Search results for: real time data.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12976

Search results for: real time data.

10216 The Tourist Satisfaction on Brand Identity Design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province

Authors: Panupong Chanplin, Kathaleeya Chanda., Wilailuk Mepracha

Abstract:

The aims of this research were twofold: 1) to brand identity design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province and 2) to study the level of tourist satisfaction towards brand identity design of Creative Agriculture Community Enterprise, Bang Khonthi District, Samut Songkhram Province. tourist satisfaction was measured using six criteria: clear brand positioning, likeable brand personality, memorable logo, attractive color palette, professional typography and on-brand supporting graphics. The researcher utilized a probability sampling method via simple random sampling. The sample consisted of 30 tourists in the Creative Agriculture Community Enterprise. Statistics utilized for data analysis were percentage, mean, and standard deviation. The results suggest that tourist had high levels of satisfaction towards all six criteria of the brand identity design that was designed to target them. This study proposes that specifically brand identity designed of Creative Agriculture Community Enterprise could also be implemented with other real media already available on the market.

Keywords: Satisfaction, brand identity, logo, creative agriculture community enterprise.

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10215 Effect of Different pH on Canthaxanthin Degradation

Authors: N. Seyedrazi, S. H. Razavi, Z. Emam-Djomeh

Abstract:

In this research, natural canthaxanthin as one of the most important carotenoids was extracted from Dietzia natronolimnaea HS-1. The changes of canthaxanthin enriched in oilin- water emulsions with vegetable oil (5 mg/ 100 mL), Arabic gum (5 mg/100 mL), and potassium sorbate (0.5 g/100 mL) was investigated. The effects of different pH (3, 5 and 7), as well as, time treatment (3, 18 and 33 days) in the environmental temperature (24°C) on the degradation were studied by response surface methodology (RSM). The Hunter values (L*, a*, and b*) and the concentration of canthaxanthin (C, mg/L) illustrated more degradation of this pigment at low pHs (pH≤ 4) by passing the time (days≥10) with R² 97.00%, 91.31%, 97.60%, and 99.54% for C, L*, a*, and b* respectively. The predicted model were found to be significant (p<0.05).

Keywords: Degradation, Emulsion, Response SurfaceMethodology (RSM)

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10214 Stability and HOPF Bifurcation Analysis in a Stage-structured Predator-prey system with Two Time Delays

Authors: Yongkun Li, Meng Hu

Abstract:

A stage-structured predator-prey system with two time delays is considered. By analyzing the corresponding characteristic equation, the local stability of a positive equilibrium is investigated and the existence of Hopf bifurcations is established. Formulae are derived to determine the direction of bifurcations and the stability of bifurcating periodic solutions by using the normal form theory and center manifold theorem. Numerical simulations are carried out to illustrate the theoretical results. Based on the global Hopf bifurcation theorem for general functional differential equations, the global existence of periodic solutions is established.

Keywords: Predator-prey system, stage structure, time delay, HOPF bifurcation, periodic solution, stability.

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10213 Analysis of Meteorological Drought in the Ruhr Basin by Using the Standardized Precipitation Index

Authors: Mosaad Khadr, Gerd Morgenschweis, Andreas Schlenkhoff

Abstract:

Drought is one of the most damaging climate-related hazards, it is generally considered as a prolonged absence of precipitation. This normal and recurring climate phenomenon had plagued civilization throughout history because of the negative impacts on economical, environmental and social sectors. Drought characteristics are thus recognized as important factors in water resources planning and management. The purpose of this study is to detect the changes in drought frequency, persistence and severity in the Ruhr river basin. The frequency of drought events was calculated using the Standardized Precipitation Index (SPI). Used data are daily precipitation records from seven meteorological stations covering the period 1961-2007. The main benefit of the application of this index is its versatility, only rainfall data is required to deliver five major dimensions of a drought : duration, intensity, severity, magnitude, and frequency. Furthermore, drought can be calculated in different time steps. In this study SPI was calculated for 1, 3, 6, 9, 12, and 24 months. Several drought events were detected in the covered period, these events contain mild, moderate and severe droughts. Also positive and negative trends in the SPI values were observed.

