Conference Paper
Browse
118 results
Search Results
Item Exploring Key Factors in Predicting the Adoption of AI Technologies in E-Commerce Firms(IEEE, 2024-12-20) Khan, T.,; Emon, M. M. H.,; Rahman, M. A.,; Aziz, A.,; Nath, A.This study aims to explore the key factors influencing the adoption of artificial intelligence (AI) technologies in e-commerce firms in Bangladesh. Utilizing the Technology-Organization-Environment (TOE) framework, the research identifies the determinants such as perceived relative advantage, technological complexity, compatibility with existing systems, top management support, organizational readiness, employee expertise/training, and competitive pressure that affect AI adoption. A quantitative research approach was adopted, using a structured questionnaire distributed to 350 employees from various e-commerce firms in Bangladesh. The study employed convenience sampling and received 231 responses, out of which 215 were deemed valid for analysis. Structural equation modeling (SEM) was conducted using SmartPLS to test the hypotheses and validate the model. The results indicated that PRA, CES, TMS, OR, ET, and CP positively influence AI adoption in e-commerce firms, while TC showed a negative, though not statistically significant, impact. The R-square value of 0.73 demonstrates the model's robustness in explaining AI adoption variance. The findings provide valuable insights for e-commerce firms, highlighting the importance of organizational support and readiness, as well as employee training, in facilitating AI adoption. The study underscores the role of AI in driving digital transformation and its potential to enhance business efficiency, contributing to economic development in emerging markets like Bangladesh. This research fills a gap in the literature by focusing on AI adoption in the context of Bangladeshi e-commerce, providing a nuanced understanding of the influencing factors using the TOE framework.Item Measuring the Influence of Brand Image on Consumer Behavioral Intentions by using AI: Exploring the Mediating Role of Trust(IEEE, 2024-09) Rahman, M. A.,; Emon, M. M. H.,; Khan, T.,; Siam, S. A. J.This study investigates the influence of various dimensions of brand image—perceived brand quality, brand loyalty, brand awareness, perceived value, brand personality, and brand communication—on consumer behavioral intentions, with trust acting as a mediating factor. Using survey data from 130 respondents and employing structural equation modeling (SEM) via Smart PLS, the research finds that brand loyalty, awareness, perceived value, personality, and communication significantly impact consumer intentions. Notably, trust mediates the relationships between perceived value and consumer intentions, and between brand communication and consumer intentions. However, perceived brand quality shows no direct impact on consumer intentions. The study acknowledges limitations such as convenience sampling and self-reported data, suggesting avenues for future research to enhance generalizability through diverse samples and longitudinal studies. Practical implications suggest that marketers should focus on strengthening these brand dimensions to build consumer trust and drive favorable behaviors, thereby potentially enhancing brand reputation and societal well-being. The study contributes to theoretical advancements by emphasizing trust as a pivotal mediator in brand-consumer relationships, offering valuable insights for strategic brand management in competitive market environments.Item Factors Influencing the Usage of Artificial Intelligence among Bangladeshi Professionals: Mediating role of Attitude Towards the Technology(IEEE, 2024-12-19) Emon, M. M. H.,; Khan, T.,; Rahman, M. A.,; Siam, S. A. J.This study investigates the factors influencing the usage of artificial intelligence (AI) among Bangladeshi professionals, with a focus on the mediating role of attitude towards technology. The purpose is to enhance understanding of AI adoption using elements from the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM). A quantitative research design was employed, utilizing a questionnaire distributed to 490 professionals, resulting in 190 usable responses. Data were analyzed using SmartPLS to assess the relationships among performance expectancy, effort expectancy, social influence, facilitating conditions, perceived usefulness, perceived ease of use, attitude towards technology, and behavioral intention to use AI. The findings indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, and perceived usefulness significantly influence AI adoption. Social influence and perceived ease of use exhibit mediated effects through attitude towards technology. The research is limited by its use of convenience sampling and a single-country focus, which may affect the generalizability of the findings. The study's practical implications include guiding policymakers and industry leaders in designing targeted strategies to promote AI adoption among professionals. Social implications highlight the importance of addressing social factors and perceived ease of use to foster positive attitudes towards AI. This research contributes originality by integrating UTAUT and TAM models in a developing country context, providing nuanced insights