Search results for: Quaternion vector measure

Authors: K. M. Rabiul Karim

Abstract:

The purpose of this study was to examine the reliability and validity of the Masculine Subordination-to-women Stress Scale (MSS) in the rural Bangladeshi population. The scale was validated using a sample of 342 Bangladeshi married men from 5 northwest villages of the country. Exploratory factor analysis revealed a single-factorial structure of the scale: masculine subordination-to-women stress. The MSS also showed adequate reliability and concurrent validity. It appears that the MSS is a reliable and valid instrument to measure masculine subordination-to-women stress for Bangladeshi men. However, further study of the scale is imperative.

Keywords: Reliability, Validity, Masculine Subordination-to-women Stress, and Bangladeshi Rural Men.

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Authors: S.Aranganayagi, K.Thangavel

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Clustering categorical data is more complicated than the numerical clustering because of its special properties. Scalability and memory constraint is the challenging problem in clustering large data set. This paper presents an incremental algorithm to cluster the categorical data. Frequencies of attribute values contribute much in clustering similar categorical objects. In this paper we propose new similarity measures based on the frequencies of attribute values and its cardinalities. The proposed measures and the algorithm are experimented with the data sets from UCI data repository. Results prove that the proposed method generates better clusters than the existing one.

Keywords: Clustering, Categorical, Incremental, Frequency, Domain

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Authors: Kunyanuth Kularbphettong, Kunnika Tenprakhon, Pattarapan Roonrakwit

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In this paper, we present a recommendation library application on Android system. The objective of this system is to support and advice user to use library resources based on mobile application. We describe the design approaches and functional components of this system. The system was developed based on under association rules, Apriori algorithm. In this project, it was divided the result by the research purposes into 2 parts: developing the Mobile application for online library service and testing and evaluating the system. Questionnaires were used to measure user satisfaction with system usability by specialists and users. The results were satisfactory both specialists and users.

Keywords: Online library, Apriori algorithm, android application, black box.

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Authors: M. Winkens, P. Nyhuis

Abstract:

Components with sensory properties such as gentelligent components developed at the Collaborative Research Centre 653 offer a new angle in terms of the full utilization of the remaining service life as well as preventive maintenance. The developed methodology of component status driven maintenance analyzes the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance required in this case. The procedure is derived from the case-based reasoning method and will be explained in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.

Keywords: Gentelligent Components, Preventive Maintenance, Case based Reasoning.

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: Building energy prediction, data mining, demand response, electricity market.

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Authors: Yung-Yuan Chen, Kuen-Long Leu

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FlexRay, as a communication protocol for automotive control systems, is developed to fulfill the increasing demand on the electronic control units for implementing systems with higher safety and more comfort. In this work, we study the impact of radiation-induced soft errors on FlexRay-based steer-by-wire system. We injected the soft errors into general purpose register set of FlexRay nodes to identify the most critical registers, the failure modes of the steer-by-wire system, and measure the probability distribution of failure modes when an error occurs in the register file.

Keywords: Soft errors, FlexRay, fault injection, steer-by-wirer

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Authors: Apirak Sombat, Teerapol Saleewong, Poom Kumam, Parin Chaipunya, Wiyada Kumam, Anantachai Padcharoen, Yeol Je Cho, Thana Sutthibutpong

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This research is aimed to study a two-step iteration process defined over a finite family of σ-asymptotically quasi-nonexpansive nonself-mappings. The strong convergence is guaranteed under the framework of Banach spaces with some additional structural properties including strict and uniform convexity, reflexivity, and smoothness assumptions. With similar projection technique for nonself-mapping in Hilbert spaces, we hereby use the generalized projection to construct a point within the corresponding domain. Moreover, we have to introduce the use of duality mapping and its inverse to overcome the unavailability of duality representation that is exploit by Hilbert space theorists. We then apply our results for σ-asymptotically quasi-nonexpansive nonself-mappings to solve for ideal efficiency of vector optimization problems composed of finitely many objective functions. We also showed that the obtained solution from our process is the closest to the origin. Moreover, we also give an illustrative numerical example to support our results.

