algorithm to maximize parings between two sets of nodes, in our case, students and courses. Two models are proposed in this paper: the one considered students’ order first, and the one considered students’ preference first. By comparing and contrasting the two models, we highlight the usability of models which potentially leads to better designs for school course registration systems.

Keywords: Bipartite graph, Ford-Fulkerson Algorithm, graph theory, maximum matching.

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Authors: Jennifer Penton, Charitha Pattiaratchi

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Surface currents play a major role in the distribution of contaminants, the connectivity of marine populations, and can influence the vertical and horizontal distribution of nutrients within the water column. This paper aims to determine the effects of sea breeze-wind patterns on the climatology of the surface currents on the continental shelf surrounding Rottnest Island, WA Australia. The alternating wind patterns allow for full cyclic rotations of wind direction, permitting the interpretation of the effect of the wind on the surface currents. It was found that the surface currents only clearly follow the northbound Capes Current in times when the Fremantle Doctor sets in. Surface currents react within an hour to a change of direction of the wind, allowing southerly currents to dominate during strong northerly sea breezes, often followed by mixed currents dominated by eddies in the inter-lying times.

Keywords: HF radar, surface currents, sea breeze.

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

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Authors: František Včelař, Zuzana Pátíková

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Recently a new type of very general relational structures, the so called (L-)complete propelattices, was introduced. These significantly generalize complete lattices and completely lattice L-ordered sets, because they do not assume the technically very strong property of transitivity. For these structures also the main part of the original Tarski’s fixed point theorem holds for (L-fuzzy) isotone maps, i.e., the part which concerns the existence of fixed points and the structure of their set. In this paper, fundamental properties of (L-)complete propelattices are recalled and the so called L-fuzzy relatively isotone maps are introduced. For these maps it is proved that they also have fixed points in L-complete propelattices, even if their set does not have to be of an awaited analogous structure of a complete propelattice.

Keywords: Fixed point, L-complete propelattice, L-fuzzy (relatively) isotone map, residuated lattice, transitivity.

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Authors: Morteza Moazami-Goudarzi, Ali Taheri, Mohammad Pooyan, Reza Mahboobi

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In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals and then, selecting it for using with SPIHT codec. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MIT-BIH database. For assessing the functionality of the different multiwavelets in compressing ECG signals, in addition to known factors such as Compression Ratio (CR), Percent Root Difference (PRD), Distortion (D), Root Mean Square Error (RMSE) in compression literature, we also employed the Cross Correlation (CC) criterion for studying the morphological relations between the reconstructed and the original ECG signal and Signal to reconstruction Noise Ratio (SNR). The simulation results show that the Cardinal Balanced Multiwavelet (cardbal2) by the means of identity (Id) prefiltering method to be the best effective transformation. After finding the most efficient multiwavelet, we apply SPIHT coding algorithm on the transformed signal by this multiwavelet.

Keywords: ECG compression, Prefiltering, Cardinal Balanced Multiwavelet.

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Authors: Keun-Chang Kwak

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This paper is concerned with motion recognition based fuzzy WP(Wavelet Packet) feature extraction approach from Vicon physical data sets. For this purpose, we use an efficient fuzzy mutual-information-based WP transform for feature extraction. This method estimates the required mutual information using a novel approach based on fuzzy membership function. The physical action data set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected from 10 subjects using the Vicon 3D tracker. The experiments consist of running, seating, and walking as physical activity motion among various activities. The experimental results revealed that the presented feature extraction approach showed good recognition performance.

Keywords: Motion recognition, fuzzy wavelet packet, Vicon physical data.

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Authors: S. S. P. M. Isa, N. M. Arifin, R. Nazar, N. Bachok, F. M. Ali, I. Pop

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A theoretical study has been presented to describe the boundary layer flow and heat transfer on an exponentially shrinking sheet with a variable wall temperature and suction, in the presence of magnetic field. The governing nonlinear partial differential equations are converted into ordinary differential equations by similarity transformation, which are then solved numerically using the shooting method. Results for the skin friction coefficient, local Nusselt number, velocity profiles as well as temperature profiles are presented through graphs and tables for several sets of values of the parameters. The effects of the governing parameters on the flow and heat transfer characteristics are thoroughly examined.

Keywords: Exponentially shrinking sheet, magnetic field, mixed convection, suction.

