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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
Predicting Shelf Life of Burfi through Soft Computing
Статья научная
Soft computing cascade multilayer models were developed for predicting the shelf life of burfi stored at 30oC. The experimental data of the product relating to moisture, titratable acidity, free fatty acids, tyrosine, and peroxide value were input variables, and the overall acceptability score was the output variable. The modelling results showed excellent agreement between the experimental data and predicted values, with a high determination coefficient (R2 = 0.993499439) and low RMSE (0.006500561), indicating that the developed model was able to analyze nonlinear multivariate data with very good performance, and can be used for predicting the shelf life of burfi.
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Статья научная
A modern technology used for extracting knowledge from a huge amount of data using different models and tasks such as prediction and description is called data mining. The data mining approach has a great contribution on solving a different problem for data miners. This paper focuses on the application of data mining in health centers using different models. The model development process helps to identify or predict the behavior of blood donors whether they are eligible or ineligible to donate blood by their right status way and protects any blood bank health center from the collection of unsafe blood. Classification techniques are used for the analysis of Blood bank datasets in this study. For continuous blood donors, it will help to enable to donate voluntary individuals and organizations systematically. J48 decision tree, neural network as well as naïve Bays algorithms have been implemented in Weka to analyze the dataset of blood donors. The study is used to classify the blood donor's eligibility or ineligibility status based on their genders, deferral time, weight, age, body priced, tattoos, HIV AIDS, blood pressure, donation frequency, hepatitis, illegal drug use attributes. From the 11 attributes, gender does not affect the result. We have used 1502 datasets for the train set and 100 datasets for testing the model using cross-fold validation. Cross-fold data, partition was used in this study. The efficiency and effectiveness of the algorisms are measured automatically by the system. The obtained result showed that the J48 classifier outperforms the best result as well as both neural network and navies, Bayes, in terms of matrix evolution, with its 97.5% overall model accuracy has offered interesting rules.
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Preparing Mammograms for Classification Task: Processing and Analysis of Mammograms
Статья научная
Breast cancer is the most common cancer found in women in the world. Mammography has become indispensable for early detection of breast cancer. Radiologists interpret patients' mammograms by looking for some significant visual features for decision making. These features could have different interpretations based on expert's opinion and experience. Therefore, to solve the problem of different interpretations among experts, the use of computer in facilitating the processing and analysis of mammograms has become necessary. This study enhanced and segmented suspicious areas on mammograms obtained from Radiology Department, Obafemi Awolowo University Teaching Hospital, Ile-Ife, Nigeria. Also, Features were extracted from the segmented region of interests in order to prepare them for classification task. The result of implementation of enhancement algorithm used on mammograms shows all the subtle and obscure regions thereby making suspicious regions well visible which in turn helps in isolating the regions for extraction of textural features from them. Also, the result of the feature extraction shows pattern that will enable a classifier to classify these mammograms to one of normal, benign and malignant classes.
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Статья научная
In early 2020, the world was shocked by the outbreak of COVID-19. World Health Organization (WHO) urged people to stay indoors to avoid the risk of infection. Thus, more people started to shop online, significantly increasing the number of e-commerce users. After some time, users noticed that a few irresponsible online retailers misled customers by hiking product prices before and during the sale, then applying huge discounts. Unfortunately, the “discounted” prices were found to be similar or only slightly lower than standard pricing. This problem occurs because users were unable to monitor product pricing due to time restrictions. This study proposes a Web application named PriceCop to help customers’ monitor product pricing. PriceCop is a significant application because it offers price prediction features to help users analyse product pricing within the next day; thus, it can help users to plan before making purchases. The price prediction model is developed by using Linear Regression (LR) technique. LR is commonly used to determine outcomes and used as predictors. Least Squares Support Vector Machine (LSSVM) and Artificial Bee Colony (ABC) are used as a comparison to evaluate the accuracy of the LR technique. LSSVM-ABC was initially proposed for stock market price predictions. The results show the accuracy of pricing prediction using LSSVM-ABC is 84%, while it is 62% when LR is employed. ABC is integrated into SVM to optimize the solution and is responsible for the best solution in every iteration. Even though LSSVM-ABC predicts product pricing more accurately than LR, this technique is best trained using at least a year’s worth of product prices, and the data is limited for this purpose. In the future, the dataset can be collected daily and trained for accuracy.
