- All articles 719
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International Journal of Information Engineering and Electronic Business @ijieeb
Journal articles - International Journal of Information Engineering and Electronic Business
All articles: 719
Security Framework for Social Internet of Things: A Relativity Strength Approach
Scientific article
The evolution of the Internet of Things (IoT) into the Social Internet of Things (SIoT) involves the integration of social networking features into smart devices. In this paradigm, smart devices emulate human social behavior by forming social relationships with other devices within the network. These relationships are leveraged for service discovery, emphasizing the need for robust security to foster collaboration and cooperation among devices. Security is paramount in the SIoT landscape, as malicious messages from devices can disrupt service functionality, impacting service quality and reliability. These challenges are particularly pronounced in social networks, introducing unique considerations such as heterogeneity and navigability. This study introduces a Security Framework for the Social Internet of Things, adopting a Relativity Strength Approach to enhance the security and reliability of IoT devices within social network contexts. The framework incorporates a relativity-based security model, utilizes Q-learning for efficient device navigation, and employs decision tree classification for assessing service availability. By optimizing hop counts and considering the strength of relationships between devices, the framework enhances security, resource utilization, and service reliability. The proposed security framework introduces a” Relationship key” derived from device-to-device relationships as a central element. This key, coupled with a standard 256-bit Advanced Encryption Standard (AES) algorithm, is employed for encryption and decryption processes. The relationship key technique ensures data protection during transmission, guaranteeing confidentiality and service integrity during network navigation. The system demonstrates an overall security effectiveness of 88.75%, showcasing its robustness in thwarting attacks and preventing unauthorized access. With an impressive overall communication efficiency of 91.75%, the framework minimizes errors and delays, facilitating optimal information trans- mission in smart environments. Furthermore, its 97.5% overall service availability assures a continuous and reliable user experience, establishing the framework’s capability to deliver secure, efficient, and highly accessible smart services.
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Security Measures in Data Mining
Scientific article
Data mining is a technique to dig the data from the large databases for analysis and executive decision making. Security aspect is one of the measure requirement for data mining applications. In this paper we present security requirement measures for the data mining. We summarize the requirements of security for data mining in tabular format. The summarization is performed by the requirements with different aspects of security measure of data mining. The performances and outcomes are determined by the given factors under the summarization criteria. Effects are also given under the tabular form for the requirements of different parameters of security aspects.
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Security and Privacy for Data Storage Service Scheme in Cloud Computing
Scientific article
The cloud computing features aim at providing security and confidentiality to its customers. The business officials have gained maximum profit using the cloud environment. Therefore the critical data moving to and from the cloud server must be secured. The security and confidentiality issue is the most critical challenge that we are facing in today’s world of the cloud environment. The business officials have gained maximum profit accessing the cloud environment. Before the disaster occurrence, the critical data moving to and from the cloud must be preserved. The privacy preservation and cloud security issue is the most serious issue that we are facing in today’s world in cloud era.
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Scientific article
In this paper research was carried out in order to evaluate the security risk analysis and management in banking company through the use of a questionnaire to determine the level of risk that customer of the financial institution is likely to encounter. It was discovered that though the majority of financial institution users are familiar with the possible risk associated with some banking transaction, some aspect still exists that financial institution users are not familiar with which serves as a vulnerable point that could be exploited. The study makes a recommendation for proper enlightenment of financial institution users so as to stay abreast with possible security challenge associated with some banking transaction processes to be able to mitigate possible exploit.
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Selection of Database Management System with Fuzzy-AHP for Electronic Medical Record
Scientific article
Database selection is one of the main problems in designing electronic medical record (EMR) Software, since there are many different data with different types and formats in it. This work provides an approach for selecting suitable database management system (DBMS) with fuzzy analytical hierarchical process that gives capabilities of requirements to electronic medical record software. Criteria are choose based upon capabilities of requirements including supporting from type of operating system and programming language, maximum of table size, indexing, replication and access control. In addition, alternatives are PostgreSQL, MySQL, Oracle, DB2 and Microsoft SQL Server. According to the application of fuzzy analytical hierarchical process a ranking is obtained to decision making the best database management system for electronic medical record software.
