- Все статьи 611
Статьи журнала - International Journal of Information Engineering and Electronic Business
Все статьи: 611
Статья научная
Control of the Steam Turbine at PLTU Tanjung Enim 3x10 MW through the use of Digital Electro-Hydraulic (DEH), which plays a critical role in the functioning of the Steam Turbine generated. Because the current control operates solely by manual loading adjustment by raising or reducing the PID percentage from DEH, it is essential to analyze the input parameter values to improve the DEH PID control's sensitivity. The DEH control mechanism of PLTU TE 3x10MW is divided into two modes: Valve Limiter and Load. At PLTU TE 3x10MW, the steam turbine frequently experiences hunting (fluctuations) on the governor control valve, causing the turbine unit to become unstable until shutdown or blackout. The DEH signal response to actuator stroking can generally operate according to the given signal command with a signal density of 1/ΔT = 100,298 Hz and ΔY/ΔT = 781,016 ms. By analyzing the DEH system in the unit and modeling it using Matlab, it is hoped that it will produce a PID control value that can be input into the system based on the return signal from the actuator stroking level and the steam turbine speed at the time of loading, thus enabling the control valve or governor to be more responsive and smoother in responding of Mining load changes, either manually or automatically.
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Dynamic Characteristics of the Hippocampal Neuron under Conductance’s Changing
Статья научная
The hippocampal CA1 pyramid neuron has plenty of discharge actions. In the thesis, the dynamic characteristics of the hippocampal neuron model are analyzed and discussed by the neurodynamic theory and methods. Under a certain amplitude current’s stimulation, the change of gNa(the maximum conductance of the transient sodium channel) and gKdr (the maximum conductance of the delay rectification potassium channel) can cause different dynamic characteristics of the neuron model. The transient Na+ current(INa ) caused by gNa is indispensable in the discharge’s formation process of the model. The model can generate the discharge process only when gNa reaches a certain threshold. In the discharge process of the neuron model, gNa’s changing affects little and the ISIs approximate to a straight line. The delay rectification K+ current(Ikdr) caused by gKdr isn’t indispensable in the discharge’s formation process of the model. But gKdr’s changing affects much in the discharge process of the neuron model. With gKdr’s changing, the neuron model undergoes different dynamic bifurcation process, and has plenty of discharge patterns such as the chaos, period, and so on. This investigation is helpful to know and investigate the dynamic characteristics and the bifurcation mechanism of the hippocampal neuron; and it provides a certain theory assist to investigate the neural diseases such as the Alzheimer disease by neurodynamics.
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Статья научная
The increasing ubiquity of Social Internet of Things (SIoT) devices necessitates innovative data aggregation techniques to distill meaningful insights from diverse sources. This study introduces a Dynamic Data Aggregation Model for SIoT devices. The model aims to amalgamate static and mobile device data, employing Density-Based Spatial Clustering of Applications with Noise (DBSCAN) for spatial clustering and Recurrent Neural Networks (RNN) for predicting mobile device movement patterns. The purpose is to offer a holistic approach to predictive analytics in the SIoT domain by seamlessly integrating these methodologies. The model begins with data preprocessing, ensuring data quality. It then applies DBSCAN for spatial clustering, enabling a comprehensive understanding of spatial relationships between devices. Simultaneously, RNNs are used for predictive modeling, specifically in forecasting mobile device movement patterns. The integration of DBSCAN clustering and RNNs forms the model’s innovative core, providing a unified solution for dynamic data aggregation. Comprehensive testing demonstrates the model’s notable accuracy in predicting mobile device movement patterns. By combining the spatial clustering capabilities of DBSCAN with the predictive power of RNNs, the model effectively unifies static and mobile data, advancing predictive analytics in the SIoT context. The proposed model yielded average values of 0.14604 (Mean Squared Error), 2.678385 (Mean Absolute Error), 0.307154 (Root Mean Squared Error), and 1.342317 (Mean Absolute Percentage Error), respectively. The Dynamic Data Aggregation Model proves its efficacy in addressing SIoT challenges. The integration of DBSCAN clustering and RNNs offers a versatile framework for dynamic data analysis, contributing significantly to predictive analytics in SIoT contexts.
