- Все статьи 584
Статьи журнала - International Journal of Information Engineering and Electronic Business
Все статьи: 584
Analysis on Shape Image Retrieval Using DNN and ELM Classifiers for MRI Brain Tumor Images
Статья научная
The problem of searching a digital image in a very huge database is called Content Based Image Retrieval (CBIR). Shape is a significant cue for describing objects. In this paper, we have developed a shape feature extraction of MRI brain tumor image retrieval. We used T1 weighted image of MRI brain tumor images. There are two modules: feature extraction process and classification. First, the shape features are extracted using techniques like Scale invariant feature transform (SIFT), Harris corner detection and Zernike Moments. Second, the supervised learning algorithms like Deep neural network (DNN) and Extreme learning machine (ELM) are used to classify the brain tumor images. Experiments are performed using 1000 brain tumor images. In the performance evaluation, sensitivity, specificity, accuracy, error rate and f-measure are five measures are used. The Experiment result shows that highest average accuracy has got at Zernike Moments– 99%. So, Zernike Moments are better than SIFT and Harris corner detection techniques. The average time taken for DNN- 0.0901 sec, ELM- 0.0218 sec. So, ELM classifier is better than DNN. It increases the retrieval time and improves the retrieval accuracy significantly.
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Android Based Forest Fire Monitoring System
Статья научная
Forest fires are burning areas of forest or land in large or small areas. Forest fires are often uncontrollable and when this happens, the fire will burn anything nearby for two reasons, one of which is burning naturally or burning caused by humans. One of the man-made fires deliberate by humans is the burning used by the community around the forest to open or clear agricultural or plantation land. The community feels that clearing land with fire does not require a long time and is more economical, if the use of fire is not used properly it can cause the forest to burn. Forest fires in Riau area are still classified as minimal or fires rarely occur. However, the community is at least aware of the forest fires in Riau due to a lack of media information about where the fire hotspots occurred. With this application, it can help the public to better know where the hotspots have been burned. This application consists of 2 levels of access, namely: admin and user. For admins and users, the manufacturing process uses the Android Studio application with Java as the programming language, this application uses Firebase as its database to find out the location of fire hotspots using the Google Maps API. Testing on the application is created to test whether the application has run as desired. Test results using white box testing method.
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Application of Biometric Security in Agent based Hotel Booking System - Android Environment
Статья научная
The process of finding the finest hotel in central location is time consuming, information overload and overwhelming and in some cases poses a security risk to the client. Some of the more advanced web sites allow for a search of the destination via a map for example hotelguidge.com and jamaica.hotels.hu. Booking of hotels is secured by the standard Secure Sockets Layer (SSL) to confirm the identity of a website or server, encrypt data during transmission, and ensure the integrity of transmitted data. Even with this in place, hackers have broken the Secure Sockets Layer (SSL) by targeting weaknesses in the MD5 algorithm. Recently good amount of work been carried in the use of Intelligent agents towards hotel search on J2ME based mobile handset which still has some weakness. So taking the weakness in the current agent based system, smart software agents been developed that overcomes the weakness in the previous system In addition to smart agent based system been developed and published elsewhere, we here propose to extend the system with the booking capability that allows the user to book a hotel of choice where the authenticity of the client may be determined securely using biometric security and information transmitted using Secure Sockets Layer (SSL) (Server-Gated Cryptography (SGC)) on the internet which is novel and unique. This will be facilitated on Android 2.2-enabled mobile phone using JADE-LEAP Agent development kit.