Keywords: Drought, Germany, Precipitation, Ruhr River, Standardized Precipitation Index (SPI), Trend Test.

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10212 Fuzzy Uncertainty Theory for Stealth Fighter Aircraft Selection in Entropic Fuzzy TOPSIS Decision Analysis Process

Authors: C. Ardil

Abstract:

The purpose of this paper is to present fuzzy TOPSIS in an entropic fuzzy environment. Due to the ambiguous concepts often represented in decision data, exact values are insufficient to model real-life situations. In this paper, the rating of each alternative is defined in fuzzy linguistic terms, which can be expressed with triangular fuzzy numbers. The weight of each criterion is then derived from the decision matrix using the entropy weighting method. Next, a vertex method is proposed to calculate the distance between two triangular fuzzy numbers. According to the TOPSIS concept, a closeness coefficient is defined to determine the ranking order of all alternatives by simultaneously calculating the distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). Finally, an illustrative example of selecting stealth fighter aircraft is shown at the end of this article to highlight the procedure of the proposed method. Correlation analysis and validation analysis using TOPSIS, WSM, and WPM methods were performed to compare the ranking order of the alternatives.

Keywords: stealth fighter aircraft selection, fuzzy uncertainty theory (FUT), fuzzy entropic decision (FED), fuzzy linguistic variables, triangular fuzzy numbers, multiple criteria decision making analysis, MCDMA, TOPSIS, WSM, WPM

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10211 Stability and Bifurcation Analysis in a Model of Hes1 Selfregulation with Time Delay

Authors: Kejun Zhuang, Hailong Zhu

Abstract:

The dynamics of a delayed mathematical model for Hes1 oscillatory expression are investigated. The linear stability of positive equilibrium and existence of local Hopf bifurcation are studied. Moreover, the global existence of large periodic solutions has been established due to the global bifurcation theorem.

Keywords: Hes1, Hopf bifurcation, time delay, transcriptional repression loop

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10210 Detection Efficient Enterprises via Data Envelopment Analysis

Authors: S. Turkan

Abstract:

In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: Data envelopment analysis, super efficiency, financial ratios, BCC model.

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10209 Socio-Technical Systems: Transforming Theory into Practice

Authors: L. Ngowi, N. H. Mvungi

Abstract:

This paper critically examines the evolution of socio-technical systems theory, its practices, and challenges in system design and development. It examines concepts put forward by researchers focusing on the application of the theory in software engineering. There are various methods developed that use socio-technical concepts based on systems engineering without remarkable success. The main constraint is the large amount of data and inefficient techniques used in the application of the concepts in system engineering for developing time-bound systems and within a limited/controlled budget. This paper critically examines each of the methods, highlight bottlenecks and suggest the way forward. Since socio-technical systems theory only explains what to do, but not how doing it, hence engineers are not using the concept to save time, costs and reduce risks associated with new frameworks. Hence, a new framework, which can be considered as a practical approach is proposed that borrows concepts from soft systems method, agile systems development and object-oriented analysis and design to bridge the gap between theory and practice. The approach will enable the development of systems using socio-technical systems theory to attract/enable the system engineers/software developers to use socio-technical systems theory in building worthwhile information systems to avoid fragilities and hostilities in the work environment.

Keywords: Socio-technical systems, human centered design, software engineering, cognitive engineering, soft systems, systems engineering.

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10208 Response Time Behavior Trends of Proptional, Propotional Integral and Proportional Integral Derivative Mode on Lab Scale

Authors: Syed Zohaib Javaid Zaidi, W. Iqbal

Abstract:

The industrial automation is dependent upon pneumatic control systems. The industrial units are now controlled with digital control systems to tackle the process variables like Temperature, Pressure, Flow rates and Composition.