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Dynamic Passenger OD Distribution and System Performance of Taxi Operation System
Статья научная
The complexity of taxi operation system grows out of the inherent dynamics and randomness of taxi services. In this paper, we consider a taxi operation system to be a special structure queuing system, and present a simulation model of cruising taxi operation system. It is supposed that vacant taxis cruise in the city to search for passengers, and their search strategies are based on drivers’ experience and available information. With a given OD distribution, the dynamic features of the taxis’ 24-hour available service can be recurred. Through a simulation experiment, it is shown that considering the time-variant effect can help to get more accurate information about taxi services. A new method of determining the system optimal taxi fleet size is developed. These are helpful to taxi supervisor for regulating urban taxi operation system more efficiently and taxi drivers for providing better service.
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E –Hospital Management & Hospital Information Systems – Changing Trends
Статья научная
The rapid growth in Information & Communication Technology (ICT), and the power of Internet has strongly impacted the business and service delivery models of today’s global environment. E-Hospital Management Systems provide the benefits of streamlined operations, enhanced administration & control, superior patient care, strict cost control and improved profitability. Globally accepted health care systems need to comply with Healthcare Insurance Portability and Accountability Act (HIPAA) standards of the US and that has become the norm of the Healthcare industry when it comes to medical records management and patient information privacy. The study is focused on understanding the performance indicators of Hospital information systems (HIS), summarizing the latest commonly agreed standards and protocols like Health Level Seven (HL7) standards for mutual message exchange, HIS components, etc… The study is qualitative and descriptive in nature and most of the data is based on secondary sources of survey data. To arrive at a conclusive idea of the larger picture on E- Hospital Management and Hospital information systems, existing survey data and specific successful case studies of HIS are considered in the study. With so many customized versions of E – hospital management solutions (E – HMS) and Hospital Information systems (HIS) available in the market, a generic module wise version of E – Hospital management system is charted out to give a clear understanding for researchers and industry experts. From the specific successful case studies analyzed in the study, the success factors and challenges faced in successful E-HMS implementation are highlighted. Some of the mandatory standards like HIPAA are discussed in detail for clarity on Healthcare system implementation requirements.
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E-Commerce Evaluation and E Business Trends
Статья научная
E–Commerce in recent times has exploded many folds due to the invention of new Information and Communication (ICT) technologies and applications. Business models of today are highly depending upon internet based transaction and trading platforms, use of Web portals and mobile applications. Proposition of new business models sans the inclusion of internet and their application has become almost impossible for business. Business data pertaining to E Commerce has become highly valuable in recent times. Social networking websites, sharing of product data and its reviews in blogs paves ways for promoting business in new methods. There is need to develop metrics to assess the strength of E Commerce penetration in Business and also evaluate the various E Commerce platforms. Use of E business tools for data analysis, prediction and decision making has become the latest order of the day. Changing trends in E business has a drastic impact on the organizations depending upon internet based applications for handling its business processes and day to day transactions.
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E-Governance Initiatives in Maharashtra (India): Problems and Challenges
Статья научная
In this digital world, research interest is being increased on e-governance, existing research isn't adequately address key issues regarding the development, implementation and integration of the e-governance projects. The delivering of e-services to the citizens at their door is the primary function of government. The Maharashtra state is the pioneer in citizen centric e-governance initiatives like Common Service Centre (Maha e-Seva, SETU), Public Distribution System (PDS), Land Record (Bhoomi Abhilekh) etc. The present research is efforts to identify and establish linkages between the factors responsible for creating a suitable environment for effective implementation of e-governance services in government offices. The objective of the present research paper is to establish the background for the development of a conceptual framework of e-governance initiatives. Based on the existing literature review the paper provides an analysis of existing empirical findings and conceptual perspectives related to e-governance initiatives in Satara District, Maharashtra, India.
