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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
Assessing the Importance of Attributes for Diagnosis of Diabetes Disease
Статья научная
Diabetes is a chronic, metabolic disease related to the rise of levels of blood glucose. According to the current data from the World Health Organization, 422 million adults have diabetes in the world and prevalence of diabetes is 13.2%. Disregarding the diagnosis and treatment of the disease leads to some major problems on kidneys, heart and blood vessels, eyes, nerves, pregnancy and wound healing. The most common type of diabetes and usually in adults, Type 2 diabetes occurs when the body becomes resistant to insulin or does not make enough insulin. The main objective of this study is to make more successful this disease by investigating the important attributes based on assessing the importance of attributes using the Stability Selection method. The proposed method might be a powerful tool for the importance of attributes, and effective diagnosis of this disease with the classification accuracy is 78.57% and ROC value is 0.75.
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Статья научная
Software development always faces unexpected events such as technology changes, environmental changes, changing user needs. These changes will increase the risk in software projects. We need to risk management to deal with software risks. Risk assessment is one of the most important factors in risk and project management of software projects. In this paper, we use Wallace’s work and five factors to present an efficient method to measure software risk using fuzzy logic. Team, Planning, Complexity, Requirements and User are factors that we use in this paper. Results of experiments shows that our framework is more efficient than other frameworks and approaches for risk assessment in software projects.
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Статья научная
Path-loss propagation models are useful in radio communications for the prediction of signal’s coverage area, link’s design and power budget. They are equally used for radio channel characterization to accurately predict television coverage, interference analysis and ensure coexistence between the primary service providers and secondary users (through frequency re-use). One of the challenges with the application of a predictive path loss model for any environment other than the one it was developed for is the issue of high prediction errors. This is due to their high dependence on environmental complexity and terrain. In this paper, we investigated the error bounds of eight empirical path loss models to evaluate their reliability of predicting path losses on the UHF band in Ekiti State, South West Nigeria. Measurement of the signal strength for the UHF channel 41 (631.25MHz), Television Broadcasting Station at Ado-Ekiti, was carried out via major routes spanning through the Urban and Suburban areas of the State, using the station as reference. The signal strength values were converted to path losses and compared with predictions of eight selected models. The prediction error, relative error, root mean square error (RMSE), spread corrected mean square error (SC-RMSE), skewness and the normalized error probability density function metrics was calculated to determine the error bound which was used to validate the best predictive model for the routes under consideration. The results of this investigation show that no single model gives an accurate prediction consistently based on the evaluating metrics. However, the Electronic Communication Committee (ECC) 33 model provides better values for the overall metrics considered with RMSE values of 8.48 dB and 9.62 dB (between it and measured values) for Ekiti Suburban and Urban routes respectively. Therefore, optimizing ECC 33 model will bring the RMSE values to the standard acceptable range for both sub - urban and urban routes. The significance of this finding is that ECC 33 model has the least prediction error compared to other selected models and by extension the closest value to the measured values. This validates it to be suitable for the prediction of path losses on the UHF band over the study area.
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Статья научная
Knowledge management is one of the contemporary developments that ensure today’s institutions generate, distribute and apply knowledge to help in administrative decision making, encourage creativity, increasing competitiveness and improving their performance. The study aimed to identify the degree of application of knowledge management concept in Sudanese banks, "Case study: Commercial Farmer's Bank". The study focuses on knowledge management and the statistical differences related to gender, age, academic qualification and period of service at the bank. To achieve the aim of the study, the descriptive analytical approach was used. The research relied on the questionnaire as the main tool for data collection. The study population consisted of bank employees in their various positions. A total of 60 questionnaires were distributed, of which 58 were returned for statistical analysis. The results of the study followed standard methodology based on the state of the arts researches. The study found that the degree of application of knowledge management was medium in the field of knowledge creation and acquisition, reaching 68% and high in the field of knowledge storage 74%, knowledge sharing 76% and knowledge application 77%. The results also showed that there were no statistical differences related to gender, age, academic qualification and period of service.
