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Material estimation and energy analysis for a domestic building using Revit architecture and insight: a sustainable approach

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Asian Journal of Civil engineering 2024年第4期25卷 3431-3447页

作者： Veerendra, G.T.N. Dey, Subhashish Mantle, Emma Jane Manoj, Akula Venkata Phani Kumaravel, B. Babu, Padavala Siva Shanmukha Anjaneya Rao, Pusala Kodanda Rama Civil Engineering Department Seshadri Rao Gudlavalleru Engineering College Andhra Pradesh Gudlavalleru India Faculty of Computing Engineering and Science University of South Wales Cardiff United Kingdom Civil Engineering Department Annamalai University Chidambaram India

Using different types of software in the Architecture, engineering and Construction (AEC) industry allows an emerging new trend, where the traditional way of designing and estimating an engineering structure will consume a lot of time and workforce. The intervention of software packages shows the best results and can be seen as a better replacement for manual designing and estimation. The current paper is formulated to investigate two levels among seven levels in BIM and compare the estimation of the material and energy cost of a drafted building. The model considered the climate and location attributes of Cardiff, Wales, U.K. As a part of adopting sustainable development, there is a need to reduce carbon emissions. The focus was to find the selected building material and energy cost estimation. The study building is a residential building with G + 3 (ground + three floors) drafted in the Revit Architecture Building Information Modelling (BIM) software. A detailed estimation of the building was performed to find the building material cost, volume, and total cost. Besides, the different types of materials are proposed for each component. The units presented in this paper are in meters with uniform across the document and the decimal numbers are applied for accuracy. The building model is applied with four different building-type materials, such as concrete for slabs and columns. Where walls with brick type that is commonly used timber and glass for windows are selected, the report shall concentrate on the cost and energy analysis of the different materials that promote BIM levels 1, 2, and 3. The model is developed with auto desk–Revit and insight software for material estimation and energy analysis. Finally, the results are compared with manual estimation to show that the use of BIM modelling can be treated as a sustainable approach that promotes life cycle analysis that allows the project stakeholders to make better decisions before the erection of the structure. ©

关键词： BIM Energy analysis Life cycle analysis Sustainable design

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Enhancing single-lead electrocardiogram arrhythmia detection with empirical mode decomposition

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Neural computing and Applications 2025年第17期37卷 11583-11605页

作者： Issa, Mohamed F. Yousry, Ahmed Tuboly, Gergely Wang, Zeyu Zoltan, Juhasz Selim, Mazen M. AbuEl-Atta, Ahmed H. Department of Scientific Computing Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Computer Science Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Electrical Engineering and Information Systems University of Pannonia Veszprem8200 Hungary Department of Mechatronics Delta University for Science and Technology Gamasa35712 Egypt

Cardiac arrhythmias pose a significant challenge to health care, requiring accurate and reliable detection methods to enable early diagnosis and treatment. However, traditional ECG beat classification methods often lack robustness and fail to generalize effectively to diverse clinical scenarios, particularly when using single-lead-I recordings, which are less studied compared to lead II. To address this gap, this paper proposes a novel method that combines deep learning and empirical mode decomposition (EMD) for arrhythmia detection using single-lead-I ECG recordings obtained with electrodes on each hand. The hybrid model comprises 149 layers of one-dimensional convolution, max pooling, and residual blocks. By leveraging EMD, it classifies ECG beats into normal beats, premature ventricular contractions, and atrial premature beats with high sensitivity (99.86%, 99.72%, and 99.84%, respectively) using the first four intrinsic mode functions (IMFs). The proposed method is applicable in clinical and out-of-hospital monitoring scenarios, and an accompanying web application provides real-time analysis and diagnostic results. This approach addresses a critical gap in lead-I ECG analysis, enhancing diagnostic precision and expanding the scope of ECG applications in health care. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Empirical mode decomposition

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Research on Garbled Circuits-Based Identity Authentication and Ciphertext Hidden Access Control in Vehicular Networks 24

Research on Garbled Circuits-Based Identity Authentication a...

