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Secure Cognitive Protocols for data Fusion in Transformative computing 23rd

Secure Cognitive Protocols for Data Fusion in Transformative...

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23rd international conference on Network-Based Information Systems, NBiS 2020

作者： Ogiela, Lidia Takizawa, Makoto Ogiela, Urszula Department of Cryptography and Cognitive Informatics Pedagogical University of Krakow Podchorążych 2 Street Kraków30-084 Poland Department of Advanced Sciences Hosei University 3-7-2 Kajino-cho Koganei-shi Tokyo184-8584 Japan Pedagogical University of Krakow Podchorążych 2 Street Kraków30-084 Poland

ISBN: (纸本)9783030578107

Transformative computing is a new computational paradigm, which join communication technologies with sensor devices, and artificial intelligence methods. It allows to acquire sensor signals and evaluate those using different AI technologies towards determining some analytics factors. Application of cognitive systems in such analysis can extend possibilities of semantic analysis and evaluation of signals towards performing semantic evaluation of their meaning. data fusion using cognitive approach can facilitate fast analysis, management, and creation new areas of such systems application in security and management protocols. © 2021, Springer Nature Switzerland AG.

关键词： Semantics

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EEG-Based Emotion Recognition Using Similarity Measures of Brain Rhythm Entropy Matrix 14th

EEG-Based Emotion Recognition Using Similarity Measures of B...

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14th international conference on Brain Inspired Cognitive Systems, BICS 2024

作者： Feng, Guanyuan Wang, Peixian Wu, Xinyu Ren, Ximing Ling, Chen Huang, Yuesheng Wang, Leijun Lv, Jujian Li, Jiawen Chen, Rongjun School of Computer Science Guangdong Polytechnic Normal University Guangzhou510665 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Hefei230601 China Guangdong Provincial Key Laboratory of Intellectual Property and Big Data Guangdong Polytechnic Normal University Guangzhou510665 China

ISBN: (纸本)9789819628810

Constructing the Brain Rhythm Entropy Matrix (BREM) as a feature for emotion recognition is feasible due to the correlation between brain rhythm activities and arousal/valence levels, as well as the effectiveness of entropy in quantifying such activities. Besides, similarity, a vital metric in bioinformatics, measures the degree of resemblance between internal elements. Building on these foundations, this paper introduces an emotion recognition method that leverages the similarity measures of BREM derived from EEG signals. The results using the DEAP database indicate that the proposed method achieves an accuracy range of 75% to 92% by employing the optimal single-channel data for emotion recognition. Furthermore, significant individual differences were observed in selected channels and time windows for emotion recognition. Such findings not only offer an innovative manner for EEG-based emotion recognition through BREM and similarity measures but also provide advances for designing portable emotion computing devices in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Bioinformatics

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Security Analysis of a Multi-server-Based e-Healthcare Scheme 6th

Security Analysis of a Multi-server-Based e-Healthcare Schem...

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6th international conference on Advanced Machine Learning technologies and Applications, AMLTA 2021

作者： Luo, Yi Chang, Kuo-Chi Li, Jian Zheng, Weimin School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350000 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9783030697167

Multi-server environments-based telecare medicine information systems (TMIS) using the smart card are widely used. Recently, Barman et al. proposed an authentication protocol in e-Healthcare for a multi-server *** paper demonstrates that their protocol is not secure against known session specific temporary information attack, leakage of the session key, and man-in-the-middle attack. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smart cards

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Improved Cybersecurity Framework based on Truckingc Heuristics Algorithm for Detecting Malicious Devices in Fog computing and Internet of Things (IoT) Environments

Improved Cybersecurity Framework based on Truckingc Heuristi...

引用

international conference on advances in Electronics, Computers and Communications (ICAECC)

作者： Isah Muhammad Lamir Abdulsalam Ya'u Gital Kabiru Musa Ibrahim Mustapha Abdulrahman Lawal Mohammed Danlami Ismail Zahraddeen Yakubu Department of Mathematical Science Abubakar Tafawa Balewa University Bauchi Nigeria Department of Management Info Tech Abubakar Tafawa Balewa University Bauchi Nigeria Department of Computing Technologies SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798350305449

