Search results for: work in process (WIP)

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

Abstract:

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: M. Amrita, R. R. Srikant, A. V. Sita Rama Raju

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Water miscible cutting fluids are conventionally used to lubricate and cool the machining zone. But issues related to health hazards, maintenance and disposal costs have limited their usage, leading to application of Minimum Quantity Lubrication (MQL). To increase the effectiveness of MQL, nanocutting fluids are proposed. In the present work, water miscible nanographite cutting fluids of varying concentration are applied at cutting zone by two systems A and B. System A utilizes high pressure air and supplies cutting fluid at a flow rate of 1ml/min. System B uses low pressure air and supplies cutting fluid at a flow rate of 5ml/min. Their performance in machining is evaluated by measuring cutting temperatures, tool wear, cutting forces and surface roughness and compared with dry machining and flood machining. Application of nanocutting fluid using both systems showed better performance than dry machining. Cutting temperatures and cutting forces obtained by both techniques are more than flood machining. But tool wear and surface roughness showed improvement compared to flood machining. Economic analysis has been carried out in all the cases to decide the applicability of the techniques.

Keywords: Economic analysis, Machining, Minimum Quantity lubrication, nanofluid.

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Authors: Agus Harjoko, Sri Hartati, Henry Dwiyasa

Abstract:

There have been numerous implementations of security system using biometric, especially for identification and verification cases. An example of pattern used in biometric is the iris pattern in human eye. The iris pattern is considered unique for each person. The use of iris pattern poses problems in encoding the human iris. In this research, an efficient iris recognition method is proposed. In the proposed method the iris segmentation is based on the observation that the pupil has lower intensity than the iris, and the iris has lower intensity than the sclera. By detecting the boundary between the pupil and the iris and the boundary between the iris and the sclera, the iris area can be separated from pupil and sclera. A step is taken to reduce the effect of eyelashes and specular reflection of pupil. Then the four levels Coiflet wavelet transform is applied to the extracted iris image. The modified Hamming distance is employed to measure the similarity between two irises. This research yields the identification success rate of 84.25% for the CASIA version 1.0 database. The method gives an accuracy of 77.78% for the left eyes of MMU 1 database and 86.67% for the right eyes. The time required for the encoding process, from the segmentation until the iris code is generated, is 0.7096 seconds. These results show that the accuracy and speed of the method is better than many other methods.

Keywords: Biometric, iris recognition, wavelet transform.

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Authors: N. Yagnesh Sharma, K. Vasudeva Karanth

Abstract:

The flow field in a centrifugal fan is highly complex with flow reversal taking place on the suction side of impeller and diffuser vanes. Generally performance of the centrifugal fan could be enhanced by judiciously introducing splitter vanes so as to improve the diffusion process. An extensive numerical whole field analysis on the effect of splitter vanes placed in discrete regions of suspected separation points is possible using CFD. This paper examines the effect of splitter vanes corresponding to various geometrical locations on the impeller and diffuser. The analysis shows that the splitter vanes located near the diffuser exit improves the static pressure recovery across the diffusing domain to a larger extent. Also it is found that splitter vanes located at the impeller trailing edge and diffuser leading edge at the mid-span of the circumferential distance between the blades show a marginal improvement in the static pressure recovery across the fan. However, splitters provided near to the suction side of the impeller trailing edge (25% of the circumferential gap between the impeller blades towards the suction side), adversely affect the static pressure recovery of the fan.

Keywords: Splitter vanes, Flow separation, Sliding mesh, Unsteady analysis, Recirculation zone, Jets and wakes.

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Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

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Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.

Keywords: Clustering, k-means, categorical datasets, pattern recognition, unsupervised learning, knowledge discovery.

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Authors: S. Sowmyayani, P. Arockia Jansi Rani

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This paper integrates Octagon and Square Search pattern (OCTSS) motion estimation algorithm into H.264/AVC (Advanced Video Coding) video codec in Adaptive Group of Pictures (AGOP) mode. AGOP structure is computed based on scene change in the video sequence. Octagon and square search pattern block-based motion estimation method is implemented in inter-prediction process of H.264/AVC. Both these methods reduce bit rate and computational complexity while maintaining the quality of the video sequence respectively. Experiments are conducted for different types of video sequence. The results substantially proved that the bit rate, computation time and PSNR gain achieved by the proposed method is better than the existing H.264/AVC with fixed GOP and AGOP. With a marginal gain in quality of 0.28dB and average gain in bitrate of 132.87kbps, the proposed method reduces the average computation time by 27.31 minutes when compared to the existing state-of-art H.264/AVC video codec.