Keywords: σ-asymptotically quasi-nonexpansive nonselfmapping, strong convergence, fixed point, uniformly convex and uniformly smooth Banach space.

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Authors: Hui-Chuan Chu, Min-Ju Liao, Wei-Kai Cheng, William Wei-Jen Tsai, Yuh-Min Chen

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Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.

Keywords: Emotion classification, Physiological and facial Expression measures, Students with autism, Mathematics e-learning.

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Authors: Mughal Yar M, Israr Ul Haq, Bushra Noman

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The stem cells have ability to differentiated themselves through mitotic cell division and various range of specialized cell types. Cellular differentiation is a way by which few specialized cell develops into more specialized.This paper studies the fundamental problem of computational schema for an artificial neural network based on chemical, physical and biological variables of state. By doing this type of study system could be model for a viable propagation of various economically important stem cells differentiation. This paper proposes various differentiation outcomes of artificial neural network into variety of potential specialized cells on implementing MATLAB version 2009. A feed-forward back propagation kind of network was created to input vector (five input elements) with single hidden layer and one output unit in output layer. The efficiency of neural network was done by the assessment of results achieved from this study with that of experimental data input and chosen target data. The propose solution for the efficiency of artificial neural network assessed by the comparatative analysis of “Mean Square Error" at zero epochs. There are different variables of data in order to test the targeted results.

Keywords: Computational shcmin, meiosis, mitosis, neuralnetwork, Stem cell SOM;

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Authors: Aliouane Toufik, Hamdi Amine, Bouzid Djamel

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Aspheric optical components are an alternative to the use of conventional lenses in the implementation of imaging systems for the visible range. Spherical lenses are capable of producing aberrations. Therefore, they are not able to focus all the light into a single point. Instead, aspherical lenses correct aberrations and provide better resolution even with compact lenses incorporating a small number of lenses.

Metrology of these components is very difficult especially when the resolution requirements increase and insufficient or complexity of conventional tools requires the development of specific approaches to characterization.

This work is part of the problem existed because the objectives are the study and comparison of different methods used to measure surface rays hybrid aspherical lenses.

Keywords: Aspherical surface, Manufacture of lenses, precision molding, radius of curvature, roughness.

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Authors: Farzaneh Ahmadzadeh

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Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

Keywords: Artificial neural network, change point estimation, monte carlo simulation, multivariate exponentially weighted movingaverage

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Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

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Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The MP is based on making the product of the speech wavelet transform coefficients (WTC). We have estimated our method on the Keele database. The results show the effectiveness of our method. It indicates that the two features can find word boundaries, and extracted the segments of the clean speech.

Keywords: Speech segmentation, Multi-scale product, Spectral centroid, Zero crossings rate.

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Authors: M. Cortés, E. Vera, O. Rojas

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The research studies of the kinetics of the corrosion process that attacks concrete and occurs within sewerage systems agree on the amount of variables that interfere in the process. This study aims to check the impact of the pH levels of the corrosive environment and the concrete surface, the concentrations of chemical sulfuric acid, and in turn, measure the resistance of concrete to this attack under controlled laboratory conditions; it also aims to contribute to the development of further research related to the topic, in order to compare the impact of biogenic sulfuric acid and chemical sulfuric acid involvement on concrete structures, especially in scenarios such as sewerage systems.

Keywords: Acid Sulfuric, concrete, corrosion.

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Authors: Mario Kubek, Herwig Unger

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Centroid terms are single words that semantically and topically characterise text documents and so may serve as their very compact representation in automatic text processing. In the present paper, centroids are used to measure the relevance of text documents with respect to a given search query. Thus, a new graphbased paradigm for searching texts in large corpora is proposed and evaluated against keyword-based methods. The first, promising experimental results demonstrate the usefulness of the centroid-based search procedure. It is shown that especially the routing of search queries in interactive and decentralised search systems can be greatly improved by applying this approach. A detailed discussion on further fields of its application completes this contribution.

Keywords: Search algorithm, centroid, query, keyword, cooccurrence, categorisation.