ISBN: (纸本)9798350305456

The ever-increasing demands for real time data generation and processing, the novel cloud computing concept alone cannot, in any way effectively and efficiently handle the high demand of resources and response time, thus, the need for the introduction of the novel fog computing concept that focuses on decentralization and as well, serves as an intermediary between the cloud and IoT. However, security challenges evolving from these trends exponentially grow at a rate exceeding the progression in security solutions remains a major concern. Security of IoT devices remains one of the notable challenges that greatly hinders successful implementation of this novel concept as justified in literatures. In this research work, an improved Cybersecurity Framework based on truckingc heuristics algorithm is proposed using three techniques: Intrusion Detection System (IDS), Hidden Markov Models (HMM) and Improved Virtual Honeypot (IVHD) to categories devices into four different levels based on their intended mission, creates logs for messages exchanged via all interfaces and as well monitors communication traffic to detect malicious edge devices, detects attack source by tracking back the channels used by malicious devices, physically localize position of malicious nodes for instant isolation to cure attacked devices and revert them back to their initial states and as well, averts and mitigates Distributed Denial of Service (DDoS) attacks respectively over the Fog layer. Experimental results indicates that the detection accuracy increases with increase in the number of deployed Honeypots. Consequently, the proposed cyber security framework work therefore improves on existing frameworks via effectively detecting, tracking & isolating malicious edge devices, recovers hacked or compromised devices back to their normal states and dynamically averts and mitigate DDoS attacks over fog computing environment and Internet of Things (IoT) environment.

关键词： Accuracy Web services Viterbi algorithm Image edge detection Hidden Markov models Denial-of-service attack Prediction algorithms

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Internet of Things for Agriculture Industry: A Bibliometric Analysis in the Last Five Years

Internet of Things for Agriculture Industry: A Bibliometric ...

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international conference on ICT For Smart Society (ICISS)

作者： Fairuz Iqbal Maulana Chasandra Puspitasari Miftahul Hamim Puput Dani Prasetyo Adi Rahman Arifuddin Vandha Pradwiyasma Widartha Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Entrepreneurship Business Creation BINUS Business School Bina Nusantara University Jakarta Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta Indonesia Department of Electrical Engineering University of Merdeka Malang Malang Indonesia Department of Information System Pukyong National University Busan South Korea

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

With the arrival of new technologies, the farm business is always changing. It is one of the most important in the world. The Internet of Things (loT) is one of the most exciting new technologies of the past few years. It could completely change the way we farm. We look at the literature about loT in agriculture over the last five years in this study. According to our findings, the use of loT in agriculture has been steadily increasing over the previous five years. This research provides a bibliometric evaluation of academic papers covering the years 2018–2022, with an emphasis on the Internet of Things (loT) in the agricultural sector. The analysis is performed using data obtained from the Scopus database. 120 documents were chosen and evaluated to acquire insights on the present state of research in this topic. Co-citation analysis identified wearable technology, farmers, loT devices, food, and wireless sensor networks (WSNs) as prominent research subjects in the agricultural industry's use of the Internet of Things (loT). The findings can provide valuable insights for scholars, practitioners, funding agencies, and policymakers in comprehending the patterns and focal points in this domain. The authors and institutes highlighted in this analysis are useful resources for collaborating and staying updated on the newest advances in the loT for Agriculture Industry.

关键词： Performance evaluation Wireless sensor networks databases Bibliometrics Market research Agriculture Internet of Things Object recognition Business

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Moringa Oleifera As An Alternative to Conventional Coagulants in Big data and data science Analytics

Moringa Oleifera As An Alternative to Conventional Coagulant...

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Tanmay Singh Harishchander Anandaram Sunil Shukla Vinod Balmiki Awadhesh Chandramauli Kapil Joshi Department of Civil Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand India Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu India University of Engineering and Technology Roorkee India Department of CSE Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand India

Ever since the population explosion began postmodern industrialization since 1950 the population has grown more than threefold. With the global population crossing the Benchmark of 8.0 billion in June 2022, while some nations reap the benefits of progress, there are still nations who face the challenges of a pre-industrialized world, even today there is a quarter of world Population that does not have access to safe and clean drinking water. In this paper, conventionally, treatment of water is carried out with the help of Chemical Coagulants (Primarily Alum), several research have linked the usage of Alum with Neurodegenerative Diseases like Alzheimer's. Hence the need arises to develop a suitable alternative, Seeds of Moringa Oleifera also known as miracle tree due to its Phytochemical Properties contain Mo-CBP3-4 a protein that causes adsorption and neutralization of the colloidal charges thereby clarifying the water, For high initial Turbidity waters the optimal Dosage was the same for Moringa Oleifera (50mg/l) and the sludge produced post treatment is not only innocuous but also three to four times less by volume when compared with Alum and specially we use big data for data analysis.

关键词： Proteins Oxygen Sociology Water quality Big data Fault location Rendering (computer graphics)

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Classification of Metabolic Pathways Using Machine Learning Techniques 1

引用

11th international conference on Innovations in Bio-Inspired computing and Applications, IBICA 2020 and 10th World Congress on Information and Communication technologies, WICT 2020

作者： Dongardive, Jyotshna Jamkhedkar, Suruchi University Department of Computer Science University of Mumbai Mumbai400098 India University Department of Life Sciences University of Mumbai Mumbai400098 India

