Search results for: data management.

Authors: S. Malathi, P. Seenuvasakumaran

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Nanomaterials ferrites have applications in making permanent magnets, high density information devices, color imaging etc. In the present examination, lithium ferrite is synthesized by sol-gel process. The x-ray diffraction (XRD) result shows that the structure of lithium ferrite is monoclinic structure. The average particle size 22 nm is calculated by Scherer formula. The lattice parameters and dislocation density (δ) are calculated from XRD data. Strain (ε) values are evaluated from Williamson – hall plot. The FT-IR study reveals the formation of ferrites showing the significant absorption bands. The VU-VIS spectroscopic data is used to calculate direct and indirect optical band gap (Eg) of 1.57eV and 1.01eV respectively for lithium ferrite by using Tauc plot at the edge of the absorption band. The energy dispersive x-ray analysis spectra showed that the expected elements exist in the material. The magnetic behaviour of the materials studied using vibrating sample magnetometer (VSM).

Keywords: Sol-gel, dislocation density, energy band gap, VSM.

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Authors: Hyungkeun Jee, Jooyoung Lee, Dowon Hong

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The most common forensic activity is searching a hard disk for string of data. Nowadays, investigators and analysts are increasingly experiencing large, even terabyte sized data sets when conducting digital investigations. Therefore consecutive searching can take weeks to complete successfully. There are two primary search methods: index-based search and bitwise search. Index-based searching is very fast after the initial indexing but initial indexing takes a long time. In this paper, we discuss a high speed bitwise search model for large-scale digital forensic investigations. We used pattern matching board, which is generally used for network security, to search for string and complex regular expressions. Our results indicate that in many cases, the use of pattern matching board can substantially increase the performance of digital forensic search tools.

Keywords: Digital forensics, search, regular expression.

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Authors: Shigeaki Sakurai, Youichi Kitahara, Ryohei Orihara

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Sequential mining methods efficiently discover all frequent sequential patterns included in sequential data. These methods use the support, which is the previous criterion that satisfies the Apriori property, to evaluate the frequency. However, the discovered patterns do not always correspond to the interests of analysts, because the patterns are common and the analysts cannot get new knowledge from the patterns. The paper proposes a new criterion, namely, the sequential interestingness, to discover sequential patterns that are more attractive for the analysts. The paper shows that the criterion satisfies the Apriori property and how the criterion is related to the support. Also, the paper proposes an efficient sequential mining method based on the proposed criterion. Lastly, the paper shows the effectiveness of the proposed method by applying the method to two kinds of sequential data.

Keywords: Sequential mining, Support, Confidence, Apriori property

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Authors: Paiboon Chuwatthanakij

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Each of the countries around the world has different ways of management and many of them depend on people to administrate their country. Thailand, for example, empowers the sovereignty of Thai people under constitution; however, our Thai voting system is not able to flow fast enough under the current Political management system. The sovereignty of Thai people is addressing this problem through representatives during current elections, in order to set a new policy for the countries ideology to change in the House and the Cabinet. This is particularly important in a democracy to be developed under our current political institution. The Organic Act on Political Parties 2007 is the establishment we have today that is causing confrontations within the establishment. There are many political parties that will soon be abolished. Many political parties have already been subsidized. This research study is to analyze the legal problems with the political party establishment under the Organic Act on Political Parties 2007. This will focus on the freedom of each political establishment compared to an effective political operation. Textbooks and academic papers will be referenced from studies home and abroad. The study revealed that Organic Act on Political Parties 2007 has strict provisions on the political structure over the number of members and the number of branches involved within political parties system. Such operations shall be completed within one year; but under the existing laws the small parties are not able to participate with the bigger parties. The cities are capable of fulfilling small political party requirements but fail to become coalesced because the current laws won't allow them to be united as one. It is important to allow all independent political parties to join our current political structure. Board members can’t help the smaller parties to become a large organization under the existing Thai laws. Creating a new establishment that functions efficiently throughout all branches would be one solution to these legal problems between all political parties. With this new operation, individual political parties can participate with the bigger parties during elections. Until current political institutions change their system to accommodate public opinion, these current Thai laws will continue to be a problem with all political parties in Thailand.