Keywords: Block Distortion Measure, Block Matching Algorithms, H.264/AVC, Motion estimation, Search patterns, Shot cut detection.

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Authors: Kiran Kumar K, Ramesh Babu Bejjam, Atul Najan

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A thermosyphon system is a heat transfer loop which operates on the basis of gravity and buoyancy forces. It guarantees a good reliability and low maintenance cost as it does not involve any mechanical pump. Therefore, it can be used in many industrial applications such as refrigeration and air conditioning, electronic cooling, nuclear reactors, geothermal heat extraction, etc. But flow instabilities and loop configuration are the major problems in this system. Several previous researchers studied that stabilities can be suppressed by using nanofluids as loop fluid. In the present study a rectangular thermosyphon loop with end heat exchangers are considered for the study. This configuration is more appropriate for many practical applications such as solar water heater, geothermal heat extraction, etc. In the present work, steady-state analysis is carried out on thermosyphon loop with parallel flow coaxial heat exchangers at heat source and heat sink. In this loop nanofluid is considered as the loop fluid and water is considered as the external fluid in both hot and cold heat exchangers. For this analysis onedimensional homogeneous model is developed. In this model, conservation equations like conservation of mass, momentum, energy are discretized using finite difference method. A computer code is written in MATLAB to simulate the flow in thermosyphon loop. A comparison in terms of heat transfer is made between water and nanofluid as working fluids in the loop.

Keywords: Heat exchanger, Heat transfer, Nanofluid, Thermosyphon loop.

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Authors: Ludovic Favre, Thibaut M. Schafer, Jean-Luc Robyr, Elena-Lavinia Niederhäuser

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This paper presents an optimization method based on genetic algorithm for the energy management inside buildings developed in the frame of the project Smart Living Lab (SLL) in Fribourg (Switzerland). This algorithm optimizes the interaction between renewable energy production, storage systems and energy consumers. In comparison with standard algorithms, the innovative aspect of this project is the extension of the smart regulation over three simultaneous criteria: the energy self-consumption, the decrease of greenhouse gas emissions and operating costs. The genetic algorithm approach was chosen due to the large quantity of optimization variables and the non-linearity of the optimization function. The optimization process includes also real time data of the building as well as weather forecast and users habits. This information is used by a physical model of the building energy resources to predict the future energy production and needs, to select the best energetic strategy, to combine production or storage of energy in order to guarantee the demand of electrical and thermal energy. The principle of operation of the algorithm as well as typical output example of the algorithm is presented.

Keywords: Building’s energy, control system, energy management, modelling, genetic optimization algorithm, renewable energy, greenhouse gases, energy storage.

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Authors: Shashank N. Mathur, Anil K. Ahlawat, Virendra P. Vishwakarma

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In this paper, a comparative study of application of supervised and unsupervised learning algorithms on illumination invariant face recognition has been carried out. The supervised learning has been carried out with the help of using a bi-layered artificial neural network having one input, two hidden and one output layer. The gradient descent with momentum and adaptive learning rate back propagation learning algorithm has been used to implement the supervised learning in a way that both the inputs and corresponding outputs are provided at the time of training the network, thus here is an inherent clustering and optimized learning of weights which provide us with efficient results.. The unsupervised learning has been implemented with the help of a modified Counterpropagation network. The Counterpropagation network involves the process of clustering followed by application of Outstar rule to obtain the recognized face. The face recognition system has been developed for recognizing faces which have varying illumination intensities, where the database images vary in lighting with respect to angle of illumination with horizontal and vertical planes. The supervised and unsupervised learning algorithms have been implemented and have been tested exhaustively, with and without application of histogram equalization to get efficient results.

Keywords: Artificial Neural Networks, back propagation, Counterpropagation networks, face recognition, learning algorithms.