This research work produces an evaluation of the response time fluctuations for proportional mode, proportional integral and proportional integral derivative modes of automated chemical process control. The controller output is measured for different values of gain with respect to time in three modes (P, PI and PID). In case of P-mode for different values of gain the controller output has negligible change. When the controller output of PI-mode is checked for constant gain, it can be seen that by decreasing the integral time the controller output has showed more fluctuations. The PID mode results have found to be more interesting in a way that when rate minute has changed, the controller output has also showed fluctuations with respect to time.  The controller output for integral mode and derivative mode are observed with lesser steady state error, minimum offset and larger response time to control the process variable.   The tuning parameters in case of P-mode are only steady state gain with greater errors with respect to controller output. The integral mode showed controller outputs with intermediate responses during integral gain (ki).  By increasing the rate minute the derivative gain (kd) also increased which showed the controlled oscillations in case of PID mode and lesser overshoot.

Keywords: Controller Output, P, PI &PID modes, Steady state gain.

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10207 Fusion of ETM+ Multispectral and Panchromatic Texture for Remote Sensing Classification

Authors: Mahesh Pal

Abstract:

This paper proposes to use ETM+ multispectral data and panchromatic band as well as texture features derived from the panchromatic band for land cover classification. Four texture features including one 'internal texture' and three GLCM based textures namely correlation, entropy, and inverse different moment were used in combination with ETM+ multispectral data. Two data sets involving combination of multispectral, panchromatic band and its texture were used and results were compared with those obtained by using multispectral data alone. A decision tree classifier with and without boosting were used to classify different datasets. Results from this study suggest that the dataset consisting of panchromatic band, four of its texture features and multispectral data was able to increase the classification accuracy by about 2%. In comparison, a boosted decision tree was able to increase the classification accuracy by about 3% with the same dataset.

Keywords: Internal texture; GLCM; decision tree; boosting; classification accuracy.

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10206 Inductance Characteristic of Annealed Titanium Dioxide on Silicon Substrate

Authors: Chih Chin Yang, Lan Hui Huang, Bo Shum Chen, Jia Liang Ke, Chung Lun Tsai

Abstract:

The control of oxygen flow rate during growth of titanium dioxide by mass flow controller in DC plasma sputtering growth system is studied. The impedance of TiO2 films for inductance effect is influenced by annealing time and oxygen flow rate. As annealing time is increased, the inductance of TiO2 film is the more. The growth condition of optimum and maximum inductance for TiO2 film to serve as sensing device are oxygen flow rate of 15 sccm and large annealing time. The large inductance of TiO2 film will be adopted to fabricate the biosensor to obtain the high sensitivity of sensing in biology.

Keywords: Annealed, Inductance, Silicon substarte, Titanium dioxide

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10205 Action Functional of the Electomagnetic Field: Effect of Gravitation

Authors: Arti Vaish, Harish Parthasarathy

Abstract:

The scalar wave equation for a potential in a curved space time, i.e., the Laplace-Beltrami equation has been studied in this work. An action principle is used to derive a finite element algorithm for determining the modes of propagation inside a waveguide of arbitrary shape. Generalizing this idea, the Maxwell theory in a curved space time determines a set of linear partial differential equations for the four electromagnetic potentials given by the metric of space-time. Similar to the Einstein-s formulation of the field equations of gravitation, these equations are also derived from an action principle. In this paper, the expressions for the action functional of the electromagnetic field have been derived in the presence of gravitational field.

Keywords: General theory of relativity, electromagnetism, metric tensor, Maxwells equations, test functions, finite element method.

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10204 Elegant: An Intuitive Software Tool for Interactive Learning of Power System Analysis

Authors: Eduardo N. Velloso, Fernando M. N. Dantas, Luciano S. Barros

Abstract:

A common complaint from power system analysis students lies in the overly complex tools they need to learn and use just to simulate very basic systems or just to check the answers to power system calculations. The most basic power system studies are power-flow solutions and short-circuit calculations. This paper presents a simple tool with an intuitive interface to perform both these studies and assess its performance in comparison with existent commercial solutions. With this in mind, Elegant is a pure Python software tool for learning power system analysis developed for undergraduate and graduate students. It solves the power-flow problem by iterative numerical methods and calculates bolted short-circuit fault currents by modeling the network in the domain of symmetrical components. Elegant can be used with a user-friendly Graphical User Interface (GUI) and automatically generates human-readable reports of the simulation results. The tool is exemplified using a typical Brazilian regional system with 18 buses. This study performs a comparative experiment with 1 undergraduate and 4 graduate students who attempted the same problem using both Elegant and a commercial tool. It was found that Elegant significantly reduces the time and labor involved in basic power system simulations while still providing some insights into real power system designs.

