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International Journal of Information Engineering and Electronic Business @ijieeb
Статьи журнала - International Journal of Information Engineering and Electronic Business
Все статьи: 626
Статья научная
Employee Performance Assessment is a part of the Decision Support System. One of the decision support system methods that are most used in performance assessment is Simple Additive Weighting (SAW). In the SAW method, each criterion has a weight value to show the interest level. The determination of the criteria on the SAW method is subjective and the final result is on the ranked system and creates many problems. The study utilizes the Weighted Performance Indicators (WPI) method to solve the problems in the SAW method. The criterion is determined based on the respondent's opinion so that it will be more realistic to achieve the target. The population of the study is the employee of Indo Global Mandiri University which reach 30 persons. WPI method consists of 9 steps. The research result is shown that 4 employees has a performance below MSV and 36 employee has above MSV. The general value of the employee performance value = is 0.69. It shows that the performance of the employee at Indo Global Mandiri University is good enough. However, it needs to be increased, so that the target could be achieved. WPI method is easy to implement, it is not just limited to the employee performance assessment only, but it could be implemented for the other performance assessment, for example, human resource performance, finance, company, industry, system, etc.
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Development of a hybridized diversity combiner over nakagami fading channel
Статья научная
Wireless communication system is of paramount importance in the world of telecommunication infrastructure and is expected to be a leading role in the development of a nation. However, the system is characterized by multipath propagation effects that lead to variability of the received signal thereby degrading the performance. Equal Gain Combiner (EGC) being used to address this problem is associated with hardware complexity that results in long processing time, while Threshold Combiner (TC) with low processing time has poor performance. Hence, in this paper, a hybridized Diversity Combiner (DC) consisting of EGC and TC, (TC-EGC) with a closed form expression over Nakagami fading channel is developed. TC-EGC is derived using the conventional EGC and TC at the receiver. Randomly generated bits used as source data are modulated using M-ary Quadrature Amplitude Modulation (M-QAM) and transmitted over Nakagami channel after filtering. The faded signals generated at varying paths ‘L’ (2, 3, 4) are scanned by TC to select the strongest paths. The outputs from the three TCs are combined by EGC to obtain the received signal which is converted to baseband through demodulation. A mathematical expression using the Probability Density Function (PDF) of Nakagami fading channel at varying paths ‘L’ for Outage Probability (OP) is also derived. The technique is simulated using Matrix Laboratory (version 7.2). The performance is evaluated using Signal-to-Noise Ratio (SNR), Outage Probability (OP) and Processing Time (PT). The study shows that the TC-EGC gives lower OP and PT values when compared with conventional EGC and TC, with reduction in hardware complexity. The TC-EGC developed can be used to enhance the performance of wireless communication system.
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Development of a mobile-based hypertension risk monitoring system
Статья научная
Hypertension is a silent killer, which gives no warning signs to alert a patient and can only be detected through regular blood pressure check¬ups. Uncontrolled and unmonitored hypertension contributed to stroke, chronic kidney disease, eye problem, and heart failure. It is an ongoing challenge to health care systems worldwide. Early detection of hypertension and creating awareness will greatly reduce the effect of hypertension and its related diseases. Also, having a mobile-based system will help patients to know their status, relate with Doctor and enjoy the quick response from the Doctor on hypertension diagnostic effect on their health. The mobile application will help in monitoring patients anytime, anywhere and provide services for each patient based on their personal health condition. The mobile application was designed using unified modeling language and implemented using the Extensible Mark-Up Language and Java programming language for the mobile layout and content, while JavaScript Object Notation was used to implement the data storage and retrieval mechanism of the system. The system was tested using data collected from hospital, which yielded an accuracy of 100%. In conclusion, the system will assist in providing timely, efficient, accurate and comprehensive information about hypertension, which is useful for Doctors and patients in detecting, diagnosing, classifying and managing hypertension and its risk.
