Search results for: Forensic anthropology population data

Authors: Chien-Hua Wang, Chin-Tzong Pang

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In data mining, the association rules are used to search for the relations of items of the transactions database. Following the data is collected and stored, it can find rules of value through association rules, and assist manager to proceed marketing strategy and plan market framework. In this paper, we attempt fuzzy partition methods and decide membership function of quantitative values of each transaction item. Also, by managers we can reflect the importance of items as linguistic terms, which are transformed as fuzzy sets of weights. Next, fuzzy weighted frequent pattern growth (FWFP-Growth) is used to complete the process of data mining. The method above is expected to improve Apriori algorithm for its better efficiency of the whole association rules. An example is given to clearly illustrate the proposed approach.

Keywords: Association Rule, Fuzzy Partition Methods, FWFP-Growth, Apiroir algorithm

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Authors: Dewi Nasien, Habibollah Haron, Siti SophiayatiYuhaniz

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This paper presents a comparison of metaheuristic algorithms, Genetic Algorithm (GA) and Ant Colony Optimization (ACO), in producing freeman chain code (FCC). The main problem in representing characters using FCC is the length of the FCC depends on the starting points. Isolated characters, especially the upper-case characters, usually have branches that make the traversing process difficult. The study in FCC construction using one continuous route has not been widely explored. This is our motivation to use the population-based metaheuristics. The experimental result shows that the route length using GA is better than ACO, however, ACO is better in computation time than GA.

Keywords: Handwriting Recognition, Feature Extraction, Freeman Chain Code, Genetic Algorithm and Ant ColonyOptimization.

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Authors: Amjad Abdullah, Amjad Yahya, Bushra Aljohani, Amani S. Alghamdi

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Change point detection is an important part of data analysis. The presence of a change point refers to a significant change in the behavior of a time series. In this article, we examine the detection of multiple change points of parameters of the exponential Lomax distribution, which is broad and flexible compared with other distributions while fitting data. We used the Schwarz information criterion and binary segmentation to detect multiple change points in publicly available data on the average temperature in the ozone layer. The change points were successfully located.

Keywords: Binary segmentation, change point, exponential Lomax distribution, information criterion.

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Authors: Jiratta Phuboon-ob, Raweewan Auepanwiriyakul

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A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance. Therefore, in this paper, we introduce a new approach aimed to solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that 2PO outperform the original algorithms in terms of query processing cost and view maintenance cost.

Keywords: Data warehouse, materialized views, view selectionproblem, two-phase optimization.

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Authors: Thanomsin Chakreeves, Atichat Preittigun, Ajchara Phu-ang

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This paper presents a stakeholder analysis of agricultural drone policies that meet the government's goal of building an agricultural drone ecosystem in Thailand. Firstly, case studies from other countries are reviewed. The stakeholder analysis method and qualitative data from the interviews are then presented including data from the Institute of Innovation and Management, the Office of National Higher Education Science Research and Innovation Policy Council, agricultural entrepreneurs and farmers. Study and interview data are then employed to describe the current ecosystem and to guide the implementation of agricultural drone policies that are suitable for the ecosystem of Thailand. Finally, policy recommendations are then made that the Thai government should adopt in the future.

Keywords: Drone public policy, drone ecosystem, policy development, agricultural drone.

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Authors: Boudene Maamar, Xu Mai

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Optical Intersatellite Links (OISLs) are wireless communications using optical signals to interconnect satellites. It is expected to be the next generation wireless communication technology according to its inherent characteristics like: an increased bandwidth, a high data rate, a data transmission security, an immunity to interference, and an unregulated spectrum etc. Optical space links are the best choice for the classical communication schemes due to its distinctive properties; high frequency, small antenna diameter and lowest transmitted power, which are critical factors to define a space communication. This paper discusses the development of free space technology and analyses the parameters and factors to establish a reliable intersatellite links using an optical signal to exchange data between satellites.

