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2020 International Conference on Intelligent systems and Computer Vision (ISCV)

作者： Mouden, Zakariyaa Ait El Jakimi, Abdeslam Moulay Ismail University Software Engineering Information Systems Engineering Research Team Faculty of Sciences and Techniques Errachidia Meknes Morocco

ISBN: (数字)9781728180410

ISBN: (纸本)9781728180410

In machine learning, the power of an approach is measured by its capability to be adapted for different applications and using different formats of data. Spectral Clustering is an unsupervised method that can be adopted for many research fields in and beyond computer science. In this paper, we present and analyze the existing algorithms of spectral clustering, and based on their limits we propose our modified version to deal with the most common challenge in this context which is the dynamic estimation of the output number of clusters. © 2020 IEEE.

关键词： Machine learning

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Optimizing Collective Building Management through a Machine Learning-based Decision Support System 4

Optimizing Collective Building Management through a Machine ...

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4th International Informatics and software engineering Conference, IISEC 2023

作者： Guvencli, Mert Kiran, Halil Dogan, Erkan Dag, Hasan Ozyuruyen, Burcu Cakar, Tuna Apsiyon Informatics Sys. Inc. Software-Team Lead Istanbul Turkey Apsiyon Informatics Sys. Inc. Product-Team Lead Istanbul Turkey Apsiyon Informatics Sys. Inc. Software-Management CPO Istanbul Turkey Kadir Has University Informatics Management Systems Istanbul Turkey Apsiyon Informatics Sys. Inc. R and D and Innovation Incentives Sen. Sp. Istanbul Turkey MEF University Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350318036

This study presents the design, implementation, and evaluation of a Decision Support System (DSS) developed for Collective Building Management. Given the potential advantages of machine learning techniques in this domain, the research explores how these techniques can be used to improve collective building management. The dataset consists of 824,932 records and 15 attributes, after preprocessing the data to fill in missing values with the median. The random forest algorithm was chosen for model training and achieved a performance rate of 71.2%. This model can be used to optimize decision processes in collective building management. The proposed prototype is notable for its ability to automatically generate operational plans. In conclusion, machine learning-based DSSs are effective tools for collective building management. © 2023 IEEE.

关键词： Decision support systems

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Baby Bump: A Monitoring System for Pregnant Mothers and Babies

Baby Bump: A Monitoring System for Pregnant Mothers and Babi...

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International Conference for Convergence of Technology (I2CT)

作者： Dhanuka Balasooriya Sasini Perera Dinuka R. Wijendra Sahani Rathnayaka Rajendra Kishan Karthiga Rajendran Markandu Thirukumar Department of Computer Systems and Software Engineering Sri Lankan Institute of Information Technology Malabe Sri Lanka Department of Obstetrics & Gynaecology Teaching Hospital Batticaloa Sri Lanka

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

In contemporary times, nations like Sri Lanka are actively enhancing their efforts to improve the life expectancy of their citizens, with a strong focus on public health. The relationship between health and life expectancy is pivotal. Poor health conditions tend to diminish life expectancy, while robust health measures tend to extend it. Within the context of health, birth and death events are of paramount importance. Birth represents the genesis of life, enabling individuals to contribute to future generations and the overall population's expansion. It's the cornerstone of life on our planet. However, modern times have witnessed challenges in pregnancy and childbirth, with some infants not surviving the prenatal period or being born with health complications. Consequently, there is a pressing need to present a solution that can contribute to the betterment of maternal and infant health, ultimately augmenting Sri Lanka's life expectancy. The proposed solution is the development of a mobile application, encompassing features such as a Nutrition Predictor, Medicine Effect Predictor, AI chatbot, and Baby Status Predictor. This innovative application aims to address the complex issues surrounding pregnancy and childbirth, with the overarching goal of improving the nation's life expectancy.

关键词： Pregnancy Pediatrics Planets Pressing Extraterrestrial measurements Chatbots Mobile applications

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Design of a Smart and Green Industry 4.0 Architecture

Design of a Smart and Green Industry 4.0 Architecture

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information Technology (ACIT)

作者： Khaled Hamdan Okba Kazar Dept. of Computer Science and Software Engineering College of IT UAEU UAE Dept. of Information Systems & Security College of IT UAEU UAE

The industrial sector has entered a phase of profound change which sees digital technologies being integrated into the heart of industrial processes. This fourth industrial era gives birth to a new generation of factory called “Digital Factory”, “Industry 4.0”. This industrial change is the result of the integration of new digital technologies into manufacturing processes and the optimization of energy consumption. The commitment to the environment is also a key and success factor of Industry 4.0 and green in particular the reduction of carbon emissions and pollution. This is how smart green industry try to take in charge the problem of energy consumption and to reduce the Co2 pollution. The goal of this paper is to present the new model of smart green industry using distributed artificial intelligence based on multi-agent system (MAS). The motivation to use the intelligent approach based on MAS is based on the similarity between the fundamental concepts of the cyber-physical system and those contained in the architecture and operation of MAS such as communication, coordination, decision and cooperation.

