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检索条件"丛书名=Lecture Notes in Networks and Systems"

共 9905 条记录，以下是2271-2280 订阅

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Selection of Refrigerant for Data Center Cooling System Utilising MOORA MCDM Method 10th

Selection of Refrigerant for Data Center Cooling System Util...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Kadric, Dzana Blazevic, Rejhana Vatres, Ajdin Kadric, Edin Univ Sarajevo Fac Mech Engn St Vilsonovosetaliste 9 Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662676;9783031662683

This paper presents the findings of a study aimed at identifying the most efficient refrigerant for cooling systems in data centers. Given the high cooling demands of data centers, which result in substantial energy consumption, the selection of best performing refrigerant can significantly decrease energy consumption and environmental impact. The cooling system of data center, located in Sarajevo, is analysed with cooling load modelled in DesignBuilder software. Five potential alternatives to the current R410A refrigerant were evaluated for 77 kW single stage cooling system, with an internal heat exchanger (IHX). The Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) method was used to rank the refrigerants based on six criteria, including technical, environmental, safety, and cost criteria. The objective was to minimize environmental impact, safety and cost while maximizing the system coefficient of performance (COP). The MOORA method was used to evaluate and rank the refrigerants and select the best performing for use in considered cooling system.

关键词： data center refrigerant selection GWP COP MOORA method

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Hepatitis C Diagnosis Using Computational Intelligence Techniques

Hepatitis C Diagnosis Using Computational Intelligence Techn...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Cedolin, Michele Genevois, Mujde Erol Canbulat, Zeynep Amer Univ Middle East Coll Engn & Technol Kuwait Kuwait Galatasaray Univ Fac Engn & Technol Istanbul Turkiye

ISBN: (纸本)9783031671913;9783031671920

The global impact of chronic Hepatitis C virus (HCV) infections, estimating around 58 million affected individuals worldwide with 1.5 million new cases annually. In 2019, approximately 290,000 deaths were attributed to Hepatitis C, as per the World Health Organization (WHO). Despite the availability of numerous laboratory tests for liver disease assessment, patients often show normal range laboratory values, and there are asymptomatic cases. The passage highlights the necessity for a sophisticated system to diagnose the disease accurately and efficiently, emphasizing the support of machine learning in this endeavor. It mentions the use of HCV data from the "UCI Machine Learning Repository" and the application of six computational intelligence algorithms, namely, logistic regression, random forest, k-NN, SVM, light-GBM, and XG-Boost. After data normalization, imputation, and oversampling processes light-GBM showed the best performance with 98,9% accuracy.

关键词： Hepatitis C Risk Analysis Machine Learning Health Data

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Fuzzy Models and Optimization by Distillation Units in the Aspenhysys Software Environment

Fuzzy Models and Optimization by Distillation Units in the A...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Rustambekovich, Yusupbekov Nodirbek Tulkunovich, Adilov Farux Alibekovich, Aytbaev Janibek Tashkent State Tech Univ Tashkent Uzbekistan LLC XIMAVTOMATIKA Tashkent Uzbekistan

ISBN: (纸本)9783031671944;9783031671951

Developed fuzzy models and optimization of a deethanizer distillation column in the aspenhysys software environment. This article presents the results of studies related to fuzzymodeling of distillation columns using the example of a typical deethanizer. A fuzzy computer model and optimization based on mathematical process modeling has been developed, which describes in detail technological processes using differential equations of energy transfer, material balance, hydraulics and physico-chemical kinetics inside the distillation column.

关键词： Aspenhysys software environment ethane deethanizer reflux distillation column

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Cyber Attacks and Review of Recent Data Breach Incidents Their Trends and Measures

Cyber Attacks and Review of Recent Data Breach Incidents The...

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2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： Prajapat, Shaligram Gaur, Aishwarya Singh Soni, Priyanshi Nagar, Nitin Goswami, Prakshep Int Inst Profess Studies DAVV Indore India Tata Consultancy Serv Ahmadabad Gujarat India

ISBN: (纸本)9783031744426;9783031744433

With the exponential growth of AI and advanced computing facilities, data breaches their trend and impact is the common talk of the town of the cyberspace. The periodic cyber-attack analysis is also important to find trends or shifts in cyberspace. It is also important to understand how these attacks impact organisational, personal, financial, and national security data. This paper presents a review of security incidents over the past 20 years, highlighting the consequences on organisations. The outcome of this study is to be aware that cyber incidents can severely disrupt organisational operations and damage reputations. The cost of recovery from cyber incidents, particularly ransom ware attacks is also one of the objectives of this study. Finally, the attack tree model and associated risk assessment metrics have been discussed.

