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

共 9495 条记录，以下是531-540 订阅

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Dynamic Hybrid Model for Biopesticides Production Using Bacillus Thuringiensis Strains 21st

Dynamic Hybrid Model for Biopesticides Production Using Baci...

引用

21st International Symposium on Distributed Computing and Artificial Intelligence

作者： Figueroa-Cardona, Sergio Robles-Rodriguez, Carlos E. El-Jeni, Rim Fillaudeau, Luc Aceves-Lara, Cesar A. Univ Toulouse CNRS TBI INRAEINSA Toulouse France

ISBN: (纸本)9783031820724;9783031820731

Commercial biopesticides are primarily based on the bacterium Bacillus Thuringiensis which produces insecticidal proteins. Dynamic models have been proposed to describe the production of these proteins, but their approximation can still be improved. Dynamic hybrid modelling combines kinetic models with data-driven algorithms which could be promising to improve the existing dynamic models. This work presents a dynamic hybrid model using Support Vector Machine (SVM) to predict the specific production of protein and spore by different strains of B. thuringiensis. The dynamic hybrid model was trained and validated with independent datasets of batch fermentations using the production rates of biomass, protein and spores computed with a kinetic model and the strain type as predictors. Additionally, Shapley values were calculated to determine the pertinence of each predictor. The Normalized root mean squared errors (NRMSE) revealed an improvement of the dynamic hybrid model of 12% for proteins and 7% for spores over the dynamic model. Although good, the model could be further improved by training the model with a larger quantity of data.

关键词： B.thuringiensis Support Vector Machine hybrid modelling optimization fermentation

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Examining the Effects of Static Personality Traits with Dynamic Affective and Emotional States on Depression Severity 9th

Examining the Effects of Static Personality Traits with Dyna...

引用

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

作者： Ahmed, Abdullah Ramesh, Jayroop Ganguly, Sandipan Aburukba, Raafat Sagahyroon, Assim Aloul, Fadi Univ Massachusetts Amherst Dept Elect & Comp Engn Amherst MA 01003 USA Amer Univ Sharjah Dept Comp Sci & Engn Sharjah 26666 Shj U Arab Emirates

ISBN: (纸本)9789819750344;9789819750351

Depression is a condition that impacts individuals by causing low mood and a diminished interest in usual activities, ultimately affecting their quality of life. The Experience Sampling Method (ESM) offers a valuable tool for examining the relationships among depression, personality traits, and emotional experiences in the context of daily behaviors and responses to stimuli. In this study, multivariable logistic regression was employed to investigate the link between (i) emotions during ESM with depression and (ii) pre-ESM characteristics. The characteristics considered encompassed the Big Five personality traits (BFI), Meaning in Life Questionnaire (MLQ), Self-Concept Scale (SCS), Self-Esteem Scale (SES), Positive and Negative Affect Scale (PANAS), as well as valence and arousal. The participants (N=142) considered in this study had the following categories of depression: moderate and severe. We observe that prior to ESM, the low self-esteem (odds ratio [OR], 0.787;95% confidence interval [CI] 0.693-0.895;P = 0.001) and during ESM the negative affect adjusted for prior covariates (OR, 1.077;95% CI 1.052 to 1.103;P = 0.003) were more apparent in individuals with severe depression.

关键词： Depression Affective states Big five Personality Statistical analysis Stress

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Multi-player System: Fostering Emotional Interaction via EEG Data 9th

Multi-player System: Fostering Emotional Interaction via EEG...

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

作者： Fang, Fang Tongji Univ Coll Design & Innovat Fu Xin Rd Shanghai 200092 Peoples R China

ISBN: (纸本)9789819754403;9789819754410

The paper explores a system designed for enhancing emotional connectivity through cooperative interactions and clear biofeedback. Utilizing the Muse device for data collection and the Mind Monitor software for EEG data processing, along with Python for system development, this research investigates the potential of clear biofeedback to boost empathy within a multi-user, cooperative setting. By applying design science research methodology and examining the responses of 10 participants, this study establishes a link between EEG data and emotional experience, providing fresh insights into emotional interactions among multiple users.

关键词： EEG Biological data Multi-player Emotional interaction

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Developing aWeb Application for Enhanced Analysis of Respiratory Sounds, with a Particular Emphasis on Clustering 9th

Developing aWeb Application for Enhanced Analysis of Respira...

引用

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

作者： Veliko, Sindi Xu, Mohan Wiese, Lena Fraunhofer Inst Toxicol & Expt Med Hannover Germany Goethe Univ Frankfurt Inst Comp Sci Frankfurt Germany

ISBN: (纸本)9789819754403;9789819754410

This paper merges bioinformatics and medical engineering to enhance respiratory health research. We developed a web application for processing and analyzing respiratory sound time-series data. Ou development demonstrates promising results in various tasks and highlights the potential of unsupervised learning methods like k-means for future advancements in health informatics. The application offers a novel interface for comprehensive respiratory sound analysis. The source code for the DigitaLung WebApp is available on Github.