Keywords: Free- and open-source software, power-flow, power system analysis, Python, short-circuit.

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10203 Solar Radiation Time Series Prediction

Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

Abstract:

A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled direct normal irradiance field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: Artificial Neural Networks, Resilient Propagation, Solar Radiation, Time Series Forecasting.

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10202 Optimization of Ethanol Fermentation from Pineapple Peel Extract Using Response Surface Methodology (RSM)

Authors: Nadya Hajar, Zainal, S., Atikah, O., Tengku Elida, T. Z. M.

Abstract:

Ethanol has been known for a long time, being perhaps the oldest product obtained through traditional biotechnology fermentation. Agriculture waste as substrate in fermentation is vastly discussed as alternative to replace edible food and utilization of organic material. Pineapple peel, highly potential source as substrate is a by-product of the pineapple processing industry. Bio-ethanol from pineapple (Ananas comosus) peel extract was carried out by controlling fermentation without any treatment. Saccharomyces ellipsoides was used as inoculum in this fermentation process as it is naturally found at the pineapple skin. In this study, the capability of Response Surface Methodology (RSM) for optimization of ethanol production from pineapple peel extract using Saccharomyces ellipsoideus in batch fermentation process was investigated. Effect of five test variables in a defined range of inoculum concentration 6- 14% (v/v), pH (4.0-6.0), sugar concentration (14-22°Brix), temperature (24-32°C) and time of incubation (30-54 hrs) on the ethanol production were evaluated. Data obtained from experiment were analyzed with RSM of MINITAB Software (Version 15) whereby optimum ethanol concentration of 8.637% (v/v) was determined. The optimum condition of 14% (v/v) inoculum concentration, pH 6, 22°Brix, 26°C and 30hours of incubation. The significant regression equation or model at the 5% level with correlation value of 99.96% was also obtained.

Keywords: Bio-ethanol, pineapple peel extract, Response Surface Methodology (RSM), Saccharomyces ellipsoideus.

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10201 A Beacon Based Priority Routing Scheme for Solar Power Plants in WSNs

Authors: Ki-Sung Park, Dae-Hee Lee, Dae-Ho Won, Yeon-Mo Yang

Abstract:

Solar power plants(SPPs) have shown a lot of good outcomes in providing a various functions depending on industrial expectations by deploying ad-hoc networking with helps of light loaded and battery powered sensor nodes. In particular, it is strongly requested to develop an algorithm to deriver the sensing data from the end node of solar power plants to the sink node on time. In this paper, based on the above observation we have proposed an IEEE802.15.4 based self routing scheme for solar power plants. The proposed beacon based priority routing Algorithm (BPRA) scheme utilizes beacon periods in sending message with embedding the high priority data and thus provides high quality of service(QoS) in the given criteria. The performance measures are the packet Throughput, delivery, latency, total energy consumption. Simulation results under TinyOS Simulator(TOSSIM) have shown the proposed scheme outcome the conventional Ad hoc On-Demand Distance Vector(AODV) Routing in solar power plants.

Keywords: Solar Power Plants(SPPs), Self routing, Quality of Service(QoS), WPANs, WSNs, TinyOS, TOSSIM, IEEE802.15.4

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10200 Optimal Policy for a Deteriorating Inventory Model with Finite Replenishment Rate and with Price Dependant Demand Rate and Cycle Length Dependant Price

Authors: Hamed Sabahno

Abstract:

In this paper, an inventory model with finite and constant replenishment rate, price dependant demand rate, time value of money and inflation, finite time horizon, lead time and exponential deterioration rate and with the objective of maximizing the present worth of the total system profit is developed. Using a dynamic programming based solution algorithm, the optimal sequence of the cycles can be found and also different optimal selling prices, optimal order quantities and optimal maximum inventories can be obtained for the cycles with unequal lengths, which have never been done before for this model. Also, a numerical example is used to show accuracy of the solution procedure.

Keywords: Deteriorating items, Dynamic programming, Finitereplenishment rate, Inventory control, Operation Research.