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9th International Conference on Cloud computing and Internet of Things, CCIOT 2024

作者： Jiao, Zhilong Bai, Fenhua Zhang, Chi Zhang, Xiaohui Gong, Bei Faculty of Information Engineering and Automation Kunming University of Science and Technology China Kunming China Department of Computing Beijing University of Technology China Beijing China

ISBN: (纸本)9798400717161

Since most communications in vehicular networks rely on wireless transmissions, information broadcast by vehicles is highly susceptible to interception and eavesdropping by third parties, making it vulnerable to various attacks. This can result in communication messages being tampered with and the leakage of vehicle locations and identity privacy. From a security perspective, this paper introduces Yao's garbled circuit mechanism, combining random bytes with the solutions of linear equations as identity information assigned to vehicle nodes. By employing dual authentication, the proposed approach addresses issues such as privacy protection, anonymity, replay attacks, and collusion attacks in vehicular networks, thereby enhancing security. Moreover, considering the post-authentication access control scenario, this paper proposes a novel LSSS matrix transformation algorithm for ciphertext hidden access control strategy. It realizes a partially hidden policy, which makes matrix generation more efficient by supporting both AND and OR gates, thus improving the access control efficiency while ensuring security. Performance analysis indicates that in terms of identity authentication, the scheme reduces computational costs by an average of 96.25%, and in access control, the scheme reduces key generation time by an average of 80%. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Ciphertext

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Electrical Load Classification Using Combinative Current-Power Characteristics in Time Domain and Machine-Learning-Based NILM Techniques 3rd

Electrical Load Classification Using Combinative Current-Pow...

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3rd International Conference on Advances in Information and Communication Technology, ICTA 2024

作者： Nguyen, Thanh Cong Van Pham, Nam Truong, Hai Nam Nguyen, Ngoc Son Cao, Song Toan Nguyen, Huy Tinh Dang, Quoc-Viet Ware, Jonathan Andrew Nguyen, Ngoc An VNU University of Engineering and Technology Hanoi Viet Nam Samueli School of Engineering University of California Irvine United States Faculty of Computing Engineering and Science University of South Wales Wales United Kingdom

ISBN: (纸本)9783031809422

Non-intrusive load monitoring (NILM) is a large research topic dedicated to the detection and management of electrical loads, drawing international interest in the context of a growing global concern on sustainability in the energy sector. However, most current public datasets offer inadequate and non-unified sets of measured features, electrical devices and measurement methods, causing difficulties in method comparison and the application of research in new environments. In addition, previous studies faced challenges in classifying appliances with small and similar operational power or with large disparities in operational power. In this study, we utilized a combination of current-power characteristics in the time domain (e.g. RMS current (Irms), real power (P), power factor (pf), reactive power (Q), apparent power (S)) to monitor electrical appliances using their steady states. The combinative current-power characteristics were used to train machine learning models that can efficiently distinguish between appliances while addressing the posed challenges. Our dataset comprises 128 device combinations sampled at steady-state from 07 common electrical appliances in Vietnam, collected at a high sampling rate of 600 Hz, resulting in 73 million data points. By leveraging the current-power signatures in the time domain, we achieved a classification accuracy of approximately 99.1%, capable of differentiating between combinations containing devices with small and similar operational power and those with substantial disparities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： appliance classification load disaggregation load monitoring machine learning Non-intrusive Load Monitoring (NILM)

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Improving Biometric Security Using PulsePrint: Real-Time Defense Against Fingerprint Spoofing 2

Improving Biometric Security Using PulsePrint: Real-Time Def...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Vigneshwaran, P. Maranco, M. Ivaturi, Kashyapa Abhiram Takur, Purab Acharya University Department of Computer Science and Engineering Karakul Bukhara Uzbekistan SRM Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Networking and Communications Chengalpattu Kattankulathur603203 India