Keywords: Coalesced, Political Party, Sovereignty.

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Authors: Takayuki Shiina

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Mathematical programming has been applied to various problems. For many actual problems, the assumption that the parameters involved are deterministic known data is often unjustified. In such cases, these data contain uncertainty and are thus represented as random variables, since they represent information about the future. Decision-making under uncertainty involves potential risk. Stochastic programming is a commonly used method for optimization under uncertainty. A stochastic programming problem with recourse is referred to as a two-stage stochastic problem. In this study, we consider a stochastic programming problem with simple integer recourse in which the value of the recourse variable is restricted to a multiple of a nonnegative integer. The algorithm of a dynamic slope scaling procedure for solving this problem is developed by using a property of the expected recourse function. Numerical experiments demonstrate that the proposed algorithm is quite efficient. The stochastic programming model defined in this paper is quite useful for a variety of design and operational problems.

Keywords: stochastic programming problem with recourse, simple integer recourse, dynamic slope scaling procedure

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Authors: Bujar Ismaili, Bahti Ismajli, Venhar Ismaili, Skender Ramadani

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In Kosovo, the problem with the electricity supply is huge and it does not meet the demands of consumers. Older thermal power plants, which are regarded as big environmental polluters, produce most of the energy. Our experiment is based on the production of electricity using the closed method that does not affect environmental pollution by using waste as fuel that is considered to pollute the environment. The experiment was carried out in the village of Godanc, municipality of Shtime, Kosovo. In the experiment, a production line based on the production of electricity and central heating was designed at the same time. The results are the benefits of electricity as well as the release of temperature for heating with minimal expenses and with the release of 0% gases into the atmosphere. During this experiment, coal, plastic, waste from wood processing, and agricultural wastes were used as raw materials. The method utilized in the experiment allows for the release of gas through pipes and filters during the top-to-bottom combustion of the raw material in the boiler, followed by the method of gas filtration from waste wood processing (sawdust). During this process, the final product, gas, is obtained. This gas passes through the carburetor, enabling the combustion process to put the internal combustion machine and the generator into operation and produce electricity that does not release gases into the atmosphere. The results show that the system provides energy stability without environmental pollution from toxic substances and waste, as well as with low production costs. From the final results, it follows that, in the case of using coal fuel, we have benefited from more electricity and higher temperature release, followed by plastic waste, which also gave good results. The results obtained during these experiments prove that the current problems of lack of electricity and heating can be met at a lower cost and have a clean environment and waste management.

Keywords: Energy, heating, atmosphere, waste management, gasification.

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Authors: Basak Oguz Yolcular

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A large amount of valuable information is available in plain text clinical reports. New techniques and technologies are applied to extract information from these reports. In this study, we developed a domain based software system to transform 600 Otorhinolaryngology discharge notes to a structured form for extracting clinical data from the discharge notes. In order to decrease the system process time discharge notes were transformed into a data table after preprocessing. Several word lists were constituted to identify common section in the discharge notes, including patient history, age, problems, and diagnosis etc. N-gram method was used for discovering terms co-Occurrences within each section. Using this method a dataset of concept candidates has been generated for the validation step, and then Predictive Apriori algorithm for Association Rule Mining (ARM) was applied to validate candidate concepts.

Keywords: association rule mining, otorhinolaryngology, predictive apriori, text mining

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Authors: Fatma Didin Sonmez, Pinar Sener

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Technology transfer by international trade and foreign direct investment is the most important positive outcome of open economy. It is widely accepted that new technology and knowledge have an important role in enhancing economic growth. Human capital is the other important factor assisting economic growth. In this study, the role of human capital in the growth process is examined in a view of new endogenous growth theory emphasizing on the technology transfer resulting from international trade. Using the panel data of 10 developed and 10 developing countries, impact of human capital and openness on the rate of economic growth of different countries is analysed. Evidence suggests the view that human capital and openness contribute to the economic growth in both developing and developed countries, but with different rates.