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10199 Contributory Factors to Diabetes Dietary Regimen Non Adherence in Adults with Diabetes

Authors: Okolie Uchenna, Ehiemere Ijeoma, Ezenduka Pauline, Ogbu Sylvester

Abstract:

A cross sectional survey design was used to collect data from 370 diabetic patients. Two instruments were used in obtaining data; in-depth interview guide and researchers- developed questionnaire. Fisher's exact test was used to investigate association between the identified factors and nonadherence. Factors identified were: socio-demographic factors such as: gender, age, marital status, educational level and occupation; psychosocial obstacles such as: non-affordability of prescribed diet, frustration due to the restriction, limited spousal support, feelings of deprivation, feeling that temptation is inevitable, difficulty in adhering in social gatherings and difficulty in revealing to host that one is diabetic; health care providers obstacles were: poor attitude of health workers, irregular diabetes education in clinics , limited number of nutrition education sessions/ inability of the patients to estimate the desired quantity of food, no reminder post cards or phone calls about upcoming patient appointments and delayed start of appointment / time wasting in clinics.

Keywords: Behavior change, diabetes mellitus, dietarymanagement, diet adherence.

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10198 A Revisited View to the Paced Auditory Serial Addition Test (PASAT) in Female and Male Normal Subjects

Authors: Javad Razjouyan, Shahriar Gharibzadeh, Ali Fallah, Mehdi Moghaddasi, Mohsen Seyfi, Amir Kasaeian

Abstract:

Paced Auditory Serial Addition Test (PASAT) has been used as a common research tool for different neurological disorders like Multiple Sclerosis. Recently, technology let researchers to introduce a new versions of the visual test, the paced visual serial addition test (PVSAT). In this paper, the computerized version of these two tests is introduced. Beside the number of true responses are interpreted, the reaction time of subjects are calculated by the software. We hypothesize that paying attention to the reaction time may be valuable. For this purpose, sixty eight female normal subjects and fifty eight male normal subjects are enrolled in the study. We investigate the similarity between the PASAT3 and PVSAT3 in number of true responses and the new criterion (the average reaction time of each subject). The similarity between two tests were rejected (p-value = 0.000) which means that these two test differ. The effect of sex in the tests were not approved since the pvalues of different between PASAT3 and PVSAT3 in both sex is the same (p-value = 0.000) which means that male and female subjects performed the tests at no different level of performance. The new criterion shows a negative correlation with the age which offers aged normal subjects may have the same number of true responses as the young subjects but they have latent responses. This will give prove for the importance of reaction time.

Keywords: Paced Auditory Serial Addition Test, Pace Visual Serial Addition Test, reaction time.

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10197 C-LNRD: A Cross-Layered Neighbor Route Discovery for Effective Packet Communication in Wireless Sensor Network

Authors: K. Kalaikumar, E. Baburaj

Abstract:

One of the problems to be addressed in wireless sensor networks is the issues related to cross layer communication. Cross layer architecture shares the information across the layer, ensuring Quality of Services (QoS). With this shared information, MAC protocol adapts effective functionality maintenance such as route selection on changeable sensor network environment. However, time slot assignment and neighbour route selection time duration for cross layer have not been carried out. The time varying physical layer communication over cross layer causes high traffic load in the sensor network. Though, the traffic load was reduced using cross layer optimization procedure, the computational cost is high. To improve communication efficacy in the sensor network, a self-determined time slot based Cross-Layered Neighbour Route Discovery (C-LNRD) method is presented in this paper. In the presented work, the initial process is to discover the route in the sensor network using Dynamic Source Routing based Medium Access Control (MAC) sub layers. This process considers MAC layer operation with dynamic route neighbour table discovery. Then, the discovered route path for packet communication employs Broad Route Distributed Time Slot Assignment method on Cross-Layered Sensor Network system. Broad Route means time slotting on varying length of the route paths. During packet communication in this sensor network, transmission of packets is adjusted over the different time with varying ranges for controlling the traffic rate. Finally, Rayleigh fading model is developed in C-LNRD to identify the performance of the sensor network communication structure. The main task of Rayleigh Fading is to measure the power level of each communication under MAC sub layer. The minimized power level helps to easily reduce the computational cost of packet communication in the sensor network. Experiments are conducted on factors such as power factor, on packet communication, neighbour route discovery time, and information (i.e., packet) propagation speed.