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Automated Identification of Security-Relevant Configuration Settings Using NLP 22

Automated Identification of Security-Relevant Configuration ...

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Proceedings of the 37th IEEE/ACM International Conference on Automated software engineering

作者： Patrick Stöckle Theresa Wasserer Bernd Grobauer Alexander Pretschner School of Computation Information and Technology / Chair of Software and Systems Engineering Technical University of Munich Germany T CST Siemens AG Germany

ISBN: (纸本)9781450394758

To secure computer infrastructure, we need to configure all security-relevant settings. We need security experts to identify security-relevant settings, but this process is time-consuming and expensive. Our proposed solution uses state-of-the-art natural language processing to classify settings as security-relevant based on their description. Our evaluation shows that our trained classifiers do not perform well enough to replace the human security experts but can help them classify the settings. By publishing our labeled data sets and the code of our trained model, we want to help security experts analyze configuration settings and enable further research in this area.

关键词： Security Configuration Hardening Natural Language Processing

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AI LipReader-Transcribing Speech from Lip Movements

AI LipReader-Transcribing Speech from Lip Movements

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： D Ajitha Disha Dutta Falguni Saha Parus Giri Rohan Kant Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Vellore Vellore India Department of Database Systems School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Information Security School of Computer Science and Engineering Vellore Institute of Technology Vellore Vellore India

Lip Reading AI is a discipline that is rapidly changing and has numerous applications in security, accessibility and human-computer interaction. This paper proposes a model which combines Convolutional Neural Networks (CNNs) to capture spatial capabilities, Long Short-Term Memory (LSTM) networks to examine temporal dependencies, and an adaptive interest mechanism. Meticulous preprocessing of the MIRACL VC-l dataset addressing challenges including one of a kind lip moves and occlusions accompanied with the aid of transitioning this study effortlessly to LRS2 dataset to complement lexemic versatility is one of its key function. The effects verify its robustness throughout unique datasets with superior overall performance towards cutting-edge techniques. Ablation checks suggest the crucial significance of every element in phrases of improving lip analyzing accuracy. Our proposed model version additionally suggests flexibility in restricted and naturalistic language situations.

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Control of Multipath Transmissions in the Nodes of Switching Segments of Reserved Paths 6

Control of Multipath Transmissions in the Nodes of Switching...

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6th International Scientific Conference on information, Control, and Communication Technologies, ICCT 2022

作者： Bogatyrev, Vladimir A. Bogatyrev, Stanislav V. Bogatyrev, Anatoly V. Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia Itmo University Faculty of Software Engineering and Computer Systems Saint Petersburg Russia Yadro Cloud Storage Development Center Saint Petersburg Russia

ISBN: (数字)9781665493673

ISBN: (纸本)9781665493673

The options for ensuring timely delivery of packages to the addressee in networks with duplication of communication paths with the addressee for some subscribers are analyzed. Connecting subscribers to two communication routes with the addressee allows you to load-balance routes and carry out duplicated transmissions aimed at increasing the probability of delivering at least one copy of the transmitted packet in the required time. The possibilities of using route switch nodes for traffic management and replication of transmitted packets are analyzed. At the same time, two variants of duplicated transmissions are considered. For the first option, new replicas and ways of their transmission to the addressee are formed in one of the nodes connecting the existing paths by the first accepted replica. The replica coming in second is destroyed. For the second option, changing the transmission paths of replicas generated from the source in the nodes linking the paths is not carried out. The area of effectiveness of the proposed variants of duplicated transmissions is shown. The influence of the location of route switches on the timeliness of package delivery from subscribers connected to one or two communication paths with the addressee is investigated. The existence of an optimal arrangement of route switches is shown. © 2022 IEEE.

关键词： Real time control

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Pros and Cons of Weight Pruning for Out-of-Distribution Detection: An Empirical Survey

Pros and Cons of Weight Pruning for Out-of-Distribution Dete...