Keywords: economic growth, human capital, openness, technology

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Authors: Liu Yi, Bao Liyong

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Aiming at the problem of low efficiency of pipelined scheduling in periodic query-qualified service, this paper proposes a system service resource scheduling strategy with parallel optimized qualified service polling control. The paper constructs the polling queuing system and its mathematical model; firstly, the first-order and second-order characteristic parameter equations are obtained by partial derivation of the probability mother function of the system state variables, and the complete mathematical, analytical expressions of each system parameter are deduced after the joint solution. The simulation experimental results are consistent with the theoretical calculated values. The system performance analysis shows that the average captain and average period of the system have been greatly improved, which can better adapt to the service demand of delay-sensitive data in the dense data environment.

Keywords: Polling, parallel scheduling, mean queue length, average cycle time.

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: Time series modelling, ARIMA model, River runoff, Karkheh River, CLS method.

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Authors: F. Djeffal, N. Lakhdar, T. Bendib

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The study of the transport coefficients in electronic devices is currently carried out by analytical and empirical models. This study requires several simplifying assumptions, generally necessary to lead to analytical expressions in order to study the different characteristics of the electronic silicon-based devices. Further progress in the development, design and optimization of Silicon-based devices necessarily requires new theory and modeling tools. In our study, we use the PSO (Particle Swarm Optimization) technique as a computational tool to develop analytical approaches in order to study the transport phenomenon of the electron in crystalline silicon as function of temperature and doping concentration. Good agreement between our results and measured data has been found. The optimized analytical models can also be incorporated into the circuits simulators to study Si-based devices without impact on the computational time and data storage.

Keywords: Particle Swarm, electron mobility, Si-based devices, Optimization.

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Authors: T Panigrahi, G Panda, Mulgrew

Abstract:

This paper introduces a new approach for the performance analysis of adaptive filter with error saturation nonlinearity in the presence of impulsive noise. The performance analysis of adaptive filters includes both transient analysis which shows that how fast a filter learns and the steady-state analysis gives how well a filter learns. The recursive expressions for mean-square deviation(MSD) and excess mean-square error(EMSE) are derived based on weighted energy conservation arguments which provide the transient behavior of the adaptive algorithm. The steady-state analysis for co-related input regressor data is analyzed, so this approach leads to a new performance results without restricting the input regression data to be white.

Keywords: Error saturation nonlinearity, transient analysis, impulsive noise.

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Authors: Hui-Min Ting, Tsair-Fwu Lee, Ming-Yuan Cho, Pei-Ju Chao, Chun-Ming Chang, Long-Chang Chen, Fu-Min Fang

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To evaluate the ability to predict xerostomia after radiotherapy, we constructed and compared neural network and logistic regression models. In this study, 61 patients who completed a questionnaire about their quality of life (QoL) before and after a full course of radiation therapy were included. Based on this questionnaire, some statistical data about the condition of the patients’ salivary glands were obtained, and these subjects were included as the inputs of the neural network and logistic regression models in order to predict the probability of xerostomia. Seven variables were then selected from the statistical data according to Cramer’s V and point-biserial correlation values and were trained by each model to obtain the respective outputs which were 0.88 and 0.89 for AUC, 9.20 and 7.65 for SSE, and 13.7% and 19.0% for MAPE, respectively. These parameters demonstrate that both neural network and logistic regression methods are effective for predicting conditions of parotid glands.

Keywords: NPC, ANN, logistic regression, xerostomia.

