- All articles 732
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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: 732
Innovative Privacy Preserving Strategies in Federal Learning
Scientific article
Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, but it remains vulnerable to privacy risks. This study introduces FL-ODP-DFT, a novel framework that integrates Optimal Differential Privacy (ODP) with Discrete Fourier Transform (DFT) to enhance both model performance and privacy. By transforming local gradients into the frequency domain, the method reduces data size and adds a layer of encryption before transmission. Adaptive Gaussian Clipping (AGC) is employed to dynamically adjust clipping thresholds based on gradient distribution, further improving gradient handling. ODP then calibrates noise addition based on data sensitivity and privacy budgets, ensuring a balance between privacy and accuracy. Extensive experiments demonstrate that FL-ODP-DFT outperforms existing techniques in terms of accuracy, computational efficiency, convergence speed, and privacy protection, making it a robust and scalable solution for privacy-preserving FL.
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Insan AI: Integrated Artificial Intelligence Learning Platform
Scientific article
The integration of artificial intelligence (AI) in education presents significant challenges, such as gaps in educators' digital adaptability, ethical considerations, and inconsistent infrastructure. This study details the development and validation of the Insan AI Platform, an integrated learning solution designed to address these obstacles through adaptive AI tools for both teachers and students. The platform was developed using a user-centered prototyping methodology, drawing on comprehensive literature analysis, Focus Group Discussions with 26 educational stakeholders, and expert interviews. Key features include an AI Content Generator, a Virtual Tutor, and a Learning Analytics dashboard, all intended to facilitate personalized learning experiences and enhance teaching efficiency. User Acceptance Testing with 20 teachers demonstrated the platform's functional robustness, with perfect pass rates on all core features and a high usability score (SUS: 84.0). The platform architecture integrates multiple AI application programming interfaces (APIs) while maintaining responsive performance under varied network conditions. These findings indicate that the Insan AI Platform effectively meets user requirements and provides a strong foundation for broader educational implementation. Future development will focus on incorporating multilingual support and advanced learning analytics capabilities. According to a questionnaire completed by 26 users, there was a score increase of 22.42 after using the Insan AI platform. This indicates that the application has successfully met user requirements.
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Instructor’s Performance:A Proposed Model for Online Evaluation
Scientific article
Currently due to high awareness and quality audits, the higher education institutions have made to keep a track on various performances of the institutions. One such most important activity that has to be analyzed and evaluated is Instructor’s classroom performance. As the students are the main stakeholders of the educational process, their concerns over the instructor, teaching pedagogies and methodologies, assessment techniques need to be collected and analyzed for achieving the institution’s goals and objectives. The students shall give their opinions related to the various performance indicators of instructor.In general, the higher education institutions use various techniques to evaluate instructor’s performance in the classroom from the students. The latest technological developments help in data collection using web technologies. Online system with required questionnaire and attributes will help the higher education institutions in easy data collection. Apart from that the students shall give their opinions without any fear from any place and at any time. In this paper, we have identified the major factors and users of an instructor online evaluation system. Also, we have proposed a model for such system with subsystem interface, entity relationship diagram and context diagram.
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Integrating Asymmetric Cryptographic Digital Wallet for Online Services in Nigeria
Scientific article
Online stores have integrated one or more payment gateways on their website to facilitate the transaction of goods and services. In the Nigerian case, many physical stores are moving online. However, there is a gap in the payment methods which have slowed down business due to limited payment methods, charges incurred on gateways, and insecurity of websites. This paper is tailored towards the security of online transactions, reduced credit card usage and yet accentuation of cashless policy in Nigeria. Inline with the above stated, this paper proposed a secured digital wallet using cryptography to proffer a solution to exposing confidential information to different sites and curb fraudulent actions. By means of qualitative and quantitative research approach, data on user transactions were collected through google survey forms on how often they make transactions, 91.3% shop online but only 48.1% shop very often and 55% of sample questioned security of online payment, from the quantitative facts above, a larger percent of people who uses financial tools in their shopping activities have more security concern which this study solely aim at. In response to the corncern in the preceeding clauses, a mathematical model was formulated to generate keys for the wallet using an asymmetric cryptography scheme to improve the security process while using an online service. Furthermore, wallet referred in this paper uses the fund preload techniques which limits how often users needs to swipe their credit card for an handshake with the commercial banks, the end goal thus strengthen the Nigeria cashless policy. This paper generated encryption and decryption keys from the extension of the Euclid theorem and implemented a system that can generate keys for fund and asset transfer with the crypto service. The system was tested using unit testing and alpha and beta testing to assert the aims of the research. The result showed that digital wallet usage reduces the exposure of sensitive information on funds and allows using the account on different sites.