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Authors: Gulshan Sharma

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This article presents the design of optimal automatic generation control (AGC) based on full state feedback control for a multi-area interconnected power system. An extra high voltage AC transmission line in parallel with a high voltage DC link is considered as an area interconnection between the areas. The optimal AGC are designed and implemented in the wake of 1% load perturbation in one of the areas and the system dynamic response plots for various system states are obtained to investigate the system dynamic performance. The pattern of closed-loop eigenvalues are also determined to analyze the system stability. From the investigations carried out in the work, it is revealed that the dynamic performance of the system under consideration has an appreciable improvement when a high voltage DC line is paralleled with an extra high voltage AC line as an interconnection between the areas. The investigation of closed-loop eigenvalues reveals that the system stability is ensured in all case studies carried out with the designed optimal AGC.

Keywords: Automatic generation control, area control error, DC link, optimal AGC regulator, closed-loop eigenvalues.

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Authors: Carlos Sanchís-Pedregosa, María del Mar González-Zamora, José A. D. Machuca

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Logistics outsourcing is a growing trend and measuring its performance, a challenge. It must be consistent with the objectives set for logistics outsourcing, but we have found no objective-based performance measurement system. We have conducted a comprehensive review of the specialist literature to cover this gap, which has led us to identify and define these objectives. The outcome is that we have obtained a list of the most relevant objectives and their descriptions. This will enable us to analyse in a future study whether the indicators used for measuring logistics outsourcing performance are consistent with the objectives pursued with the outsourcing. If this is not the case, a proposal will be made for a set of financial and operational indicators to measure performance in logistics outsourcing that take the goals being pursued into account.

Keywords: Outsourcing, Performance measurement, Logistics, Objectives, Indicators

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Authors: Ravi Shah, V. L. Manekar, R. A. Christian, N. J. Mistry

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There are two types of drought as conceptual drought and operational drought. The three parameters as the beginning, the end and the degree of severity of the drought can be identifying in operational drought by average precipitation in the whole region. One of the methods classified to measure drought is Reconnaissance Drought Index (RDI). Evapotranspiration is calculated using Penman-Monteith method by analyzing thirty nine years prolong climatic data. The evapotranspiration is then utilized in RDI to classify normalized and standardized RDI. These RDI classifications led to what kind of drought faced in Bhavnagar region on 12 month time scale basis. The comparison between actual drought conditions and RDI method used to find out drought are also illustrated. It can be concluded that the index results of drought in a particular year are same in both methods but having different index values where as severity remain same.

Keywords: Drought, Drought index, Reconnaissance Drought Index (RDI), Precipitation.

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Authors: R. C. Joshi, Shashikala Tapaswi

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The paper proposes an approach using genetic algorithm for computing the region based image similarity. The image is denoted using a set of segmented regions reflecting color and texture properties of an image. An image is associated with a family of image features corresponding to the regions. The resemblance of two images is then defined as the overall similarity between two families of image features, and quantified by a similarity measure, which integrates properties of all the regions in the images. A genetic algorithm is applied to decide the most plausible matching. The performance of the proposed method is illustrated using examples from an image database of general-purpose images, and is shown to produce good results.

Keywords: Image Features, color descriptor, segmented classes, texture descriptors, genetic algorithm.

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Authors: Abdelhamid Louliej, Younes Jabrane

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Satellites are becoming indispensable assets to fifth-generation (5G) new radio architecture, complementing wireless and terrestrial communication links. The combination of satellites and 5G architecture allows consumers to access all next-generation services anytime, anywhere, including scenarios, like traveling to remote areas (without coverage). Nevertheless, this solution faces several challenges, such as a significant propagation delay, Doppler frequency shift, and high Peak-to-Average Power Ratio (PAPR), causing signal distortion due to the non-linear saturation of the High-Power Amplifier (HPA). To compensate for HPA non-linearity in 5G satellite transmission, an efficient pre-distorter scheme using Neural Networks (NN) is proposed. To assess the proposed NN pre-distorter, two types of HPA were investigated: Travelling Wave Tube Amplifier (TWTA) and Solid-State Power Amplifier (SSPA). The results show that the NN pre-distorter design presents an Error Vector Magnitude (EVM) improvement by 95.26%. Normalized Mean Square Error (NMSE) and Adjacent Channel Power Ratio (ACPR) were reduced by -43,66 dB and 24.56 dBm, respectively. Moreover, the system suffers no degradation of the Bit Error Rate (BER) for TWTA and SSPA amplifiers.