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E-health Implementation by Private Dental Service Providers in Bulawayo, Zimbabwe
Статья научная
The 2030 Agenda for Sustainable Development Goals recognises the role of Information and Communication Technologies (ICT) in accelerating human development and progress by bridging the digital divide and developing knowledge societies. Internet technologies affect every sphere of human and organisational life. The study was motivated by low e-health adoption in developing countries such as Zimbabwe. A cross-sectional quantitative survey investigated e-health implementation by private dental care service providers in Bulawayo. The research population comprised private dental service providers in Bulawayo. Data was collected using a five-point Likert scale questionnaire that was self-administered. Regression and factor analysis, Kaiser-Meyer-Olkin Measure of Sampling Adequacy, Bartlett’s sphericity test, and the Principal Component Analysis were used for data analysis. The study found that private dental service providers in Bulawayo were already implementing some rudimentary elements of e-health in their day-to-day practice. The findings also revealed that private dental care providers positively perceived the benefits of implementing e-health, such as improved quality of health service delivery, enhanced efficiency, and improved accessibility of services. Participants highlighted ICT costs, communication, lack of experience, and e-readiness as significant barriers to e-health implementation. Most participants were concerned that personal health information may fall into the wrong hands resulting in privacy violations and loss of personal data. The regression coefficient showed that combined variations in the independent variables explain at least 76.4% of the dependent variable (adoption). The study recommends the government enact policies that support private dental service providers in implementing e-health systems to improve service delivery. The study contributes to the literature on e-health adoption in developing countries.
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Early Skin Cancer Detection Using Deep Convolutional Neural Networks on Mobile Smartphone
Статья научная
Malignant melanoma is the most dangerous kind of skin cancer. It is mostly misidentified as benign lesion. The chance of surviving melanoma disease is high if detected early. In recent years, deep convolutional neural networks have attracted great attention owing to its outstanding performance in recognizing and classifying images. This research work performs a comparative analysis of three different convolutional neural networks (CNN) trained on skin cancerous and non-cancerous images, namely: a custom 3-layer CNN, VGG-16 CNN, and Google Inception V3. Google Inception V3 achieved the best result, with training and test accuracy of 90% and 81% respectively and a sensitivity of 84%. This work contribution is mainly in the development of an android application that uses Google Inception V3 model for early detection of skin cancer.
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Echo Cancellation Research of Channel Estimation based on PN Sequence
Статья научная
For the problem of estimation sequence effect on channel estimation accuracy and echo cancellation effect, this paper, based on the basic principle of echo cancellation, analyses the effect of PN sequence mechanism and the correlation on the channel estimation parameters. Comparing with using the input signal itself as the estimation sequence. With the input signal OFDM, the results of simulation and actual operation show that the method can increase both the accuracy of channel estimation and echo cancellation effect effectively.
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Educational Data Mining: RT and RF Classification Models for Higher Education Professional Courses
Статья научная
Computer applications and business administrations have gained significant importance in higher education. The type of education, students get in these areas depend on the geo-economical and the social demography. The choice of a institution in these area of higher education dependent on several factors like economic condition of students, geographical area of the institution, quality of educational organizations etc. To have a strategic approach for the development of importing knowledge in this area requires understanding the behavior aspect of these parameters. The scientific understanding of these can be had from obtaining patterns or recognizing the attribute behavior from previous academic years. Further, applying data mining tool to the previous data on the attributes identified will throw better light on the behavioral aspects of the identified patterns. In this paper, an attempt has been made to use of some techniques of education data mining on the dataset of MBA and MCA admission for the academic year 2014-15. The paper discusses the result obtained by applying RF and RT techniques. The results are analyzed for the knowledge discovery and are presented.
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Effect of Four Wave Mixing on AP-DCDM-WDM Fiber Optic System with Different Power per Channel
Статья научная
Absolute polar duty cycle division multiplexing over WDM is a multiplexing technique which promises better spectral efficiency. Non linearities in fiber optic communication are major issues, especially the effect of four wave mixing. This paper presents the effect of four wave mixing on 40 Gbps AP-DCDM over WDM fiber optic systems. The system was tested by simulating the AP-DCDM-WDM design in Optisystem software and MATLAB code. From the results the effect of four wave mixing on the system is presented under different configurations such as input power per channel. Simulation results have shown that AP-DCDM-WDM systems have greater tolerance to dispersion and have better receiver sensitivity than other conventional techniques. The effect of FWM on AP-DCDM-WDM system is also less than on other conventional techniques on basis of simulation.