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Статья научная
With the rapid advancement in technology, smart homes have become applicable and so the need arise to solve the security challenges that are accompanied with its operation. Passwords and identity cards have been used as traditional authentication mechanisms in home environments, however, the rise of misuse of these mechanisms are proving them to be less reliable. For instance, ID cards can be misplaced, copied or counterfeited and being misused. Conversely, studies have shown that biometrics authentication systems particularly Iris Recognition Technology (IRT) and Fingerprint Recognition Technology (FRT) have the most reliable mechanisms to date providing tremendous accuracy and speed. As the technology becomes less expensive, application of IRT& FRT in smart-homes becomes more reliable and appropriate solution for security challenges. In this paper, we present our approach to design an authentication system for smart homes based on IRT, FRT and ARM7TDMI-S.The system employs two biometrics mechanisms for high reliability whereby initially, system users must enroll their fingerprints and eyes into the camera. Iris and fingerprint biometrics are scanned and the images are stored in the database. In the stage of authentication, FRT and IRT fingerprint scan and analyze points of the user's current input iris and fingerprint and match with the database contents. If one or more captured images do not match with the one in the database, then the system will not give authorization.
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Automated agricultural field analysis and monitoring system using IOT
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Smarter world is the resultant of the smarter technology. Agriculture was implemented in the nine of sedentary human civilization and it is the backbone of our Indian Economy. But the same traditional techniques like manual field monitoring, water feeding, pest detection, soil testing, etc., we are using for monitoring the field and frequently applying pesticides with or without having the knowledge of quantity to be used to control pests that affect the crops. So it is very important to enhance the agricultural production by making use of technology to overcome the damages being done. Our aim is to provide smart monitoring system using the current technologies like IoT, cloud computing and image processing. To address the above problems the authors of this paper are coming up with a model named “AAFAMS”( Automated Agricultural Field Analysis and Monitoring System Using IOT) which is used not only for monitoring the field but also to suggest the farmers about the moisture content in soil, detecting pest and the type of crop suited for the soil. In AAFAMS, a line follower robot is developed by using a hardware kit called Raspberry pi, which monitors the soil moisture level at every 100m distance using a soil moisture sensor and the information obtained from the sensor will be sent to cloud for storage. A camera will be connected to the AAFAMS which will detect the pests. After complete survey of field AAFAMS retrieves all stored data from cloud and SQLite database to provide a detailed report of Moisture content and Pests information and suggests farmer with the required pesticide. AAFAMS runs either on batteries or solar panel by utilizing the solar energy available and thereby helping farmers to monitor their fields effectively.
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Статья научная
In this paper the results are evaluated on a conventional modulation system. Here the system of communication is presented by modeling and analysis and the results so calculated are presented. The approach made in this paper is solely based on initial description which includes a combinational approach of spatial diversity well represented by OSTBC (Orthogonal Space Time Block Codes) encoder and combiner. Next the system of OSTBC encoder and combiner are put together in a MIMO(Multiple Input Multiple Output) channel using Rayleigh and Rician channel coupled with white Gaussian channel. In modeling of such systems interleavers and encoders are also used that helps to identify the performance with simple model without these techniques. In overall system the methodical approach using Multiple Input Multiple Output antenna with the modulator, encoder and interleaver is analyzed and the resultant bit error rate has been identified. The simulation platform is MATLAB and SIMULINK in which communication block sets are used. Alamouti's and 4x4 MIMO antennas are used and hence performance so evaluated is delivered. Best results are found when number of antennas increases using Interleaver and modulation or only with modulation techniques.
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Barriers to E-Commerce Adoption in Egyptian SMEs
Статья научная
E-commerce has been predicted to be a new driver of economic growth for developing countries. The SME sector plays a significant role in its contribution to the national economy in terms of the wealth created and the number of people employed. Small and Medium Enterprises (SMEs) in Egypt represent the greatest share of the productive units of the Egyptian economy and the current national policy directions address ways and means of developing the capacities of SMEs. Many factors could be responsible for the low usage of e-commerce among the SMEs in Egypt. In order to determine the factors that promote the adoption of e-commerce, SMEs adopters and non-adopters of e-commerce were asked to indicate the factors inhibiting the adoption of e-commerce. The results show that technical barriers are the most important barriers followed by legal and regulatory barriers, whereas lack of Internet security is the highest barrier that inhibit the implementation of e-commerce in SMEs in Egypt followed by limited use of Internet banking and web portals by SMEs. Also, findings implied that more efforts are needed to help and encourage SMEs in Egypt to speed up e-commerce adoption, particularly the more advanced applications.
