Search results for: scientific database

Authors: R. Mokhtari Malekabadi, S. Ghaed Rahmati, S. Aram

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Optimal cultural site selection is one of the ways that can lead to the promotion of citizenship culture in addition to ensuring the health and leisure of city residents. This study examines the social and cultural needs of the community and optimal cultural site allocation and after identifying the problems and shortcomings, provides a suitable model for finding the best location for these centers where there is the greatest impact on the promotion of citizenship culture. On the other hand, non-scientific methods cause irreversible impacts to the urban environment and citizens. But modern efficient methods can reduce these impacts. One of these methods is using geographical information systems (GIS). In this study, Analytical Hierarchy Process (AHP) method was used to locate the optimal cultural site. In AHP, three principles (decomposition), (comparative analysis), and (combining preferences) are used. The objectives of this research include providing optimal contexts for passing time and performing cultural activities by Shiraz residents and also proposing construction of some cultural sites in different areas of the city. The results of this study show the correct positioning of cultural sites based on social needs of citizens. Thus, considering the population parameters and radii access, GIS and AHP model for locating cultural centers can meet social needs of citizens.

Keywords: Analytical Hierarchy Process (AHP), geographical information systems (GIS), Cultural site, locating, Shiraz.

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Authors: Al-Khalid Othman, Wan A. Wan Zainal Abidin, Kee M. Lee, Hushairi Zen, Tengku. M. A. Zulcaffle, Kuryati Kipli

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This paper provides an in-depth study of Wireless Sensor Network (WSN) application to monitor and control the swiftlet habitat. A set of system design is designed and developed that includes the hardware design of the nodes, Graphical User Interface (GUI) software, sensor network, and interconnectivity for remote data access and management. System architecture is proposed to address the requirements for habitat monitoring. Such applicationdriven design provides and identify important areas of further work in data sampling, communications and networking. For this monitoring system, a sensor node (MTS400), IRIS and Micaz radio transceivers, and a USB interfaced gateway base station of Crossbow (Xbow) Technology WSN are employed. The GUI of this monitoring system is written using a Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) along with Xbow Technology drivers provided by National Instrument. As a result, this monitoring system is capable of collecting data and presents it in both tables and waveform charts for further analysis. This system is also able to send notification message by email provided Internet connectivity is available whenever changes on habitat at remote sites (swiftlet farms) occur. Other functions that have been implemented in this system are the database system for record and management purposes; remote access through the internet using LogMeIn software. Finally, this research draws a conclusion that a WSN for monitoring swiftlet habitat can be effectively used to monitor and manage swiftlet farming industry in Sarawak.

Keywords: Swiftlet, WSN, Habitat Monitoring, Networking.

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Authors: W. Devapriya, C. Nelson Kennedy Babu, T. Srihari

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Automatic License plate recognition (ALPR) is a technology which recognizes the registration plate or number plate or License plate of a vehicle. In this paper, an Indian vehicle number plate is mined and the characters are predicted in efficient manner. ALPR involves four major technique i) Pre-processing ii) License Plate Location Identification iii) Individual Character Segmentation iv) Character Recognition. The opening phase, named pre-processing helps to remove noises and enhances the quality of the image using the conception of Morphological Operation and Image subtraction. The second phase, the most puzzling stage ascertain the location of license plate using the protocol Canny Edge detection, dilation and erosion. In the third phase, each characters characterized by Connected Component Approach (CCA) and in the ending phase, each segmented characters are conceptualized using cross correlation template matching- a scheme specifically appropriate for fixed format. Major application of ALPR is Tolling collection, Border Control, Parking, Stolen cars, Enforcement, Access Control, Traffic control. The database consists of 500 car images taken under dissimilar lighting condition is used. The efficiency of the system is 97%. Our future focus is Indian Vehicle License Plate Validation (Whether License plate of a vehicle is as per Road transport and highway standard).

Keywords: Automatic License plate recognition, Character recognition, Number plate Recognition, Template matching, morphological operation, canny edge detection.