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Статья научная
The present system performs analysis of snapshots of cursive and non-cursive font character text images and yields customizable text files using optical character recognition technology. In the previous versions the authors have discussed the user training mechanism that introduces new non-cursive font styles and writing formats into the system and incorporates optimization, noise reduction and background detection modules. This system specifically focuses on enhancing the process of character recognition by introducing a mechanism for handling simple cursive fonts.
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Problems of Regulation and Prospective Development of E-commerce Systems in the Post-coronavirus Era
Статья научная
The article examines the application of e-commerce systems and technologies that have a positive impact on the development of the economy of the post-coronavirus period and the formation of appropriate technical and technological infrastructure for it, as well as promising features and directions of e-commerce. The physical and virtual opportunities created by e-commerce technologies for buyers and sellers are explained. The advantages of e-commerce in the international economic space have been identified. The functions of e-business models in accordance with the commercial stages of enterprises are explained. It was noted that the development of ICT has accelerated the process of transition from traditional commerce to e-commerce, led to the emergence of new global trends in e-commerce. These innovations have raised the issue of the application of modern ICT in the development of e-commerce on the platform of the 4.0 Industrial Revolution. Taking into account these factors, the presented article discusses the application of modern technologies in e-commerce systems, such as 3D modeling, the Internet of Things, artificial intelligence, big data. Features of application and regulation mechanisms of E-commerce systems in real economic sectors, which have a direct stimulating effect on economic growth in Azerbaijan, have been studied. Recommendations were given for the modernization and use of e-commerce systems with the application of the latest ICT technologies.
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Proposal of Enhanced Extreme Programming Model
Статья научная
Extreme programming is one of the commonly used agile methodologies in software development. It is very responsive to changing requirements even in the late phases of the project. However, quality activities in extreme programming phases are implemented sequentially along with the activities that work on the functional requirements. This reduces the agility to deliver increments continuously and makes an inverse relationship between quality and agility. Due to this relationship, extreme programming does not consume enough time on making extensive documentation and robust design. To overcome these issues, an enhanced extreme programming model is proposed. Enhanced extreme programming introduces parallelism in the activities' execution through putting quality activities into a separate execution line. In this way, the focus on delivering increments quickly is achieved without affecting the quality of the final output. In enhanced extreme programming, the quality concept is extended to include refinement of all phases of classical extreme programming and creating architectural design based on the refined design documents.
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Proposal to Decrease Code Defects to Improve Software Quality
Статья научная
Software quality is an important topic of software development and it is always challenging to deliver high-quality software. The major challenges, to complete the software, are time and cost without losing the software quality. Software quality has a significant impact on software performance. The acceptability, success, and failure of software are depending on its level of quality and number of defects. Software defects are one of the fundamental factors that can determine the time of software delivery. In addition, defects or errors need to be eliminated before software delivery. Software companies spend a lot to reduce code defects. The aim is to detect defects early with cheaper methods. This paper proposes a code quality scanner to decrease the code defects. The proposed solution is a combination of code scanner and code review. Moreover, the paper presents results using quantitative analysis to show the effectiveness of the proposed solution. The results are found encouraging.
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Quality Test Template toward Multi-user Access Control of Internet-Based System
Статья научная
Aiming at three kinds of Internet-based system quality problems, which is performance, liability and security, the paper proposes a kind of test template during multi-user login and resource access control, which includes test requirement, login script, role-resource correlating and mutation test technique. Some Internet-based systems are tested and diagnosed by automation test technique of test template. At last, system quality can be verified and improved through the realization mechanism of test template.
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Quality of Experience Assessment of Banking Service
Статья научная
In this paper, Quality of Experience (QoE) is used to assess and improve Bank’s customer satisfaction and provide quality of service (QoS) according to their demands. QoE based web platform was developed for the assessment of customer satisfaction. The Eclipse Neon Enterprise Edition was used for the design and development of platform and MySQL database was used for backend database storage. The front interface of the platform provided user facility to enter their complaints and information, which will store in the database. The stored data will be used for the analysis of a particular employee’s evaluations of his performance and behavior with customers. Management can observe the performance of the bank’s employees and can overcome their flaws by providing the required training. If one employee is lacking communication skills and is unable to convey his message to the customer of the bank, then the management can arrange training for improving his/her communication skills.