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Authors: Ginhsuan Li, Chiuyun Hung, Desheng Chen, Yiwen Wang

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Application-Specific Instruction (ASI ) set Processors (ASIP) have become an important design choice for embedded systems due to runtime flexibility, which cannot be provided by custom ASIC solutions. One major bottleneck in maximizing ASIP performance is the limitation on the data bandwidth between the General Purpose Register File (GPRF) and ASIs. This paper presents the Implicit Registers (IRs) to provide the desirable data bandwidth. An ASI Input/Output model is proposed to formulate the overheads of the additional data transfer between the GPRF and IRs, therefore, an IRs allocation algorithm is used to achieve the better performance by minimizing the number of extra data transfer instructions. The experiment results show an up to 3.33x speedup compared to the results without using IRs.

Keywords: Application-Specific Instruction-set Processors, data bandwidth, configurable processor, implicit register.

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Authors: Ana Bobirca, Paul-Gabriel Miclaus

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International competitiveness receives much attention nowadays, but up to now its assessment has been heavily based on manufacturing industry statistics. This paper addresses the need for competitiveness indicators that cover the service sector and sets out a multilevel framework for measuring international services trade competitiveness. The approach undertaken here aims at comparatively examining the international competitiveness of the EU-25 (the twenty-five European Union member states before the 1st of January 2007), Romanian and Bulgarian services trade, as well as the last two countries- structure of specialization on the EU-25 services market. The primary changes in the international competitiveness of three major services sectors – transportation, travel and other services - are analyzed. This research attempts to determine the ability of the two recent European Union (EU) member states to contend with the challenges that might arise from the hard competition within the enlarged EU, in the field of services trade.

Keywords: Bulgaria, EU-25, international competitiveness, international services trade, Romania.

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Authors: Yaser Mohammad Taheri, Alireza Zolghadr–asli, Mehran Yazdi

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Video watermarking is usually considered as watermarking of a set of still images. In frame-by-frame watermarking approach, each video frame is seen as a single watermarked image, so collusion attack is more critical in video watermarking. If the same or redundant watermark is used for embedding in every frame of video, the watermark can be estimated and then removed by watermark estimate remodolulation (WER) attack. Also if uncorrelated watermarks are used for every frame, these watermarks can be washed out with frame temporal filtering (FTF). Switching watermark system or so-called SS-N system has better performance against WER and FTF attacks. In this system, for each frame, the watermark is randomly picked up from a finite pool of watermark patterns. At first SS-N system will be surveyed and then a new collusion attack for SS-N system will be proposed using a new algorithm for separating video frame based on watermark pattern. So N sets will be built in which every set contains frames carrying the same watermark. After that, using WER attack in every set, N different watermark patterns will be estimated and removed later.

Keywords: Watermark estimation remodulation (WER), Frame Temporal Averaging (FTF), switching watermark system.

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Authors: Ilkka Niskanen, Jarmo Kalaoja, Julia Kantorovitch, Toni Piirainen

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Ontologies are broadly used in the context of networked home environments. With ontologies it is possible to define and store context information, as well as to model different kinds of physical environments. Ontologies are central to networked home environments as they carry the meaning. However, ontologies and the OWL language is complex. Several ontology visualization approaches have been developed to enhance the understanding of ontologies. The domain of networked home environments sets some special requirements for the ontology visualization approach. The visualization tool presented here, visualizes ontologies in a domain-specific way. It represents effectively the physical structures and spatial relationships of networked home environments. In addition, it provides extensive interaction possibilities for editing and manipulating the visualization. The tool shortens the gap from beginner to intermediate OWL ontology reader by visualizing instances in their actual locations and making OWL ontologies more interesting and concrete, and above all easier to comprehend.

Keywords: Ontologies, visualization, interaction.

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Authors: Wiem Gadri

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This study delves into the intriguing properties of Pisot and Salem numbers within the framework of formal Laurent series over finite fields, a domain where these numbers’ spectral characteristics, Λm(β) and lm(β), have yet to be fully explored. Utilizing a methodological approach that combines algebraic number theory with the analysis of power series, we extend the foundational work of Erdos, Joo, and Komornik to this setting. Our research uncovers bounds for lm(β), revealing how these depend on the degree of the minimal polynomial of β and thus offering a characterization of Pisot and Salem formal power series. The findings significantly contribute to our understanding of these numbers, highlighting their distribution and properties in the context of formal power series. This investigation not only bridges number theory with formal power series analysis but also sets the stage for further interdisciplinary research in these areas.

