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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: 642
Статья научная
In this research, an artificial chattering free adaptive fuzzy modified sliding mode control design and application to continuum robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy logic controller and online tuning method, the output improves. Each method by adding to the previous controller has covered negative points. The main target in this research is design of model free estimator on-line sliding mode fuzzy algorithm for continuum robot manipulator to reach an acceptable performance. Continuum robot manipulators are highly nonlinear, and a number of parameters are uncertain, therefore design model free controller by both analytical and empirical paradigms are the main goal. Although classical sliding mode methodology has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. To solve the chattering fuzzy logic inference applied instead of dead zone function. To solve the equivalent problems in classical sliding mode controller this paper focuses on applied on-line tuning method in classical controller. This algorithm works very well in certain and uncertain environment. The system performance in sliding mode controller is sensitive to the sliding function. Therefore, compute the optimum value of sliding function for a system is the next challenge. This problem has solved by adjusting sliding function of the on-line method continuously in real-time. In this way, the overall system performance has improved with respect to the classical sliding mode controller. This controller solved chattering phenomenon as well as mathematical nonlinear equivalent part by applied modified PID supervisory method in modified fuzzy sliding mode controller and tuning the sliding function.
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Assessing Similarity between Software Requirements: A Semantic Approach
Статья научная
The majority of projects fail to achieve their intended objectives, according to research. This could arise for a number of reasons, such as ensuring requirements are managed, excessive documentation of the code, or the difficulty in delivering software that includes all the requested features on time. An effort could be made to overcome such failure rates by establishing a proper management of requirements and concept of reusability. The correct requirements can be identified by checking similarity between the requirements received from the various stakeholders. A reusable software component can result in substantial savings in both time and money. It can be challenging to make a choice regarding the reuse of certain software components. A comparison of the requirements of a new project with those of previous projects prior to starting a new project or even at a later stage during development is useful for identifying reusable components. This paper proposes a framework (ReSim) for identifying software requirements' similarities, in an attempt to improve reusability and identify the correct requirements. A crucial component of ReSim is to measure similarity between software requirements. Different well-known similarity measurement techniques used by the researchers to evaluate the similarity between the software requirements. Some of the methods used to measure this include dice, jaccard, and cosine coefficients, but in this paper, we have used recently developed hybrid method which considers not only semantic information including lexical databases, word embeddings, and corpus statistics, but also implied word order information and produced significant improvements in the results related to the measurement of semantic similarity between words and sentences. As part of the experiments, the study used PURE dataset - in order to demonstrate the efficacy of the proposed framework. As a result, recently developed hybrid method of measuring the requirements similarity is more accurate than Dice, Jaccard, and Cosine, while Cosine is a better choice than Dice, and Jaccard is more accurate than Dice. Thus, ReSim outperforms existing approaches when tested on the PURE dataset, providing the most accurate results for both functional and non-functional requirements.
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Assessing the Behaviour of Web Services using Finite States
Статья научная
Web service are the technology of a choice when developing business applications that needs to be loosely coupled, platform independent and capable to cross enterprise boundaries. The interactions that occur between web services need to be captured because such interactions would be very useful if captured using appropriate structures and analyzed for various purposes such as assessing the responsiveness of a web service to complete peer's requests. Since the invocations of web services (WS) are dynamic, the behaviour of the WS will be dynamic depending on how the invocations discover, and get serviced by WSs. For this reason if the states of the behaviour of a WS can be captured and assessed, then tuning the WS and its performance improvement can be engineered at any stage. This work is presented in this paper.
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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
Статья научная
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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