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Self-Healing Mechanism for Reliable Architecture with Focus on Failure Detection
Scientific article
Many companies are embracing e-commerce, or business conducted on-line over electronically networks, as a means of expanding markets, improving customer service, reducing costs, and enhancing productivity. Like other companies, banks are taking steps to expand the use of computer science technology in their business operations. On the other hand, in recent years, the adoption of e-banking began to occur quite extensively as a channel of distribution for financial services due to rapid advances in IT and intensive competitive banking markets. For a bank that wants to remain in the competition, it's more important that each e-banking service have some features such as reliability, availability, extensibility. So we have represented a new e-banking framework which used a biology concept so called self-healing. In our framework, we presented some additional services respect to self-healing cycle for decrease the failure frequency and consequently increase services reliability.
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Sensing as a Service: Vision, Practices and Architecture
Scientific article
The Internet of Things (IoT) is becoming pervasive and immersive due to the recent advancements in communication and sensing technologies. The proliferation of smart devices and their sensing capabilities has opened new opportunities and business models. The billions of connected sensing devices are generating enormous amount of data. The sensing as a service concept has the potential to provide a wide variety of services to citizens, companies and public administrations. This paper presents a sensing as service vision for IoT in different domains such as agriculture, waste management, supply chain, traffic management and others. Moreover, different applications of sensing as service model is analyzed and discussed in detail. In this paper, we specifically propose a service oriented sensing as service architecture to realize the vision of sensing as a service. The proposed service oriented architecture has the potential to address the challenges of heterogeneity, integration and interoperability of a sensing as service concept and can open new business opportunities.
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Sensing the Material Position in Construction Project
Scientific article
In order to improve the monitoring and controlling performances in construction projects, especially in multi-story projects, This paper researched the approaches to track the materials and components on construction project. A locating model in 3 dimensional spaces is proposed. The mentioned locating algorithms are compared, and shortages and advantages of each are given. The purpose is to find an optimal solution to manage the location information in construction project site with lower costs, higher locating accuracy and ideal reliability.
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Sentence Clustering Using Parts-of-Speech
Scientific article
Clustering algorithms are used in many Natural Language Processing (NLP) tasks. They have proven to be popular and effective tools to use to discover groups of similar linguistic items. In this exploratory paper, we propose a new clustering algorithm to automatically cluster together similar sentences based on the sentences’ part-of-speech syntax. The algorithm generates and merges together the clusters using a syntactic similarity metric based on a hierarchical organization of the parts-of-speech. We demonstrate the features of this algorithm by implementing it in a question type classification system, in order to determine the positive or negative impact of different changes to the algorithm.
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Sentiment Analysis of Review Datasets Using Naïve Bayes' and K-NN Classifier
Scientific article
The advent of Web 2.0 has led to an increase in the amount of sentimental content available in the Web. Such content is often found in social media web sites in the form of movie or product reviews, user comments, testimonials, messages in discussion forums etc. Timely discovery of the sentimental or opinionated web content has a number of advantages, the most important of all being monetization. Understanding of the sentiments of human masses towards different entities and products enables better services for contextual advertisements, recommendation systems and analysis of market trends. The focus of our project is sentiment focussed web crawling framework to facilitate the quick discovery of sentimental contents of movie reviews and hotel reviews and analysis of the same. We use statistical methods to capture elements of subjective style and the sentence polarity. The paper elaborately discusses two supervised machine learning algorithms: K-Nearest Neighbour(K-NN) and Naïve Bayes' and compares their overall accuracy, precisions as well as recall values. It was seen that in case of movie reviews Naïve Bayes' gave far better results than K-NN but for hotel reviews these algorithms gave lesser, almost same accuracies.
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Shape Design of Lifting body Based on Genetic Algorithm
Scientific article
This paper briefly introduces the concept and history of lifting body, and puts forward a new method for the optimization of lifting body. This method has drawn lessons from the die line design of airplane is used to parametric numerical modeling for the lifting body, and extract the characterization of shape parameters as design variables, a combination of lifting body reentry vehicle aerodynamic conditions, aerodynamic heating, volumetric Rate and the stability of performance. Multi-objective hybrid genetic algorithm is adopted to complete the aerodynamic shape optimization and design of hypersonic lifting body vehicle when under more variable and constrained condition in order to obtain the Pareto optimal solution of Common Aero Vehicle shape.