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Scientific article
The article discusses methods for averting irrational product placement in warehouses. This problem is relevant for many manufacturing enterprises and trade organizations. The most common embodiments of the problem are unoccupied areas, or a lack of free storage space, difficulty in locating a specific product, and challenges in shipping it from the warehouse. All this leads to unnecessary costs for the business entity and hurts its financial and economic activities. The author suggests an integrated approach to warehousing. It integrates both classical optimization models and iterative approval procedures for accounting for the human factor. The key criteria in this case are minimizing costs, the cargo flow in the warehouse, and maximizing the utilization factor of the usable area. The optimal placement of goods is to achieve maximum compression of their residues in the warehouse while minimizing their movement. The presence of two contradictory criteria makes the task a task of consistent optimization. The article discusses the possibilities for solving the optimization problem when conflicting target criteria and differing preferences are present. We are using the example of a storage room with 16 racks for water heaters and similar equipment. As a result of matching optimization procedures, it was possible to reduce the average cost of moving goods by 7.1% and increase the free warehouse area by 15 times. We performed the experiments over the seven days of the warehouse’s operation. The practical value of the research is that, through this approach, we find a compromise in conditions of conflicting opinions and interests.
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Integrating QR Code to e-Class System for Managing Attendance Lecture Services in Higher Education
Scientific article
Currently attendance is still done manually by recapping each lecturer's attendance sheet. The method used is the prototype method and testing using the User Acceptant Test (UAT) method. This takes a long time, even misinterpretations of existing absences sometimes cause problems when giving salary receipts to lecturers, besides that, reporting to campus management also takes time. The lecturer attendance system can help the finance department to calculate lecturer teaching attendance faster and more easily, which can be used to calculate salaries and evaluate lecturer attendance. The system at the implementation stage and during implementation the average teaching attendance of lecturers is easier to control. Some of the features in this attendance system include Check-in, Lecturer, profile, History, Schedule, Help, Tutorial and Chat Group. Apart from that, the main menu also provides information regarding the check-in time limit, waiting time for the next check-in, campus information, and application updates. The system was built with a QR Code and is Android-based to make things easier for lecturers, admin, and the finance department.
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Integration of Heterogeneous Cloud Storages through an Intermediate WCF Service
Scientific article
Many organizations provide computing resources or services to the client like hardware, software, storage etc. Storage is one of important service that is popular and commonly used today and it provides storage space online to store the data. Service providers give a storage space to consumers on the basis of renting criteria with a trust of high and powerful security. Consumer and organizations uses these storages to secure own personal data. There are many reasons come across that causes to move data from one place to another. Some of them are: reconstruction of storage, backup, new technologies, security etc. So, data migration, data transfer between different cloud storages, often requires. Achieving mechanism of Data migration between clouds is very difficult because of its different architecture to store data. For example Window Azure cloud storage creates a primary key name ID automatically whenever a new table is created. Architecture of cloud storage is depending upon its implementation done by corresponding cloud vendors (like Microsoft). The main vision of this research work is to provide an intermediate service to move the data between both homogeneous and heterogeneous cloud storages. This intermediate service is a two way strategy that built in a SOA technology called WCF that helps the clients, organizations to move data between same and different cloud storages (Window Azure and Go Daddy cloud storages mainly used in this research work).
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Intelligent Network Architecture Development for E-Business Processes Based on Ontological Models
Scientific article
The use of ontological models for intelligent systems construction allows for improved quality characteristics at all stages of the life cycle of a software product. The main source of improvement in quality characteristics is the possibility of reusing the conceptualization and code provided by the corresponding models. Due to the use of a single conceptualization when creating various software products, the degree of interoperability and code portability increases. The new-generation electronic business analytics systems implementation is based on the use of active models for business processes (BP). Such models, on the one hand, reflect the BPs taking place in the organization on a real-time scale, and on the other hand, embody corporate and other regulatory rules and restrictions and monitor their compliance. The purpose of this article is to research the methods of presenting and building active executable BP models, determining the methods of their execution and coordination, and building the resulting intelligent network of BP models. In the process of its implementation, such a network ensures the implementation, support of decision-making and compliance with regulatory rules in the relevant real BPs. A formal specification of an intelligent system for modelling a complex of BPs of the enterprise using models has been proposed. A hierarchical approach to the introduction of intelligent functions into the modelling system has been proposed. The simulation system is designed to be used for the design and management of complex intelligent systems. Achieving the set goal involves solving several development tasks: methods of presenting BP models for different types of such models; methods of analysis and display of time relations and attributes in BP models; ways of presenting the association of artefacts, and business analytics models with individual BP operations; metric ratios for evaluating the quality of process execution; methods of interaction of various BPs and coordination of their implementation. The purpose of functioning an intelligent model-driven software system is achieved through the interaction of a large number of simple models. At the same time, each model encapsulates a certain aspect of the expert's knowledge about the subject area. To apply executable conceptual models in the field of modelling BPes, it is necessary to determine the types of conceptual models used, their purpose and functions, and the role they play in the operation of an intelligent system. Models used in modelling BPes can be classified according to various characteristics. At the same time, the same model can be included in different classifications.