Keywords: Optical intersatellite links, optical wireless communications, free space optical communications, next generation wireless communication.

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Authors: Gh. Jandaghi, H. Zarei Matin, A. Farjami

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In this article, while it is attempted to describe the problem and its importance, transformational leadership is studied by considering leadership theories. Issues such as the definition of transformational leadership and its aspects are compared on the basis of the ideas of various connoisseurs and then it (transformational leadership) is examined in successful and unsuccessful companies. According to the methodology, the method of research, hypotheses, population and statistical sample are investigated and research findings are analyzed by using descriptive and inferential statistical methods in the framework of analytical tables. Finally, our conclusion is provided by considering the results of statistical tests. The final result shows that transformational leadership is significantly higher in successful companies than unsuccessful ones P<0.0001).

Keywords: Idealized influence, individualized considerations, inspirational motivation, intellectual stimulation, transformational leadership

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Authors: Frank Emmert-Streib, Matthias Dehmer, Jing Liu, Max Muhlhauser

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The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, generalized trees, graph alignment, DNA microarray data, cervical cancer.

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Authors: Md Khairullah, Hai-Xiang Lin, Remus G. Hanea, Arnold W. Heemink

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In this paper we describe the design and implementation of a parallel algorithm for data assimilation with ensemble Kalman filter (EnKF) for oil reservoir history matching problem. The use of large number of observations from time-lapse seismic leads to a large turnaround time for the analysis step, in addition to the time consuming simulations of the realizations. For efficient parallelization it is important to consider parallel computation at the analysis step. Our experiments show that parallelization of the analysis step in addition to the forecast step has good scalability, exploiting the same set of resources with some additional efforts.

Keywords: EnKF, Data assimilation, Parallel computing, Parallel efficiency.

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Authors: Dominykas Broga

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Until recently it would have been unusual to consider classifying population movements and refugees as security problem. However, efforts at shaping our world to make ourselves secure have paradoxically led to ever greater insecurity. The feeling of uncertainty, pertinent throughout all discourses of security, has led to the creation of security production into seemingly benign routines of everyday life. Yet, the paper argues, neither of security discourses accounted for, disclosed and challenged the fundamental aporias embedded in Western security narratives. In turn, the paper aims to unpick the conventional security wisdom, which is haunted with strong ontologies, embedded in the politics of Orientalism, and (in)security nexus. The paper concludes that current security affair conceals the integral impossibility of fulfilling its very own promise of assured security. The paper also provides suggestions about alternative security discourse based on mutual dialogue.

Keywords: Identity, (in)security, migration, ontology

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Authors: Khaja Kamaluddin, Muhammed Yousoof

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Available Bit Rate Service (ABR) is the lower priority service and the better service for the transmission of data. On wireline ATM networks ABR source is always getting the feedback from switches about increase or decrease of bandwidth according to the changing network conditions and minimum bandwidth is guaranteed. In wireless networks guaranteeing the minimum bandwidth is really a challenging task as the source is always in mobile and traveling from one cell to another cell. Re establishment of virtual circuits from start to end every time causes the delay in transmission. In our proposed solution we proposed the mechanism to provide more available bandwidth to the ABR source by re-usage of part of old Virtual Channels and establishing the new ones. We want the ABR source to transmit the data continuously (non-stop) inorderto avoid the delay. In worst case scenario at least minimum bandwidth is to be allocated. In order to keep the data flow continuously, priority is given to the handoff ABR call against new ABR call.

Keywords: Bandwidth allocation, Virtual Channel (VC), CBR, ABR, MCR and QOS.

