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Experiments and modeling on thermal performance evaluation of standalone and M-cycle based desiccant air-conditioning systems

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Energy Reports 2024年 11卷 1445-1454页

作者： Bhat, Showkat Ahmad Sajjad, Uzair Hussain, Imtiyaz Yan, Wei-Mon Raza, Hafiz M.U. Ali, Hafiz Muhammad Sultan, Muhammad Omar, Hani Azam, Muhammad Waheed Bozzoli, Fabio Huang, Nen-Fu Center of Innovative Incubator National Tsing Hua University Hsinchu300044 Taiwan Department of Computer Science National Tsing Hua University Hsinchu300044 Taiwan Department of Energy and Refrigerating Air-Conditioning Engineering National Taipei University of Technology Taipei10608 Taiwan Research Center of Energy Conservation for New Generation of Residential Commercial and Industrial Sectors National Taipei University of Technology Taipei10608 Taiwan Department of Agricultural Engineering Bahauddin Zakariya University Bosan Road Multan60800 Pakistan Dhahran31261 Saudi Arabia Faculty of Information Technology Zarqa University Zarqa Jordan Department of Architecture and Engineering University of Parma Parco Area delle Science 181/A Parma43124 Italy IRC-Renewable Energy and Power Systems King Fahd University of Petroleum and Minerals Dammam Dhahran Saudi Arabia

This study aims to evaluate the performance of standalone and Maisotsenko-cycle based desiccant air-conditioning systems with silica gel through experimental and explainable artificial intelligence methods. In order to examine the desiccant systems' performance, deep neural networks have been constructed based on the optimal hyper-parameters provided by the Bayesian surrogacy. The influential factors, such as regeneration air temperature and relative humidity, primary air temperature and relative humidity, among other system features like regeneration temperature and humidity, are chosen as the inputs using feature engineering and correlation heat maps. The results indicated that with the right framework and training data, the proposed model can forecast the performance of the standalone and M-cycle-based desiccant air conditioning systems with a great accuracy (i.e. R2 = 0.99). In addition, regeneration temperature and humidity, and inlet regeneration air temperature are considered to be the primary parameters that affect the thermal performance of Maisotsenko-cycle and stand-alone desiccant systems. The regeneration conditions are shown to have a positive correlation with the primary and regeneration outlet temperatures while having a negative correlation with the primary and regeneration outlet relative humidity. The primary inlet relative humidity has the greatest impact on the primary outlet relative humidity while the regeneration inlet temperature has the highest impact on the regeneration outlet relative humidity of the system. In addition, the primary inlet relative humidity is found to have positive correlations with the outlet regeneration and primary relative humidity and outlet regeneration temperature. Also, the primary air inlet temperature is found to be directly associated with the outlet primary relative humidity and temperature for the considered systems. © 2024 The Authors

关键词： Air conditioning

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Predictive analysis of stochastic stock pattern utilizing fractional order dynamics and heteroscedastic with a radial neural network framework

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Engineering Applications of Artificial Intelligence 2024年 135卷

作者： Bukhari, Ayaz Hussain Raja, Muhammad Asif Zahoor Alquhayz, Hani Almazah, Mohammed M.A. Abdalla, Manal Z.M. Hassan, Mehdi Shoaib, Muhammad Department of Computer Science Air University Islamabad44000 Pakistan Future Technology Research Center National Yunlin University of Science and Technology Section 3 123 University Road Douliou Yunlin64002 Taiwan Department of Computer Science and Information College of Science in Zulfi Majmaah University Al-Majmaah 11952 Saudi Arabia King Khalid University Muhyil Saudi Arabia Yuan Ze University AI Center 320 Taoyuan Taiwan

Modelling of high-dimension chaotic, noisy, and non-stationary time series of complex fractal dynamics is a big challenge. In this research work, a novel approach of Leverage Convolution LC ARFIMA– GARCH model is presented for sequential learning of irregular, fractal dynamic patterns of stochastic time series dynamics. Different classical methods including the auto-regressive approach indecently are unable to capture fragile patterns and consequently convert some weak signals into random errors by creating white noise patterns. The Convolution Leverage provides an additional degree of freedom for critical noisy points and asymmetrical distribution dynamics to regulate the frequency of imbalance and skewed observation. The designed transformation in the ARFIMA model preserves the loss of information by shifting the skewed data distribution toward a normal pattern. The pattern of population parameters in the proposed leverage paradigm provides out of box approach to track and extract additional information on population variance patterns in the form of an additional degree of freedom to stabilize imbalance signals. The model can provide reliable performance for long-range dependence, particularly for mean reversion chaotic phase variation at critical non-differentiable points. The performance of the dynamic model is verified on chaotic real data of the Ireland Stock Market (ISEQ). The result statistics confirmed the optimized outcome with the addition of the GARCH heteroscedastic multimodal and radial basis neural network. The novel technique can help to address inherited challenges in the imbalance learning and extreme events of the time series modeling by monitoring the chaotic trajectory of fractal physical phenomena, particularly in, finance healthcare, climate, and intelligent sustainability. © 2024 Elsevier Ltd