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Authors: Dinesh Acharya U., N. V. Subba Reddy, Krishnamoorthi Makkithaya

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The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

Keywords: Fuzzy k Nearest Neighbor, Multiple Classifiers, Numeral Recognition, Structural features.

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Authors: Leandro Marcos Alves Vaz

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In this article, we analyze the different approaches to the topic Magnetism of Matter in physics textbooks of Brazilian schools. For this, we compared the approach to the concepts of the magnetic characteristics of materials (diamagnetism, paramagnetism, ferromagnetism and antiferromagnetism) in different sources of information and in different levels of education, from Higher Education to High School. In this sense, we used as reference the theory of the Didactic Transposition of Yves Chevallard, a French educational theorist, who conceived in his theory three types of knowledge – Scholarly Knowledge, Knowledge to be taught and Taught Knowledge – related to teaching practice. As a research methodology, from the reading of the works used in teacher training and those destined to basic education students, we compared the treatment of a higher education physics book, a scientific article published in a Brazilian journal of the educational area, and four high school textbooks, in order to establish in which there is a greater or lesser degree of approximation with the knowledge produced by the scholars – scholarly knowledge – or even with the knowledge to be taught (to that found in books intended for teaching). Thus, we evaluated the level of proximity of the subjects conveyed in high school and higher education, as well as the relevance that some textbook authors give to the theme.

Keywords: Magnetism of matter, teaching of physics, didactic transposition, Brazilian physics books.

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: Classification, fuzzy, inspection system, image analysis.

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Authors: Anju Luthra, Rajender Lal, Dhananjoy Shaw

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Participation in games and sports in the contemporary times has become more competing with the developed scientific knowledge, skills and methods, along with the equipment and applied research in the field. In spite of India being a large country having vast resources and potential, its performance in the world of sports on the whole needs sincere attention for better achievements. Beside numerous factors responsible for the dismal performance of a sportsperson, the physique and body composition, including the size, shape and form are known to play a significant role. The present investigation was undertaken to study the specific morphological characteristics of Indian female Track and Field athletes. A total of 300 athletes were randomly selected as sample for the purpose of the study from the six events having 50 athletes in each event including 100m., 400m., Shot Put, Discus Throw, Long Jump and High Jump. The study included body weight, body fat percentage, lean body weight, endomorphy, mesomorphy and ectomorphy as variables. The data were computed statistically by using Mean, Standard Deviation and Analysis of Variance. The post-hoc analysis was conducted where the F-ratio was found to be significant at .05 level. The study concluded that there is a significant difference with regard to the selected variables among the Indian female athletes of different track and field events.

Keywords: Indian female athletes, body composition, morphology, somatotypes, track and field.

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Authors: Wernhuar Tarng, Yuan-Yuan Chen, Chien-Lung Li, Kun-Rong Hsie, Mingteh Chen

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An emotional speech recognition system for the applications on smart phones was proposed in this study to combine with 3G mobile communications and social networks to provide users and their groups with more interaction and care. This study developed a mechanism using the support vector machines (SVM) to recognize the emotions of speech such as happiness, anger, sadness and normal. The mechanism uses a hierarchical classifier to adjust the weights of acoustic features and divides various parameters into the categories of energy and frequency for training. In this study, 28 commonly used acoustic features including pitch and volume were proposed for training. In addition, a time-frequency parameter obtained by continuous wavelet transforms was also used to identify the accent and intonation in a sentence during the recognition process. The Berlin Database of Emotional Speech was used by dividing the speech into male and female data sets for training. According to the experimental results, the accuracies of male and female test sets were increased by 4.6% and 5.2% respectively after using the time-frequency parameter for classifying happy and angry emotions. For the classification of all emotions, the average accuracy, including male and female data, was 63.5% for the test set and 90.9% for the whole data set.

Keywords: Smart phones, emotional speech recognition, socialnetworks, support vector machines, time-frequency parameter, Mel-scale frequency cepstral coefficients (MFCC).