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Scientific article
Refer to this paper, an intelligent-fuzzy feed-forward computed torque estimator for Proportional-Integral-Derivative (PID) controller is proposed for highly nonlinear continuum robot manipulator. In the absence of robot knowledge, PID may be the best controller, because it is model-free, and its parameters can be adjusted easily and separately and it is the most used in robot manipulators. In order to remove steady-state error caused by uncertainties and noise, the integrator gain has to be increased. This leads to worse transient performance, even destroys the stability. The integrator in a PID controller also reduces the bandwidth of the closed-loop system. Model-based compensation for PD control is an alternative method to substitute PID control. Computed torque compensation is one of the nonlinear compensator. The main problem of the pure computed torque compensator (CTC) was highly nonlinear dynamic parameters which related to system’s dynamic parameters in certain and uncertain systems. The nonlinear equivalent dynamic problem in uncertain system is solved by using feed-forward fuzzy inference system. To eliminate the continuum robot manipulator system’s dynamic; Mamdani fuzzy inference system is design and applied to CTC. This methodology is based on design feed-forward fuzzy inference system and applied to CTC. The results demonstrate that the model base feed-forward fuzzy CTC estimator works well to compensate linear PID controller in presence of partly uncertainty system (e.g., continuum robot).
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Scientific article
During the implementation of the work on the creation of the system of tonality recognition and text categorization in the news, a study of the subject area was conducted, which allowed the understanding of the processes of text analysis in the mass media to be enriched. The necessary data for further processing was found. The work resulted from a program that consists of an information parser, a data analyser and cleaner, a Large Language Models model, a neural network, and a database with vectorized data. These components were integrated into the user interface and implemented as a program window. The program can analyse news texts, determining their tone and categories. At the same time, it provides the user with a convenient interface for entering text and receiving analysis results. Therefore, the created system is a powerful tool for automated analysis of textual data in mass media, which can be used for various purposes, including monitoring the news space, analysis of public opinion, and others. Also, the developed information technology successfully meets the set tasks aimed at tonality analysis and categorization of news. It effectively solves the task of collecting, analysing and classifying news materials, which allows users to receive operational and objective information. Its architecture and functionality allow for easy changes and additions in the future, making it a flexible and adaptable tool for news analytics and decision-making in various business sectors.
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Intergovernmental Allocation of Public Resources, Fiscal Decentralization and Economic Growth
Scientific article
Incorporating a two-level government structure into an endogenous growth model, we discussed the growth impacts of different intergovernmental allocation of public resources, i.e. intergovernmental transfer payments and the power of revenue autonomy of the lower-level government, along with fiscal decentralization. we showed that (1) there was an “Inverted U-shaped” relationship between fiscal decentralization and economic growth; (2) Different intergovernmental allocation of public resources does not affect the “Inverted U-shape” relationship between fiscal decentralization and economic growth.
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Internal Control Improvement for Creating Good Governance
Scientific article
Cooperative, which support the national economy of Indonesia, still has many problems. In 2015 the report by the Ministry of Cooperatives and SMEs shows many cooperatives are inactive because of having incompetence. Some issues such as the value of savings that do not fit between the cooperative and its customers, embezzlement of customer funds by parties who are not responsible, refunds troubled loans so that the cooperative suffered losses. These problems will be used as a critical point to do mapping with COBIT 5 framework. Based on the result of this mapping, it will be prepared internal control based on the framework of possible internal controls such as COBIT(Control Objective for Information & Related Technology), COSO(Committee of Sponsoring Organizations), ITIL(IT Infrastructure Library) and national regulations that are prevailing in Indonesia. Control is expected to discuss the internal problems that occurred in each business process that used in the cooperative.
