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Abstract
This paper introduces a quantum-inspired ultra-lightweight encryption algorithm tailored for Internet of things devices with limited resources. The proposed algorithm excels in processing speed, memory usage, and energy efficiency, significantly outperforming existing lightweight cryptographic algorithms. With a processing speed of 12.4 ms, memory usage of 3.2 kilobytes, and energy consumption of 0.7 milli-Joules per kilobyte, the proposed algorithm stands out for its robust security and potential to enhance the security of Internet of things devices across various applications. This paper explores the methodology behind the proposed algorithm, comparing its performance metrics with conventional S-box generation approaches, and demonstrates its superiority in both theoretical and practical aspects.
Abstract
As urbanization advances and societal shifts unfold, the integration of rural development and activity spaces has become a focal point in academic discourse. This study aims to explore the synergistic effects of the creative market model on rural activity spaces, dissecting its role in shaping these spaces, enhancing community engagement, and generating socio-economic benefits. Empirical findings highlight the affirmative role of the creative market model in this fusion. The research on community participation and spatial design reveals how creative markets enhance residents' sense of involvement and explores the influence of activity space design on community interaction. This study, by thoroughly examining the integration of the creative market model and rural activity spaces, offers theoretical and empirical support for advancing rural development.
Abstract
Automation in the construction has seen progress in using modern techniques, which has opened new perspectives for the verification of construction structures using point clouds. This paper discusses wall structure geometry verification, using point cloud data with geometry information extracted from building information modeling models as reference data. The research is focusing on automating the verification of wall structures using a software solution developed in Python. It involves processing and extracting geometric data from models in industry foundation classes' format, comparing the data and visualization of deviation. Results, conclusion, and future workplans are given for achieving better understanding.
Abstract
Nowadays, predicting the value of electrical usage has made it easier for electricity consumers to reduce their residential bills. This is done by introducing a new prediction method based on the design and foundation of artificial neural network (P-EANN) technology, which is a branch of intelligent machine learning (ML) technology. The P-EANN method is based on actual data of actual power quantities that can be measured by electricity meters for the electrical model and is compared with training data that is predicted and set to the electrical usage for comparison with the reading needed to reduce residential bills. From the root mean square error (RMSE), we can find the accuracy of the residential bills ($) in the P-EANN method, which is equal to 35.69%, and the accuracy of the residential bills ($) in the standard method, which is equal to 0.00%. then the results of the MATLAB simulation for the P-EANN method enhance and reduce the residential bills from 0.5 to 4.5 dollars per day. Thus, the problem of excessive electrical usage is solved, and consumers know how to consume energy well in any place.
Abstract
Reduction of design errors, minimisation of rework and the improvement of the design productivity are key factors in building engineering systems (including structural and architectural solutions, ventilation systems, sewerage systems, water supply and heating systems, power supply systems, and communication networks). These goals can be achieved with a complex approach that prioritises the design of different building engineering systems in the model during the design phase, in order to provide a consistent design for different building engineering systems. The paper presents a novel approach for the application of plugins in building service systems with the elimination of collision in the focus. Collision reduction actions in this methodology are categorised into three levels: the code level, which pertains to plugin developers; the algorithm level, which relates to BIM coordinators; and the user level, which concerns engineers performing the check. This new systematic approach to collision resolution prioritises maintaining the consistency of collision detection across different systems and storing all information about each collision. Collision checking is based on several key factors, such as complying with the sequence of checking systems, excluding irrelevant collisions, and setting tolerances when joining system elements. The aim of our approach is to automate and expedite not only the identification of the intersections but also the subsequent work with it throughout the entire project life cycle. The results are demonstrated by a case study conducted in the frame of a real project.