Keywords: Satellites, 5G, Neural Networks, High-Power Amplifier, Travelling Wave Tube Amplifier, Solid-State Power Amplifier, EVM, NMSE, ACPR.

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Authors: Thossaporn Thossansin, Auttapon Pomsathit

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This paper presents a comparison between using a desktop web application and a mobile application for students enrolling in courses at Rangsit University, Thailand. In addition, Rangsit University has enhanced the enrollment process by leveraging its information systems, which allows students to choose to enroll in courses online. In order to use the system, students must provide their identification and personal documents for registration. The reason to have a mobile application is to support students’ ability to access the system at anytime, anywhere and anyplace. The objective of this paper was to: 1. Evaluate the success of developing a user friendly mobile device system and 2. Measure user interest in future mobile development.

Keywords: Mobile Application, Web Application and Enrollment System.

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Authors: Zbigniew Les, Magdalena Les

Abstract:

Intelligence tests are series of tasks designed to measure the capacity to make abstractions, to learn, and to deal with novel situations. Testing of the visual abilities of the shape understanding system (SUS) is performed based on the visual intelligence tests. In this paper the progressive matrices tests are formulated as tasks given to SUS. These tests require good visual problem solving abilities of the human subject. SUS solves these tests by performing complex visual reasoning transforming the visual forms (tests) into the string forms. The experiment proved that the proposed method, which is part of the SUS visual understanding abilities, can solve a test that is very difficult for human subject.

Keywords: Shape understanding, intelligence test, visual concept, visual reasoning.

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Authors: Sanghyeok Oh, Yunli Lee, Kwangjin Hong, Kirak Kim, Keechul Jung

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This paper proposes view-point insensitive human pose recognition system using neural network. Recognition system consists of silhouette image capturing module, data driven database, and neural network. The advantages of our system are first, it is possible to capture multiple view-point silhouette images of 3D human model automatically. This automatic capture module is helpful to reduce time consuming task of database construction. Second, we develop huge feature database to offer view-point insensitivity at pose recognition. Third, we use neural network to recognize human pose from multiple-view because every pose from each model have similar feature patterns, even though each model has different appearance and view-point. To construct database, we need to create 3D human model using 3D manipulate tools. Contour shape is used to convert silhouette image to feature vector of 12 degree. This extraction task is processed semi-automatically, which benefits in that capturing images and converting to silhouette images from the real capturing environment is needless. We demonstrate the effectiveness of our approach with experiments on virtual environment.

Keywords: Computer vision, neural network, pose recognition, view-point insensitive.

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Authors: Pushp Lata Rajpoot, Pushpa Vaishnav

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Anxiety is a common psychological problem and also implicated as a contributor to many chronic diseases which decreased quality of life even with pharmacological treatment. At the present time several yogic practices- meditation, pranayama, and mantra, etcetera are playing important role in treating physiological and psychological problems. Hence, the present investigation is aimed to see the effect of Trataka on the level of anxiety among adolescents. For the present study, a sample of 30 adolescents belonging to the age range 20-30 years was selected from Devsanskriti Vishwa Vidyalaya Haridwar through random sampling. In this investigation, Sinha’s Comprehensive anxiety test has been used to measure the level of anxiety. Statistical analysis has been done by using t-test. Findings of this study reveal that Trataka significantly decreases the level of anxiety among adolescents.

Keywords: Adolescents, Anxiety, Trataka.

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Authors: Jeong-Tae Kim, Tchanghee Hyun

Abstract:

The number of intrusions and attacks against critical infrastructures and other information networks is increasing rapidly. While there is no identified evidence that terrorist organizations are currently planning a coordinated attack against the vulnerabilities of computer systems and network connected to critical infrastructure, and origins of the indiscriminate cyber attacks that infect computers on network remain largely unknown. The growing trend toward the use of more automated and menacing attack tools has also overwhelmed some of the current methodologies used for tracking cyber attacks. There is an ample possibility that this kind of cyber attacks can be transform to cyberterrorism caused by illegal purposes. Cyberterrorism is a matter of vital importance to national welfare. Therefore, each countries and organizations have to take a proper measure to meet the situation and consider effective legislation about cyberterrorism.