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Authors: Odenigbo Veronica Ngozi, Lorreta Chika Ukwuaba

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This study focuses on how the strengthening adult literacy programs can help accelerate transformative strategies to end Female Genital Mutilation (FGM) in Nigeria, specifically in Nsukka Local Government Area of Enugu State. The research delved into the definition of FGM, adult literacy programs, and how to achieve ending FGM in order to attain Sustainable Development Goals (SDGs) in 2030. It further discussed the practice of FGM in Nigeria and emphasized the statement of the problem. Main purpose of the study was to investigate how strengthening adult literacy programs can help accelerate transformative strategies to end FGM in Nigeria and achieve SDGs in 2030. A survey research design was used to conduct the study in Nsukka L.G.A. The population was composed of 26 facilitators and adult learners in five adult learning centres in the area. The entire population was used as a sample. Structured questionnaires were employed to elicit information from the respondents. The items on the questionnaire were face-validated by three experts while the reliability of the instrument was verified using Cronbach Alpha Reliability Technique. The research questions were analysed using means and standard deviation while the hypothesis was tested at 0.05 level of degree of significance using a t-test statistics. The result of the findings shows that the practices of FGM can end through strengthening adult literacy programs. Strengthening adult literacy programs is a good channel to end or stop FGM through the knowledge and skill acquired from the learning centres. The theoretical importance of the study lies in the fact that it highlights the role of adult literacy programs in accelerating transformative strategies to combat harmful cultural practices such as FGM. It further supports the importance of education and knowledge in achieving SDGs by 2030. The study addressed the question of how strengthening adult literacy programs can help accelerate transformative strategies which can end FGM in Nigeria and achieve SDGs by 2030. In conclusion, the study revealed that adult literacy is a good tool to end FGM in Nigeria. The recommendation was that (NGOs), community-based organizations (CBOs), and individuals should support the funding and establishment of adult literacy centres in communities so as to reach all illiterate parents or individuals so that they can acquire the knowledge and skill needed to understand the negative effect of FGM in the life of a girl child.

Keywords: Adult literacy, female genital mutilation, learning centres, Sustainable Development Goals.

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Authors: Anuj K. Sharma, Amit Sharma, Kulbhushan Agnihotri

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In this work, we propose and analyze a model of Phytoplankton-Zooplankton interaction with harvesting considering that some species are exploited commercially for food. Criteria for local stability, instability and global stability are derived and some threshold harvesting levels are explored to maintain the population at an appropriate equilibrium level even if the species are exploited continuously.Further,biological and bionomic equilibria of the system are obtained and an optimal harvesting policy is also analysed using the Pantryagin’s Maximum Principle.Finally analytical findings are also supported by some numerical simulations.

Keywords: Phytoplankton-Zooplankton, Global stability, Bionomic Equilibrium, Pontrying-Maximum Principal.

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Authors: Chrysoula Karathanasi, Senad Karavdic, Angela Odero, Michèle Baumann

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It is not only the economic determinants that impact on life conditions, but maintaining a good level of life satisfaction (LS) may also be an important challenge currently. In Luxembourg, university students receive financial aid from the government. They are then registered at the Centre for Documentation and Information on Higher Education (CEDIES). Luxembourg is built on migration with almost half its population consisting of foreigners. It is upon this basis that our research aims to analyze the associations with mental health factors (health satisfaction, psychological quality of life, worry), perceived financial situation, career attitudes (adaptability, optimism, knowledge, planning) and LS, for non-Luxembourgish and native postgraduate students. Between 2012 and 2013, postgraduates registered at CEDIES were contacted by post and asked to participate in an online survey with either the option of English or French. The study population comprised of 644 respondents. Our statistical analysis excluded: those born abroad who had Luxembourgish citizenship, or those born in Luxembourg who did not have citizenship. Two groups were formed one consisting 147 non-Luxembourgish and the other 284 natives. A single item measured LS (1=not at all satisfied to 10=very satisfied). Bivariate tests, correlations and multiple linear regression models were used in which only significant relationships (p<0.05) were integrated. Among the two groups no differences were found between LS indicators (7.8/10 non-Luxembourgish; 8.0/10 natives) as both were higher than the European indicator of 7.2/10 (for 25-34 years). In the case of non-Luxembourgish students, they were older than natives (29.3 years vs. 26.3 years) perceived their financial situation as more difficult, and a higher percentage of their parents had an education level higher than a Bachelor's degree (father 59.2% vs 44.6% for natives; mother 51.4% vs 33.7% for natives). In addition, the father’s education was related to the LS of postgraduates and the higher was the score, the greater was the contribution to LS. Whereas for native students, when their scores of health satisfaction and career optimism were higher, their LS’ score was higher. For both groups their LS was linked to mental health-related factors, perception of their financial situation, career optimism, adaptability and planning. The higher the psychological quality of life score was, the greater the LS of postgraduates’ was. Good health and positive attitudes related to the job market enhanced their LS indicator.