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Authors: Ching-I Chen

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The continued rise of e-commerce is the main driver of the rapid growth of global online purchase. Consumers can nearly buy everything they want at one occasion through online shopping. The purchase behavior models which focus on single product category are insufficient to describe online shopping behavior. Therefore, analysis of multi-category purchase gets more and more popular. For example, market basket analysis explores customers’ buying tendency of the association between product categories. The information derived from market basket analysis facilitates to make cross-selling strategies and product recommendation system.

To detect the association between different product categories, we use the market basket analysis with the multidimensional scaling technique to build an associated map which describes how likely multiple product categories are bought at the same time. Besides, we also build an inter-purchase time model for associated products to describe how likely a product will be bought after its associated product is bought. We classify inter-purchase time behaviors of multi-category products into nine types, and use a mixture regression model to integrate those behaviors under our assumptions of purchase sequences. Our sample data is from comScore which provides a panelist-label database that captures detailed browsing and buying behavior of internet users across the United States. Finding the inter-purchase time from books to movie is shorter than the inter-purchase time from movies to books. According to the model analysis and empirical results, this research finally proposes the applications and recommendations in the management.

Keywords: Multiple-category purchase behavior, inter-purchase time, market basket analysis.

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Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

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This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: Image registration techniques, medical images, neural networks, optimisation, transformation.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: N. Mansouri, A. Asadi

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Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: Data grid, data replication, simulation, replica selection, replica placement.

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Authors: A. Sharma, R. Tewari, S. K. Soni

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Biofuels production has come forth as a future technology to combat the problem of depleting fossil fuels. Bio-based ethanol production from enzymatic lignocellulosic biomass degradation serves an efficient method and catching the eye of scientific community. High cost of the enzyme is the major obstacle in preventing the commercialization of this process. Thus main objective of the present study was to optimize composition of medium components for enhancing cellulase production by newly isolated strain of Bacillus tequilensis. Nineteen factors were taken into account using statistical Plackett-Burman Design. The significant variables influencing the cellulose production were further employed in statistical Response Surface Methodology using Central Composite Design for maximizing cellulase production. The optimum medium composition for cellulase production was: peptone (4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L), Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride (0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at 37oC. Analysis of variance (ANOVA) revealed high coefficient of determination (R2) of 0.99. Maximum cellulase productivity of 11.5 IU/ml was observed against the model predicted value of 13 IU/ml. This was found to be optimally active at 60oC and pH 5.5.

Keywords: Bacillus tequilensis, CMCase, Submerged Fermentation, Optimization, Plackett-Burman Design, Response Surface Methodology.

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Authors: Jiakai Li, Gursel Serpen, Steven Selman, Matt Franchetti, Mike Riesen, Cynthia Schneider

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This paper presents the development of a Bayesian belief network classifier for prediction of graft status and survival period in renal transplantation using the patient profile information prior to the transplantation. The objective was to explore feasibility of developing a decision making tool for identifying the most suitable recipient among the candidate pool members. The dataset was compiled from the University of Toledo Medical Center Hospital patients as reported to the United Network Organ Sharing, and had 1228 patient records for the period covering 1987 through 2009. The Bayes net classifiers were developed using the Weka machine learning software workbench. Two separate classifiers were induced from the data set, one to predict the status of the graft as either failed or living, and a second classifier to predict the graft survival period. The classifier for graft status prediction performed very well with a prediction accuracy of 97.8% and true positive values of 0.967 and 0.988 for the living and failed classes, respectively. The second classifier to predict the graft survival period yielded a prediction accuracy of 68.2% and a true positive rate of 0.85 for the class representing those instances with kidneys failing during the first year following transplantation. Simulation results indicated that it is feasible to develop a successful Bayesian belief network classifier for prediction of graft status, but not the graft survival period, using the information in UNOS database.