Abstract
The Energy Management System (EMS) is critical for electric vehicle (EV) in order to optimize energy consumption, improve efficiency, and enhance vehicle performance. The EMS provides the optimization of energy distribution among various vehicle components, reduces energy losses and maximizes the vehicle's efficacy. The EMS reduces battery stress to prevent excessive charging and discharging cycles; thereby, decreases the necessity for premature battery replacement which, in turn, contributes to the battery's life time. The goal of this research is to develop robust control technique to maximize the use of energy storage systems, renewable energy sources and the bidirectional power flow associated with EVs. The proposed robust control approach is based on combination of flatness theory with artificial neural network. The controller is responsible for maintaining the voltage DC bus stabilized and enhancing the quality of the power fed to the EV side. The performance of controlled EMS is verified via computer simulation within MATLAB/SIMULINK environment. As compared to classical proportional-integral (PI) control, the computer results show the proposed controller (FEMS-ANN) gives higher power quality of EV, lower overshot level in the DC voltage, faster response to abnormal conditions, and less steady state error.
Abstract
The rise of e-commerce necessitates sustainable practices for a greener future. While the e-commerce boom offers immense economic opportunities, minimizing its environmental impact and upholding ethical business conduct are essential. Current research on e-commerce heavily focuses on information technology (IT) for understanding and improving consumer acceptance. However, a critical gap exists in exploring IT's potential contributions to sustainability, crime prevention, and environmental safety. This study bridges this gap by exploring the role of IT integration in managerial practices to enhance environmental protection, crime prevention, and foster sustainability within Bangladesh's booming e-commerce sector. Focusing on e-commerce managers' perspectives, the research examines effective leadership strategies for IT implementation. Additionally, it utilizes the Technology Acceptance Model (TAM) to analyze the relationships between user perception and its impact on e-commerce performance. Using a structured questionnaire, we collected the data from 418 e-commerce managers. The research design incorporates a robust framework, hypothesis formulation, and methodological rigor grounded in TAM principles. The findings reveal a significant positive contribution of IT to environmental protection, crime prevention, and overall sustainability within the e-commerce sector. Managers' perceptions highlight that effective IT utilization ensures environmental safety, safeguards data against criminal activity, and promotes organizational sustainability. Furthermore, this research provides a roadmap for e-commerce businesses to accelerate their sustainability efforts. It also equips academics with valuable insights to advance knowledge on building a secure and sustainable future in the digital age.
Abstract
As cities continue to grow and diversify, urban planners, and architects face the challenge of creating housing solutions that can flexibly respond to many demands and changes over time. This rapid change in the urban landscape necessitates adaptable housing design typologies to meet the evolving needs of urban residents. Several residential building, typologies have emerged with the intent of solving the problems arising from overpopulation. This paper aims to shed light on the importance of adaptability in urban housing design and its potential to enhance urban living environments. It reviews adaptability through various urban housing typologies, exploring the concept, its significance, and strategies that can be employed to achieve adaptable dense housing solutions.
Abstract
Wildfire simulations can help to better understand the dynamics and effects of forest fires. The basis of wildfire simulation is the tree-burning simulation. In this paper, the fire simulation of 7 different geometry Hungarian trees in the case of arson is presented. It was observed that the trees were burned down fast. The maximum mass loss rate and maximum heat release rate were larger as the tree was larger. The largest intensity fire could be observed in the case of the smallest tree. The maximum temperature was higher in the case of a large crown diameter. The maximum aerosol reached high pollutant concentrations. In the case of large crown height, the maximum CO2 concentration was higher. The results presented in this paper can be the basis of the following forest fire simulations.
Abstract
An intelligent tutoring system is a computer-based educational tool designed to provide adaptive learning environment to learners, mimicking the role of a human tutor. Its most typical areas of application are language learning, mathematics education, programming courses and medical training. Intelligent Tutoring Systems are based on the knowledge-module that is holding the system's knowledge in a well-structured format. Considering the current state of the art knowledge-module representations, a model that can represent evolving information is lacking. Representing evolving information is needed for those tutoring systems that are working with dynamically changing domains, e.g., software science. In this paper a new combined model is presented that is based on the ontology model and the fundamentals of knowledge space theory. The proposed model introduces the term of abstract time to be able to formulate an evolving knowledge graph. This paper introduces the term of evoking-hooks that makes it possible to realize connections between external domain elements and the nodes of the proposed model.