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Bengali News Headline Categorization Using Optimized Machine Learning Pipeline
Статья научная
Bengali text based news portal is now very common and increasing day by day. With easy access of internet technology, reading news through online is now a regular task. Different types of news are represented in the news portal. The system presented in this paper categorizes the news headline of news portal or sites. Prediction is made by machine learning algorithm. Large number of collected data are trained and tested. As pre-processing tasks such as tokenization, digit removal, removing punctuation marks, symbols, and deletion of stop words are processed. A set of stop words is also created manually. Strong stop words leads to better performance. Stop words deletion plays a lead role in feature selection. For optimization, genetic algorithm is used which results in reduced feature size. A comparison is also explored without optimization process. Dataset is established by collecting news headline from various Bengali news portal and sites. Resultant output shows well performance in categorization.
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Bi-gram based Query Expansion Technique for Amharic Information Retrieval System
Статья научная
Information retrieval system has been using to connect users of the information and information repository corpora. Even though the task of information retrieval systems is to retrieve relevant information, it is very difficult to find a perfect information retrieval system which is capable of retrieving relevant and only relevant documents as per user's query. The aim of this research is to increase precision of an Amharic information retrieval system while preserving the original recall. In order to achieve this bi-gram technique has been adopted for the query expansion. The main reason for performing query expansion is to provide relevant documents as per users' query that can satisfy their information need. Because users are not fully knowledgeable about the information domain area, they mostly formulate weak queries to retrieve documents. Thus, they end up frustrated with the results found from an information retrieval system. Amharic language has many meaning for a single word and also the word can be found in different form. These are some of the challenges that made the information retrieval system performing at very low level. Query expansion methods outperform in differentiating the various meanings of a polysemous term and find synonymous terms for reformulating users' query. Bi-gram technique uses the underling theory of expanding a query; using terms that appear adjacent to a query term frequently. The proposed technique was integrated to an information retrieval system. Then the retrieval system is tested with and without using bi-gram technique query expansion. The test result showed that bi-gram based method outperformed the original query based retrieval, and scored 8% improvement in total F-measure. This is an encouraging result to design an applicable search engine, for Amharic language.
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Big data optimization techniques: a survey
Статья научная
As the world is getting digitized the speed in which the amount of data is over owing from different sources in different format, it is not possible for the traditional system to compute and analysis this kind of big data for which big data tool like Hadoop is used which is an open source software. It stores and computes data in a distributed environment. In the last few years developing Big Data Applications has become increasingly important. In fact many organizations are depending upon knowledge extracted from huge amount of data. However traditional data technique shows a reduced performance, accuracy, slow responsiveness and lack of scalability. To solve the complicated Big Data problem, lots of work has been carried out. As a result various types of technologies have been developed. As the world is getting digitized the speed in which the amount of data is over owing from different sources in different format, it is not possible for the traditional system to compute and analysis this kind of big data for which big data tool like Hadoop is used which is an open source software. This research work is a survey about the survey of recent optimization technologies and their applications developed for Big Data. It aims to help to choose the right collaboration of various Big Data technologies according to requirements.
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Статья научная
Sentiment analysis, the process of determining the emotional tone of a text, is essential for comprehending user opinions and preferences. Unfortunately, the majority of research on sentiment analysis has focused on reviews written in English, leaving a void in the study of reviews written in other languages. This research focuses on the understudied topic of sentiment analysis of Bangla-language product reviews. The objective of this study is to compare the performance of machine learning models for binary and multiclass sentiment classification in the Bangla language in order to gain a deeper understanding of user sentiments regarding e-commerce product reviews. Creating a dataset of approximately one thousand Bangla product reviews from the e-commerce website 'Daraz', we classified sentiments using a variety of machine learning algorithms and natural language processing (NLP) feature extraction techniques such as TF-IDF, Count Vectorizer with N-gram methods. The overall performance of machine learning models for multiclass sentiment classification was lower than binary class sentiment classification. In multiclass sentiment classification, Logistic Regression with bigram count vectorizer achieved the maximum accuracy of 82.64%, while Random Forest with unigram TF-IDF vectorizer achieved the highest accuracy of 94.44%. Our proposed system outperforms previous multiclass sentiment classification techniques by a fine margin.