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Effective Networking Model for Efficient Implementation of E-Governance: A Case Study of Nigeria
Статья научная
Nigeria is a nation full of potentials ranging from its human resources advantage to its mineral resources – the list is endless. Ambitious too, it has come to terms with the fact that ICT must be utilized even for the delivery of democracy dividends to actualize its vision of being among the top 20 economies by year 2020. In this paper, we explore the nation's drive towards adopting e-governance by generally itemizing the requirements for e-governance, appraising how far Nigeria has gone in implementing it and then proposing a workable way to achieve it. Our study reveals that while the visions for e-government implementation are well articulated in terms of required components and intended deliverables, there are no clear statements on the processes of implementation. To this end, we propose some networking models adoptable towards realizing the different dimensions of e-government.
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Статья научная
The purpose of this study is basically to explore (know and study) the effectiveness of intelligence which in this case consists of variables of intellectual intelligence (IQ), emotional intelligence (EQ), and spiritual intelligence (SQ) on employee performance in a retail business organization (case study at eramart store in Timbau sub-district, Tenggarong, Indonesia). The sample in this study was 26 employees of eramart store in Timbau sub-district, Tenggarong, Indonesia. Sampling technique by random sampling. The analysis tool used is a multiple regression equation with a hypothesis test used by the F and t tests. The calculation result of the F test obtained F count is 45.252, while the table F value is obtained a value of 2.80 this means that (Fcount 45, 252 > Ft 2.80) with a significant value of < 0.05, so it can be said that the variables of intellectual intelligence, emotional intelligence and spiritual intelligence together / simultaneously are able to show their influence on employee performance at the eramart store in Timbau sub-district, Tenggarong or it can be explained that the regression model that was built can be used to predict the size of employee performance at the eramart store in Timbau sub-district, Tenggarong, so that the first hypothesis in this study was accepted. The three free variables, namely intellectual intelligence, emotional intelligence, and spiritual intelligence, simultaneously have a meaningful (real) effect on employee performance in retail business organizations (case study at eramart store in Timbau sub-district, Tenggarong, Indonesia). The three free variables were able to explain changes in employee performance by 84.2% (Adjusted R square = 0.842) while the remaining 15.2% was influenced by other variables that were not included in this study such as career development, compensation, work stress. From the three results of the t test above, the partial correlation value of the spiritual intelligence variable is the largest compared to the intellectual intelligence and emotional intelligence variables, which is 0.617 or 61.7%, From this description, it can be concluded that spiritual intelligence is the intelligence we use to access our deepest meanings, values, goals, and highest motivations. Spiritual intelligence is our moral intelligence, which gives us an innate ability to distinguish between right and wrong. Spiritual intelligence is the intelligence we use to create goodness, truth, beauty and compassion in our lives. The spiritual intelligence of Eramart Timbau Tenggarong minimarket employees is likely to be largely influenced by the proximity of mosque facilities near the Eramart Timbau Tenggarong minimarket and most of them live close to the mosque/musholla, so that most employees rarely miss prayer time when working when the time comes.
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Статья научная
The study determined the effects of concept mapping and guided discovery instructional strategies on student’s learning achievement in Redox concept in Chemistry in Oyo State, Nigeria. The pretest-posttest control group quasi experimental design with 3x2 factorial matrix was adopted, while six schools with one intact class each; two each for experimental groups and two for control group were used. A total of 176 senior secondary school 2 Chemistry students participated in the study. A validated Chemistry Student Achievement Test (r = 0.77) was used for data collection, while Analysis of covariance and Bonferroni post hoc were used to analyze the data collected at 0.05 level of significance. There was a significant main effect of treatment (F(2, 175) =11.84; p<0.05, partial η2 = 0.13) on student’s achievement. The participants in concept mapping strategy obtained the highest post achievement mean score (12.71), followed by guided discovery instructional strategy (9.24) and conventional strategy (8.60) groups. There was no significant main effect of gender on student’s achievement. There was no significant two- way interaction effect of treatment and gender on student’s achievement in Redox concept of chemistry. Concept mapping and guided discovery instructional strategies enhanced student’s achievement in Redox concept of chemistry. It is therefore recommended that chemistry teachers should adopt these strategies to improve student’s achievement in Chemistry.