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Authors: Victor Krebss

Abstract:

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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Authors: Wann-Ming Wey, Yi-Chih Huang

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Proper maintenance and preservation of significant cultural heritages or historic buildings is necessary. It can not only enhance environmental benefits and a sense of community, but also preserve a city's history and people’s memory. It allows the next generation to be able to get a glimpse of our past, and achieve the goal of sustainable preserved cultural assets. However, the management of maintenance work has not been appropriate for many designated heritages or historic buildings so far. The planning and implementation of the reuse has yet to have a breakthrough specification. It leads the heritages to a mere formality of being “reserved”, instead of the real meaning of “conservation”. For the restoration and preservation of cultural heritages study issues, it is very important due to the consideration of historical significance, symbolism, and economic benefits effects. However, the decision makers such as the officials from public sector they often encounter which heritage should be prioritized to be restored first under the available limited budgets. Only very few techniques are available today to determine the appropriately restoration priorities for the diverse historical heritages, perhaps because of a lack of systematized decision-making aids been proposed before. In the past, the discussions of management and maintenance towards cultural assets were limited to the selection of reuse alternatives instead of the allocation of resources. In view of this, this research will adopt some integrated research methods to solve the existing problems that decision-makers might encounter when allocating resources in the management and maintenance of heritages and historic buildings.

The purpose of this study is to develop a sustainable decision making model for local governments to resolve these problems. We propose an alternative decision support model to prioritize restoration needs within the limited budgets. The model is constructed based on fuzzy Delphi, fuzzy analysis network process (FANP) and goal programming (GP) methods. In order to avoid misallocate resources; this research proposes a precise procedure that can take multi-stakeholders views, limited costs and resources into consideration. Also, the combination of many factors and goals has been taken into account to find the highest priority and feasible solution results. To illustrate the approach we propose in this research, seven cultural heritages in Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.

Keywords: Cultural Heritage, Historic Buildings, Priority Evaluation, Multi-Criteria Decision Making, Goal Programming, Fuzzy Analytic Network Process, Resource Allocation.

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Authors: S. M. Abbas, M. A. Hannan, S. A. Samad, A. Hussain

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This paper presented a modified efficient inductive powering link based on ASK modulator and proposed efficient class- E power amplifier. The design presents the external part which is located outside the body to transfer power and data to the implanted devices such as implanted Microsystems to stimulate and monitoring the nerves and muscles. The system operated with low band frequency 10MHZ according to industrial- scientific – medical (ISM) band to avoid the tissue heating. For external part, the modulation index is 11.1% and the modulation rate 7.2% with data rate 1 Mbit/s assuming Tbit = 1us. The system has been designed using 0.35-μm fabricated CMOS technology. The mathematical model is given and the design is simulated using OrCAD P Spice 16.2 software tool and for real-time simulation, the electronic workbench MULISIM 11 has been used.

Keywords: Implanted devices, ASK techniques, Class-E power amplifier, Inductive powering and low-frequency ISM band.

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Authors: Afrooz Moatari Kazerouni

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In a competitive production environment, critical decision making are based on data resulted by random sampling of product units. Efficiency of these decisions depends on data quality and also their reliability scale. This point leads to the necessity of a reliable measurement system. Therefore, the conjecture process and analysing the errors contributes to a measurement system known as Measurement System Analysis (MSA). The aim of this research is on determining the necessity and assurance of extensive development in analysing measurement systems, particularly with the use of Repeatability and Reproducibility Gages (GR&R) to improve physical measurements. Nowadays in productive industries, repeatability and reproducibility gages released so well but they are not applicable as well as other measurement system analysis methods. To get familiar with this method and gain a feedback in improving measurement systems, this survey would be on “ANOVA" method as the most widespread way of calculating Repeatability and Reproducibility (R&R).

Keywords: Analysis of Variance (ANOVA), MeasurementSystem Analysis (MSA), Part-Operator interaction effect, Repeatability and Reproducibility.