Keywords: Career attitudes, fathers’ education level, life satisfaction, mental health.

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Authors: Herminio Martínez-García, Juan Gámiz, Yolanda Bolea, Antoni Grau

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This article presents an interactive system for data acquisition in vehicle testing according to the test process defined in automotive directive 2004/104/EC. The project has been designed and developed by authors for the Spanish company Applus-LGAI. The developed project will result in a new process, which will involve the creation of braking cycle test defined in the aforementioned automotive directive. It will also allow the analysis of new vehicle features that was not feasible, allowing an increasing interaction with the vehicle. Potential users of this system in the short term will be vehicle manufacturers and in a medium term the system can be extended to testing other automotive components and EMC tests.

Keywords: Automotive process, data acquisition system, electromagnetic compatibility (EMC) testing, European Directive 2004/104/EC.

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Authors: Warangkana Juangjandee

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The rapidly increasing number of population in the limited area creates an effect on the idea of the improvement of the area to suit the environment and the needs of people. Faculty of architecture Chiang Mai University is also expanding in both variety fields of study and quality of education. In 2020, the new department will be introduced in the faculty which is Department of Landscape Architecture. With the limitation of the area in the existing building, the faculty plan to renovate some parts of its school for anticipates the number of students who will join the program in the next two years. As a result, the old wooden workshop area is selected to be renovated as student studio space. With such condition, it is necessary to study the restriction and the distinctive environment of the site prior to the improvement in order to find ways to manage the existing space due to the fact that the primary functions that have been practiced in the site, an old wooden workshop space and the new function, studio space, are too different. 72.9% of the annual times in the room are considered to be out of the thermal comfort condition with high relative humidity. This causes non-comfort condition for occupants which could promote mould growth. This study aims to analyze thermal comfort condition in the Landscape Learning Studio Area for finding the solution to improve indoor air quality and respond to local conditions. The research methodology will be in two parts: 1) field gathering data on the case study 2) analysis and finding the solution of improving indoor air quality. The result of the survey indicated that the room needs to solve non-comfort condition problem. This can be divided into two ways which are raising ventilation and indoor temperature, e.g. improving building design and stack driven ventilation, using fan for enhancing more internal ventilation.

Keywords: Relative humidity, renovation, temperature, thermal comfort.

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Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf, .doc, .ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: Education technology, learning management system, decentralized applications, blockchain.

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Authors: S. Wongkoon, M. Pollar, M. Jaroensutasinee, K. Jaroensutasinee

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This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.

Keywords: Dengue, SARIMA, Time Series Analysis, Northern Thailand.

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: Artificial neural networks, fuel consumption, machine learning, regression, statistical tests.

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Authors: Alae El Alami, Mohamed Bahaj

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This paper proposes an approach for translating an existing relational database (RDB) schema into ORDB. The transition is done with methods that can extract various functions from a RDB which is based on aggregations, associations between the various tables, and the reflexive relationships. These methods can extract even the inheritance knowing that no process of reverse engineering can know that it is an Inheritance; therefore, our approach exceeded all of the previous studies made for ​​the transition from RDB to ORDB. In summation, the creation of the New Data Model (NDM) that stocks the RDB in a form of a structured table, and from the NDM we create our navigational model in order to simplify the implementation object from which we develop our different types. Through these types we precede to the last step, the creation of tables.