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Quantum Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem
Статья научная
This paper presents a quantum behaved particle swarm algorithm for solving the multi-objective reactive power dispatch problem .Particle swarm optimization (PSO) is a population-based swarm intellect algorithm that share various similarities with evolutionary computation methods. Yet, PSO is determined by the imitation of a societal psychosomatic metaphor aggravated by cooperative behaviours of bird and other societal organisms instead of, the endurance of the fittest individual. Stimulated by the traditional PSO method and quantum procedure theories, this work presents a new Quantum behaved PSO (QPSO). The simulation results reveal high-quality performance of the QPSO in solving an optimal reactive power dispatch problem. In order to appraise the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
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Queuing Effect on Multipath Routing in Mobile Ad Hoc Networks
Статья научная
In Mobile Ad Hoc Network, data delivery is very challenging through single path due to dynamic changes in the network topology. To cope up this issue multipath data delivery is very useful. Recently, many works have been carried out in this domain but few are addressing the queueing effect on multipath scenarios. In this paper, we have designed a network model that based on the existence of multipath between source and destination node and every node behave as M/M/1 queue. In order to do this we generate K (K=1, 2, 3…i) paths are available between each source toward the destination node. The traffic arrivals in each node follow poisson process with arrival rate λ packets/sec. The simulation work of this multipath scenario based on varying mean inter-arrival time. The effect of arrival rate on the performance of multipath network model is analysed and compared. To better understand the effect of arrival rate in application and network layer various QoS metrics are computed. Significant performance of individual node is noticed in the obtained results with various arrival rates.
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Rank University Websites Using Fuzzy AHP and Fuzzy TOPSIS Approach on Usability
Статья научная
With the advent of dynamic website usually all business processes of a business organization are linked with the website of the organization. This is resulted in designing of a complex and gigantic website which may result in slow download and unfriendly navigation. Satisfying the end user need is one of the key principles of designing an effective website. As there are different users for given website, hence there are different criteria on which user wants to get satisfied, hence evaluating a website is a multi-criteria decision making problem. In order to incorporate uncertainties and vagueness in decision making Fuzzy Analytic Hierarchy (FAHP) approach is extended with Fuzzy TOPSIS approach, where different decision makers (DM's) opinion was considered for ranking the website.
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Real Time Speaker Recognition System for Hindi Words
Статья научная
Real time speaker recognition is needed for various voice controlled applications. Background noise influences the overall efficiency of speaker recognition system and is still considered a challenge in Speaker Recognition System (SRS). In this paper MFCC feature is used along with VQLBG algorithm for designing SRS. A new approach for designing a Voice Activity Detector (VAD) has been proposed which can discriminate between silence and voice activity and this can significantly improve the performance of SRS under noisy conditions. MFCC feature is extracted from the input speech and then vector quantization of the extracted MFCC features is done using VQLBG algorithm. Speaker identification is done by comparing the features of a newly recorded voice with the database under a specific threshold using Euclidean distance approach. The entire processing is done using MATLAB tool.The experimental result shows that the proposed method gives good results.
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Real estate recommendation using historical data and surrounding environments
Статья научная
Recommending appropriate things to the user by analyzing available data is becoming popular day by day. There are no sufficient researches on Real-estate recommendation with historical data and surrounding environments. We have collected real-estate, historical and point of interest (POI) data from the various sources. In this research, a hybrid filtering technique is used for recommending real-estate consisting of collaborative and content-based filtering. Generally, in every website user ratings are collected for the recommendation. But we have considered historical data and surrounding environments of a real-estate location for recommendation by which it will be easy for a user to decide that which place would be better for him/her. If any user request for any specific location then the system will find the POI data using google map API. Then the system will consider historical data of that area, got from the trusted sources. So considering the minimum price and optimal facilities, our system will recommend top-k real-estate. After extensive experiments on real and synthetic data, we have proved the efficiency of our proposed recommender system.
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Real-Time Obstacle Detection Approach using Stereoscopic Images
Статья научная
In this paper, we propose a new and simple approach to obstacle and free space detection in an indoor and outdoor environment in real-time using stereo vision as sensor. The real-time obstacle detection algorithm uses two dimensional disparity map to detect obstacles in the scene without constructing the ground plane. The proposed approach combines an accumulating and thresholding techniques to detect and cluster obstacle pixels into objects using a dense disparity map. The results from both analysis modules are combined to provide information of the free space. Experimental results are presented to show the effectiveness of the proposed method in real-time.