Keywords: Bayesian network classifier, renal transplantation, graft survival period, United Network for Organ Sharing

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Authors: Manuela Nayantara Jeyaraj

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Having moved into the 21^st century, it is way past being arguable that innovative technology needs to be incorporated into conventional classroom teaching. Though the Western world has found presumable success in achieving this, it is still a concept under battle in developing countries such as Sri Lanka. Reaching the acme of implementing interactive virtual learning within classrooms is a struggling idealistic fascination within the island. In order to overcome this problem, this study is set to reveal facts that limit the implementation of virtual, interactive learning within the school classrooms and provide hacks that could prove the augmented use of the Virtual World to enhance teaching and learning experiences. As each classroom moves along with the usage of technology to fulfill its functionalities, a few intense hacks provided will build the administrative onuses on a virtual system. These hacks may divulge barriers based on social conventions, financial boundaries, digital literacy, intellectual capacity of the staff, and highlight the impediments in introducing students to an interactive virtual learning environment and thereby provide the necessary actions or changes to be made to succeed and march along in creating an intellectual society built on virtual learning and lifestyle. This digital learning environment will be composed of multimedia presentations, trivia and pop quizzes conducted on a GUI, assessments conducted via a virtual system, records maintained on a database, etc. The ultimate objective of this study could enhance every child's basic learning environment; hence, diminishing the digital divide that exists in certain communities.

Keywords: Digital divide, digital learning, digitization, Sri Lanka, teaching methodologies.

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Authors: SP. Chokkalingam, K. Komathy

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Advances in the field of image processing envision a new era of evaluation techniques and application of procedures in various different fields. One such field being considered is the biomedical field for prognosis as well as diagnosis of diseases. This plethora of methods though provides a wide range of options to select from, it also proves confusion in selecting the apt process and also in finding which one is more suitable. Our objective is to use a series of techniques on bone scans, so as to detect the occurrence of rheumatoid arthritis (RA) as accurately as possible. Amongst other techniques existing in the field our proposed system tends to be more effective as it depends on new methodologies that have been proved to be better and more consistent than others. Computer aided diagnosis will provide more accurate and infallible rate of consistency that will help to improve the efficiency of the system. The image first undergoes histogram smoothing and specification, morphing operation, boundary detection by edge following algorithm and finally image subtraction to determine the presence of rheumatoid arthritis in a more efficient and effective way. Using preprocessing noises are removed from images and using segmentation, region of interest is found and Histogram smoothing is applied for a specific portion of the images. Gray level co-occurrence matrix (GLCM) features like Mean, Median, Energy, Correlation, Bone Mineral Density (BMD) and etc. After finding all the features it stores in the database. This dataset is trained with inflamed and noninflamed values and with the help of neural network all the new images are checked properly for their status and Rough set is implemented for further reduction.

Keywords: Computer Aided Diagnosis, Edge Detection, Histogram Smoothing, Rheumatoid Arthritis.

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Authors: Raja Das, M. K. Pradhan

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This paper presents a comparative study between two neural network models namely General Regression Neural Network (GRNN) and Back Propagation Neural Network (BPNN) are used to estimate radial overcut produced during Electrical Discharge Machining (EDM). Four input parameters have been employed: discharge current (Ip), pulse on time (Ton), Duty fraction (Tau) and discharge voltage (V). Recently, artificial intelligence techniques, as it is emerged as an effective tool that could be used to replace time consuming procedures in various scientific or engineering applications, explicitly in prediction and estimation of the complex and nonlinear process. The both networks are trained, and the prediction results are tested with the unseen validation set of the experiment and analysed. It is found that the performance of both the networks are found to be in good agreement with average percentage error less than 11% and the correlation coefficient obtained for the validation data set for GRNN and BPNN is more than 91%. However, it is much faster to train GRNN network than a BPNN and GRNN is often more accurate than BPNN. GRNN requires more memory space to store the model, GRNN features fast learning that does not require an iterative procedure, and highly parallel structure. GRNN networks are slower than multilayer perceptron networks at classifying new cases.

Keywords: Electrical-discharge machining, General Regression Neural Network, Back-propagation Neural Network, Radial Overcut.