Keywords: Cyberterrorism, cyber attack, information security, legislation

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Authors: Huan Chen, Bo-Chao Cheng, Chih-Chuan Cheng, Yi-Geng Chen, Yu Ling Chou

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Wireless Sensor Network (WSN) comprises of sensor nodes which are designed to sense the environment, transmit sensed data back to the base station via multi-hop routing to reconstruct physical phenomena. Since physical phenomena exists significant overlaps between temporal redundancy and spatial redundancy, it is necessary to use Redundancy Suppression Algorithms (RSA) for sensor node to lower energy consumption by reducing the transmission of redundancy. A conventional algorithm of RSAs is threshold-based RSA, which sets threshold to suppress redundant data. Although many temporal and spatial RSAs are proposed, temporal-spatial RSA are seldom to be proposed because it is difficult to determine when to utilize temporal or spatial RSAs. In this paper, we proposed a novel temporal-spatial redundancy suppression algorithm, Codebookbase Redundancy Suppression Mechanism (CRSM). CRSM adopts vector quantization to generate a codebook, which is easily used to implement temporal-spatial RSA. CRSM not only achieves power saving and reliability for WSN, but also provides the predictability of network lifetime. Simulation result shows that the network lifetime of CRSM outperforms at least 23% of that of other RSAs.

Keywords: Redundancy Suppression Algorithm (RSA), Threshold-based RSA, Temporal RSA, Spatial RSA and Codebookbase Redundancy Suppression Mechanism (CRSM)

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Authors: Ferawati, H. Purwanto, Y. F. Kurnia, E. Purwati

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The aim of this study was to evaluate the microbiological quality and safety of meatball obtained from five different manufacturers around Payakumbuh City, West Sumatra, Indonesia. Microbiological analysis of meatball sample resulted in aerobic plate count range from 7 log CFU/gr to 8.623 log CFU/gr, respectively. Total coliform ranges from 1.041 log Most Probable Number (MPN)/gr to 3.380 log MPN/gr, respectively. Chemical analysis of meatball sample consisted of borax and formalin content. The result of qualitative detection of borax and formalin content on all meatball samples were not detected. Thus, it remains essential to include the significance of effective hygiene practices as an important safety measure in consumer education programmes.

Keywords: Borax, formalin, meatball, microbiological quality.

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine (SVM), Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: Student performance, supervised machine learning, prediction, classification, cross-validation.

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Authors: Young-Su Ryu, Kyung-Won Park, Jae-Hoon Song, Ki-Won Kwon

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In this paper, an embedded frequency modulation (FM) transmission control software (SW) for a low power battery system is designed and implemented. The simultaneous translation systems for various languages are needed as so many international conferences and festivals are held in world wide. Especially in portable transmitting and receiving systems, the ability of long operation life is used for a measure of value. This paper proposes an embedded FM transmission control SW for low power battery system and shows the results of the SW implemented on a portable FM transmission system.

Keywords: FM transmission, simultaneous translation system, portable transmitting and receiving systems, low power embedded control SW.

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Authors: Assem M. F. Sallam, Ah. El-S. Makled

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This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Keywords: Launch vehicle modeling, launch vehicle trajectory, mathematical modeling, MATLAB-Simulink.

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Authors: Rattanathip Rattanachai, Kunyanuth Kularbphettong

Abstract:

This paper describes the development of a Vegetation Searching System based on Web Application in case of Suan Sunandha Rajabhat University. The model was developed by PHP, JavaScript and MySQL database system and it was designed to support searching for endemic and rare species of trees on Web site. We describe the design methods and functional components of this prototype. To evaluate the system performance, questionnaires for the system usability and Black Box Testing were used to measure expert and user satisfaction. The results were satisfactory as followed: Means for experts and users were 4.30 and 4.50, and standard deviation for experts and users were 0.61and 0.73 respectively. Further analysis showed that the quality of the plant searching Website was also at a good level as well.

Keywords: Endemic species, Vegetation, Web based System, and Black Box Testing.

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