Keywords: Pisot numbers, Salem numbers, Formal power series, Minimal polynomial degree.

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Authors: Khalil Shihab, Nida Al-Chalabi

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This article describes Uruk, the virtual museum of Iraq that we developed for visual exploration and retrieval of image collections. The system largely exploits the loosely-structured hierarchy of XML documents that provides a useful representation method to store semi-structured or unstructured data, which does not easily fit into existing database. The system offers users the capability to mine and manage the XML-based image collections through a web-based Graphical User Interface (GUI). Typically, at an interactive session with the system, the user can browse a visual structural summary of the XML database in order to select interesting elements. Using this intermediate result, queries combining structure and textual references can be composed and presented to the system. After query evaluation, the full set of answers is presented in a visual and structured way.

Keywords: Data-centric XML, graphical user interfaces, information retrieval, case-based reasoning, fuzzy sets

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Authors: S. Raissi, R- Eslami Farsani

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In recent years, response surface methodology (RSM) has brought many attentions of many quality engineers in different industries. Most of the published literature on robust design methodology is basically concerned with optimization of a single response or quality characteristic which is often most critical to consumers. For most products, however, quality is multidimensional, so it is common to observe multiple responses in an experimental situation. Through this paper interested person will be familiarize with this methodology via surveying of the most cited technical papers. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with more than two responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

Keywords: Multi-Response Surface Methodology (MRSM), Design of Experiments (DOE), Process modeling, Quality improvement; Robust Design.

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Authors: Jovana Dj. Jovanovic, Svetlana M. Stevovic

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The highest priority of so called, projected passive houses is to meet the appropriate energy demand. Every single material and layer which is injected into a dwelling has a certain energy quantity stored. The passive houses include optimized insulation levels with minimal thermal bridges, minimum of air leakage through the building, utilization of passive solar and internal gains, and good circulation of air which leans on mechanical ventilation system. The focus of this paper is on passive house features, benefits and targets, their feasibility and energy demands which are set up during each project. Numerous passive house-standards outline the very significant role of zero-energy dwellings towards the modern label of sustainable development. It is clear that the performance of both built and existing housing stock must be addressed if the population across the world sets out the energy objectives. This scientific article examines passive house features since the many passive house cases are launched.

Keywords: Benefits, energy demands, passive houses, sustainable development.

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Authors: Linyu Wang, Furui Huo, Jianhong Xiang

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The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit (SOMP) algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low Signal-to-Noise Ratio (SNR) stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms.

Keywords: OFDM, doubly selective, channel estimation, compressed sensing

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Authors: Sandeep Chandana, Rene V. Mayorga

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The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.

Keywords: Boundary neuron, neuro-fuzzy, output excitation factor, RANFIS, rough approximation, rough neural computing.

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Authors: Melike Şah, Konstantin Y.Degtiarev

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This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy time series. In contrast to traditional forecasting methods, fuzzy time series can be also applied to problems, in which historical data are linguistic values. It is shown that proposed time-invariant method improves the performance of forecasting process. Further, the effect of using different number of fuzzy sets is tested as well. As with the most of cited papers, historical enrollment of the University of Alabama is used in this study to illustrate the forecasting process. Subsequently, the performance of the proposed method is compared with existing fuzzy time series time-invariant models based on forecasting accuracy. It reveals a certain performance superiority of the proposed method over methods described in the literature.

Keywords: Forecasting, fuzzy time series, linguistic values, student enrollment, time-invariant model.

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Authors: Andreas Theissler, Ian Dear

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The one-class support vector machine “support vector data description” (SVDD) is an ideal approach for anomaly or outlier detection. However, for the applicability of SVDD in real-world applications, the ease of use is crucial. The results of SVDD are massively determined by the choice of the regularisation parameter C and the kernel parameter  of the widely used RBF kernel. While for two-class SVMs the parameters can be tuned using cross-validation based on the confusion matrix, for a one-class SVM this is not possible, because only true positives and false negatives can occur during training. This paper proposes an approach to find the optimal set of parameters for SVDD solely based on a training set from one class and without any user parameterisation. Results on artificial and real data sets are presented, underpinning the usefulness of the approach.

Keywords: Support vector data description, anomaly detection, one-class classification, parameter tuning.