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Authors: Baghdasaryan Marinka, Ulikyan Azatuhi

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The efficient usage of the compensation abilities of the electrical drive synchronous motors used in production processes can essentially improve the technical and economic indices of the process.  Reducing the flows of the reactive electrical energy due to the compensation of reactive power allows to significantly reduce the load losses of power in the electrical networks. As a result of analyzing the scientific works devoted to the issues of regulating the excitation of the synchronous motors, the need for comprehensive investigation and estimation of the excitation mode has been substantiated. By means of the obtained transmission functions, in the Simulink environment of the software package MATLAB, the transition processes of the excitation mode have been studied. As a result of obtaining and estimating the graph of the Nyquist plot and the transient process, the necessity of developing the Proportional-Integral-Derivative (PID) regulator has been justified. The transient processes of the system of the PID regulator have been investigated, and the amplitude–phase characteristics of the system have been estimated. The analysis of the obtained results has shown that the regulation indices of the developed system have been improved. The developed system can be successfully applied for regulating the excitation voltage of different-power synchronous motors, operating with a changing load, ensuring a value of the power coefficient close to 1.

Keywords: Transient process, synchronous motor, excitation mode, regulator, reactive power.

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Authors: Rafal Michalski, Jakub Zygadlo

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We present the concept and scientific methods and algorithms of our computation system called ATOMIC MATTERS. This is the first presentation of the new computer package, that allows its user to describe physical properties of atomic localized electron systems subject to electromagnetic interactions. Our solution applies to situations where an unclosed electron 2p/3p/3d/4d/5d/4f/5f subshell interacts with an electrostatic potential of definable symmetry and external magnetic field. Our methods are based on Crystal Electric Field (CEF) approach, which takes into consideration the electrostatic ligands field as well as the magnetic Zeeman effect. The application allowed us to predict macroscopic properties of materials such as: Magnetic, spectral and calorimetric as a result of physical properties of their fine electronic structure. We emphasize the importance of symmetry of charge surroundings of atom/ion, spin-orbit interactions (spin-orbit coupling) and the use of complex number matrices in the definition of the Hamiltonian. Calculation methods, algorithms and convention recalculation tools collected in ATOMIC MATTERS were chosen to permit the prediction of magnetic and spectral properties of materials in isostructural series.

Keywords: Atomic matters, crystal electric field, spin-orbit coupling, localized states, electron subshell, fine electronic structure.

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: Impersonation, image registration, incrimination, object detection, threshold evaluation.

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Authors: Pallavi Bhogaram, Xiaolong Wu, Min He, Onyedikachi Okenwa

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A transportation network is a realization of a spatial network, describing a structure which permits either vehicular movement or flow of some commodity. Examples include road networks, railways, air routes, pipelines, and many more. The transportation network plays a vital role in maintaining the vigor of the nation’s economy. Hence, ensuring the network stays resilient all the time, especially in the face of challenges such as heavy traffic loads and large scale natural disasters, is of utmost importance. In this paper, we used the Neo4j application to develop the graph. Neo4j is the world's leading open-source, NoSQL, a native graph database that implements an ACID-compliant transactional backend to applications. The Southern California network model is developed using the Neo4j application and obtained the most critical and optimal nodes and paths in the network using centrality algorithms. The edge betweenness centrality algorithm calculates the critical or optimal paths using Yen's k-shortest paths algorithm, and the node betweenness centrality algorithm calculates the amount of influence a node has over the network. The preliminary study results confirm that the Neo4j application can be a suitable tool to study the important nodes and the critical paths for the major congested metropolitan area.

Keywords: Transportation network, critical path, connectivity reliability, network model, Neo4J application, optimal path, critical path, edge betweenness centrality index, node betweenness centrality index, Yen’s k-shortest paths.