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Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Henrik Skov Midtiby, Anders Krogh Mortensen, Sanmohan Baby

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This work contributes a statistical model and simulation framework yielding the best estimate possible for the potential herbicide reduction when using the MoDiCoVi algorithm all the while requiring a efficacy comparable to conventional spraying. In June 2013 a maize field located in Denmark were seeded. The field was divided into parcels which was assigned to one of two main groups: 1) Control, consisting of subgroups of no spray and full dose spraty; 2) MoDiCoVi algorithm subdivided into five different leaf cover thresholds for spray activation. In addition approximately 25% of the parcels were seeded with additional weeds perpendicular to the maize rows. In total 299 parcels were randomly assigned with the 28 different treatment combinations. In the statistical analysis, bootstrapping was used for balancing the number of replicates. The achieved potential herbicide savings was found to be 70% to 95% depending on the initial weed coverage. However additional field trials covering more seasons and locations are needed to verify the generalisation of these results. There is a potential for further herbicide savings as the time interval between the first and second spraying session was not long enough for the weeds to turn yellow, instead they only stagnated in growth.

Keywords: Weed crop discrimination, macrosprayer, herbicide reduction, site-specific, sprayer-boom.

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Authors: Marwah Mohsin, Thomas Beach, Alan Kwan, Mahdi Ismail

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This paper describes the differences in views on sustainable development between the general public and experts in a developing country, Iraq. This paper will answer the question: How do the views of the public differ from the generally accepted view of experts in the context of sustainable urban development in Iraq? In order to answer this question, the views of both the public and the experts will be analysed. These results are taken from a public survey and a Delphi questionnaire. These will be analysed using statistical methods in order to identify the significant differences. This will enable investigation of the different perceptions between the public perceptions and the experts’ views towards urban sustainable development factors. This is important due to the fact that different viewpoints between policy-makers and the public will impact on the acceptance by the public of any future sustainable development work that is undertaken. The brief findings of the statistical analysis show that the views of both the public and the experts are considered different in most of the variables except six variables show no differences. Those variables are ‘The importance of establishing sustainable cities in Iraq’, ‘Mitigate traffic congestion’, ‘Waste recycling and separating’, ‘Use wastewater recycling’, ‘Parks and green spaces’, and ‘Promote investment’.

Keywords: Urban sustainable development, experts’ views, public views, statistical analysis.

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Authors: Farhan Ismaeel Dakheel, Raoof Smko, K. Negrat, Abdelsalam Almarimi

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In this paper we used data mining techniques to identify outlier patients who are using large amount of drugs over a long period of time. Any healthcare or health insurance system should deal with the quantities of drugs utilized by chronic diseases patients. In Kingdom of Bahrain, about 20% of health budget is spent on medications. For the managers of healthcare systems, there is no enough information about the ways of drug utilization by chronic diseases patients, is there any misuse or is there outliers patients. In this work, which has been done in cooperation with information department in the Bahrain Defence Force hospital; we select the data for Cardiac patients in the period starting from 1/1/2008 to December 31/12/2008 to be the data for the model in this paper. We used three techniques for finding the drug utilization for cardiac patients. First we applied a clustering technique, followed by measuring of clustering validity, and finally we applied a decision tree as classification algorithm. The clustering results is divided into three clusters according to the drug utilization, for 1603 patients, who received 15,806 prescriptions during this period can be partitioned into three groups, where 23 patients (2.59%) who received 1316 prescriptions (8.32%) are classified to be outliers. The classification algorithm shows that the use of average drug utilization and the age, and the gender of the patient can be considered to be the main predictive factors in the induced model.

Keywords: Data Mining, Clustering, Classification, Drug Utilization..