关键词： Cyber Attack Data breach Phishing Ransomware Financial loss zero trust

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Aspect-Based Sentiment Classification Using Supervised Classifiers and Polarity Prediction Using Sentiment Analyzer for Mobile Phone Tweets 1

引用

4th Congress on Intelligent systems (CIS)

作者： Venkatesh, Naramula Kalavani, A. SR Univ Warangal Andhra Pradesh India Rajalakshmi Engn Coll Chennai Tamil Nadu India

ISBN: (数字)9789819990375

ISBN: (纸本)9789819990368;9789819990375

Twitter platform finds an important part in social marketing, election campaigns, academia and news. Sentiment analysis came into existence for finding polarities on different domains based on customer tweets online such as to check the opinions of people on a particular topic. Aspect-based sentiment analysis (ABSA) is a text analysis which identifies an entity or feature present in a given sentence and provides an opinion according to the given aspect. In this paper, we proposed an automatic approach for aspect sentiment classification and polarity prediction using mobile phone tweets. So, research contribution is given in the modules of tweets collection and preprocessing, implicit aspect term extraction towards sentiment classification and polarity prediction for mobile phone tweets. In order to predict sentiment polarity for aspect category, we use Vander sentiment analyzer and predict overall polarity as a compound value.

关键词： ABSA ATP ATE Mobile phone

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An Anomaly Detection Framework for IIoT in Agriculture 9th

An Anomaly Detection Framework for IIoT in Agriculture

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9th International Congress on Information and Communication Technology (ICICT)

作者： Swate, Clementine Sithungu, Siphesihle Philezwini Lebea, Khutso Univ Johannesburg Johannesburg South Africa

ISBN: (纸本)9789819733019;9789819733026

The Industrial Internet of Things (IIoT) has ushered in a transformative era in global food production and sustainability, with a profound impact on agriculture and farming practices. This technological advancement has paved the way for precision agriculture, revolutionizing crop cultivation, animal management, and supply chain operations. However, the same advancement introduced challenges, underscoring the need for robust anomaly detection systems to promote the safety, efficacy, and reliability of IIoT-based farming practices. This paper delves into the intricate landscape of IIoT in agriculture, analyzing its advantages and drawbacks. The study recognizes the pressing demand for dependable anomaly detection frameworks tailored to the specific requirements of the agricultural sector. To overcome the challenges posed by the heterogeneity of IIoT devices, the research advocates for the adoption of uniform communication protocols like MQTT, CoAP, or AMQP. These protocols facilitate standardized communication across diverse devices, ensuring interoperability and streamlined data exchange. Simultaneously, the study underscores the significance of edge and fog computing in agricultural contexts. As part of this research, a tailored anomaly detection framework is proposed for agriculture, integrating these technological advancements. By utilizing uniform communication protocols and leveraging edge and fog computing, this framework ensures that farmers can make informed decisions in near real-time, enhancing the overall safety, quality, and efficiency of IIoT-based agricultural practices.

关键词： Industrial Internet of things (IIoT) Agriculture Farming Anomaly detection Precision agriculture

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Diagnosing ADHD and Personality Disorders as Per DSM-5 Using Novel APK, PDPK, and DDPK Machine Learning Algorithms 1

引用

4th Congress on Intelligent systems (CIS)

作者： Jayachandran, Chris M. Shyamala, K. JUBATUS Inst Management & Technol JIMTEC Chennai Tamil Nadu India Dr Ambedkar Govt Arts Coll Chennai 600039 Tamil Nadu India

ISBN: (数字)9789819990405

ISBN: (纸本)9789819990399;9789819990405

One of the key constraints hurdling the adaption of machine learning (ML) algorithms in psychopathology lies in the fact that there is no silver bullet among both supervised and unsupervised ML algorithms that can be a fit and provide the diagnoses of prevalence or the onset of all developmental disorders. Considering any pertinent dataset available, the features required to diagnose the prevalence of ADHD using any ML model and the model so evolved will be strikingly different from the features required to diagnose personality disorders. Both ADHD and personality disorders are two among the widely diagnosed developmental disorders. From the general perspective, there are no well-researched and DSM-5 compatible psychopathological tools available in the form of a Web app or mobile app, for diagnosing developmental disorders. Thus, the authors of this research paper were motivated to envisage a framework for the development of a psychopathological tool for diagnosing ADHD and PD developmental disorders as per DSM-5 criteria, using the technology stack Google Colab IDE, Python, NumPy, Pandas, Scikitlearn, and Matplotlib.