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International Joint Conference on Neural Networks (IJCNN)

作者： Satoru Koda Alon Zolfi Edita Grolman Asaf Shabtai Ikuya Morikawa Yuval Elovici AI Trust Research Centre Fujitsu Limited Japan Department of Software and Information Systems Engineering Ben-Gurion University of the Negev Israel

Deep neural networks (DNNs) perform well on samples from the training distribution. However, DNNs deployed in the real world are exposed to out-of-distribution (OOD) samples, which refer to the samples from distributions that differ from the training distribution. OOD detection is indispensable to the DNNs as OOD samples can cause unexpected behaviors for them. This paper empirically explores the effectiveness of weight pruning of DNNs for OOD detection in a post-hoc setting (i.e., performing OOD detection based on pretrained DNN models). We conduct experiments on image, text, and tabular datasets to thoroughly evaluate OOD detection performance of weight-pruned DNNs. Our experimental results bring the following three novel findings: (i) Weight pruning improves OOD detection per-formance more significantly with a Mahalanobis distance-based detection approach, which performs OOD detection on DNN hidden representations using the Mahalanobis distance, than with logit-based detection approaches. (ii) Weight-pruned DNNs tend to extract global features of inputs, which improves the OOD detection on samples much dissimilar to the in-distribution samples. (iii) The weights that are useless for classification are often useful for OOD detection, and thus weight importance should not be quantified as the sensitivity of weights only to classification error. On the basis of these findings, we advocate practical techniques of DNN weight pruning that enable weight-pruned DNNs to maintain both OOD detection and classification capabilities.

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COVID-19 Detection System: A Comparative Analysis of System Performance Based on Acoustic Features of Cough Audio Signals

arXiv

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arXiv 2023年

作者： Shati, Asmaa Hassan, Ghulam Mubashar Datta, Amitava Department of Computer Science and Software Engineering University of Western Australia Australia Department of Information Systems King Khalid University Saudi Arabia

A wide range of respiratory diseases, such as cold and flu, asthma, and COVID-19, affect people’s daily lives worldwide. In medical practice, respiratory sounds are widely used in medical services to diagnose various respiratory illnesses and lung disorders. The traditional diagnosis of such sounds requires specialized knowledge, which can be costly and reliant on human expertise. Recently, cough audio recordings have been used to automate the process of detecting respiratory conditions. This research aims to examine various acoustic features that enhance the performance of machine learning (ML) models in detecting COVID-19 from cough signals. This study investigates the efficacy of three feature extraction techniques, including Mel Frequency Cepstral Coefficients (MFCC), Chroma, and Spectral Contrast features, on two ML algorithms, Support Vector Machine (SVM) and Multilayer Perceptron (MLP), and thus proposes an efficient COVID-19 detection system. The proposed system produces a practical solution and demonstrates higher state-of-the-art classification performance with an AUC of 0.843 on the COUGHVID dataset and 0.953 on the Virufy dataset for COVID-19 detection. Copyright © 2023, The Authors. All rights reserved.

关键词： COVID-19

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Exploring the Abstraction Levels of Design Principles: The Case of Chatbots 17

Exploring the Abstraction Levels of Design Principles: The C...

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17th International Conference on Wirtschaftsinformatik, WI 2022

作者： Wache, Hendrik Möller, Frederik Schoormann, Thorsten Strobel, Gero Petrik, Dimitri Chemnitz University of Technology Business Information Systems – Business Process and Information Management Chemnitz Germany TU Dortmund University Industrial Information Man Germany Fraunhofer ISST Dortmund Germany University of Hildesheim Enterprise Modeling and Information Syst. Hildesheim Germany University Duisburg-Essen Business Informatics and Software Engineering Essen Germany University of Stuttgart Information Systems II Stuttgart Germany

Formulating design principles is the primary mechanism to codify design knowledge which elevates its meaning to a general level and applicability. Although we can observe a great variety of abstraction levels in available design principles, spanning from more situated to more generic levels, there is only limited knowledge about the corresponding (dis-)advantages of using a certain level of abstraction. That is problematic because it hinders researchers in making informed decisions regarding the (intended) level of abstraction and practitioners in being oriented whether the principles are already contextualized or still require effort to apply them within their situation. Against this backdrop, this paper (1) explores different abstraction levels based on a sample of 69 design principles from the chatbot domain as well as (2) provides a preliminary positioning framework and lessons learned. We aim to complement methodological guidance and strengthen the principles' applicability, leading to knowledge reuse. © 2022 17th International Conference on Wirtschaftsinformatik, WI 2022. All rights reserved.

关键词： Design Principles Design Science Prescriptive Design Knowledge

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