The step mentioned above does not require any human interference. All this is done automatically, and a prototype has already been created which proves the effectiveness of this approach.

Keywords: Relational databases, Object-relational databases, Semantic enrichment.

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Authors: B. S. Jatau, Nandom Abu

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Structural interpretation of aeromagnetic data and Landsat imagery over the Middle Benue Trough was carried out to determine the depth to basement, delineate the basement morphology and relief, and the structural features within the basin. The aeromagnetic and Landsat data were subjected to various image and data enhancement and transformation routines. Results of the study revealed lineaments with trend directions in the N-S, NE-SW, NWSE and E-W directions, with the NE-SW trends been dominant. The depths to basement within the trough were established to be at 1.8, 0.3 and 0.8km, as shown from the spectral analysis plot. The Source Parameter Imaging (SPI) plot generated showed the centralsouth/ eastern portion of the study area as being deeper in contrast to the western-south-west portion. The basement morphology of the trough was interpreted as having parallel sets of micro-basins which could be considered as grabens and horsts in agreement with the general features interpreted by early workers.

Keywords: Morphology, Middle Benue Trough, Spectral Analysis, Source Parameter Imaging.

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: GIS, Outliers, PSO, Traffic Data.

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Authors: Salima Kouici, Abdelkader Khelladi

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In this work, we begin with the presentation of the Tθ family of usual similarity measures concerning multidimensional binary data. Subsequently, some properties of these measures are proposed. Finally the impact of the use of different inter-elements measures on the results of the Agglomerative Hierarchical Clustering Methods is studied.

Keywords: Binary data, similarity measure, Tθ measures, Agglomerative Hierarchical Clustering.

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Authors: Zhang Linan, Jihwan Song, Dongchoul Kim

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In this study, a three-dimensional haptotaxis model to simulate the migration of a population of cancer cells has been proposed. The invasion of cancer cells is related with the hapto-attractant and the effect of the interface energies between the cells and the ECM. The diffuse interface model, which incorporates the haptotaxis mechanism and interface energies, is employed. The semi-implicit Fourier spectral scheme is adopted for efficient evaluation of the simulation. The simulation results thoroughly reveal the dynamics of cancer-cell migration.

Keywords: Haptotaxis, Cancer Cells, Cell Migration, Interface Energy, Diffuse Interface Model

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Authors: M. Saravanan, M. Madheswaran

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Wireless Sensor Network (WSN) clustering architecture enables features like network scalability, communication overhead reduction, and fault tolerance. After clustering, aggregated data is transferred to data sink and reducing unnecessary, redundant data transfer. It reduces nodes transmitting, and so saves energy consumption. Also, it allows scalability for many nodes, reduces communication overhead, and allows efficient use of WSN resources. Clustering based routing methods manage network energy consumption efficiently. Building spanning trees for data collection rooted at a sink node is a fundamental data aggregation method in sensor networks. The problem of determining Cluster Head (CH) optimal number is an NP-Hard problem. In this paper, we combine cluster based routing features for cluster formation and CH selection and use Minimum Spanning Tree (MST) for intra-cluster communication. The proposed method is based on optimizing MST using Simulated Annealing (SA). In this work, normalized values of mobility, delay, and remaining energy are considered for finding optimal MST. Simulation results demonstrate the effectiveness of the proposed method in improving the packet delivery ratio and reducing the end to end delay.

Keywords: Wireless sensor network, clustering, minimum spanning tree, genetic algorithm, low energy adaptive clustering hierarchy, simulated annealing.

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Authors: Isao Taguchi, Yasuo Sugai

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This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.

Keywords: data selection, function approximation problem, multistage leaning, neural network, voluntary oscillation.