ISBN: (纸本)9798350365269

Biometric authentication systems have become increasingly popular due to their convenience and perceived security benefits. However, traditional biometric modalities such as fingerprint recognition are vulnerable to spoofing attacks, where fake fingerprints can be used to deceive the system. In this paper, we propose PulsePrint, a novel biometric authentication solution that enhances security by incorporating real-time pulse detection alongside fingerprint recognition. By leveraging the unique pulsatile nature of blood flow in the fingertip, PulsePrint adds an additional layer of authentication, making it significantly more difficult for attackers to spoof fingerprints. We present the design and implementation of the PulsePrint system, detailing the integration of pulse detection algorithms with existing fingerprint recognition technologies. Furthermore, we evaluate the performance of PulsePrint through extensive experimentation, including testing against various spoofing techniques and benchmarking against conventional fingerprint recognition systems. Our results demonstrate that PulsePrint offers robust protection against fingerprint spoofing attacks while maintaining user convenience and real-time authentication speed. Overall, PulsePrint represents a promising advancement in biometric security, offering enhanced protection for applications requiring reliable and secure authentication. © 2024 IEEE.

关键词： Authentication

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Svante Wold 1941 -2022

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Spectroscopy Europe 2022年第1期34卷 27-29页

作者： Davies, Antony N. Sustainable Environment Research Centre Faculty of Computing University of South Wales SERC Engineering and Science United Kingdom

Davies presents an obituary for Svante Wold who died on Jan 4, 2022. Wold wasn't the first statistically talented person in the Wold family, his father Herman Ole Andreas Wold was a famous statistician in his own right, born in Skien, Norway on Christmas Day 1908, Herman and his family emigrated to Sweden where they settled. Svante decided to work in the field of chemical data processing and provided us with the term "Chemometrics".

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Enhancement of Prototype Driving Simulator Using Available AI-Based Game Technology 8th

Enhancement of Prototype Driving Simulator Using Available ...

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8th International Congress on Information and Communication Technology, ICICT 2023

作者： Cheng, Yun-Quan Mansor, Sarina Chin, Ji-Jian Karim, Hezerul Abdul Kar-Weng, Ban Faculty of Engineering Multimedia University Selangor Cyberjaya Malaysia Faculty of Computing and Informatics Multimedia University Selangor Cyberjaya Malaysia Faculty of Science and Engineering University of Plymouth Plymouth United Kingdom

ISBN: (纸本)9789819930906

Simulators—games that simulate the real world in a virtual environment, such as racing simulators, have been widely studied and documented. Their uses could, however, be further expanded into the field of driving education. The motivations behind this study are to dive into the trend of immersive learning and exploit artificial intelligence (AI)-based game technology to benefit driving education. The preliminary work shows that the use of a driving simulator as a teaching tool for driving education has improved the passing rate of driving training. This paper proposes several enhancements to the prototype driving simulator, by utilizing rudimentary AIs to simulate basic traffic for certain scenarios. The driving simulator is developed in Unity and is paired with a driving rig consisting of a steering wheel and pedals. The project currently is a functioning driving simulator that can accept both controller and steering wheel inputs. For prototype enhancement, three scenario-based tracks and a mock-up town with a traffic light system and AI traffic were added. The prototype now includes five circuit tracks and two on-the-road tracks based on the Standard Examination syllabus, three scenario-based tracks, and a mock-up town with AI traffic, together with an automated test mode for the syllabus tracks. The free practice mode will be available for all tracks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Virtual reality

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Exploring information hiding in images – problems and measures: a survey

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Multimedia Tools and Applications 2025年 1-63页

作者： Khan, Ahmed Sarfaraz, Aaliya School of Computer Science Taylor’s University Subang Jaya Malaysia School of Computing and Artificial Intelligence Faculty of Engineering and Technology Sunway University No. 5 Jalan Universiti Selangor Darul Ehsan Bandar Sunway47500 Malaysia