into AI adoption among professionals. Future research should explore AI adoption across different developing countries and consider longitudinal and qualitative studies for a deeper understanding of technology adoption dynamics.Item Cruise shipping: Problems and prospects from blue economy perspectives(American Institute of Physics Inc., 2020-07-23) Chawdhury, D.,; Islam, M.A.The demand for cruise shipping has progressively developed over the centuries in EU countries and Americas region. In the recent years, it has steadily multiplied attractiveness amongst vacationers in Asia especially in the countries of South East Asia and the Far East. The wave of cruise tourism has also touched Bangladesh, which has ample scope and opportunity to improve this promising sector. The fast growth of river and ocean cruise and geographic expansion has amplified the traveling involvedness rising the financial, socio-economic, ecological and cultural impacts. Consequently, the significance of cruise improvement must be evaluated on how it marks initially to society in a travel destination. It is a descriptive investigation and the study was grounded on together primary and secondary sources to study consequences, which would highlight on the following features: instituting a 24X7 visitor service point, ensuring a wide-ranging logistic facilities associated with cruise tourism, welcoming overseas cruise line operators to scrutinize exceptional sights in Bangladesh, collaborating with other Asian nations, forming a distinctive management division, along with development and emerging exclusive resources related with the travel and tourism sector of Bangladesh.Item An Autoencoder-Based Approach for DDoS Attack Detection Using Semi-Supervised Learning(Institute of Electrical and Electronics Engineers Inc., 2023-06) Fardusy, T.,; Afrin, S.,; Sraboni, I.J.,; Dey, U.K.A Distributed Denial of Service (DDoS) attack is a malicious cyber-attack strategy that seeks to disrupt normal traffic to a specific server by overwhelming it with an excessive amount of requests or data. In recent years, there has been a persistent increase in the use of DDoS attacks to exploit Internet networks. Although advanced intrusion detection and protection systems have been developed, network security remains a difficult problem and requires the development of effective defense mechanisms to detect these threats. Most of the current approaches are based on supervised learning which requires large and well-balanced datasets. Still, they struggle to identify new types of attacks. To address these issues, we propose a semi-supervised DDoS detection model using Autoencoder (AE) and Support Vector Machine (SVM). We compared our proposed approach with various supervised and semi-supervised models on the CICDDoS2019 dataset. Our proposed model outperformed the other models by achieving an accuracy of 99.57% and over 99% precision, recall, and F1 score.Item BSEVOTING: A Conceptual Framework to Develop Electronic Voting System using Sidechain(Institute of Electrical and Electronics Engineers Inc., 2021-08) Alvi, S.T.,; Islam, L.,; Rashme, T.Y.,; Uddin, M.N.In a democratic society, a citizen's ability to vote is regarded as one of the most significant legal rights he or she may exercise. For e-voting methods, blockchain presents new possibilities to properly meet transparency, integrity, anonymity and many other security properties. As the need for blockchains keeps rising, demand for bigger, more scalable, more adaptable, and more cost-effective multipurpose chain is also high. Conventional blockchains are incapable of meeting all of these demands. To solve the problems (mostly performance) associated with main blockchains, sidechain technology has recently evolved as a separate chain connected to the main chain that runs in parallel with transactions. Our proposed method is designed to operate on a public blockchain, but we separate the storage of voting information of each candidate using a sidechain to offer a cost-effective blockchain-based voting mechanism by ensuring the security properties such as anonymity, integrity, privacy, security, fairness, receipt freeness and so many. In future, we will broadly discuss and implement this voting system.Item IoT-based Automatic Pan Evaporimeter Monitoring and Irrigation Control System for Crops(Institute of Electrical and Electronics Engineers Inc., 2024-10-03) Kabir, M.S., , , ,; Niloy, K.M.; Hossen, M.I.; Afrose, S.; Mofazzol, M.I.H.This research study intends to automate the manual pan evaporimeter system and scheduling irrigation by considering soil water content and crop evapotranspiration. Automating the pan evaporimeter means performing tasks without human intervention, such as measuring the daily water evaporation amount, calculating and storing data, and refilling the pan with water. A waterproof ultrasonic sensor was used to measure the water evaporation amount. The ultrasonic sensor was installed on an innovatively designed structure facing the pan's water surface. The sensor measured the distance between the water surface and the sensor. The surface level decreased as the water evaporated over time, which caused an increment in the distance between the ultrasonic and water surfaces. By this, the sensor calculated