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Authors: Hock Chuan, Lim

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This paper presents an approach for identifying interactive effects using Network Science (NS) supported by Social Network Analysis (SNA) techniques. Based on general observations that learning processes and behaviors are shaped by the social relationships and influenced by learning environment, the central idea was to understand both the human and non-human interactive effects for a blended learning mode of delivery of computer science modules. Important findings include (a) the importance of non-human nodes to influence the centrality and transfer; (b) the degree of non-human and human connectivity impacts learning. This project reveals that the NS pattern and connectivity as measured by node relationships offer alternative approach for hypothesis generation and design of qualitative data collection. An iterative process further reinforces the analysis, whereas the experimental simulation option itself is an interesting alternative option, a hybrid combination of both experimental simulation and qualitative data collection presents itself as a promising and viable means to study complex scenario such as blended learning delivery mode. The primary value of this paper lies in the design of the approach for studying interactive effects of human (social nodes) and non-human (learning/study environment, Information and Communication Technologies (ICT) infrastructures nodes) components. In conclusion, this project adds to the understanding and the use of SNA to model and study interactive effects in blended social learning.

Keywords: Blended learning, network science, social learning, social network analysis, study environment.

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Authors: Norazah Mohd Suki, T Ramayah

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e-Government structures permits the government to operate in a more transparent and accountable manner of which it increases the power of the individual in relation to that of the government. This paper identifies the factors that determine customer-s attitude towards e-Government services using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents. The research model was tested using Structural Equation Modeling (SEM) techniques via the Analysis of Moment Structure (AMOS 16) computer software. SEM is a comprehensive approach to testing hypotheses about relations among observed and latent variables. The proposed model fits the data well. The results demonstrated that e- Government services acceptance can be explained in terms of compatibility and attitude towards e-Government services. The setup of the e-Government services will be compatible with the way users work and are more likely to adopt e-Government services owing to their familiarity with the Internet for various official, personal, and recreational uses. In addition, managerial implications for government policy makers, government agencies, and system developers are also discussed.

Keywords: E-government, structural equation modelling, attitude, service.

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Authors: Munther I. Kandah, Fahmi A. Abu Al-Rub, Lucy Bawarish, Mira Bawarish, Hiba Al-Tamimi, Reem Khalil, Raja'a Sa, ada

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In this project cadmium ions were adsorbed from aqueous solutions onto either date pits; a cheap agricultural and nontoxic material, or chemically activated carbon prepared from date pits using phosphoric acid. A series of experiments were conducted in a batch adsorption technique to assess the feasibility of using the prepared adsorbents. The effects of the process variables such as initial cadmium ions concentration, contact time, solution pH and adsorbent dose on the adsorption capacity of both adsorbents were studied. The experimental data were tested using different isotherm models such as Langmuir, Freundlich, Tempkin and Dubinin- Radushkevich. The results showed that although the equilibrium data could be described by all models used, Langmuir model gave slightly better results when using activated carbon while Freundlich model, gave better results with date pits.

Keywords: Adsorption, Cadmium, Chemical Activation, DatePits.

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Authors: Sahar Khedr, Dina Sayed, Ayman Hanafy

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Arabic is one of the most ancient and critical languages in the world. It has over than 250 million Arabic native speakers and more than twenty countries having Arabic as one of its official languages. In the past decade, we have witnessed a rapid evolution in smart devices, social network and technology sector which led to the need to provide tools and libraries that properly tackle the Arabic language in different domains. Stemming is one of the most crucial linguistic fundamentals. It is used in many applications especially in information extraction and text mining fields. The motivation behind this work is to enhance the Arabic light stemmer to serve the data mining industry and leverage it in an open source community. The presented implementation works on enhancing the Arabic light stemmer by utilizing and enhancing an algorithm that provides an extension for a new set of rules and patterns accompanied by adjusted procedure. This study has proven a significant enhancement for better search accuracy with an average 10% improvement in comparison with previous works.

Keywords: Arabic data mining, Arabic Information extraction, Arabic Light stemmer, Arabic stemmer.