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Bioinformatics Analysis and Characteristics of the giant panda Interferon-alpha
Статья научная
In this report, the amino acid sequence of giant panda interferon-α (gpIFN-α) was determined and compared with 15 corresponding IFN-α sequences. Phylogenetic analysis showed that the 15 interferons fell into two large groups. The giant panda and ferret branched and were most closely related to fox and dog and evolved into a distinct phylogenetic lineage from that of eukaryotic mammalians which evolved into another lineage. After analyzing the encoded amino acid sequence of the gpIFN-α using bioinformatics, the results revealed that in the full amino acid sequence, there were no transmembrane domain, one N-glycosylation sites, eight O-glycosylation sites and nine antigenic determinants. Secondary structure analyzed showed that the Alpha helix, Extended strand, Beta turn and Random coil each occupied 60.37%(99aa), 4.88%(8aa), 9.76%, 25%(41aa) respectively. In conclusion, our results will give the opportunity to investigate more in detail function study in giant panda and add to studies on the evolution of the IFN system in vertebrates and avian more generally.
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Blockchain and IFPS based Secure System for Managing e-FIR
Статья научная
In recent times, various forms of crime have been happening worldwide. The law-and-order department of any country officially records a crime in electronic forms or on paper when the crime is reported by a victim or someone on behalf of the victim. The document that is prepared to file any perceptible committed crimes including dowry, kidnap, murder, rape, theft, and others is called First Information Report(FIR). Nowadays, online FIR also known as e-FIR has been used worldwide. Every day a number of e-FIR are filed, and they are maintained in a centralized database with the aid of third-party trust. Consequently, malicious entities including insiders and outsiders’ dishonest personnel, and third-party authorities may tamper with e-FIR that questions the transparency and integrity of FIR reports. To address this exposure, in this paper, we propose a blockchain based FIR system to store all kinds of offense-related records to assure security, fidelity and privacy of FIR records. In this proposed system, the blockchain technology that refers to a decentralized and distributed ledger across peer-to-peer networks continually updates the shared ledger and strictly maintains synchronization among all network nodes. Though blockchain technology guarantees tamper-proof of the data, it cannot store a large amount of data due to the replication of ledger among all network nodes. To solve this issue, we adopt the Inter-Planetary File system (IPFS) protocol to store data in the blockchain. IPFS is a distributed file-sharing system that can be leveraged to store and share large files. The blockchain based FIR system has been tested on an Ethereum environment using blockchain and IPFS technology.
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Body and Face Animation Based on Motion Capture
Статья научная
This paper introduces the motion capture technology and its use in computer animation. Motion capture is a powerful aid in computer animation and a supplement to the traditional key-frame animation. We use professional cameras to record the body motion and facial expression of the actor and then manipulate the data in software to eliminate some occlusion and confusion errors. As to data that is still not satisfying, we use data filter to smooth the motion by cutting some awry frames. Then we import the captured data into Motionbuilder to adjust the motion and preview the real-time animation. At last in Maya we combine the motion data and character model, let the captured data drive the character and add the scene model and music to export the whole animation. In the course of computer animation, we use this method to design the animation of military boxing, basketball playing, folk dancing and facial expression.
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Boosting Afaan Oromo Named Entity Recognition with Multiple Methods
Статья научная
Named Entity Recognizer (NER) is a widely used method of Information extraction (IE) in Natural language processing (NLP) and Information Retrieval (IR) aimed at predicting and categorizing words of a given text into predefined classes of Named Entities like a person, date/time, organization, location, etc. This paper adopts boosting NER for Afaan Oromo by using multiple methods. Combinations of approaches such as machine learning, the stored rules, and pattern matching make a system more efficient and accurate to recognize candidates name entities (NEs). It takes the strongest points from each method to boost the system performance by voting a candidate NE which is detected in more than 1 entity category or out of context because of word ambiguity, it penalized by Word senses disambiguation. Subsequent NEs tagged with identical tags merged as a single tag before the final output. The evaluation shows the system is outperformed. Finally, the future direction is forwarded a hybrid approach of rule-based with unsupervised zero-resource cross-lingual to enhance more.