关键词： White noise

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Human movement science-informed multi-task spatio temporal graph convolutional networks for fitness action recognition and evaluation

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Applied Soft Computing 2024年 164卷

作者： Chang, Jia-Wei Chen, Ming-Hung Ma, Hao-Shang Liu, Hao-Lan Department of Computer Science and Information Engineering National Taichung University of Science and Technology No. 129 Section 3 Sanmin Road North District Taichung City404 Taiwan Physical Education Section National Taichung University of Science and Technology No. 129 Section 3 Sanmin Road North District Taichung City404 Taiwan

In recent years, with the rise of health consciousness, people's demand for fitness has steadily increased. Utilizing automated human action recognition technology to monitor users’ movements during exercise continuously would help prevent situations where incorrect movements lead to injuries while working out. Skeleton-based human action recognition methods can overcome the susceptibility of past color-based and depth-based methods to various external backgrounds and noise, becoming a more successful solution in recent years. In this study, the auto-fitness advisor system we propose not only identifies the category of the action but also assesses the quality of the action and provides suggestions. We integrate human movement science, such as the Five Primary Kinetic Chains (5PKC), which defines the primary physiological principles in human movement, to enhance the accuracy of fitness action recognition by providing a more precise relationship between the human skeleton and muscles. For assessing the quality of movements and providing suggestions, we have designed a multi-task objective function within our model. Overall, the proposed model is a multi-task model based on Spatio Temporal Graph Convolutional Networks (ST-GCN), which employs the Five Primary Kinetic Chains (5PKC) as a partitioning strategy for skeletal information. In our experiments, we not only collected a certain amount of datasets in gyms to validate the performance of our model but also compared it with other current methods using existing public datasets. © 2024 Elsevier B.V.

关键词： Kinetics

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Numerical Feature Preprocessing Method for Daily Solar Radiation Pattern Classification 15th

Numerical Feature Preprocessing Method for Daily Solar Radia...

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15th International Conference on computer science and its Applications, CSA 2023 and 17th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2023

作者： Li, You Wang, Yafei Zheng, Ying Qian, Hui Zhou, Weisheng Dual-Carbon Research Center Hangzhou City University Hangzhou310015 China Asia-Japan Research Institute Ritsumeikan University Ibaraki567-8570 Japan School of Civil Engineering and Architecture Zhejiang University of Science and Technology Hangzhou310023 China Department of Computer Science and Information Technologies Frostburg State University FrostburgMD21532 United States College of Policy Science Ritsumeikan University Ibaraki567-8570 Japan

ISBN: (纸本)9789819724468

One challenging issue in daily solar radiation classification involves addressing the geometric differences in daily solar radiation patterns caused by geographic location and seasonal influences. A standardization method based on matrix transformation has been proposed to eliminate the daily geometric variations of solar radiation using classification for daily patterns of solar radiation. This method was tested using measurements taken at the Tokyo monitoring station from 2000 to 2021. Through the implementation of the proposed classification algorithm, this paper discerned twelve categories of daily clearness index distributions. The suggested classification framework has the potential to assist in the development of solar radiation transformation systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Solar irradiance

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Leveraging Machine Learning for Crime Intent Detection in Social Media Posts 1st

Leveraging Machine Learning for Crime Intent Detection in ...

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1st International Conference on AI-generated Content, AIGC 2023

作者： Bokolo, Biodoumoye George Onyehanere, Praise Ogegbene-Ise, Ebikela Olufemi, Itunu Tettey, Josiah Nii Armah Department of Computer Science Sam Houston State University HuntsvilleTX77340 United States Department of Architecture Technology and Engineering University of Brighton BrightonBN2 4AT United Kingdom Department of Computer and Software Engineering Kennesaw State University KennesawGA United States Department of Computer Science and Quantitative Methods Austin Peay State University ClarksvilleTN37044 United States Department of Computer Science and Engineering Wright State University DaytonOH45435 United States