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Authors: Kaushal Kumar Jha

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Nagaland, the 16th state of India in order of statehood, is situated between 25° 6' and 27° 4' latitude north and between 93º 20' E and 95º 15' E longitude of equator in the North Eastern part of the India. Endowed with varied topography, soil and agro climatic conditions it is known for its potentiality to grow all most all kinds of horticultural crops. Pineapple being grown since long organically by default is one of the most promising crops of the state with emphasis being laid for commercialization by the government of Nagaland. In light of commercialization, globalization and scope of setting small-scale industries, a research study was undertaken to examine the socio-economic and personal characteristics, entrepreneurial characteristics and attitude of the pineapple growers towards improved package of practices of pineapple cultivation. The study was conducted in Medziphema block of Dimapur district of the Nagaland state of India following ex post facto research design. Ninety pineapple growers were selected from four different villages of Medziphema block based on proportionate random selection procedure. Findings of the study revealed that majority of the respondents had medium level of entrepreneurial characteristics in terms of knowledge level, risk orientation, self confidence, management orientation, farm decision making ability and leadership ability and most of them had favourable attitude towards improved package of practices of pineapple cultivation. The variables age, education, farm size, risk orientation, management orientation and sources of information utilized were found important to influence the attitude of the respondents. The study revealed that favourable attitude and entrepreneurial characteristics of the pineapple cultivators might be harnessed for increased production of pineapple in the state thereby bringing socio economic upliftment of the marginal and small-scale farmers.

Keywords: Attitude, Entrepreneurial characteristics, Pineapple, Socio economic upliftment.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour , Foad Saadi

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In this paper back-propagation artificial neural network (BPANN) is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

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Authors: Eman AbuKhousa, Marwan Z. Bataineh

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The 21^st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.

Keywords: Clustering analysis, community of practice, data mining, higher education, new faculty challenges, social networks, social influence, professional development.

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Authors: Y. O’Connor, C. Heavin, S. O’ Connor, J. Gallagher, J. Wu, J. O’Donoghue

Abstract:

Background: To improve the delivery of paediatric healthcare in low resource settings, Community Health Workers (CHW) have been provided with a paper-based set of protocols known as Community Case Management (CCM). Yet research has shown that CHW adherence to CCM guidelines is poor, ultimately impacting health service delivery. Digitising the CCM guidelines via mobile technology is argued in extant literature to improve CHW adherence. However, little research exist which outlines how (a) this process can be digitised and (b) adherence could be improved as a result. Aim: To explore how an electronic mobile version of CCM (eCCM) can overcome issues associated with the paper-based CCM protocol (inadequate adherence to guidelines) vis-à-vis service blueprinting. This service blueprint will outline how (a) the CCM process can be digitised using mobile Clinical Decision Support Systems software to support clinical decision-making and (b) adherence can be improved as a result. Method: Development of a single service blueprint for a standalone application which visually depicts the service processes (eCCM) when supporting the CHWs, using an application known as Supporting LIFE (SL eCCM app) as an exemplar. Results: A service blueprint is developed which illustrates how the SL eCCM app can be utilised by CHWs to assist with the delivery of healthcare services to children. Leveraging smartphone technologies can (a) provide CHWs with just-in-time data to assist with their decision making at the point-of-care and (b) improve CHW adherence to CCM guidelines. Conclusions: The development of the eCCM opens up opportunities for the CHWs to leverage the inherent benefit of mobile devices to assist them with health service delivery in rural settings. To ensure that benefits are achieved, it is imperative to comprehend the functionality and form of the eCCM service process. By creating such a service blueprint for an eCCM approach, CHWs are provided with a clear picture regarding the role of the eCCM solution, often resulting in buy-in from the end-users.

Keywords: Adherence, community health workers, developing countries, mobile clinical decision support systems, CDSS, service blueprint.

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Authors: M. Capocelli, A. Caputo, M. De Falco, D. Mazzei, V. Piemonte

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This paper presents the experimental results and the related modeling of a thermal energy storage (TES) facility, ideated and realized by ENEA and realizing the thermocline with an innovative geometry. Firstly, the thermal energy exchange model of an equivalent shell & tube heat exchanger is described and tested to reproduce the performance of the spiral exchanger installed in the TES. Through the regression of the experimental data, a first-order thermocline model was also validated to provide an analytical function of the thermocline, useful for the performance evaluation and the comparison with other systems and implementation in simulations of integrated systems (e.g. power plants). The experimental data obtained from the plant start-up and the short-cut modeling of the system can be useful for the process analysis, for the scale-up of the thermal storage system and to investigate the feasibility of its implementation in actual case-studies.