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Building Consumers' Trust Based on Pick-up Goods Behavior in the Convenience Stores in Taiwan
Статья научная
With the adoption of Internet, online shopping has provided a convenience way to purchase goods or services from anywhere at any time in recent years globally. Especially, convenience stores are available for consumers to pick up goods ordered from Internet shops in Taiwan. Therefore, convenience stores have become an important success factor for increasing a lot of profit in online shopping in Taiwan. In the past, researches have indicated that consumers dare not or are not willing to purchase goods in online shopping. The reasons include the problem of security and the lack of consumers’ trust. Thus, these problems constitute a key barrier to the use of online shopping as well as long-term commitment to the relationship building. Therefore, there is a need to build up consumers’ trust in order to overcome the influential factors in online shopping. In this paper, we use statistic analysis method by questionnaires to discuss the characteristics of pick-up goods in the convenience stores and illustrate the relationship between consumers’ trust in online shopping and pick-up goods behavior in convenience stores. In our experiment, questionnaire items are measured by Likert scale. In 227 valid questionnaires, 90% participants deeply believe that pick-up goods in the convenience stores can promote consumers’ trust in online shopping.
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Business Process Re-Engineering in Public Administration of Kingdom of Saudi Arabia
Статья научная
The government of Saudi Arabia is in the phase of transformation. Business process reengineering (BPR) can play a vital role in assessing this conversion. BPR methodologies provide ways to optimize the use of resources while maintaining high-quality services. The aim of this paper is to investigate the introduction of BPR in Saudi Arabia public sector. A framework is proposed to transform change using a knowledge based. The proposed solution is validated through survey. The results of the survey show that Saudi Governmental Agencies acquire the power to implement the BPR successfully especially if it is implemented with knowledge management and the BPR movement started at small scale.
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Business decision support system based on sentiment analysis
Статья научная
Since organizational decisions are vital to organizational development, customers’ views and feedback are equally important to inform good decisions. Given this relevance, this paper seeks to automate a sentiment analysis system - SentDesk- that can aid tracking sentiments in customers’ reviews and feedback. The study was contextualised in some business organisations in Ghana. Three business organizational marketers were made to annotate emotions and as well tag sentiments to each instance in the corpora. Kappa and Krippendoff coefficients were computed to obtain the annotation agreement in the corpora. The SentDesk system was evaluated in the environment alongside comparing the output to that of the average sentiments tagged by the marketers. Also, the SentDesk system was evaluated in the environment by the selected marketers after they had tested the platform. By finding the average kappa value from the corpora (CFR + ISEAR), the average kappa coefficient was found to be 0.40 (40%). The results of evaluating the SentDesk system with humans shows that the system performed as better as humans. The study also revealed that, while annotating emotions and sentiments in the datasets, counsellor’s own emotions influences their perception of emotions.
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CSRFDtool: Automated Detection and Prevention of a Reflected Cross-Site Request Forgery
Статья научная
The number of Internet users is dramatically increased every year. Most of these users are exposed to the dangers of attackers in one way or another. The reason for this lies in the presence of many weaknesses that are not known for ordinary users. In addition, the lack of user awareness is considered as the main reason for falling into the attackers' snares. Cross Site Request Forgery (CSRF) has placed in the list of the most dangerous threats to security in OWASP Top Ten for 2013. CSRF is an attack that forces the user's browser to send or perform unwanted request or action without user awareness by exploiting a valid session between the browser and the server. When CSRF attack success, it leads to many bad consequences. An attacker may reach private and personal information and modify it. This paper aims to detect and prevent a specific type of CSRF, called reflected CSRF. In a reflected CSRF, a malicious code could be injected by the attackers. This paper explores how CSRF Detection Extension prevents the reflected CSRF by checking browser specific information. Our evaluation shows that the proposed solution is successful in preventing this type of attack.
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