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Authors: L. Bih Ni, D. Norizah Ag Kiflee, T. Choon Keong, R. Talip, S. Singh Bikar Singh, M. Noor Mad Japuni, R. Talin

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The purpose of this study is to determine the effectiveness of video clips to enhance students' achievement and motivation towards learning and facilitating of history. We use narrative literature studies to illustrate the current state of the two art and science in focused areas of inquiry. We used experimental method. The experimental method is a systematic scientific research method in which the researchers manipulate one or more variables to control and measure any changes in other variables. For this purpose, two experimental groups have been designed: one experimental and one groups consisting of 30 lower secondary students. The session is given to the first batch using a computer presentation program that uses video clips to be considered as experimental group, while the second group is assigned as the same class using traditional methods using dialogue and discussion techniques that are considered a control group. Both groups are subject to pre and post-trial in matters that are handled by the class. The findings show that the results of the pre-test analysis did not show statistically significant differences, which in turn proved the equality of the two groups. Meanwhile, post-test analysis results show that there was a statistically significant difference between the experimental group and the control group at an importance level of 0.05 for the benefit of the experimental group.

Keywords: Video clips, Historical Learning and Facilitation, Achievement, Motivation.

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Authors: Nikola Radovanovic, Petros Gkotsis, Mathieu Doussineau

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Aeronautics is regarded as a strategically important sector for European competitiveness. It was at the heart of European entrepreneurial development since the industry was born. Currently, the EU is the world leader in the production of civil aircraft, including helicopters, aircraft engines, parts, and components. It is recording a surplus in trade relating to aerospace products, which are exported all over the globe. Also, this industry shows above-average investments in research and development, as demonstrated in the patent activity in this area. The post-pandemic recovery of the industry will partly depend on the possibilities to streamline collaboration in further research and innovation activities. Aeronautics features as one of the often-selected priority domains in smart specialisation, which represents the main regional and national approach in developing and implementing innovation policies in Europe. The basis for the selection of priority domains for smart specialisation lies in the mapping of innovative potential, with research and patent activities being among the key elements of this analysis. This research is aimed at identifying characteristics of the trends in research and patent activities in the regions and countries that base their competitiveness on the aeronautics sector. It is also aimed at determining the scope and patterns of collaborations in aeronautics between innovators from the European regions, focusing on revealing new technology areas that emerge from these collaborations. For this purpose, we developed a methodology based on desk research and the analysis of the PATSTAT patent database as well as the databases of R&I framework programmes.

Keywords: aeronautics, smart specialisation, innovation policy, regional policy.

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Authors: Sara Jelodarian

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Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20^th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.

Keywords: Development, production markets, progress, strategic role, technology.

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Authors: Romeo A. Botes, Imelda Smit

Abstract:

The demands of an ever changing and complex higher education environment, along with the profile of modern learners challenge current approaches to assessment and feedback. More learners enter the education system every year. The younger generation expects immediate feedback. At the same time, feedback should be meaningful. The assessment of practical activities in programming poses a particular problem, since both lecturers and learners in the information and computer science discipline acknowledge that paper-based assessment for programming subjects lacks meaningful real-life testing. At the same time, feedback lacks promptness, consistency, comprehensiveness and individualisation. Most of these aspects may be addressed by modern, technology-assisted assessment. The focus of this paper is the continuous development of an artefact that is used to assist the lecturer in the assessment and feedback of practical programming activities in a senior database programming class. The artefact was developed using three Design Science Research cycles. The first implementation allowed one programming activity submission per assessment intervention. This pilot provided valuable insight into the obstacles regarding the implementation of this type of assessment tool. A second implementation improved the initial version to allow multiple programming activity submissions per assessment. The focus of this version is on providing scaffold feedback to the learner – allowing improvement with each subsequent submission. It also has a built-in capability to provide the lecturer with information regarding the key problem areas of each assessment intervention.

Keywords: Programming, computer-aided assessment, technology-assisted assessment, programming assessment software, design science research, mixed-method.

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

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In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: Thermal remote sensing, insolation model, land surface temperature, geothermal anomalies.

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Authors: K. Atashgar

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When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.

Keywords: Artificial neural network, Multivariate process, Statistical process control, Change point.