Keywords: Thermocline, modelling, heat exchange, spiral, shell, tube.

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Authors: Mohammadreza Razzazi, Maryam Bayat

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Selection of the best possible set of suppliers has a significant impact on the overall profitability and success of any business. For this reason, it is usually necessary to optimize all business processes and to make use of cost-effective alternatives for additional savings. This paper proposes a new efficient context-aware supplier selection model that takes into account possible changes of the environment while significantly reducing selection costs. The proposed model is based on data clustering techniques while inspiring certain principles of online algorithms for an optimally selection of suppliers. Unlike common selection models which re-run the selection algorithm from the scratch-line for any decision-making sub-period on the whole environment, our model considers the changes only and superimposes it to the previously defined best set of suppliers to obtain a new best set of suppliers. Therefore, any recomputation of unchanged elements of the environment is avoided and selection costs are consequently reduced significantly. A numerical evaluation confirms applicability of this model and proves that it is a more optimal solution compared with common static selection models in this field.

Keywords: Supplier Selection, Context-Awareness, OnlineAlgorithms, Data Clustering.

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Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

Abstract:

In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: Client classification, loan suitability, risk rating, CART analysis, decision tree.

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Authors: P. Phokharatkul, K. Sankhuangaw, S. Somkuarnpanit, S. Phaiboon, C. Kimpan

Abstract:

Much research into handwritten Thai character recognition have been proposed, such as comparing heads of characters, Fuzzy logic and structure trees, etc. This paper presents a system of handwritten Thai character recognition, which is based on the Ant-minor algorithm (data mining based on Ant colony optimization). Zoning is initially used to determine each character. Then three distinct features (also called attributes) of each character in each zone are extracted. The attributes are Head zone, End point, and Feature code. All attributes are used for construct the classification rules by an Ant-miner algorithm in order to classify 112 Thai characters. For this experiment, the Ant-miner algorithm is adapted, with a small change to increase the recognition rate. The result of this experiment is a 97% recognition rate of the training set (11200 characters) and 82.7% recognition rate of unseen data test (22400 characters).

Keywords: Hand written, Thai character recognition, Ant-mineralgorithm, distinct feature.

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Authors: Mohammad Borhani, Ahmad Jamshidzaei, Mehdi Koohsari

Abstract:

The study of climate has captivated human interest throughout history. In response to this fascination, individuals historically organized their daily activities in alignment with prevailing climatic conditions and seasonal variations. Understanding the elements and specific climatic parameters of each region, such as precipitation, which directly impacts human life, is essential because, in recent years, there has been a significant increase in heavy rainfall in various parts of the world attributed to the effects of climate change. Climate prediction models suggest a future scenario characterized by an increase in severe precipitation events and related floods on a global scale. This is a result of human-induced greenhouse gas emissions causing changes in the natural precipitation patterns. The present study focused on examining the trend of monthly, seasonal, and annual precipitation in Sistan and Baluchestan provinces. The study employed data obtained from 13 precipitation measurement stations managed by the Iran Water Resources Management Company, encompassing daily precipitation records spanning the period from 1997 to 2016. The results indicated that the total monthly precipitation at the studied stations in Sistan and Baluchestan province follows a sinusoidal trend. The highest intense precipitation was observed in January, February, and March, while the lowest occurred in September, October, and then November. The investigation of the trend of seasonal precipitation in this province showed that precipitation follows an upward trend in the autumn season, reaching its peak in winter, and then shows a decreasing trend in spring and summer. Also, the examination of average precipitation indicated that the highest yearly precipitation occurred in 1997 and then in 2004, while the lowest annual precipitation took place between 1999 and 2001. The analysis of the annual precipitation trend demonstrates a decrease in precipitation from 1997 to 2016 in Sistan and Baluchestan province.

Keywords: Climate change, extreme precipitation, greenhouse gas, trend analysis.

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