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Interoperability in Nigeria Healthcare System: The Ways Forward
Scientific article
Interoperability of health related information is one of the agendas of many counties in the world, with no exception to Nigeria and other developing countries. This is because healthcare costs are rising exponentially. However, interoperability of health related information seem largely unattainable in Nigeria due to reluctance to change from the traditional paper based healthcare system to the use of e-health systems, inadequate ICT infrastructure, poor utilization of the available ICT resources, erratic power supply, increased burden of underdevelopment, poverty, political instability, shortage of educational capacity in Nigeria rural and urban healthcare centers, low level of ICT awareness, poor maintenance culture as well as corruption. Consequently, the healthcare system in Nigeria is saddled with high cost, high rate of disease outbreak driven by HIV/AIDs, malaria and other infectious diseases which results in a high rate of mortality. Nevertheless, the urgent need to meaningfully exchange safe and reliable health information is a key priority to the healthcare system in Nigeria as the qualities of patients’ care depend majorly on the timely acquisition, processing and retrieval of data related to the patient. Thus, this paper attempts to unravel the factors hindering interoperability in the Nigeria healthcare system and suggests ways of making total interoperability a reality in Nigeria healthcare system as well as other developing countries.
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Scientific article
Neutrosophic set is a power general formal framework, which generalizes the concept of the classic set, fuzzy set, interval valued fuzzy set, intuitionistic fuzzy set, and interval intuitionistic fuzzy set from philosophical point of view. In Geographical Information Systems (GIS) there is a need to model spatial regions with indeterminate boundary and under indeterminacy. In this paper, we first gives fundamental concepts and properties of a neutrosophic spatial region.
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Investigation of Machine Learning Algorithms for Network Intrusion Detection
Scientific article
Network intrusion is an increasing major concern as we are rapidly advancing in technology. To detect network intrusion, Intrusion Detection Systems are required. Among the wide range of intrusion detection technologies, machine learning methods are the most appropriate. In this paper we investigated different machine learning techniques using NSL-KDD dataset, with steps of building a model. We used Decision Tree, Support Vector Machine, Random Forest, Naïve Bayes, Neural network, adaBoost machine leaning algorithms. At step one, one-hot-encoding is applied to convert categorical to numeric features. At step two, different feature scaling techniques, including normalization and standardization, are applied on these six selected machine learning algorithms with the encoded dataset. Further in this step, for each of the six machine learning algorithms, the better scaling technique application outcome is selected for the comparison in the next step. We considered six pairs of better scaling technique with each machine learning algorithm. Among these six scaling-machine learning pairs, one pair (Naïve Bayes) is dropped for having inferior performance. Hence, the outcome of this step is five scaling-machine learning pairs. At step three, different feature reduction techniques, including low variance filter, high correlation filter, Random Forest, Incremental PCA, are applied to the five scaling-machine learning pairs from step two. Further in this step, for each of the five scaling-machine learning pairs, the better feature reduction technique application outcome is selected for the comparison in the next step. The outcome of this step is five feature reduced scaling-machine learning pairs. At step four, different sampling techniques, including SMOTE, Borderline-SMOTE, ADASYN are applied to the five feature reduced scaling-machine learning pairs. The outcome of this step is five over sampled, feature reduced scaling-machine learning pairs. This outcome is then finally compared to find the best pairs to be used for intrusion detection system.
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Investigations of Cellular Automata Game of Life Rules for Noise Filtering and Edge Detection
Scientific article
In digital image processing, edge detection of images is an important and difficult task. Also, if the images are corrupted by noise, it smears some details and thus resulting in inaccurate edge detection. Hence, a pre-processing step must be taken before the edge detection. In this paper a new approach for edge detection with noise filtering of digital images using Cellular Automata Game of Life is presented. This procedure can easily be generalized and used for any type of digital media. To illustrate the proposed method, some experiments have been performed on standard test images and compared with popular methods. The results reveal that the proposed method has relatively desirable performance.