关键词： Health informatics Respiratory sound Time-series analysis Unsupervised machine learning K-means clustering E-health

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An Ant Colony Optimization Approach to Optimize Biblical Sermons 21st

An Ant Colony Optimization Approach to Optimize Biblical Ser...

引用

21st International Symposium on Distributed Computing and Artificial Intelligence

作者： Lima, Bruno C. S. Frango, Ismar S. de Castro, Leandro N. Univ Prebiteriana Mackenzie Sao Paulo SP Brazil State Univ Campinas Unicamp Grad Program Technol Sch Technol Sao Paulo SP Brazil Florida Gulf Coast Univ Human Centered Artificial Intelligence & Nat Comp Ft Myers FL 33965 USA

ISBN: (纸本)9783031820724;9783031820731

Religious literature is among the most widely read ones. The Bible is the normative corpus for Christians. However, it is not a trivial text to read, due to its high degree of literary and linguistic variability, making sermon construction a laborious activity. This work proposes a method, called SwarmaBle, for automating the construction of Biblical sermons through a combination of natural language processing and swarm intelligence. The study combines quantitative and qualitative assessments of SwarmaBle, exploring its sensitivity to two hyperparameters and presenting a discussion about expert-evaluated recommended passages. The results show a consistent performance of SwarmaBle, achieving an average performance above 70% in the quantitative analysis. Domain experts reported positive evaluations regarding SwarmaBle's ability to recommend meaningful Biblical passages for the given topic.

关键词： Biblical Sermon Construction Swarm Intelligence Ant Colony Optimization Natural Language Processing Holy Bible

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QRCrop: A QR Code-Based Edge-Cloud Framework for Crop Yield Prediction 3rd

QRCrop: A QR Code-Based Edge-Cloud Framework for Crop Yield ...

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3rd International Conference on Network Security and Blockchain Technology

作者： Dey, Tanushree Bera, Somnath Mukherjee, Anwesha Roy, Samarjit De, Debashis Maulana Abul Kalam Azad Univ Technol Ctr Mobile Cloud Comp Dept Comp Sci & Engn BengalNH-12SimhatHaringhata Nadia 741249 W Bengal India Mahishadal Raj Coll Dept Comp Sci Mahishadal 721628 W Bengal India Eastern Int Univ Sch Comp & Informat Technol Nam Ky Khoi Nghia StHoa Phu Ward Thu Dau Mot City Vietnam

ISBN: (纸本)9789819780501;9789819780518

In this paper, a crop yield prediction system is proposed based on QR code and edge-cloud framework. In traditional systems, the cloud is used for IoT data analysis and storage. The concerns over the cloud-only system include security, latency, energy consumption, etc. The use of edge-cloud computing deals with the problem of latency and energy consumption. Nevertheless, the security is still amajor concern. In the proposed system, the user uploads soil and environmental parameters' data to the edge server using QR code to achieve secure data transmission. The data are analyzed using gated recurrent unit and long short-term memory network, and the result is sent to the cloud, from which the user can access the result anytime, anywhere. From the results, we observe that the proposed framework reduces the latency and energy consumption by similar to 28% than the cloud-only framework. The results also demonstrate that the proposed framework has an accuracy of similar to 99% in crop yield prediction.

关键词： QR code Deep learning Crop yield prediction Energy Latency

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Design Website for Buying and Selling Property Transactions to Enhance Customer Experience 1

引用

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

作者： Kristin, Desi Maya Alexandra, Jennifer Bina Nusantara Univ Sch Informat Syst Dept Informat Syst Jakarta 11480 Indonesia Univ Teknol MARA Selangor Coll Comp Informat & Media Informat Informat Management Dept Shah Alam Malaysia

ISBN: (数字)9789819754410

ISBN: (纸本)9789819754403;9789819754410

The Covid-19 pandemic which has been going on for 4 years has changed the lifestyle of interaction between people and the economy and business continuity, including in Indonesia. All activities that were previously carried out onsite now can be carried out online using internet. Especially in the business processes that run in property companies, which generally require an interaction before buying a property, such as seeing show units directly and completing files and signature documents in making the documents needed to buy or rent a property. With the current technological developments, it is very possible that all these process can be carried out online. This study aims to analyze and design a prototype of a website, where this website will be used to show all show units that are carried out virtually and activities that will be carried out with further online property sales. The scope of this research starts from customers who can see the show unit virtually through the website. This research has limitations, it does not discuss security and does not discuss the process of paying for houses and their administration (required documents). The research method used is SDLC (System Development Life Cycle) and for object-oriented analysis and design (Object-Oriented Analysis and Design).

关键词： Property Transactions Research Virtual tour

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Fundamental Study of Empirical Experiments with New Institutional Research (IR) Practitioners Using Large Language Models (LLM) Such as ChatGPT 9th

Fundamental Study of Empirical Experiments with New Institut...