the daily evaporation amount. The pan needed to be refilled when all water evaporated; a submersible pump was used to refill the pan automatically. A relay switch controlled the pump, and a microcontroller turned on the switch based on sensor value. The entire setup was IoT-enabled to monitor and control the system remotely on a mobile device. The entire system was backed up by solar energy to run on clean energy. A solenoid valve was used to control the flow of irrigation water. Pan evaporation estimated the amount of water that could be lost owing to evaporation and transpiration. Soil moisture sensors provided a direct measurement of the amount of water present in the soil. The two combined generated a dynamic and responsive irrigation plan that maximized water use and promoted the healthy development of crops. That approach was used. The ultrasonic sensor accurately measured water evaporation, but the installation process was complex. So, a need arises to develop a simple system or scale-type sensors to overcome the complexity. © 2024 IEEE.Item A Comparative Study of Economic Load Dispatch Problem using Computer Simulation Tool, Conventional and Evolutionary Algorithms(Institute of Electrical and Electronics Engineers Inc., 2024-05-02) Islam, A.,,; Aktar, S.; Poly, F.A.; Ali, T.Enhancing power generation to meet demand while simultaneously mitigating the operational expenses of power plants is a pivotal endeavor. The optimization of economic load dispatch (ELD) presents itself as a requisite process to curtail operational costs, including fuel expenses and incremental costs. In the context of this study, a comprehensive examination is conducted utilizing the Power World Simulator alongside the Lambda Iteration (LI) Method, the Particle Swarm Optimization (PSO) Method, and the Teaching Learning-Based Method, employing a standard IEEE 9 bus system as a benchmark. The execution of LI, PSO, and TLBO methodologies is facilitated through the MATLAB programming language. Comparative analysis reveals TLBO's superior efficacy in optimizing fuel costs, incremental costs, and power losses, outperforming both Power World Simulator and PSO, as well as the lambda iteration method. Noteworthy findings indicate a reduction in total fuel costs, incremental costs, and power losses with an increase in the number of generators, while the introduction of unconnected branch lines to the transformer escalates costs and losses. Furthermore, heightened load demand correlates with increased costs and losses within the system. Additionally, TLBO exhibits a smoother convergence curve in contrast to PSO, further accentuating its optimization capabilities. © 2024 IEEE.Item Studies on Synthesis, Characterization, and Monitoring of Ag NPs for Power Production Using Tomato(Springer Science and Business Media Deutschland GmbH, 2023-06-27) Islam, F.,; Khan, K.A.,; Hossain, M.S.; Rasel, S.R.; Akter, S.In this research paper, tomato extract has been synthesized and characterized for Ag NPs. This synthesized Ag NPs have been used for power production. This produced Ag NPs using tomato extract are very useful and eco-friendly. Different characterizations have been conducted UV-visible spectroscopy, FTIR, XRD, and FESEM. It is found that the absorption peak at around 428 nm for UV-visible spectrum. It is also found that the biomolecule compounds were responsible for the reduction and capping material of silver nanoparticles using FTIR spectra. It is also found that the particles to be crystalline in nature by XRD study, with a face-centered cubic (FCC) structure. The power production activity of Ag NPs was assessed to find their potential use in electrochemical cell. It is found that the open circuit voltage (Voc), short circuit current (Isc), and maximum power (Pmax) were better for using Ag NPs from the tomato extract of a single electrochemical cell.Item Solving Economic Load Dispatch: A Hybrid Approach Integrating Particle Swarm Optimization and Teaching Learning based Optimization(Institute of Electrical and Electronics Engineers Inc., 2024-03-08) Islam, A., Poly, F.A.; , Aktar, S.; Poly, F.A.Power generation must be increased in order to meet demand while minimizing operating costs. In order to reduce these operational costs, such as fuel costs and incremental costs, it is necessary to solve the economic load dispatch (ELD) problem, which requires an optimization process. The purpose of this research is to compare various parameters of a standard IEEE 30 bus system using metaheuristic algorithms, which include teaching learning-based optimization (TLBO), particle swarm optimization (PSO), and a hybrid algorithm that is a combination of PSO and TLBO. In comparison to PSO and TLBO, hybrid PSO-TLBO efficiently optimizes fuel cost, incremental cost, and power loss. Furthermore, an increase in load demand will result in an increase in the system's costs and losses. On the other hand, by increasing the step size of the TLBO method, the total fuel cost and power loss will decrease. However, it may occasionally cause the algorithm to overreach and miss the desired outcome if the step size is not within the standard value. Moreover, the hybrid PSO-TLBO algorithm is intelligent enough to reduce intervals compared to the PSO and TLBO algorithms. © 2024 IEEE.