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Authors: Erna Astuti, Supranto, Rochmadi, Agus Prasetya

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Biodiesel production from vegetable oil will produce glycerol as by-product about 10% of the biodiesel production. The amount of glycerol that was produced needed alternative way to handling immediately so as to not become the waste that polluted environment. One of the solutions was to process glycerol to polyglycidyl nitrate (PGN). PGN is synthesized from glycerol by three-step reactions i.e. nitration of glycerol, cyclization of 13- dinitroglycerine and polymerization of glycosyl nitrate. Optimum condition of nitration of glycerol with nitric acid has not been known. Thermodynamic feasibility should be done before run experiments in the laboratory. The aim of this study was to determine the parameters those affect nitration of glycerol and nitric acid and chose the operation condition. Many parameters were simulated to verify its possibility to experiment under conditions which would get the highest conversion of 1, 3-dinitroglycerine and which was the ideal condition to get it. The parameters that need to be studied to obtain the highest conversion of 1, 3-dinitroglycerine were mol ratio of nitric acid/glycerol, reaction temperature, mol ratio of glycerol/dichloromethane and pressure. The highest conversion was obtained in the range of mol ratio of nitric acid /glycerol between 2/1 – 5/1, reaction temperature of 5-25oC and pressure of 1 atm. The parameters that need to be studied further to obtain the highest conversion of 1.3 DNG are mol ratio of nitric acid/glycerol and reaction temperature.

Keywords: Nitration, glycerol, thermodynamic, optimum condition.

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Authors: Melvin A. Ballera

Abstract:

Prior literature in the field of adaptive and personalized learning sequence in e-learning have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization, but complex to implement due to expensive algorithmic programming and need of extensive and prior data. The main objective of personalizing learning sequence is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning competency of learner. In this paper, a revolutionary technique has been proposed and tested to perform individualization and personalization using modified reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance matrix such as examinations, reviews, and study to form the RWSA single numerical fitness value. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on student's prior knowledge and real performance matrix.

Keywords: E-learning, fitness value, personalized learning sequence, reversed roulette wheel selection algorithms.

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Authors: E. Movahednejad, F. Ommi

Abstract:

Droplet size distributions in the cold spray of a fuel are important in observed combustion behavior. Specification of droplet size and velocity distributions in the immediate downstream of injectors is also essential as boundary conditions for advanced computational fluid dynamics (CFD) and two-phase spray transport calculations. This paper describes the development of a new model to be incorporated into maximum entropy principle (MEP) formalism for prediction of droplet size distribution in droplet formation region. The MEP approach can predict the most likely droplet size and velocity distributions under a set of constraints expressing the available information related to the distribution. In this article, by considering the mechanisms of turbulence generation inside the nozzle and wave growth on jet surface, it is attempted to provide a logical framework coupling the flow inside the nozzle to the resulting atomization process. The purpose of this paper is to describe the formulation of this new model and to incorporate it into the maximum entropy principle (MEP) by coupling sub-models together using source terms of momentum and energy. Comparison between the model prediction and experimental data for a gas turbine swirling nozzle and an annular spray indicate good agreement between model and experiment.

Keywords: Droplet, instability, Size Distribution, Turbulence, Maximum Entropy

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Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

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The elastic period has a primary role in the seismic assessment of buildings. Reliable calculations and/or estimates of the fundamental frequency of a building and its site are essential during analysis and design process. Various code formulas based on empirical data are generally used to estimate the fundamental frequency of a structure. For existing structures, in addition to code formulas and available analytical tools such as modal analyses, various methods of testing including ambient and forced vibration testing procedures may be used to determine dynamic characteristics. In this study, the dynamic properties of the 32 buildings located in the Madinah of Saudi Arabia were identified using ambient motions recorded at several, spatially-distributed locations within each building. Ambient vibration measurements of buildings have been analyzed and the fundamental longitudinal and transverse periods for all tested buildings are presented. The fundamental mode of vibration has been compared in plots with codes formulae (Saudi Building Code, EC8, and UBC1997). The results indicate that measured periods of existing buildings are shorter than that given by most empirical code formulas. Recommendations are given based on the common design and construction practice in Madinah city.

Keywords: Ambient vibration, Fundamental period, RC buildings, Infill walls.

