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2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Hossain, Md. Sabbir Rumpa, Ummay Khadiza Sharma, Shatabdi Rashid, Mamunur Rahman, Habibur Shovon, Sazzadul Islam East West University Department of Computer Science and Engineering Dhaka Bangladesh Central Michigan University Department of Information System MI United States

ISBN: (纸本)9798331529529

We are dwelling in the golden age of science development. Smart domestic automation has now ended up in the middle of enchantment in the lookup field. The guide machine of switching every so often motives an excessive strength loss. Keeping that in mind, we tried to make a computerized domestic which will now not require any remote, Bluetooth, or any kind of controlling device. In this paper, we have introduced a benchmark contrast of current some hardware the usage of the equal algorithm. For that, we tried to use some sensors, haar cascade documents, and some OpenCV codes for our design. After doing some processes we have chosen a layout that is convenient. In our chosen layout we tend to use a camera, laptop, ARDUINO and made human detection feasible the use of laptop vision. Through the digital camera, rooms are being monitored always, and from that actual time, the image processing presence of human beings is being determined by using the machine automatically. Finally, the microcontroller triggers in accordance with the decision, when it no longer locates any human in the room, it turns the lights, followers, off and on the opposite, it turns the lights, followers, on. © 2024 IEEE.

关键词： Microcontrollers

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A Multi-label Classification Method for Positive and Unlabeled Dataset. 23

A Multi-label Classification Method for Positive and Unlabel...

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Proceedings of the 2023 4th Asia Service Sciences and Software engineering Conference

作者： Hikaru Takahashi Zhao Qiangfu Computer Science and Engineering Computer Information System System Intelligence Lab. University of Aizu Japan Computer Science and Engineering System Intelligence Lab. University of Aizu Japan

ISBN: (纸本)9798400708534

Positive and Unlabeled (PU) learning is a learning method which can be applied to various field such as recommendation and big data analysis. A direct method to solve PU learning is transform it into a weighted classification problem. However, previously proposed methods assume a strict condition. In this paper, we first investigate if the condition can be satisfied in real world situations and then propose a normalized weighted method which can relax the difficultly of PU learning.

关键词： Machine Learning Multi-class Classification Positive and Unlabeled Learning

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Lung Cancer Risk Prediction Features Influence Model Based on Machine Learning Techniques 38

Lung Cancer Risk Prediction Features Influence Model Based o...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Mondal, Subhash Maity, Ranjan Rai, Chirag Pramanik, Souptik Nag, Amitava Central Institute of Technology Kokrajhar Computer Science and Engineering Kokrajhar India Meghnad Saha Institute of Technology Computer Science and Bussiness System Kolkata India

ISBN: (纸本)9798350302196

Currently, lung cancer is a very common form of cancer. This is because many people are chain smokers nowadays, and many are affected due to their work hazards. The pollution level in modern cities is also a major cause of this type of cancer. This model is built to predict the chances of the occurrence of lung cancer in an individual with the help of certain conditions. The acquired dataset used in this study contains multiple features, but not all are necessary for predicting the risk of lung cancer. Hence, an embedding feature importance model Light Gradient Boosting Machine (LGBM) is used to find the impact of every feature, and the model had trained using the features with maximum influence. The dataset has been divided into two parts for training and testing the model. The models achieve a k-fold mean accuracy of 97.63% and above with all the features and more than 93% on the reduced features for all the deployed models. The models are developed based on a resource-constrained device perspective over the reduced features low resource dataset and use an algorithm to measure the execution time taken for every model to run and complete its prediction after fitting with the respective classifiers. The model developed on medical data should have maximum accuracy and is necessary for time efficiency that reflects on all the deployed models with stability and efficacy, indicating the robustness and non-overfitted model. © 2023 IEEE.

关键词： Forecasting

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Heterogeneous system Data Storage and Retrieval Scheme Based on Blockchain 7th

Heterogeneous System Data Storage and Retrieval Scheme Based...

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7th International Conference on Smart Computing and Communication, SmartCom 2022

作者： Zhang, Ni Ma, BaoQuan Wang, Peng Lei, XuHua Cheng, YeJian Li, JiaXin Huai, XiaoYong Shen, ZhiWei Song, NingNing Wang, Long National Computer System Engineering Research Institute of China Beijing102200 China School of Computer Science and Technology Xidian University Xi’an710071 China

ISBN: (纸本)9783031281235

In the field of information interaction, when a project involves a large amount of heterogeneous information, it is difficult to transmit and update the required information timely, accurately, reliably and securely in such a complex environment to maintain synchronization. At present, blockchain itself has problems such as high storage pressure of nodes, low access efficiency, and simple query. Therefore, this paper takes this as a starting point and proposes a data mapping method of physical resources based on node attributes and heterogeneous nodes, which provides a general method for the data mapping from actual physical resources to information domain. This method can define the attributes of heterogeneous physical information nodes and support unified expression of various physical information resources on the same platform in the real physical world, then connect heterogeneous physical information nodes and improve the sharing ability of data resources between nodes. When accessing data, the corresponding content can be found in the off-chain database by obtaining the index information of the off-chain location stored on the chain. This method takes advantage of the large space and high access efficiency of the off-chain storage system to share the pressure of on-chain data storage. This paper expounds the design idea of the system, introduces the design objective and method in detail, gives the flow chart of the system operation, and carries out a simple software test and verification. Finally, this paper summarizes the work and prospects the development direction of future work, hoping to provide inspiration for solving such problems. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Blockchain