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Application of Data Mining Techniques in Weather Prediction and Climate Change Studies
Статья научная
Weather forecasting is a vital application in meteorology and has been one of the most scientifically and technologically challenging problems around the world in the last century. In this paper, we investigate the use of data mining techniques in forecasting maximum temperature, rainfall, evaporation and wind speed. This was carried out using Artificial Neural Network and Decision Tree algorithms and meteorological data collected between 2000 and 2009 from the city of Ibadan, Nigeria. A data model for the meteorological data was developed and this was used to train the classifier algorithms. The performances of these algorithms were compared using standard performance metrics, and the algorithm which gave the best results used to generate classification rules for the mean weather variables. A predictive Neural Network model was also developed for the weather prediction program and the results compared with actual weather data for the predicted periods. The results show that given enough case data, Data Mining techniques can be used for weather forecasting and climate change studies.
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Application of Krill Herd and Water Cycle Algorithms on Dynamic Economic Load Dispatch Problem
Статья научная
Dynamic economic dispatch (DED) is a complicated nonlinear constrained optimization problem and one of the most important problems in operation of power systems. In this paper two novel optimization algorithms have been proposed to be applied on DED problem. The first method, Krill herd (KHA) is a novel meta heuristic algorithm for solving optimization problems which is based on the simulation of the herding of the krill swarms as a biological and environmental inspired method and is applied on DED problem with two configurations named KHA1 and KHA2. The second algorithm is based on how the streams and rivers flow downhill toward the sea and change back in nature, named Water Cycle (WCA) method. Two common case studies considering various constraints have been used to show the effectiveness of these methods. The results and convergence characteristics show that the proposed methods are capable of giving high quality results which are better than many other previously applied algorithms.
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Application of an integrated support vector regression method in prediction of financial returns
Статья научная
Nowadays there are lots of novel forecasting approaches to improve the forecasting accuracy in the financial markets. Support Vector Machine (SVM) as a modern statistical tool has been successfully used to solve nonlinear regression and time series problem. Unlike most conventional neural network models which are based on the empirical risk minimization principle, SVM applies the structural risk minimization principle to minimize an upper bound of the generalization error rather than minimizing the training error. To build an effective SVM model, SVM parameters must be set carefully. This study proposes a novel approach, support vector machine method combined with genetic algorithm (GA) for feature selection and chaotic particle swarm optimization(CPSO) for parameter optimization support vector Regression(SVR),to predict financial returns. The advantage of the GA-CPSO-SVR (Support Vector Regression) is that it can deal with feature selection and SVM parameter optimization simultaneously A numerical example is employed to compare the performance of the proposed model. Experiment results show that the proposed model outperforms the other approaches in forecasting financial returns.
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Architecture model of integrated Web-based e-trading business process management system
Статья научная
This paper describes development of architecture for integrated informational Web-based e-trading business process management system. An approach is justified for formation of embedded informational system architecture based on typical IT solutions. A Service Oriented Architecture (SOA) using Enterprise Service Bus (ESB) concept is offered for architectural implementation of the Web-based system. Typical informational systems that belong to the Web-system are used as services. The web-services implement SOAP protocol based on WSDL (Web Services Description Language) and UDDI (Universal Description, Discovery and Integration) specifications. Application of ESB and SOA provides scalability of Web-based e-trading management system, possibility for their enhancement and upgrading. The principle of basic architecture of Internet has been implemented in the architecture of integrated trading informational system taking into account transition to informational level.
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Area & power optimization of asynchronous processor using Xilinx ISE & Vivado
Статья научная
As the technology era has been changing, the designing pattern of an IC is also changing. An IC de-signing is now divided into two definite fields i.e. Front-End design and Back-End design. The Front-End design is using HDLs (Hardware Description Languages i.e. VHDL or Verilog) and the verification of those ICs, whereas the Back-End Design is related to the Physical Design techniques. But both of the IC design techniques required some extra efforts in terms of their Speed, Shape, and Size, which needs the Optimization efforts. This pa-per deals with the area and power optimization efforts in terms of the logic utilization by using XST & Vivado Tools. After applying area optimization techniques i.e. Logic Optimization, LUT mapping and Resource Sharing etc. on already designed asynchronous microprocessor to be used as model for proposed optimization, reasonable results in terms of power and area utilization have been achieved.
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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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