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Authors: Voss Harrigan, Korey Carter, Mohammad Reza Shaeri

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Detrimental effects of lunar dust on space hardware, spacesuits, and astronauts’ health have been already identified during Apollo missions. Developing effective dust mitigation technologies is critically important for successful space exploration and related missions in NASA applications. In this study, an electrostatic cleaning system (ECS) integrated with a negatively ionized Thunderon brush was developed to mitigate small-sized lunar dust particles with diameters ranging from 0.04 µm to 35 µm, and the mean and median size of 7 µm and 5 µm, respectively. It was found that the frequency pulses of the negative ion generator caused particles to stick to the Thunderon bristles and repel between the pulses. The brush was used manually to ensure that particles were removed from areas where the ECS failed to mitigate the lunar simulant. The acquired data demonstrated that the developed system removed over 91-96% of the lunar dust particles. The present study was performed as a proof-of-concept to enhance the cleaning performance of ECSs by integrating a brushing process. Suggestions were made to further improve the performance of the developed technology through future research.

Keywords: lunar dust mitigation, electrostatic cleaning system, brushing, Thunderon brush, cleaning rate

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Authors: C. Ardil

Abstract:

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: Shiferaw R. Jufar, Rong F. Huang, Ching M. Hsu

Abstract:

The spreading characteristics of acoustically excited swirling double-concentric jets were studied experimentally. The central jet was acoustically excited at low and high pulsation intensities. A smoke wire flow visualization and a hot-wire anemometer velocity measurement results show that excitation forces a vortex ring to roll-up from the edge of the central tube during each excitation period. At low pulsation intensities, the vortex ring evolves downstream, and eventually breaks up into turbulent eddies. At high pulsation intensities, the primary vortex ring evolves and a series of trailing vortex rings form during the same period of excitation. The trailing vortex rings accelerate while evolving downstream and overtake the primary vortex ring within the same cycle. In the process, the primary vortex ring becomes unstable and breaks up early. The effect of the fast traveling trailing vortex rings combined with the swirl motion of the annular flow improve jet spreading compared with the naturally evolving jets.

Keywords: Acoustic excitation, double–concentric jets, flow control, swirling jet.

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Authors: Haifeng Wang, Haili Zhang

Abstract:

Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: Computational social science, movie preference, machine learning, SVM.

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Authors: Vasudha Bansal, M. L. Singla, C. Ghanshyam

Abstract:

The effect of nonthermal pulsed electric field (PEF) and thermal treatment (90⁰C for 60s) was studied on quality parameters of emblica officinalis juice for the period of 6 weeks at 4⁰C using monopolar rectangular pulse of 1µs width. The PEF treatment was given using static chamber at 24kV/cm for 500µs. The quality of emblica officinalis juice was investigated in terms of non enzymatic browning index (NEBI), 5-hydroxymethyl-2-furfural (HMF), total polyphenol content and antioxidant capacity. ⁰Brix, pH and conductivity were evaluated as physical parameters. The aim of the work was to investigate the effect of PEF on the retention of bioactive compounds and retardation of browning activity. The results showed that conventional thermal treatment had led to a significant (p < 0.05) decrease of 48.15% in polyphenol content (129.56 mg of GAE L^-1), with higher NEBI and HMF formation (p < 0.05) whilst PEF suppressed NEBI and retained higher polyphenol compounds (168.59 mg GAE L^-1) with limiting the loss to 32.56% along maximum free radical scavenging activity (92.07%). However, pH, ⁰brix and electrical conductivity of treated juice samples remain unaffected. Therefore, PEF can be considered as an effective nonthermal treatment for retaining bioactive compounds along suppressing browning of emblica juice.

 

Keywords: Emblica officinalis juice, Free radical scavenging activity, Pulsed electric field, Total polyphenol content.

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Authors: J. Mizuno, S. Takahashi

Abstract:

In this paper, design and fabrication of an actuated parallel-plate mirror based on a 3D-printer is described. The mirror and electrode layers are fabricated separately and assembled thereafter. The alignment is performed by dowel pin-hole pairs fabricated on the respective layers. The electrodes are formed on the surface of the electrode layer by Au ion sputtering using a suitable mask, which is also fabricated by a 3D-printer.For grounding the mirror layer, except the contact area with the electrode paths, all the surface is Au ion sputtered. 3D-printers are widely used for creating 3D models or mock-ups. The authors have recently proposed that these models can perform electromechanical functions such as actuators by suitably masking them followed by metallization process. Since the smallest possible fabrication size is in the order of sub-millimeters, these electromechanical devices are named by the authors as SMEMS (Sub-Milli Electro-Mechanical Systems) devices. The proposed mirror described in this paper which consists of parallel-plate electrostatic actuators is also one type of SMEMS devices. In addition, SMEMS is totally environment-clean compared to MEMS (Micro Electro-Mechanical Systems) fabrication processes because any hazardous chemicals or gases are utilized.