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An Integrated Demand Side Management Framework Utilizing Smart Grid Technologies and IoT for Enhanced Residential Energy Efficiency

An Integrated Demand Side Management Framework Utilizing Sma...

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2024 IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2024

作者： Venkatesan, P. Gopinath, C. Prabhavathy, P. Department of Electrical and Electronics Engineering India Center for Integrated Smart Waste Management System Department of Electrical and Electronics Engineering Sriperumbudur India Anna University Department of Computer Science and Engineering College of Engineering Guindy Chennai India

ISBN: (纸本)9798331535476

Increasing energy demands and the need for efficient management necessitate innovative solutions. This study introduces an integrated Demand Side Management (DSM) framework tailored for residential buildings within smart grid systems. The proposed methodology employs Earth Worm Optimization Algorithm (EWOA) and Virulence Optimization Algorithm (VOA) to optimize scheduling for household appliance using integration of Renewable Energy Storage (RES) and Renewable Energy Resources (RERs). Real-Time Electricity Scheduling (RTES) is implemented using IoT technologies to enable adaptive energy management. This system demonstrates significant performance improvements, achieving a 76.19% reduction in the Peak-to-Average Ratio (PAR) using VOA and a 73.8% reduction with EWOA when RES is included. Comparative analyses highlight substantial cost reductions, enhanced grid stability, and improved energy efficiency. This work not only showcases the novelty of integrating advanced optimization algorithms with IoT but also provides a robust approach to achieve sustainable and cost-effective energy management. © 2024 IEEE.

关键词： Smart power grids

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Real-Time 4-Mode MDM Transmission Using Commercial 400G OTN Transceivers and All-Fiber Mode Multiplexers

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ZTE Communications 2024年第1期22卷 106-110页

作者： REN Fang LI Yidan YE Bing LIU Jianguo CHEN Weizhang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Department of WDM System Design ZTE CorporationBeijing 100029China

Weakly-coupled mode division multiplexing(MDM)technique is considered a promising candidate to enhance the capacity of an optical transmission system,in which mode multiplexers/demultiplexers(MMUX/MDEMUX)with low insertion loss and modal crosstalk are the key *** this paper,a low-modal-crosstalk 4-mode MMUX/MDEMUX for the weakly-coupled triple-ring-core few-mode fiber(TRC-FMF)is designed and fabricated with side-polishing *** measurement results show that a pair of MMUX/MDEMUX and 25 km weakly-coupled TRC-FMF MDM link achieve low modal crosstalk of lower than−17.5 dB and insertion loss of lower than 11.56 dB for all the four *** on the TRC-FMF and all-fiber MMUX/MDEMUX,an experiment for 25 km real-time 4-mode 3-λwavelength division multiplexing(WDM)-MDM transmission is conducted using commercial 400G optical transport network(OTN)*** experimental results prove weakly-coupled MDM techniques facilitate a smooth upgrade of the optical transmission system.

关键词： optical fiber couplers mode(de)multiplexers mode division multiplexing transmission

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Machine learning classifiers with pre-processing techniques for rumour detection on social media: an empirical study

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International Journal of Cloud Computing 2022年第4期11卷 330-344页

作者： Al-Sarem, Mohammed Al-Harby, Muna Saeed, Faisal Hezzam, Essa Abdullah College of Computer Science and Engineering Taibah University Medina Saudi Arabia Saba'a Region University Mareb Yemen Information System Department College of Computer Science and Engineering Taibah University Medina Saudi Arabia

The rapid increase in popularity of social media helped the users to easily post and share information with others. However, due to uncontrolled nature of social media platforms, such as Twitter and Facebook, it becomes easy to post fake news and misleading information. The task of detecting such problem is known as rumour detection. This task requires data analytics tools due to the massive amount of shared content and the rapid speed at which it is generated. In this work, the authors aimed to study the impact of different text pre-processing techniques on the performance of classifiers when performing rumour detection. The experiments were performed on a dataset of tweets on emerging breaking news stories which cover several events of Saudi political context (EBNS-SPC). The results have shown that pre-processing techniques have a significant impact on increasing the performance of machine learning methods such as support vector machine (SVM), multinomial naïve Bayes (MNB), and K-nearest neighbour (KNN) classifiers. However, the classifiers react differently when different combinations of pre-processing techniques were used. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Support vector machines

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A Composite Decomposition Method for Large-Scale Global Optimization