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Статья научная
This paper presents an intelligent tutoring system as seen to be successful in assisting in the instruction of basic skill, particularly, reading comprehension. The goal of the study is to develop an Intelligent Tutoring System that will greatly help the Grade 7. The system adapted considerable instructional needs of learners from early development to advanced reading comprehension skills. The developed system provided an immediate feedback to learners upon completion of an activity without requiring intervention from a Teacher. To improve the system, learners and teachers filled out survey questionnaires. The result reveals that teachers and students want the system to be user-friendly, have a user log-in, lesson content with text, audio and video as well as various types of questions in quizzes. They also perceived that the developed ITS is useful and the content is valid thus is very acceptable to be utilized by the learners. In addition, result reveals that student’s reading comprehension could be improved and developed by the proposed ITS.
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Diabetes prediction: a deep learning approach
Статья научная
Nowadays, Diabetes is one of the most common and severe diseases in Bangladesh as well as all over the world. It is not only harmful to the blood but also causes different kinds of diseases like blindness, renal disease, kidney problem, heart diseases etc. that causes a lot of death per year. So, it badly needs to develop a system that can effectively diagnose the diabetes patients using medical details. We propose a strategy for the diagnosis of diabetes using deep neural network by training its attributes in five and ten-fold cross-validation fashion. The Pima Indian Diabetes (PID) data set is retrieved from the UCI machine learning repository database. The results on PID dataset demonstrate that deep learning approach design an auspicious system for the prediction of diabetes with prediction accuracy of 98.35%, F1 score of 98, and MCC of 97 for five-fold cross-validation. Additionally, accuracy of 97.11%, sensitivity of 96.25%, and specificity of 98.80% are obtained for ten-fold cross-validation. The experimental results exhibit that the proposed system provides promising results in case of five-fold cross-validation.
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Diagnostic Path-Oriented Test Data Generation by Hyper Cuboids
Статья научная
One of the ways of test data generation is using the path-oriented (path-wise) test data generator. This generator takes the program code and test adequacy criteria as input and generates the test data in order to satisfy the adequacy criteria. One of the problems of this generator in test data generation is the lack of attention to generating the diagnostic test data. In this paper a new approach has been proposed for path-oriented test data generation and by utilizing it, test data is generated automatically realizing the goal of discovering more important errors in the least amount of time. Since that some of the instructions of any programming language are more error-prone, so the paths that contain these instructions are selected for perform test data generation process. Then, the input domains of these paths variables are divided by a divide-and-conquer algorithm to the subdomains. A set of different subdomains is called hypercuboids, and test data will be generated by these hypercuboids. We apply our method in some programs, and compare it with some previous methods. Experimental results show proposed approach outperforms same previous approaches.
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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-Commerce Information System for Marketing Agricultural Products in Kutai Kartanegara Regency
Статья научная
The research aims to develop an innovative solution to address the marketing challenges faced by Kutai Kartanegara Regency, where a majority of the population is engaged in agriculture. Limited access for farmers to sell their harvests poses a significant obstacle. The proposed solution involves the implementation of a Business-to-Business (B2B) e-commerce system to enhance sales and expand marketing opportunities. In the context of global digital transformation, the integration of e-commerce is not only advantageous but also deemed a necessity. Adopting a research and development approach, the study utilizes the PHP programming language and MySQL database to create a dynamic, web-based B2B sales application. The potential broader impacts of this research extend beyond facilitating agricultural product sales; the envisioned e-commerce system holds the promise of catalyzing economic growth. By providing farmers with a platform not only for selling their products but also for engaging in strategic B2B transactions, the system becomes a driver of economic empowerment. The research incorporates insights from relevant studies emphasizing the role of e-commerce in enhancing agricultural outcomes, addressing both technological and socio-economic factors comprehensively. The research methods, including interviews, direct observations, and literature studies, reflect a holistic understanding of the challenges and needs faced by the agricultural community. The outcome is the proposed B2B e-commerce system, which has the potential to streamline processes, enhance efficiency, and broaden market reach. Use case diagrams and class diagrams serve not only as technical guides but also as visual representations of a user-friendly system, emphasizing a user-centric approach and the potential for transformative change from the main page to sales reports. The significance of this research extends beyond technological advancements; it holds the potential to redefine the socio-economic landscape of Kutai Kartanegara Regency. By empowering farmers, facilitating strategic transactions, and fostering collaboration between traditional agriculture and modern commerce, the proposed B2B e-commerce system becomes a catalyst for sustainable growth and a potential contributor to broader economic prosperity.
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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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