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Статья научная
The study sought to investigate the effects of network infrastructure challenges on open ICT infrastructure sharing by Mobile Service Providers in Kenya. Specifically, the study investigated network sharing challenges as the main determinants to open ICT infrastructure sharing by Mobile Service Providers in Kenya. The empirical literature revealed that Open ICT Infrastructure sharing can substantially reduce capital and operational expenditure thereby increasing the speed of network rollouts, improve coverage and help meet the capacity demands of increased data traffic. Other reviews revealed that each sharing environment is different and may have pressures and priorities that change throughout the process of establishing a partnership between two operators with a view to developing a framework for Open ICT infrastructure sharing. Data was collected from employees from Safaricom, Airtel and Orange in order to study the population. A target population of 800 employees from the three Mobile Service Providers in Kenya was considered. Both Stratified and purposive sampling techniques were used to identify the respondents. A sample size of 86 respondents was used in this study using both structured questionnaires and scheduled interviews. Both descriptive and inferential statistics were used to analyse data collected from respondents in this study. Network service control and Coverage, Network growth and Experience and Resources were identified as the main challenges facing Network sharing by Mobile Service Providers. It is hoped that the results obtained from this study will be beneficial to stakeholders in Mobile Service industry formulate policies that promote ICT Infrastructure sharing with a view to promoting universal access and saving on expenditures.
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Статья научная
Electronic passports have known a wide and fast deployment all around the world since the International Civil Aviation Organization the world has adopted standards whereby passports can store biometric identifiers. The use of biometrics for identification has the potential to make the lives easier, and the world people live in a safer place. The purpose of biometric passports is to prevent the illegal entry of traveler into a specific country and limit the use of counterfeit documents by more accurate identification of an individual. The paper analyses the face, fingerprint, palm print and iris biometric e-passport design. The paper also provides a cryptographic security analysis of the e-passport using face fingerprint, palm print and iris biometric that are intended to provide improved security in protecting biometric information of the e-passport bearer.
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Статья научная
In this paper, we have focused on the data mining technique on market data to establish meaningful relationships or patterns to determine the determinate critical factors of commodity price. The data is taken from Ethiopia commodity exchange and 18141 data sets were used. The dataset contains all main information. The hybrid methodology is followed to explore the application of data mining on the market dataset. Data cleaning and data transformation were used for preprocessing the data. WEKA 3.8.1 data mining tool, classification algorithms are applied as a means to address the research problem. The classification task was made using J48 decision tree classification algorithms, and different experimentations were conducted. The experiments have been done using pruning and unpruning for all attributes. The developed models were evaluated using the standard metrics of accuracy, ROC area. The most effective model to determine the determinate critical factors for the commodity has an accuracy of 88.35% and this result is a good experiment result.
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Статья научная
The Electronic Fiscal Device (EFD) Machines have been operating in Tanzania since the year 2010 for the purpose of helping the Tanzania Revenue Authority (TRA) to increase revenues from tax collection. Regard-less of years of its existence, there are still reported cases of tax evasion, and this study was conducted to review the current tax collection system and analyze require-ments for the development of Stock Tracking Module (STM) to be embedded in the current tax collection sys-tem. This paper earmarked some problems relating to Electronic Fiscal Device Machine Management System (EFDMS) and EFD machine. Data collection was done in Kilimanjaro and Arusha, the two regions of Tanzania that involved tax officers and Information Technology (IT) personnel from TRA and drug traders. Data collection process involved both qualitative and quantitative methods to gather data for the development of the system Stock Tracking Module (STM) such as interview, questionnaire, role-playing and observation. The major findings of the study: The efficiency of the EFDMS is at average, thus, need some improvements. The major problems encountered by TRA are; under declaration of sales by traders, non-usage of EFD machines, usage of fake EFD, overestimate of expenses, division of business and conducting business in unknown areas. The proposed solution will reduce the existing challenges and increase revenue collections, reduce manual work and human resource, and improve accuracy on tax estimation process.
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Emotion Recognition System Based On Skew Gaussian Mixture Model and MFCC Coefficients
Статья научная
Emotion recognition is an important research area in speech recognition. The features of the emotions will affect the recognition efficiency of the speech recognition systems. Various techniques are used in identifying the emotions. In this paper a novel methodology for identification of emotions generated from speech signals has been addressed. This system is proposed using Skew Gaussian mixture model. The proposed model has been experimented over a gender independent emotion database. In order to extract the features from the speech signals cepstral coefficients are used. The developed model is tested using real-time speech data set and also using the standard and data set of Berlin. This model is evaluated in the presence of noise and without noise the efficiency of the model is evaluated and is presented by using confusion matrix.
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