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6304-6319页

作者： Tian, Maojiang Chen, Minyang Du, Wei Tang, Yang Jin, Yaochu Yen, Gary G. Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China East China University of Science and Technology Engineering Research Center of Process System Engineering Ministry of Education Shanghai200237 China Westlake University School of Engineering Hangzhou310030 China Oklahoma State University School of Electrical and Computer Engineering StillwaterOK74048 United States

Cooperative coevolution (CC) algorithms, based on the divide-and-conquer strategy, have emerged as the predominant approach to solving large-scale global optimization (LSGO) problems. The efficiency and accuracy of the grouping stage significantly impact the performance of the optimization process. While the general separability grouping (GSG) method has overcome the limitation of previous differential grouping (DG) methods by enabling the decomposition of nonadditively separable functions, it suffers from high computational complexity. To address this challenge, this article proposes a composite separability grouping (CSG) method, seamlessly integrating DG and GSG into a problem decomposition framework to utilize the strengths of both approaches. CSG introduces a step-by-step decomposition framework that accurately decomposes various problem types using fewer computational resources. By sequentially identifying additively, multiplicatively and generally separable variables, CSG progressively groups nonseparable variables by recursively considering the interactions between each nonseparable variable and the formed nonseparable groups. Furthermore, to enhance the efficiency and accuracy of CSG, we introduce two innovative methods: a multiplicatively separable variable detection method and a nonseparable variable grouping method. These two methods are designed to effectively detect multiplicatively separable variables and efficiently group nonseparable variables, respectively. Extensive experimental results demonstrate that CSG achieves more accurate variable grouping with lower computational complexity compared to GSG and state-of-the-art DG-series designs. © 2024 IEEE.

关键词： Computational efficiency

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A reliable method for data aggregation on the industrial internet of things using a hybrid optimization algorithm and density correlation degree

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Cluster Computing 2024年第6期27卷 7521-7539页

作者： Heidari, Arash Shishehlou, Houshang Darbandi, Mehdi Navimipour, Nima Jafari Yalcin, Senay Department of Software Engineering Haliç University Istanbul34060 Turkey Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran Pôle Universitaire Léonard de Vinci Paris France Department of Computer Engineering Kadir Has University Istanbul Turkiye and Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan Department of Energy System Engineering School of Engineering and Natural Sciences Bahçeşehir University Istanbul Turkey

The Internet of Things (IoT) is a new information technology sector in which each device may receive and distribute data across a network. Industrial IoT (IIoT) and related areas, such as Industrial Wireless Networks (IWNs), big data, and cloud computing, have made significant strides recently. Using IIoT requires a reliable and effective data collection system, such as a spanning tree. Many previous spanning tree algorithms ignore failure and mobility. In such cases, the spanning tree is broken, making data delivery to the base station difficult. This study proposes an algorithm to construct an optimal spanning tree by combining an artificial bee colony, genetic operators, and density correlation degree to make suitable trees. The trees’ fitness is measured using hop count distances of the devices from the base station, residual energy of the devices, and their mobility probabilities in this technique. The simulation outcomes highlight the enhanced data collection reliability achieved by the suggested algorithm when compared to established methods like the Reliable Spanning Tree (RST) construction algorithm in IIoT and the Hop Count Distance (HCD) based construction algorithm. This proposed algorithm shows improved reliability across diverse node numbers, considering key parameters including reliability, energy consumption, displacement probability, and distance. © The Author(s) 2024.

关键词： Reliability

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Stable Stochastic MPC for Uncertain Wind Energy Conversion system Over Whole Operating Regions

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IEEE Transactions on Energy Conversion 2025年第1期40卷 515-528页

作者： Liu, Xiangjie Guo, Shifan Ma, Lele Kong, Xiaobing Lee, Kwang Y. North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China Baylor University Department of Electrical and Computer Engineering WacoTX76798-7356 United States

The stochastic uncertainty of wind speed presents a great challenge for achieving reliable power control in wind energy conversion system (WECS). Due to the excellence in handling the uncertainties based on probabilistic descriptions, stochastic model predictive control (SMPC) has been regarded as a promising strategy for WECS. However, owing to fluctuation characteristic of wind speed, operating points commonly change in WECS. Thus, an important limitation of applying SMPC to WECS stems from the fact that feasibility and stability of the traditional SMPC can only be ensured at one single predesigned operating point. Regarding this issue, a stable SMPC strategy for uncertain WECS is proposed in this paper to ensure the feasibility and stability of WECS under changing operating points over the whole operating regions. A Luenberger observer is employed to estimate model-plant mismatch introduced by linearization process, while a tube-based control framework is deployed to cope with stochastic wind speed disturbance. The feasibility of SMPC is ensured by incorporating artificial steady targets as optimization variables, while the stability of WECS is guaranteed by modifying the cost function and extending the terminal constraint. The effectiveness of the proposed strategy is validated through simulations and experiments under different scenarios. © 1986-2012 IEEE.

关键词： Stochastic systems

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