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IoT Based Smart Energy Consumption Prediction for Home Appliances
Scientific article
Optimizing energy management for household appliances is essential for maximizing domestic energy utilization and enabling preventive maintenance. Recent studies indicate that traditional forecasting approaches frequently lack the necessary accuracy and real-time learning capabilities required for effective management of household energy. This study demonstrates the implementation of a comprehensive strategy that integrates Internet of Things (IoT) data, machine learning (ML), and explainable artificial intelligence (XAI) to improve the accuracy and interpretability of predicting energy usage in residential buildings. Our research focuses on the rising issues faced by IoT-based smart systems, partic- ularly the deficiencies in the performance of current solutions. Therefore, as compared to the other 17 models that were examined, polynomial regression demonstrated outstanding performance. Our solution utilizes a non-intrusive sensor to collect data without disrupting its operation. Real-time data collecting is achieved through a Flask-based web page with Ngrok for external access.The efficacy of the proposed system was assessed using many metrics, yielding highly satisfac- tory results: the root mean square error (RMSE) was 0.03, the mean absolute error (MAE) was 0.02, the mean absolute percentage error (MAPE) was 0.04, and the coefficient of determination (R²) was 0.9989. However, modern cutting-edge methods still face considerable hurdles when it comes to interpretability. In order to tackle these problems, we include XAI techniques such as SHAP and LIME. Explainable Artificial Intelligence (XAI) improves the interpretability of the model by elucidating the impact of various variables on energy consumption forecasts. Not only does this increase the effectiveness of the model, but it also promotes comprehension of the data and enables them to identify the elements that influence home energy usage.
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IoT for Industrial Automation: A Review on Industry 4.0 Applications
Scientific article
The beginning of the fourth industrial revolution or Industry 4.0 has changed the concept of automation in industries by adopting the Internet of Things (IoT) in manufacturing, logistics, and production processes. The IoT is the digital foundation of Industry 4.0 that allows real-time monitoring, predictive maintenance, data-based decision making, and autonomous processes with in-between devices and smart sensors. This review explores the uses of the IoT in industrial automation through analyzing the enabling technologies, communication protocols, integration with cloud computing, wireless sensor networks, edge computing, artificial intelligence (AI) and machine learning (ML), as well as presenting important applications, current challenges, and future trends in smart industrial systems. Instead of considering the technologies separately, this paper takes the system-level viewpoint by integrating the way IoT architecture, communication protocol, intelligent analytics, and security controls collectively facilitate Industry 4.0 automation.
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Scientific article
Precision agriculture is revolutionizing the agricultural sector by integrating advanced technologies to enhance productivity and sustainability. In aquaculture, precision agriculture can significantly improve fish farming practices through precise monitoring and data-driven decision-making, addressing challenges such as optimizing resource usage and improving fish health. This paper presents the development and implementation of an IoT-based Fish Recommendation System designed to optimize aquaculture practices through a mobile application. This system uses different sensors for extracting data continuously regarding temperature, PH and Turbidity etc. These parameters can be analysed in real-time to help fish farmers make decisions on when or how much the system should feed and aerate, and what approach of water treatment is best for their fishes. This information is stored to create individual datasets, offering researchers valuable insights into optimal conditions for each fish species. This can enhance their survival rates and promote growth. In this study, we evaluate a series of machine learning algorithms for their ability to predict the optimal fish species based on water quality parameters. Among these algorithms, Random Forest demonstrated superior performance, achieving an accuracy of 92.5%, precision of 93%, recall of 93%, and F1-score of 92%. These findings highlight the effectiveness of our approach in integrating machine learning with IoT for precise aquaculture management. Implemented through a user-friendly mobile application, our system enhances accessibility and usability for fish farmers.
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IoT-Based Smart Homes: Technologies, Security Risks and Countermeasures
Scientific article
The advent of (Internet of Things) IoT technologies has essentially transformed traditional houses into intelligent, equipped, and networked smart houses that serve to improve the quality in the lives of human beings with respect to security, energy efficiency, and comfort through massive automation, sensing, and remote control. However, with such a shift of paradigm, due to the diversity of devices, the limitation of resources, problems of interoperability, and a growing array of cyberthreats, opens up numerous avenues for security and privacy threats. This review attempts a holistic coverage of IoT-based smart home technologies and then provides a systematic classification of the security vulnerabilities from device, network, cloud, and application layers. The key threats include unauthorized access, data leakage, propagation of malware, denial of service, and exploits targeted against AI, with an analysis of their causes and occurrences in the real world. The paper undertakes a critical assessment of contemporary countermeasures, ranging from lightweight cryptographic protocols, AI-driven intrusion detection systems, blockchain-based authentication, privacy-preserving edge computing, and zero-trust frameworks. A comparative insight into each approach conversed with the views of the established literature draws out trade-offs between security efficacy, scalability, computational overheads, and user adoption. Based on a synthesis of the modern findings, continued gaps are identified, and future directions provided: including quantum-resistant encryption, interoperable standards, and user-centric security design, acting as the working platform or actionable directions for any researchers, developers, or policymakers in building of secure, resilient, and privacy preserving smart home ecosystem.
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