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Simulation and Optimization of VHDL code for FPGA-Based Design using Simulink
Scientific article
Simulations and prototyping have been a very important part of the electronics industry since a very long time. In recent years, FPGA's have become increasingly important and have found their way into all kind of digital system design This paper presents a novel, easy and efficient approach of implementation and verification of VHDL code using Simulink and then to regenerate the optimized VHDL code again using Simulink. The VHDL code written for the complicated digital design of 32-bit floating point arithmetic unit has been synthesized on Xilinx, verified and simulated on Simulink. The same VHDL code in Modelsim was optimized using this approach and the optimized code so generated by Simulinkhas also been synthesized to compare the results. Power dissipations for both synthesized designs using Xilinx Power Estimator were also extracted for comparison.
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Simulation of electric power plant performance using Excel®-VBA
Scientific article
This paper presents the failure and repair simulation for electric power house with N Turbo-alternator, where N may be up to 32. The program employs a pseudo-random number generator for individual power plant that can be described by exponential probability density functions. The resulting sequences of failure and repair events are then combined for the plants to give scenarios for different time horizons. The implementation in Excel®-VBA includes an appropriately designed userform containing the macro Active-X control for input of relevant information. The result shows that as the number of samples increased the behavior of the random events better represented the desired form with a correlation of almost 99% for 25 trials. This corresponds to a confidence interval of better than 95% and hence should be used as the median for practical applications. The results were tested and the distributions of the events were found to be close approximation of the target exponential distributions.
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Scientific article
This paper presents a customized application in term of LCD interfacing through soft-core microcontroller by implementing its control circuitry in FPGA. Therefore optimum efficiency is achieved. This provide the single chip solution by replacing conventional model which contain separate microcontroller circuit, therefore the efficient resource utilization of FPGA is made, day by day as an increase in the complexity of Embedded system design thus gives many advantages over conventional designed processors such as platform independence, less cost, flexibility and greater immunity to obsolescence.
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Scientific article
Remote sensing images are complex, which makes it difficult to interpret and generate semantically appropriate textual description. To get a semantically relevant description, it is important to identify complex objects and understand the contextual relationships between them. In such cases, deriving contextually accurate information while maintaining semantic coherence is challenging. Therefore, a specifically designed model architecture is required to generate semantically relevant descriptions. This paper discusses a deep learning-based approach to generate remote sensing image descriptions using an end-to-end encoder-decoder model with soft attention. The UC Merced (UCM) dataset is used for training, which includes multiple captions per image capturing various scene aspects. To further assess the robustness and generalizability of the proposed approach, its performance is additionally evaluated on more complex datasets such as RSCID and Sydney Captions. This study presents an end-to-end CNN–LSTM encoder–decoder framework enhanced with soft attention for semantic description generation from remote sensing imagery. The framework employs a VGG16 encoder to extract a 4096-dimensional visual feature vector, which is projected into a 256-dimensional representation and processed by a 256-unit LSTM decoder. The soft attention mechanism dynamically computes attention weights using the encoder features and decoder hidden state, enabling the model to emphasize relevant visual information during word generation. Multiple CNN encoders and learning rates are evaluated with LSTM decoders, both with and without attention, on the UCM, RSCID, and Sydney Caption datasets. At a learning rate of 0.0001, VGG16–LSTM with soft attention achieves BLEU-4 (B4) scores of 0.6636, 0.6636, and 0.5864 on the UCM, RSCID, and Sydney Caption datasets, respectively, compared with 0.1643, 0.1647, and 0.1745 for VGG16–LSTM without attention. The results demonstrate that soft attention substantially improves description generation by strengthening visual–linguistic alignment and enabling more contextually relevant and semantically coherent descriptions across datasets with varying scene complexity.