引用

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

作者： Seki, Masayuki Noda, Ikuhiro Omori, Msato Sakai, Tomoyuki Murakami, Katsuhiko Takamatsu, Kunihiko Kobe Tokiwa Univ Kobe Hyogo 6530838 Japan KEI Adv Tokyo 1020083 Japan Univ Tokyo Tokyo 1088639 Japan Tokyo Inst Technol Tokyo 1528550 Japan

ISBN: (纸本)9789819750344;9789819750351

This paper presents a fundamental study on the application of Large Language Models (LLM), such as ChatGPT, for enhancing Institutional Research (IR) practices among new practitioners. Emphasizing the transition to low or no-code methodologies, this study explored the potential of semi-automated analysis and visualization methods to streamline the data handling processes in higher education. With the advancement of LLMs, traditional programming barriers are being dismantled, allowing for more efficient and accessible data analysis. This study particularly investigated the feasibility of utilizing ChatGPT in reducing the programming workload for IR practitioners, which could lead to a substantial transformation in the field. Through empirical experiments and the development of new visualization techniques, the research determined the benefits and practicalities of integrating LLMs into IR, promoting a future where sophisticated data analysis becomes more inclusive and user-friendly for all IR professionals. The findings suggest that embracing such technological tools not only broadens the capabilities of IR practitioners but also strengthens the strategic impact of their role within educational institutions.

关键词： Institutional Research (IR) Large Language Model (LLM) ChatGPT Programming Data analysis Visualization Higher education Empirical experiment Low-code development No-code development

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Acoustic Anomaly Detection on Weather Radar Machine Sounds Using Augmented Spectrograms 9th

Acoustic Anomaly Detection on Weather Radar Machine Sounds U...

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

作者： Loufakis, Michail Styanidis, Aristotelis Symeonidis, Panagiotis Ioannidis, Dimosthenis Tzovaras, Dimitrios Oikonomou, George Kourmpetis, Ioannis Papagianni, Panagiota Agoudimos, Ilias Informat Technol Inst Ctr Res & Technol Hellas Thessaloniki 57001 Greece Austriacard SA Thessaloniki 54636 Greece Hellen Air Force Telecommun & Elect Depot Appl Res & Technol Dev Directorate Attiki 16562 Greece

ISBN: (纸本)9789819750344;9789819750351

Weather radars play a crucial role in monitoring atmospheric conditions, especially in regions prone to adverse weather phenomena and near critical infrastructure hubs like airports. Ensuring their continuous and reliable operation is essential for accurate weather forecasting and early warning systems. This paper addresses the challenge of acoustic anomaly detection in weather radar systems through a novel approach using augmented spectrograms and autoencoders. We detail the development of a model capable of distinguishing between normal and abnormal operational sounds, an essential step toward effective predictive maintenance. Our method demonstrates outstanding performance, particularly on a dataset provided by the Hellenic Air Force, achieving an AUC of 1.00, signifying flawless anomaly detection. The study's outcomes highlight the potential of machine learning in reducing the need for manual inspections and pave the way for further exploration in applying these techniques in real-world scenarios for enhanced radar system reliability.

关键词： Acoustic anomaly detection Weather radar Autoencoder Spectrograms Augmentation Predictive maintenance Sound processing Machine learning Unsupervised learning

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Privacy-Preserved Covid and Inter-BAN Communication Status Maintenance with Key and Random Value Update in Blockchain 3rd

Privacy-Preserved Covid and Inter-BAN Communication Status M...

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3rd International Conference on Network Security and Blockchain Technology

作者： Pattanayak, Anupam Baruah, Barnana Dhal, Subhasish Indian Inst Informat Technol Gauhati India Assam Kaziranga Univ Jorhat Assam India

ISBN: (纸本)9789819780501;9789819780518

To efficiently detect Covid-19 like pandemic infection body area network (BAN) can be used in smart society. Whenever two BUs come close to each other, inter-BAN communication (IBC) takes place. BAN user (BU) stores her Covid status and IBC into the distributed immutable database in blockchain network for tampering free contact tracing. As Covid status and inter-BANcommunication (IBC) are privacy sensitive information, BU stores her Covid status and IBC in encrypted form using public key of trusted authority (TA). Public key of TA is used to encrypt IBC event and it is stored in blockchain network. Adjacency matrix data structure has been used to maintain both IBC and Covid status in the blockchain network. Adjacency matrix element A(i, j), i not equal j keeps the IBC status between BUi and BUj. Diagonal element of adjacency matrix, A(i, i) keeps the Covid status of BUi. Refreshing of key of TA is required and so is the random numbers generated by BU which are being used in adjacency matrix data structure. Update of TA key and BU generated random numbers is necessary for security reasons. Random number update should not affect the other information present in adjacencymatrix elements. Miners use homomorphic encryption for updating the BU generated random numbers. TA generates proxy reencryption key RKK -> K ' by which Mi obtains ciphertext E-K '(m) from E-K(m) to update the adjacency matrix elements without losing relevant Covid status or IBC status. The proposed framework in this work provides the management of privacypreserved key and random values update in blockchain network. Security analysis of the proposed framework has also been done.

关键词： Covid-19 Contact tracing Inter-BAN communication Blockchain Privacy Key update Random number update

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