关键词： Developmental disorders Psychopathological tool ML framework with APK PDPK And DDPK novel algorithms

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Sentiment Analysis Based on Twitter Comments Using Artificial Intelligence Techniques to Predict Peruvian Presidential Election Results 1

引用

13th Computer Science Online Conference

作者： Cedano, Diego Picon, Mesias Ticona, Wilfredo Univ ESAN Lima Peru Univ Tecnol Peru Lima Peru

ISBN: (数字)9783031705182

ISBN: (纸本)9783031705175;9783031705182

Currently, the use of social networks as the main means of communication and expression has increased. In Peru, the social network Twitter is preferred by political leaders and is key for political campaigns. The present research aims to implement a sentiment analysis model based on Twitter comments using artificial intelligence techniques to predict the results in the Peruvian presidential elections. The applied methodology was based on 5 phases: dataset construction, preprocessing, feature extractions, model implementations and Evaluation. Word2Vec and Tf-idf techniques were used for feature extraction. Finally, different machine learning models were developed, such as logistic regression (LR), Support Vector Machine (SVM), random forest (RF) and logistic regression (RL) and MLP classifier. The best model results from the combination of the SVM algorithm with Word2vec vectorization has superior performance in the metrics 0.89 Accuracy and 0.88 Precision. However, Recall is lower compared to the Tf-idf vectorization (0.87 Recall) and both vectorizations have the same result in the 0.87 F1-Score metric. Finally, the results of the second-round show PPK winning by a minimal margin over Keiko, 16.1% and 15.3% respectively. However, the percentage of undecided voters is about 34% on average.

关键词： Sentiment analysis Twitter Vectorization Comment classification Presidential election Twitter mining Word2Vec

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A Novel Hybrid Method for Optimizing Parameter Extraction of the Single Diode Model for Photovoltaic Devices 4th

A Novel Hybrid Method for Optimizing Parameter Extraction of...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： El Fatmi, Daoudi Arjdal, El Hanafi Ben Hmamou, Dris Elyaqouti, Mustapha Saadaoui, Driss Choulli, Imade Lidaighbi, Souad Elhammoudy, Abdelfattah Patel, Rabya Univ Ibn Zohr Fac Sci Lab Mat Signals Syst & Phys Modelling Agadir Morocco

ISBN: (纸本)9783031686498;9783031686504

In recent years, especially in the energy industry, one of the most exciting technologies is photovoltaic energy. As a result, studying the parameters of the solar cell model is critical for controlling and determining the photovoltaic cell's features. The photovoltaic parameters of the single diode model can be extracted by using three common approaches: Analytical, Numeric or iterative and approach based on the evolutionary algorithms or by using hybrid approach, for example Analytical with Numerical or Analytical with meta-heuristic. The principle objective of this new paper is to investigate and analyze the characteristics of the single diode model by employing a hybrid approach that combines Analytical and Particle Swarm Optimization method based on evolutionary algorithm. The validation of our model was carried out by using the R.C.T France solar Cell and Photowatt-PWP 210 module. The acquired results were compared to other algorithms and demonstrated their durability, outperforming other methods.

关键词： Evolutionary Algorithm single diode mode photovoltaic Cell Analytical Approach

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AI's Influence on Non-Player Character Dialogue and Gameplay Experience 1

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Computing Conference

作者： Iarovoi, Dmitrii Hebblewhite, Richard Teh, Phoey Lee Wrexham Univ Fac Art Comp & Engn Wrexham Wales

ISBN: (数字)9783031622816

ISBN: (纸本)9783031622830;9783031622816;9783031622809

OpenAI's introduction of the ChatGPT tool in late 2022 prompted varied societal responses. This study focuses on integrating the generative language algorithm into player-NPCdialogues in video games to gauge its impact on immersion. It explores ChatGPT's effects on player engagement, comparing it with traditional dialogue systems, and its role in achieving in-game goals. Using qualitative and quantitative methods, data analysis involved questionnaires, player experience evaluations, interaction comment reviews, dialogue text analysis, and player choice assessments. Results indicate potential benefits of ChatGPT in enhancing conversational scenarios, while also raising questions about dialogue purpose, player-NPC interaction motivations, and enjoyment. Factors like game genre, dialogue length, tone, and prompt configurations influence interaction satisfaction. The study concludes by addressing integration risks and suggesting avenues for future exploration in this domain.

关键词： Non player character Gameplay AI Artificial intelligent Chat GPT

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