Keywords: Medium access control, neighbour route discovery, wireless sensor network, Rayleigh fading, distributed time slot assignment

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10196 A Formal Approach for Instructional Design Integrated with Data Visualization for Learning Analytics

Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

Abstract:

Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: Educational data visualization, high-level petri nets, instructional design, learning analytics.

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10195 Reduction of False Positives in Head-Shoulder Detection Based on Multi-Part Color Segmentation

Authors: Lae-Jeong Park

Abstract:

The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: Pedestrian detection, color segmentation, false positives, feature extraction.

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10194 Churn Prediction for Telecommunication Industry Using Artificial Neural Networks

Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

Abstract:

Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: Customer relationship management, churn prediction, telecom industry, deep learning, Artificial Neural Networks, ANN.

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10193 Nonlinear Time-History Analysis of 3-Dimensional Semi-rigid Steel Frames

Authors: Phu-Cuong Nguyen, Seung-Eock Kim

Abstract:

This paper presents nonlinear elastic dynamic analysis of 3-D semi-rigid steel frames including geometric and connection nonlinearities. The geometric nonlinearity is considered by using stability functions and updating geometric stiffness matrix. The nonlinear behavior of the steel beam-to-column connection is considered by using a zero-length independent connection element comprising of six translational and rotational springs. The nonlinear dynamic equilibrium equations are solved by the Newmark numerical integration method. The nonlinear time-history analysis results are compared with those of previous studies and commercial SAP2000 software to verify the accuracy and efficiency of the proposed procedure.

Keywords: Geometric nonlinearity, nonlinear time-historyanalysis, semi-rigid connection, stability functions.

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10192 Microbial Contaminants in Drinking Water Collected from Different Regions of Kuwait

Authors: Abu Salim Mustafa

Abstract:

Water plays a major role in maintaining life on earth, but it can also serve as a matrix for pathogenic organisms, posing substantial health threats to humans. Although, outbreaks of diseases attributable to drinking water may not be common in industrialized countries, they still occur and can lead to serious acute, chronic, or sometimes fatal health consequences. The analysis of drinking water samples from different regions of Kuwait was performed in this study for bacterial and viral contaminations. Drinking tap water samples were collected from 15 different locations of the six Kuwait governorates. All samples were analyzed by confocal microscopy for the presence of bacteria. The samples were cultured in vitro to detect cultivable organisms. DNA was isolated from the cultured organisms and the identity of the bacteria was determined by sequencing the bacterial 16S rRNA genes, followed by BLAST analysis in the database of NCBI, USA. RNA was extracted from water samples and analyzed by real-time PCR for the detection of viruses with potential health risks, i.e. Astrovirus, Enterovirus, Norovirus, Rotavirus, and Hepatitis A. Confocal microscopy showed the presence of bacteria in some water samples. The 16S rRNA gene sequencing of culture grown organisms, followed by BLAST analysis, identified the presence of several non-pathogenic bacterial species. However, one sample had Acinetobacter baumannii, which often causes opportunistic infections in immunocompromised people, but none of the studied viruses could be detected in the drinking water samples analyzed. The results indicate that drinking water samples analyzed from various locations in Kuwait are relatively safe for drinking and do not contain many harmful pathogens.

Keywords: Drinking water, 16S rRNA, microbial diversity, viruses, Kuwait.

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10191 Machine Scoring Model Using Data Mining Techniques

Authors: Wimalin S. Laosiritaworn, Pongsak Holimchayachotikul

Abstract:

this article proposed a methodology for computer numerical control (CNC) machine scoring. The case study company is a manufacturer of hard disk drive parts in Thailand. In this company, sample of parts manufactured from CNC machine are usually taken randomly for quality inspection. These inspection data were used to make a decision to shut down the machine if it has tendency to produce parts that are out of specification. Large amount of data are produced in this process and data mining could be very useful technique in analyzing them. In this research, data mining techniques were used to construct a machine scoring model called 'machine priority assessment model (MPAM)'. This model helps to ensure that the machine with higher risk of producing defective parts be inspected before those with lower risk. If the defective prone machine is identified sooner, defective part and rework could be reduced hence improving the overall productivity. The results showed that the proposed method can be successfully implemented and approximately 351,000 baht of opportunity cost could have saved in the case study company.