ISBN: (数字)9783030736033

ISBN: (纸本)9783030736026

The metabolic network consists of several metabolic pathways. Classifying metabolic pathways is a subtask of the larger task of reconstructing the whole metabolic network from a genome. In present study an attempt has been made to detect various pathways in cancer and viral infections using machine learning techniques. The data was collected from metabolic networks of six different types of cancer pathways and viral infections pathways known to cause cancer in humans listed in KEGG PATHWAY database. Five different machine learning classifier techniques were applied to determine the accuracy of the classification in these two datasets. The overall results suggest that these classifiers could be able to give a range of accuracy of 71%–72% in both the dataset with a range between 50% to 100% accuracy. The results reveal that Random forest gives the highest accuracy in six out of twelve datasets followed by Decision tree. Therefore, this indicates that Random forest technique and the proposed method might be efficient in classifying the cancer and viral metabolic pathways in the present study. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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Performance Comparison of Julia with C and Python for Solving Computational Problems 8th

Performance Comparison of Julia with C and Python for So...

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8th international conference on advances in computing and data sciences, ICACDS 2024

作者： Krishna, Sabbi Vamshi Jadhav, Om Ardhapurkar, Parikshit Valmiki, Manjunatha Agrawal, Sandeep Bulusu, Ramesh Dinde, Prashant Wandhekar, Sanjay HPC Technologies Group C-DAC Maharastra Pune411008 India

ISBN: (纸本)9783031709050

This study investigates the performance of Julia and compares it with the C and Python programming languages in solving problems involving one-dimensional vectors, matrix operations, and two-dimensional equations. Through a series of experiments, Julia’s performance on different computers with different numbers of CPU cores is measured and compared. We evaluated Julia’s performance using numerical symbols for one-dimensional vector and matrix equations on a single switch, and then tested Julia’s MPI implementation using 2D thermal equations in a multi-core Compute environment. The results show that Julia offers the best performance, often compared to C and better than Python, especially on tasks that require a lot of computation, such as one-dimensional vector operations and matrix multiplication. Comparison of the performance of C and Julia is illustrated by the simultaneous use of parallelism on both sides;This demonstrates the Julia language’s ability to use parallelism. Julia’s performance in performing computational tasks demonstrates her aptitude for computational science and statistical analysis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Vectors

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Interference Aware Routing In 5G Backhaul Wireless Mesh Networks

Interference Aware Routing In 5G Backhaul Wireless Mesh Netw...

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Smart technologies in computing, Electrical and Electronics (ICSTCEE), international conference on

作者： Nirmalkumar S. Benni Sunilkumar S. Manvi Department of Information Science and Engineering RNS Institute of Technology Bengaluru India School of Computer Science and Engineering REVA University Bengaluru India

In the wireless backhaul network, the millimetre wave band can give several-Gbps transmission rates due to the presence of large volume of spectrum. However, routing is deliberated as a major problem for QoS support in wireless backhaul mesh networks (WBMN), because it decides whether the data traffic can be transmitted through the particular path or not. The routing scheme should consider link delay and interferences for ensuring accurate path quality estimation. In this paper, a Sea Lion Optimization based Link delay and interference aware (SLO-LDI) routing method is proposed for managing the inter/intra flow interferences in 5G wireless backhaul mesh network. This routing algorithm assigns weights to the individual links by estimating the quality of the link using LDI metric. Here, the transmission and contention delay along with the interferences of each link is measured by this LDI metric. Finally, the optimal link will be selected based on this weight to start data transmission. The performance of the proposed method is validated through extensive simulations under different traffic loads. The results show that, the proposed SLO-LDI outperforms other routing methods in terms of throughput and average end-to-end delay.

关键词： Wireless communication Measurement Mesh networks 5G mobile communication Routing Throughput Delays

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Analysis Method of Sensing Information in Electric Power Distribution Based on Edge computing 5th

Analysis Method of Sensing Information in Electric Power Dis...

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5th international conference on Intelligent computing, Communication and Devices, ICCD 2019

作者： Chengliang, Wang Weilian, Shui Qingsheng, Yang Yan, Ning Jiangsu Frontier Electric Technology Co. Ltd. NanjingJiangsu Province211102 China

ISBN: (纸本)9789811558863

With the comprehensive construction of smart distribution networks, a new generation of IT technologies represented by Internet of Things, cloud computing, and edge computing are widely used. With low data quality and complex data characteristics of smart distribution network, it is urgent to find a reasonable way to solve the massive data problem of cloud computing system explosion. Considering the importance, regionality, difference, and real time of the data, it is proposed to use edge calculation to evaluate the accuracy, completeness, and redundancy of the data. The cloud computing capability is sunk to the edge of the network close to the client, running on the edge of the mobile network while performing specific computing tasks. By analyzing the index weights, the evaluation model is built and evaluated. The edge information-based sensing information fusion algorithm of distribution network is studied, and the intelligent distribution network data evaluation system based on multi-dimensional analysis and mining is established. The proposed algorithm provides strong support for the operation and maintenance management and correct decision-making of smart distribution network. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electric power distribution

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