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Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su, Junjie Wang

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The Bernoulli filter is a precise Bayesian filter for single target tracking based on the random finite set theory. The standard Bernoulli filter often underestimates the number of the targets. This study proposes a Gaussian particle flow (GPF) Bernoulli filter employing particle flow to migrate particles from prior to posterior positions to improve the performance of the standard Bernoulli filter. By employing the particle flow filter, the computational speed of the Bernoulli filters is significantly improved. In addition, the GPF Bernoulli filter provides more accurate estimation compared with that of the standard Bernoulli filter. Simulation results confirm the improved tracking performance and computational speed in two- and three-dimensional scenarios compared with other algorithms.

Keywords: Bernoulli filter, particle filter, particle flow filter, random finite sets, target tracking.

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Authors: Benjamin Anderson-Sackaney, Amr Abdel-Dayem

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This paper presents a comprehensive survey of recent source camera identification (SCI) systems. Then, the performance of various sensor pattern noise (SPN) estimators was experimentally assessed, under common photo response non-uniformity (PRNU) frameworks. The experiments used 1350 natural and 900 flat-field images, captured by 18 individual cameras. 12 different experiments, grouped into three sets, were conducted. The results were analyzed using the receiver operator characteristic (ROC) curves. The experimental results demonstrated that combining the basic SPN estimator with a wavelet-based filtering scheme provides promising results. However, the phase SPN estimator fits better with both patch-based (BM3D) and anisotropic diffusion (AD) filtering schemes.

Keywords: Sensor pattern noise, source camera identification, photo response non-uniformity, anisotropic diffusion, peak to correlation energy ratio.

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Authors: Aditi Shukla, Ambarish S. Vidyarthi, Subir Samanta

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The worldwide prevalence of H3N2 influenza virus and its increasing resistance to the existing drugs necessitates for the development of an improved/better targeting anti-influenza drug. H3N2 influenza neuraminidase is one of the two membrane-bound proteins belonging to group-2 neuraminidases. It acts as key player involved in viral pathogenicity and hence, is an important target of anti-influenza drugs. Oseltamivir is one of the potent drugs targeting this neuraminidase. In the present work, we have taken subtype N2 neuraminidase as the receptor and probable analogs of oseltamivir as drug molecules to study the protein-drug interaction in anticipation of finding efficient modified candidate compound. Oseltamivir analogs were made by modifying the functional groups using Marvin Sketch software and were docked using Schrodinger-s Glide. Oseltamivir analog 10 was detected to have significant energy value (16% less compared to Oseltamivir) and could be the probable lead molecule. It infers that some of the modified compounds can interact in a novel manner with increased hydrogen bonding at the active site of neuraminidase and it might be better than the original drug. Further work can be carried out such as enzymatic inhibition studies; synthesis and crystallizing the drug-target complex to analyze the interactions biologically.

Keywords: H3N2 Influenza, Neuraminidase, Oseltamiviranalogs, structure based drug designing

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Authors: P Chockalingam, K Kok, R Vijayaram

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This paper presents a comparative study on dry and wet grinding through experimental investigation in the grinding of CSM glass fibre reinforced polymer laminates using a pink aluminium oxide wheel. Different sets of experiments were performed to study the effects of the independent grinding parameters such as grinding wheel speed, feed and depth of cut on dependent performance criteria such as cutting forces and surface finish. Experimental conditions were laid out using design of experiment central composite design. An effective coolant was sought in this study to minimise cutting forces and surface roughness for GFRP laminates grinding. Test results showed that the use of coolants reduces surface roughness, although not necessarily the cutting forces. These research findings provide useful economic machining solution in terms of optimized grinding conditions for grinding CSM GFRP.

Keywords: Chopped Strand Mat GFRP laminates, Dry and Wet Grinding, Cutting Forces, Surface Finish.

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Authors: Roman Asatryan

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The decision-making processes in Corporate Social Responsibility (CSR) among firms in the airlines industry borders on the benefits that accrue to firms through those investments. The crux of the matter is how firms can quantify the benefits derived from such investments. This paper analyses the cost benefit adjustment strategies for firms in the airline industry in their CSR strategy adoption and implementation. The paper discusses the CBA model in order to understand the ways airlines can reduce costs and increase returns on CSR, or balance the cost and benefits. The analysis indicates that, economic concepts especially the CBA are useful, though they are not without challenges. This paper concludes that the CBA model gives a basic understanding of the motivations for investing in intangible assets like CSR. It sets the tone for formulating relevant hypothesis in empirical studies in investment in CSR and other intangible assets in business operations.

Keywords: Cost Benefit Analysis, Corporate Social Responsibility, airline industry.

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