Keywords: MEMS, parallel-plate mirror, SMEMS, 3D-printer.

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Authors: Raheleh Kholghi, Soheil Behnam Roudsari, Alireza Nemaney Pour

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Spam mails are unwanted mails sent to large number of users. Spam mails not only consume the network resources, but cause security threats as well. This paper proposes an efficient technique to detect, and to prevent spam mail in the sender side rather than the receiver side. This technique is based on a counter set on the sender server. When a mail is transmitted to the server, the mail server checks the number of the recipients based on its counter policy. The counter policy performed by the mail server is based on some pre-defined criteria. When the number of recipients exceeds the counter policy, the mail server discontinues the rest of the process, and sends a failure mail to sender of the mail; otherwise the mail is transmitted through the network. By using this technique, the usage of network resources such as bandwidth, and memory is preserved. The simulation results in real network show that when the counter is set on the sender side, the time required for spam mail detection is 100 times faster than the time the counter is set on the receiver side, and the network resources are preserved largely compared with other anti-spam mail techniques in the receiver side.

Keywords: Anti-spam, Mail server, Sender side, Spam mail

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Authors: Jorge A. Schiavon

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This article analyzes the international relations of sub-State governments (IRSSG) in Mexico. It aims to answer five questions: 1) What explains the recent and dramatic increase in their international activities? 2) What is the impact of federalism on the foreign affairs of the federal units? 3) What are the levels or degrees of IRSSG and how have they changed over the last years? 4) How do Mexican federal units institutionalize their international activities? 5) What are the perceptions and capacities of the federal units in their internationalization process? The first section argues that the growth in the IRSSG is generated by growing interdependence and globalization in the international system, and democratization, decentralization and structural reform in the national arena. The second section sustains that the renewed Mexican federalism has generated the incentives for SSG to participate more intensively in international affairs. The third section defends that there is a wide variation in their degree of international participation, which is measured in three moments in time (2004 2009 and 2014), and explains how this activity has changed in the last decade. The fourth section studies the institutionalization of the IRSSG in Mexico through the analysis of Inter-Institutional Agreements (IIA). Finally, the last section concentrates in explaining the perceptions and capacities of Mexican sub-State governments to conduct international relations.

Keywords: Federalism, foreign policy, international relations of sub-state governments, paradiplomacy, Mexico.

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Authors: James Moir

Abstract:

Citizens are increasingly are provided with choice and customization in public services and this has now also become a key feature of higher education in terms of policy roll-outs on personal development planning (PDP) and more generally as part of the employability agenda. The goal here is to transform people, in this case graduates, into active, responsible citizen-workers. A key part of this rhetoric and logic is the inculcation of graduate attributes within students. However, there has also been a concern with the issue of student lack of engagement and perseverance with their studies. This paper sets out to explore some of these conceptions that link graduate attributes with citizenship as well as the notion of how identity is forged through the higher education process. Examples are drawn from a quality enhancement project that is being operated within the context of the Scottish higher education system. This is further framed within the wider context of competing and conflicting demands on higher education, exacerbated by the current worldwide economic climate. There are now pressures on students to develop their employability skills as well as their capacity to engage with global issues such as behavioural change in the light of environmental concerns. It is argued that these pressures, in effect, lead to a form of personalization that is concerned with how graduates develop their sense of identity as something that is engineered and re-engineered to meet these demands.

Keywords: students, higher education, employability, knowledge, personal development

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Authors: Deniz T. Sodiri, Venkat V S S Sastry

Abstract:

The paper presents an on-line recognition machine (RM) for continuous/isolated, dynamic and static gestures that arise in Flight Deck Officer (FDO) training. RM is based on generic pattern recognition framework. Gestures are represented as templates using summary statistics. The proposed recognition algorithm exploits temporal and spatial characteristics of gestures via dynamic programming and Markovian process. The algorithm predicts corresponding index of incremental input data in the templates in an on-line mode. Accumulated consistency in the sequence of prediction provides a similarity measurement (Score) between input data and the templates. The algorithm provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. In the present paper, we consider isolated gestures. The performance of RM is evaluated using four datasets - artificial (W TTest), hand motion (Yang) and FDO (tracker, vision-based ). RM achieves comparable results which are in agreement with other on-line and off-line algorithms such as hidden Markov model (HMM) and dynamic time warping (DTW). The proposed algorithm has the additional advantage of providing timely feedback for training purposes.