ISBN: (纸本)9789819975860

Detecting crime intent from user-generated content on social media platforms has become increasingly important for law enforcement and crime prevention. This paper presents a comprehensive approach for crime intent detection from user tweets using machine learning techniques. The study utilizes a dataset of about 400,000 tweets and applies data preprocessing, feature selection, and model training with logistic regression, ridge regression classifier, Stochastic Gradient Descent (SGD) classifier, Random Forests, and support vector machine models. Evaluation metrics such as accuracy, precision, recall, and F1 score are employed to assess the models’ performance. The results reveal that the logistic regression model achieves the highest accuracy ratio of 0.981 in detecting crime intent from tweets. This research showcases the effectiveness of machine learning and advanced transformer-based models in leveraging social media data for crime analysis. The findings provide valuable insights into the potential for early detection and monitoring of crime intent using online platforms, contributing to the field of crime prevention and law enforcement. The utilization of machine learning techniques offers new avenues for understanding and analyzing crime-related sentiments expressed by social media users. By accurately detecting crime intent from user-generated content, law enforcement agencies can enhance their proactive measures, monitor public sentiment towards crime, and shape policies and interventions to address public concerns effectively. The research highlights the significance of leveraging social media data for crime detection and emphasizes the potential impact of advanced machine learning models in improving public safety and crime prevention efforts. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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An Approach for Evaluating the Potential Impact of Anti-Patterns on Microservices Performance

An Approach for Evaluating the Potential Impact of Anti-Patt...

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IEEE International Conference on Software architecture Workshops (ICSAW)

作者： Raghad Matar Jasmin Jahić Department of Architecture-Centric Engineering Fraunhofer Institute for Experimental Software Engineering Kaiserslautern Germany Department of Computer Science and Technology University of Cambridge Cambridge UK

The microservices architectural style has been increasingly adopted in recent years due to its advantageous characteristics. While there exist design patterns for microservices that are theoretically beneficial for ensuring performance (and anti-patterns that should be avoided), they do not always lead to the expected impact. Some designs are solutions for achieving quality properties other than performance, and while they might be categorized as anti-patterns in theory, their influence on system performance can be minimal, depending on the context. Architects find it hard to reason about these trade-offs and the impact that design decisions will have on performance before implementing them. To solve this problem, in this paper, we propose an approach that enables rapid evaluation of high-level architectural models by combining both static and dynamic analysis. The static analysis identifies the design anti-patterns that are known to hinder system performance and guides the architect in reasoning about these design decisions. The approach then generates source code for the system under study based on the architectural design model for a subsequent dynamic analysis to assess whether the statically detected anti-patterns do indeed have a negative effect on the performance of the analyzed system.

关键词： Analytical models Software architecture System performance Source coding Microservice architectures Static analysis Cognition

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Evaluation of Critical Factors in Urban Matrix Environment from the Perspective of Ecological Design

Evaluation of Critical Factors in Urban Matrix Environment f...

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2022 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2022

作者： Hou, Yi-You Liu, Kuang-Sheng Lin, Jiun-Hung Lin, Ming-Hung Tin, Lou-Yang National Kaohsiung University of Science and Technology Department of Intelligent Commerce Kaohsiung City Taiwan Cheng Shiu University Department of Architecture and Interior Design Kaohsiung City Taiwan College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Cheng Shiu University Department of Electrical Engineering Kaohsiung City Taiwan

ISBN: (数字)9781665495875

ISBN: (纸本)9781665495875

The ecological environment of human-centered habitats, cities, is gradually emphasized that the idea of sustainable development is proposed to stress on the integration of development and conservation. Besides, under current resource-applied environment, long-term management of resources is planned and used for preventing resources from shortage. Current development of urban central areas is about saturated, and the rapid expansion of urban fringe is about out of control. Effective recovery of urban landscape ecological structure and function as well as retention, restoration, and regeneration of urban natural environment to balance urban ecosystem and natural ecosystem are primary issues to improve urban environmental quality. Aiming at residents in Kaohsiung City, as the questionnaire objects, 360 copies of questionnaire are distributed as the research samples, and 294 valid copies are retrieved, with the retrieval rate 82%. The research results show *** ecology as the most emphasized dimension in the evaluation of urban matrix environment from the perspective of ecological design, and *** five mostly emphasized indicators, among 20, are green coverage ratio, provision of learning opportunities, diversity of plant species, recoverable materials, and participation ways. According to the results to propose the conclusion. It is expected to dig out specific opportunities for the sustainable use and development of urban matrix and to develop a complete and systematic landscape ecological network, with the combination with other landscape elements, to promote urban ecological quality. © 2022 IEEE.