Keywords: Computer Numerical Control, Data Mining, HardDisk Drive.

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10190 The Impact of Seasonality on Rainfall Patterns: A Case Study

Authors: Priti Kaushik, Randhir Singh Baghel, Somil Khandelwal

Abstract:

This study uses whole-year data from Rajasthan, India, at the meteorological divisional level to analyze and evaluate long-term spatiotemporal trends in rainfall and looked at the data from each of the thirteen tehsils in the Jaipur district to see how the rainfall pattern has altered over the last 10 years. Data on daily rainfall from the Indian Meteorological Department (IMD) in Jaipur are available for the years 2012 through 2021. We mainly focus on comparing data of tehsil wise in the Jaipur district, Rajasthan, India. Also analyzed is the fact that July and August always see higher rainfall than any other month. Rainfall usually starts to rise around week 25th and peaks in weeks 32nd or 33rd. They showed that on several occasions, 2017 saw the least amount of rainfall during a long span of 10 years. The greatest rain fell between 2012 and 2021 in 2013, 2019, and 2020.

Keywords: Data analysis, extreme events, rainfall, descriptive case studies, precipitation temperature.

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10189 Toward Delegated Democracy: Vote by Yourself, or Trust Your Network

Authors: Hiroshi Yamakawa, Michiko Yoshida, Motohiro Tsuchiya

Abstract:

The recent development of Information and Communication Technology (ICT) enables new ways of "democratic" decision-making such as a page-ranking system, which estimates the importance of a web page based on indirect trust on that page shared by diverse group of unorganized individuals. These kinds of "democracy" have not been acclaimed yet in the world of real politics. On the other hand, a large amount of data about personal relations including trust, norms of reciprocity, and networks of civic engagement has been accumulated in a computer-readable form by computer systems (e.g., social networking systems). We can use these relations as a new type of social capital to construct a new democratic decision-making system based on a delegation network. In this paper, we propose an effective decision-making support system, which is based on empowering someone's vote whom you trust. For this purpose, we propose two new techniques: the first is for estimating entire vote distribution from a small number of votes, and the second is for estimating active voter choice to promote voting using a delegation network. We show that these techniques could increase the voting ratio and credibility of the whole decision by agent-based simulations.

Keywords: Delegation, network centrality, social network, voting ratio.

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10188 Impact of the Electricity Market Prices on Energy Storage Operation during the COVID-19 Pandemic

Authors: Marin Mandić, Elis Sutlović, Tonći Modrić, Luka Stanić

Abstract:

With the restructuring and deregulation of the power system, storage owners, generation companies or private producers can offer their multiple services on various power markets and earn income in different types of markets, such as the day-ahead, real-time, ancillary services market, etc. During the COVID-19 pandemic, electricity prices, as well as ancillary services prices, increased significantly. The optimization of the energy storage operation was performed using a suitable model for simulating the operation of a pumped storage hydropower plant under market conditions. The objective function maximizes the income earned through energy arbitration, regulation-up, regulation-down and spinning reserve services. The optimization technique used for solving the objective function is mixed integer linear programming (MILP). In numerical examples, the pumped storage hydropower plant operation has been optimized considering the already achieved hourly electricity market prices from Nord Pool for the pre-pandemic (2019) and the pandemic (2020 and 2021) years. The impact of the electricity market prices during the COVID-19 pandemic on energy storage operation is shown through the analysis of income, operating hours, reserved capacity and consumed energy for each service. The results indicate the role of energy storage during a significant fluctuation in electricity and services prices.

Keywords: Electrical market prices, electricity market, energy storage optimization, mixed integer linear programming, MILP, optimization.

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10187 Enhance the Power of Sentiment Analysis

Authors: Yu Zhang, Pedro Desouza

Abstract:

Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modeling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: Sentiment Analysis, Social Media, Twitter, Amazon, Data Mining, Machine Learning, Text Mining.

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