The widespread adoption of digital communication technologies across various domains has led to a significant shift towards digitalization. However, this evolution has also introduced vulnerabilities, including unauthorized access, data manipulation, and fabrication by malicious entities, which severely impact the confidentiality and integrity of information. The proliferation of digital images on the internet has facilitated the use of these media for embedding confidential data in a way that prevents detection or extraction by unauthorized third parties. Despite numerous efforts, existing image steganography and watermarking techniques often lack robustness. This paper proposes several novel strategies to enhance the dynamism and imperceptibility of these techniques, integrating cryptographic methods by manipulating the entropy of encrypted images using minimal pixel value differences and applying unique image transformations. Additionally, the study highlights that implementing multi-layered security mechanisms can protect confidential information from modern statistical steganalysis attacks, thereby preserving both the integrity of hidden data and image quality. A comprehensive review of information hiding, specifically focusing on image watermarking and steganography, is provided. Furthermore, this survey outlines key problem statements and offers quantitative metrics for future research in this area. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Steganography

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Dynamic Android Malware Detection Using Temporal Convolutional Networks

Dynamic Android Malware Detection Using Temporal Convolution...

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2023 IEEE International Conference on computing, ICOCO 2023

作者： Joomye, Abdurraheem Ling, Mee Hong Yau, Kok-Lim Alvin Sunway University Department of Computing and Information Systems Malaysia Lee Kong Chian Faculty of Engineering & Science Malaysia

ISBN: (纸本)9798350302684

As new malware emerges and continues to grow in number with increasing complexity, user applications are foreseen to face greater security challenges. Hence, there is a need to leverage machine learning and deep learning (DL) approaches in Android malware detection. Temporal convolutional network (TCN), is a DL approach which uses causal and dilated 1-dimensional convolution layers to process sequential data, has not been implemented with features extracted through dynamic analysis (e.g. system calls) of Android malware applications. TCN has been shown to achieve higher accuracy in applications dealing with sequential data, with lower delay due to its parallelism and less computationally exhaustiveness. This paper implements TCN for dynamic Android malware detection. Compared to long short-term memory (LSTM), TCN is shown to achieve a similar validation accuracy and a higher steady convergence, with TCN achieving an accuracy of 89.25% and LSTM achieving an accuracy of 88.42% with 1000 system calls. Therefore, it is an effective model for Android malware detection. © 2023 IEEE.

关键词： Android malware

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Broker-Less OPC UA PubSub Communication Model Performance Analysis 30

Broker-Less OPC UA PubSub Communication Model Performance An...

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30th IEEE International Conference on Telecommunications, ICT 2024

作者： Homay, Aydin Chrysoulas, Christos Watt, Tess Wollschlaege, Martin De Sousa, Mario Maglaras, Leandros Technische Universität Dresden Faculty of Computer Science Dresden Germany School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom University of Porto Faculty of Engineering Porto Portugal

ISBN: (纸本)9798350356694

The advent of Industrial Internet of Things (IIoT) has accelerated the adoption of OPC UA (Object Linking and Embedding for Process Control Unified Architecture) PubSub communication models, enabling efficient data exchange in industrial automation systems. This study delves into the performance analysis of a broker-less OPC UA PubSub communication model, a paradigm gaining prominence for its potential to streamline communication in distributed systems. Our methodology involves the establishment of a representative test environment, configuration of OPC UA PubSub components without an intermediary broker, and the design of diverse test scenarios. The results of this performance analysis not only reveal the inherent capabilities of the broker-less OPC UA PubSub communication model but also identify potential bottlenecks and areas for optimization. This research advances our understanding of broker-less OPC UA PubSub communication models, offering empirical evidence of their performance in diverse scenarios. © 2024 IEEE.

关键词： Electronic data interchange

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