关键词： Ecosystems

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Safety Guaranteed Power-Delivered-to-Load Maximization for Magnetic Wireless Power Transfer

Safety Guaranteed Power-Delivered-to-Load Maximization for M...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Wangqiu Zhou Xinyu Wang Hao Zhou Shenyao Jiang Zhi Liu Yusheng Ji LINKE Lab School of Computer Science and Technology University of Science and Technology of China CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China Deqing Alpha Innovation Institute Huzhou China Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Electromagnetic radiation (EMR) safety has always been a critical reason for hindering the development of magneticenabled wireless power transfer technology. People focus on the actual received energy at charging devices while paying attention to their health. Thus, we study this significant problem in this paper, and propose a universal safety guaranteed power-delivered-to-load (PDL) maximization scheme (called SafeGuard). Technically, we first utilize the off-the-shelf electromagnetic simulator to perform the EMR distribution analysis to ensure the universality of the method. Then, we innovatively introduce the concept of multiple importance sampling for achieving efficient EMR safety constraint extraction. Finally, we treat the proposed optimization problem as an optimal boundary point search problem from the perspective of space geometry, and devise a brand-new grid-based multi-constraint parallel processing algorithm to efficiently solve it. We implement a system prototype for SafeGuard, and conduct extensive experiments to evaluate it. The results indicate that our SafeGuard can obviously improve the achieved PDL by up to 1.75× compared with the state-of-the-art baseline while guaranteeing EMR safety. Furthermore, SafeGuard can accelerate the solution process by 29.12× compared with the traditional numerical method to satisfy the fast optimization requirement of wireless charging systems.

关键词： Performance evaluation Monte Carlo methods System performance Inductive charging Prototypes Wireless power transfer Parallel processing

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Fractional order swarming intelligence for multi-objective load dispatch with photovoltaic integration

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Engineering Applications of Artificial Intelligence 2024年第PartA期137卷

作者： Muhammad, Yasir Chaudhary, Naveed Ishtiaq Sattar, Babar Siar, Babar Awan, Saeed Ehsan Raja, Muhammad Asif Zahoor Shu, Chi-Min Department of Electrical and Computer Engineering COMSATS University Islamabad Attock Campus Attock Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin64002 Taiwan Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin64002 Taiwan

In this research work, the concept of fractional calculus is integrated inside the mathematical model of the canonical particle swarm optimization (i.e., FPSO) to enhance its optimization characteristics, namely its convergence rate, for solving the combined economic emission and load dispatch problems in the power systems. The proposed FPSO is exploited by tuning the output of the thermal and photovoltaic generation to reduce the overall operational cost, emissions, and line losses while meeting the consumer power demand in the standard Institute of Electrical and Electronic Engineering (IEEE) 30 bus network. The outcomes of the FPSO are compared with their recent state-of-the-art counterparts to endorse its efficacy for solving economic load dispatch problem, while the reliability and consistency of the FPSO are additionally confirmed through statistical illustrations that include the minimum fitness gauges in each independent execution, boxplot illustrations, histograms, plots for normal distribution, boxplots for time complexity, plots for Weibull distribution, plots for the cumulative distribution function, and quantile–quantile plots as a gauge of the diversity and central tendency. © 2024 Elsevier Ltd

关键词： Particle swarm optimization (PSO)

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The evolution of inharmonicity and noisiness in contemporary popular music

arXiv

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arXiv 2024年

作者： Deruty, Emmanuel Meredith, David Lattner, Stefan Sony Computer Science Laboratories 6 rue Amyot Paris75005 France Department of Architecture Design and Media Technology Aalborg University Rendsburggade 14 Aalborg9000 Denmark

Much of Western classical music relies on instruments based on acoustic resonance, which produce harmonic or quasi-harmonic sounds. In contrast, since the mid-twentieth century, popular music has increasingly been produced in recording studios, where it is not bound by the constraints of harmonic sounds. In this study, we use modified MPEG-7 features to explore and characterise the evolution of noise and inharmonicity in popular music since 1961. We place this evolution in the context of other broad categories of music, including Western classical piano music, orchestral music, and musique concrète. We introduce new features that distinguish between inharmonicity caused by noise and that resulting from interactions between discrete partials. Our analysis reveals that the history of popular music since 1961 can be divided into three phases. From 1961 to 1972, inharmonicity in popular music, initially only slightly higher than in orchestral music, increased significantly. Between 1972 and 1986, this rise in inharmonicity was accompanied by an increase in noise, but since 1986, both inharmonicity and noise have moderately decreased. In recent years (up to 2020), popular music has remained much more inharmonic than popular music from the 1960s or orchestral music involving acoustic resonance instruments. However, it has become less noisy, with noise levels comparable to those of orchestral music. We relate these trends to the evolution of music production techniques. In particular, the use of multi-tracking may explain the higher inharmonicity in popular music compared to orchestral music. We illustrate these trends with analyses of key artists and *** Codes 68T05, 42C40 © 2024, CC BY.

关键词： Background noise

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