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Authors: Mun Yee Chan, Sin Ming Goh, Lisa Gaik Ai Ong

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Approximately 10,000 different types of dyes and pigments are being used in various industrial applications yearly, which include the textile and printing industries. However, these dyes are difficult to degrade naturally once they enter the aquatic system. Their high persistency in natural environment poses a potential health hazard to all form of life. Hence, there is a need for alternative dye removal strategy in the environment via bioremediation. In this study, fungi laccase is investigated via commercial agar dyes plates and submerged fermentation to explore the application of fungi laccase in textile dye wastewater treatment. Two locally isolated basidiomycetes were screened for laccase activity using media added with commercial dyes such as 2, 2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS), guaiacol and Remazol Brillant Blue R (RBBR). Isolate TBB3 (1.70±0.06) and EL2 (1.78±0.08) gave the highest results for ABTS plates with the appearance of greenish halo on around the isolates. Submerged fermentation performed on Isolate TBB3 with the productivity 3.9067 U/ml/day, whereas the laccase activity for Isolate EL2 was much lower (0.2097 U/ml/day). As isolate TBB3 showed higher laccase production, it was subjected to molecular characterization by DNA isolation, PCR amplification and sequencing of ITS region of nuclear ribosomal DNA. After being compared with other sequences in National Center for Biotechnology Information (NCBI database), isolate TBB3 is probably from species Trametes hirsutei. Further research work can be performed on this isolate by upscale the production of laccase in order to meet the demands of the requirement for higher enzyme titer for the bioremediation of textile dyes.

Keywords: Bioremediation, dyes, fermentation, laccase.

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Authors: A. Naamane, M. Hasnaoui

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Numerical modeling of fluid flows, whether compressible or incompressible, laminar or turbulent presents a considerable contribution in the scientific and industrial fields. However, the development of an approximate model of a supersonic flow requires the introduction of specific and more precise techniques and methods. For this purpose, the object of this paper is modeling a supersonic flow of inviscid fluid around a dihedral airfoil. Based on the thin airfoils theory and the non-dimensional stationary Steichen equation of a two-dimensional supersonic flow in isentropic evolution, we obtained a solution for the downstream velocity potential of the oblique shock at the second order of relative thickness that characterizes a perturbation parameter. This result has been dealt with by the asymptotic analysis and characteristics method. In order to validate our model, the results are discussed in comparison with theoretical and experimental results. Indeed, firstly, the comparison of the results of our model has shown that they are quantitatively acceptable compared to the existing theoretical results. Finally, an experimental study was conducted using the AF300 supersonic wind tunnel. In this experiment, we have considered the incident upstream Mach number over a symmetrical dihedral airfoil wing. The comparison of the different Mach number downstream results of our model with those of the existing theoretical data (relative margin between 0.07% and 4%) and with experimental results (concordance for a deflection angle between 1° and 11°) support the validation of our model with accuracy.

Keywords: Asymptotic modelling, dihedral airfoil, supersonic flow, supersonic wind tunnel.

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Authors: Victor Krebss

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Task of object localization is one of the major challenges in creating intelligent transportation. Unfortunately, in densely built-up urban areas, localization based on GPS only produces a large error, or simply becomes impossible. New opportunities arise for the localization due to the rapidly emerging concept of a wireless ad-hoc network. Such network, allows estimating potential distance between these objects measuring received signal level and construct a graph of distances in which nodes are the localization objects, and edges - estimates of the distances between pairs of nodes. Due to the known coordinates of individual nodes (anchors), it is possible to determine the location of all (or part) of the remaining nodes of the graph. Moreover, road map, available in digital format can provide localization routines with valuable additional information to narrow node location search. However, despite abundance of well-known algorithms for solving the problem of localization and significant research efforts, there are still many issues that currently are addressed only partially. In this paper, we propose localization approach based on the graph mapped distances on the digital road map data basis. In fact, problem is reduced to distance graph embedding into the graph representing area geo location data. It makes possible to localize objects, in some cases even if only one reference point is available. We propose simple embedding algorithm and sample implementation as spatial queries over sensor network data stored in spatial database, allowing employing effectively spatial indexing, optimized spatial search routines and geometry functions.

Keywords: Intelligent Transportation System, Sensor Network, Localization, Spatial Query, GIS, Graph Embedding.

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