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Software Module Clustering Using Hybrid Socio-Evolutionary Algorithms
Scientific article
Design of the software system plays a crucial role in the effective and efficient maintenance of the software system. In the absence of original design structure it might be required to re-identify the design by using the source code of the concerned software. Software clustering is one of the powerful techniques which could be used to cluster large software systems into smaller manageable subsystems containing modules of similar features. This paper examines the use of novel evolutionary imperialist competitive algorithms, genetic algorithms and their combinations for software clustering. Apparently, recursive application of these algorithms result in the best performance in terms of quality of clusters, number of epochs required for convergence and standard deviation obtained by repeated application of these algorithms.
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Software Quality Appraisal Using Multi-Criteria Decision Approach
Scientific article
Software quality measurement is the key factor in the development of any software system. Various software quality models are devised to measure the performance of a software system, which consists of numerous quality parameters on the basis of which software are quantified. Different types of software quality models are already present like an ISO/IEC9126 Quality model, Boehm's model, McCall's model, etc. In this paper, an attempt has been made to increase the quality of a software system by introducing some new quality parameters in ISO/IEC9126 model. Since the quality parameters are very unpredictable in nature, so as to evaluate the performance of quality parameters, the fuzzy multi criteria approach has been used.
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Solving the Problem of Pre-Selection of Personnel Based on Fuzzy Sets
Scientific article
The article proposes a method for clarifying the degree of correspondence between the request of a company looking for a specialist for a vacant position and the request of an applicant. As practice shows, the requirements in the requests of companies and the requests of applicants are linguistic, using vague boundaries of compliance parameters. Based on the results of a survey of graduate students and representatives of potential employer companies conducted by the author of the work, the company’s image, its experience in the market, and a decent salary are significant for graduates. For potential employers, applicants with some experience in the branch and low financial expectations are substantial first of all. Thus, from the statements of both sides, the author managed to identify two linguistic variables: “Time” and “Salary level.” These variables are applied to identify correlations between requests at the preliminary stage of staff selection. Indirect methods, namely methods of statistical data and expert assessments, were used in the variable membership functions. The algorithm for detecting matches is noticeably simple and can be in almost any table processor, which expands the field of the proposed approach. The recruitment agency acts as an intermediary in recruitment. The algorithm for identifying compliance in its activities will significantly reduce recruiters’ time and labor costs.
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Some Results on Optimal Dividend Problem in Two Risk Models
Scientific article
The compound Poisson risk model and the compound Poisson risk model perturbed by diffusion are considered in the presence of a dividend barrier with solvency constraints. Moreover, it extends the known result due to [1]. Ref. [1] finds the optimal dividend policy is of a barrier type for a jump-diffusion model with exponentially distributed jumps. In this paper, it turns out that there can be two different solutions depending on the model’s parameters. Furthermore, an interesting result is given: the proportional transaction cost has no effect on the dividend barrier. The objective of the corporation is to maximize the cumulative expected discounted dividends payout with solvency constraints before the time of ruin. It is well known that under some reasonable assumptions, optimal dividend strategy is a barrier strategy, i.e., there is a level b_{1}(b_{2}) so that whenever surplus goes above the level b_{1}(b_{2}), the excess is paid out as dividends. However, the optimal level b_{1}(b_{2}) may be unacceptably low from a solvency point of view. Therefore, some constraints should imposed on an insurance company such as to pay out dividends unless the surplus has reached a level b^{1}_{c}>b_{1}(b^2_{c}>b_{2}) . We show that in this case a barrier strategy at b^{1}_{c}(b^2_{c}) is optimal.
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SourceViz: A Tool for Supporting Software Metrics Visualization
Scientific article
Maintaining and understanding large software systems is a complex and time consuming process. Understanding the internal structure of such systems is not an easy task due to the invisible nature of software. Source Code Visualization, i.e. measuring the code metrics and then visualizing them, provides an efficient solution to this problem. There are many tools available which gives an insight to the internal structure of the software. But all of them don't provide visualizations of hierarchical relationships and code complexity of the source code. In this paper, we present a tool named "SourceViz". This application computes different software metrics, code complexity, class-relations and then visualizes the calculated metrics in different metaphors. This visual analysis assists the project managers and software developers in understanding the static structure of the software by presenting project-level as well as class-level view.
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