Keywords: On-line Recognition Algorithm, IsolatedDynamic/Static Gesture Recognition, On-line Markovian/DynamicProgramming, Training in Virtual Environments.

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Authors: T. Häfele, J. Kaspar, M. Vielhaber, W. Calles, J. Griebsch

Abstract:

The demand for an increasing diversification of the product spectrum associated with the current huge customization desire and subsequently the decreasing unit quantities of each production lot is gaining more and more importance within a great variety of industrial branches, e.g. automotive industry. Nevertheless, traditional product development and production processes (molding, extrusion) are already reaching their limits or fail to address these trends of a flexible and digitized production in view of a product variability up to lot size one. Thus, upcoming innovative production concepts like the additive manufacturing technology basically create new opportunities with regard to extensive potentials in product development (constructive optimization) and manufacturing (economic individualization), but mostly suffer from insufficient strength regarding structural components. Therefore, this contribution presents an innovative technological and procedural conception of a hybrid additive manufacturing process (fiber-reinforced sandwich structures based on selective laser sintering technology) to overcome these current structural weaknesses, and consequently support the design of complex lightweight components.

Keywords: Additive manufacturing, fiber-reinforced plastics, hybrid design, lightweight design.

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Authors: Ali Akbar

Abstract:

The importance of advancing women’s rights is closely intertwined with the development of civil society and the institutionalization of democracy in Middle Eastern countries. There is indeed an intimate relationship between the process of democratization and promoting gender equality, since democracy necessitates equality between men and women. In order to advance the issue of gender equality, what is required is a solid theoretical framework which has its roots in the reexamination of pre-modern interpretation of certain Qurʾānic passages that seem to have given men more rights than it gives women. This paper suggests that those Muslim scholars who adopt a contextualist approach to the Qurʾānic text and its interpretation provide a solid theoretical background for improving women’s rights. Indeed, the aim of the paper is to discuss how the contextualist approach to the Qurʾānic text and its interpretation given by a number of prominent scholars is capable of promoting the issue of gender equality. The paper concludes that since (1) much of the gender inequality found in the primary sources of Islam as well as pre-modern Muslim writings is rooted in the natural cultural norms and standards of early Islamic societies and (2) since the context of today’s world is so different from that of the pre-modern era, the proposed models provide a solid theoretical framework for promoting women’s rights and gender equality.

Keywords: Contextualism, Gender equality, Islam, Women’s rights.

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Authors: K. Amudha, C. Nelson Kennedy Babu, S. Balu

Abstract:

The security of the medical images and its related data is the major research area which is to be concentrated in today’s era. Security in the medical image indicates that the physician may hide patients’ related data in the medical image and transfer it safely to a defined location using reversible watermarking. Many reversible watermarking methods had proposed over the decade. This paper enhances the security level in brain tumor images to hide the patient’s detail, which has to be conferred with other physician’s suggestions. The details or the information will be hidden in Non-ROI area of the image by using the block cipher algorithm. The block cipher uses different keys to extract the details that are difficult for the intruder to detect all the keys and to spot the details, which are the key advantage of this method. The ROI is the tumor area and Non-ROI is the area rest of ROI. The Non-ROI should not be spoiled in any cause and the details in the Non-ROI should be extracted correctly. The reversible watermarking method proposed in this paper performs well when compared to existing methods in the process of extraction of an original image and providing information security.

Keywords: Brain tumor images, Block Cipher, Reversible watermarking, ROI.

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Authors: Sandipan Chakroborty, Anindya Roy, Goutam Saha

Abstract:

A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.

Keywords: Complementary Information, Filter Bank, GMM, IMFCC, MFCC, Speaker Identification, Speaker Recognition.

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