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Authors: Guy Leshem, Ya'acov Ritov

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Traffic Management and Information Systems, which rely on a system of sensors, aim to describe in real-time traffic in urban areas using a set of parameters and estimating them. Though the state of the art focuses on data analysis, little is done in the sense of prediction. In this paper, we describe a machine learning system for traffic flow management and control for a prediction of traffic flow problem. This new algorithm is obtained by combining Random Forests algorithm into Adaboost algorithm as a weak learner. We show that our algorithm performs relatively well on real data, and enables, according to the Traffic Flow Evaluation model, to estimate and predict whether there is congestion or not at a given time on road intersections.

Keywords: Machine Learning, Boosting, Classification, TrafficCongestion, Data Collecting, Magnetic Loop Detectors, SignalizedIntersections, Traffic Signal Timing Optimization.

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Authors: Cholpassorn Sitthiwarongchai, Chutikarn Sriviboon

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The two primary objectives of this research were (1)  to examine the current knowledge and actual circumstance of  agricultural workers about mangosteen product processing; and (2) to  analyze and evaluate ways to develop capacity of mangosteen  product processing. The population of this study was 15,125 people  who work in the agricultural sector, in this context, mangosteen  production, in the eastern part of Thailand that included Chantaburi  Province, Rayong Province, Trad Province and Pracheenburi  Province. The sample size based on Yamane’s calculation with 95%  reliability was therefore 392 samples. Mixed method was employed  included questionnaire and focus group discussion with  Connoisseurship Model used in order to collect quantitative and  qualitative data. Key informants were used in the focus group  including agricultural business owners, academic people in agro food  processing, local academics, local community development staff,  OTOP subcommittee, and representatives of agro processing  industry professional organizations. The study found that the  majority of the respondents agreed with a high level (in five- rating  scale) towards most of variables of knowledge management in agro  food processing. The result of the current knowledge and actual  circumstance of agricultural human resource in an arena of  mangosteen product processing revealed that mostly, the respondents  agreed at a high level to establish 7 variables. The guideline to  developing the body of knowledge in order to enhance the capacity  of the agricultural workers in mangosteen product processing was  delivered in the focus group discussion. The discussion finally  contributed to an idea to produce manuals for mangosteen product  processing methods, with 4 products chosen: (1) mangosteen soap;  (2) mangosteen juice; (3) mangosteen toffee; and (4) mangosteen  preserves or jam.

Keywords: Capacity Enhancement, Agricultural Workers, Mangosteen Product Processing.

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Authors: Alexander Y. Vaninsky

Abstract:

This paper presents a method of economic factorial analysis of the CO₂ emissions based on the extension of the Divisia index to interconnected factors. This approach, contrary to the Kaya identity, considers three main factors of the CO₂ emissions: gross domestic product, energy consumption, and population - as equally important, and allows for accounting of all of them simultaneously. The three factors are included into analysis together with their carbon intensities that allows for obtaining a comprehensive picture of the change in the CO₂ emissions. A computer program in R-language that is available for free download serves automation of the calculations. A case study of the U.S. carbon dioxide emissions is used as an example. 

Keywords: CO2 emissions, Economic analysis, Factorial analysis, Divisia index, Interconnected factors.

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Authors: Ramin Halavati, Saeed B. Shouraki, Mahdieh Noroozian, Saman H. Zadeh

Abstract:

Packing problems arise in a wide variety of application areas. The basic problem is that of determining an efficient arrangement of different objects in a region without any overlap and with minimal wasted gap between shapes. This paper presents a novel population based approach for optimizing arrangement of irregular shapes. In this approach, each shape is coded as an agent and the agents' reproductions and grouping policies results in arrangements of the objects in positions with least wasted area between them. The approach is implemented in an application for cutting sheets and test results on several problems from literature are presented.

Keywords: Optimization, Bin Packing, Agent Based Systems.

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