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Recommender System in Tourism Using Case based Reasoning Approach
Статья научная
Using recommender systems with the help of computer systems technology to support the Tourist advising process offers many advantages over the traditional system. A knowledge based recommender reasons about the fit between a user’s need and the features of available products. Providing an effective service in Ethiopian Tourism sector is critical to attract more foreign and local tourists. However, there are major problems that need immediate solution. First, the difficulty of getting fast, reliable, and consistent expert advice in the sector that is suitable to each visitor’s characteristics and capabilities. Second, inadequacy of the number of experienced experts and consulting individuals who can give advice on tourism issues in the country. Therefore, this paper aims to design a recommender system for tourist attraction area and visiting time selection that can assist experts and tourists to make timely decisions that helps them to get fast and consistent advisory service. So that, visitors can identify tourist attraction areas that have the highest potential of success/satisfaction and that match their personal characteristics. The system provides recommendation to visitors based on previously solved cases and new query given by the tourist. For this study, about 615 cases which are collected from National Tour operation and 10 attributes which are collected from experts are used as case base. These attributes and cases are used as knowledge base to construct case based recommender. The system calculates similarity between existing cases and new queries that are provided by the visitors, and provide solution or recommendation by taking best cases to the new query. In this study, JCOLIBRI case base development tool is used to develop the prototype. JCOLIBRI contains both user interface which enables visitors to enter their query and programming codes with the help of Java script language. To decide the applicability of the prototype in the domain area, the system has been evaluated by involving domain experts and visitors through visual interaction using the criteria of easiness to use, time efficiency, applicability in the domain area and providing correct recommendation. Based on prototype user acceptance testing, the average performance of the system is 80% and 82% by domain experts and visitors respectively. The performance of the system is also measured using the standard measure of relevance (IR system) recall, precision and accuracy measures, where the system registers 83% recall, 61% precision and 85.4% accuracy.
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Redesign Sanjai Chips Packaging Using Kansei Engineering Method
Статья научная
Sanjai chips made from cassava is typical tradisional Minang food. Packaging design is fundamental because 89% of consumer responses to buying a product are influenced by packaging. Current packaging weakness are plastic packaging is thin, no accompanying brands, and unattractive packaging, so less attractive, greasy, leaks, and make the chips contained in it be destroyed when bought for souvenirs. For this reason, it is necessary to redesign packaging for sanjai chips to increase product protection and influence consumers. Kansei Engineering is a method that deals with the psychological aspects of consumers when interacting with products to obtain a relationship between feelings and product characteristics. Because of that, this method has been chosen. The kansei process begins with a span of semantic space which begins with determining the kansei word. Kansei words were obtained from the distribution of open questionnaires and also based on previous research. After that, the span of the space of properties is determined which is useful for identifying what product properties should be in the design. after that the synthesis, design and evaluation are carried out. Based on the results from the results of the synthesis of span of semantic space and span of the space of properties, it was found that to design Sanjai Chips packaging, the criteria for packaging design are simple, good, informative, unique, and convincing for packaging materials must be non-greasy, made of plastic, good, strong, and convincing, while for other facilities criteria must be flexible.
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Reducing Multicast Redundancy and Latency in Multi-Interface Multi-Channel Wireless Mesh Networks
Статья научная
In wireless mesh networks, each node can be equipped with multiple network interface cards tuned to different channels. In this paper, we study the problem of collision-free multicast in multi-interface multi-channel wireless mesh networks. The concept of interface redundancy is proposed as a new criterion for the multicast/broadcast redundancy in wireless mesh networks, and we prove that building a multicast/broadcast tree with the minimum interface redundancy is NP-hard. We also prove that the minimum-latency multicasting problem in multi-channel wireless mesh networks is NP-hard. We present two heuristic-based algorithms which jointly reduce the interface redundancy and the multicast latency. Since broadcast can be considered as a special case of multicast, an approximate algorithm for low-redundancy broadcast tree construction is also proposed, which has a constant approximation ratio. Finally, the simulation results prove the effectiveness of our approach.
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Reduction of Multiple Move Method Suggestions Using Total Call-Frequencies of Distinct Entities
Статья научная
Inappropriate placement of methods causes Feature Envy (FE) code smell and makes classes coupled with each other. To achieve cohesion among classes, FE code smell can be removed using automated Move Method Refactoring (MMR) suggestions. However, challenges arise when existing techniques provide multiple MMR suggestions for a single FE instance. The developers need to manually find an appropriate target classes for applying MMR as an FE instance cannot be moved to multiple classes. In this paper, a technique is proposed named MultiMMRSReducer, to reduce multiple MMR suggestions by considering the Total Call-Frequencies of Distinct Entities (TCFDE). Experimental results show that TCFDE can reduce the multiple MMR suggestions of an FE instance and performs 77.92% better than an existing approach, namely, JDeodorant. Moreover, it can ensure minimum future changes in the dependent classes of an FE instance.
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