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ACS/IEEE International Conference on computer Systems and Applications

作者： Heba Helal Mohamed A. Sharaf College of Information Technology United Arab Emirates University UAE Dept. of Computer Engineering and Systems College of Engineering Mansoura University Egypt

Dealing with high-dimensional time series data makes the process of recommending visualizations with "interesting" insights difficult. The challenge originates from finding a way to obtain the recommended visualizations efficiently without compromising their quality. Identifying such visualizations manually is considered a labor-intensive and time-consuming process. In response, this paper introduces different techniques designed to optimize the automated recommendation process. These techniques are entirely based on the concept of computation sharing and pruning. Furthermore, we provide a glimpse into our future research works in PhD thesis. The objective is to broaden the scope of our current work and enhance the generality of our problem statement.

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Artificial Neural Network and ARIMA model to estimate ICT sector investment, a comparative approach

Artificial Neural Network and ARIMA model to estimate ICT se...

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International Symposium on Telecommunications, IST

作者： Leila Mansourifar Niloofar Moradhasel Matin Sadat Borghei Arman Heidari dept. Strategic Studies and Digital Economics Center Iran Telecommuniction research cenetr(ITRC) Tehran Iran dept. Computer Science and Engineering Iran University of Science and Technology (IUST) Tehran Iran

ISBN: (数字)9798350356250

ISBN: (纸本)9798350356267

The purpose of this research is to predict the required ICT sector for the time period leading up to ١٤٠٥. The ICT sector was predicted based on Autoregressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN). The major difference between the results of the two models indicates the difference between these two methods in forecasting, and it was shown that the ARIMA model is not a suitable method for program-oriented forecasts because it is not possible to consider variables in its calculations like economic growth. On the other hand, the neural network method can provide a more reliable prediction due to the inclusion of the economic growth variable in the learning process.

关键词： Economics Hands Biological system modeling Input variables Artificial neural networks Predictive models Market research Telecommunications Telecommunication network reliability Investment

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Digital Data Protection Using Feistel Network and DNA Cryptography

Digital Data Protection Using Feistel Network and DNA Crypto...

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International Conference on Advanced Aspects of Software engineering (ICAASE)

作者： Aya Goudjil Lylia Djilali Amira Benabdelmoumene M'hamed Hamadouche Mohamed Amine Riahla dept. Computer Science LIMOSE Laboratory University of M'hamed Bougara Faculty of Science Boumerdes Algeria dept. Electrical Engineering University of M'hamed Bougara Faculty of Technology Boumerdes Algeria

ISBN: (数字)9798331522810

ISBN: (纸本)9798331522827

The growing importance of digital data security has led to increased exploration of advanced cryptographic methods, including innovative bio-inspired techniques such as DNA cryptography. In this paper, we present an enhanced encryption technique that combines a Feistel Network with DNA cryptography. This is achieved by using DNA encoding alongside an R-Box for mapping octal values to RNA codons, integrated with an XOR operation and random round keys. This hybrid approach achieves an impressive avalanche effect of 56 % with just four Feistel rounds, compared to the 53 % achieved by the DES algorithm in 16 rounds. The results highlight the efficiency and robustness of our method in protecting digital information while reducing computational overhead.

关键词： RNA DNA Robustness Encoding Encryption Computational efficiency Cryptography Codons Digital information Software engineering

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AI in Medicine: CNN Techniques for Pneumonia and Pandemic Pathogen Identification

AI in Medicine: CNN Techniques for Pneumonia and Pandemic Pa...

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Advanced Computing & Communication Technologies (ICACCTech), International Conference on

作者： Ganji Ramanjaiah Nagendar Yamsani Smritilekha Das Balajee Maram Ananda Babu Rudrubati Katakam Venkateswara Rao Dept. of Computer Science & Engineering (Data Science) R VR & JC College of Engineering Chowdavaram Guntur Andhra Pradesh India School of Computer Science and Artificial Intelligence SR University Warangal Telangana Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Dept. Of Computer Science & Engineering (AI & DS) Kallam Haranadhareddy Institute of Technology Chowdavaram Guntur Andhra Pradesh India Dept of Computer Science and Engineering Koneru lakshmaiah Education Foundation Vaddeswaram Guntur DT Andhra Pradesh India

ISBN: (数字)9798331519056

ISBN: (纸本)9798331519063

The current paper deals with the applicability of Convolutional Neural Networks in the detection of pneumonia and pandemic pathogens using medical imaging data. Leveraging the transformative power of AI in our study, we have placed a focus on the development and evaluation of a CNN model that will be trained on a heterogeneous dataset of chest X-rays and CT scans. This paper will propose a method for developing a CNN to classify images from a diverse dataset of chest X-rays and CT scans, ensuring diagnostic accuracy and speed to meet the critical challenges involved in disease diagnosis in a timely manner. Our results show that the CNN model has high accuracy, sensitivity, and specificity for the identification of pneumonia and differentiation of pandemic pathogens from others, surpassing conventional diagnostic techniques. What was more important to underline in this study was that the model demonstrated strong performance across multiple datasets and, more importantly, can easily be transplanted to clinical workflows. Improvement in the early detection capacity made this research emblematic of the huge role AI is expected to play in redefining health care, especially with respiratory diseases and pandemic preparedness. Future work will extend to the augmentation of the dataset and the fine-tuning of the model for its full clinical application.

关键词： Pathogens Pneumonia Accuracy Pandemics Computed tomography Sensitivity and specificity Convolutional neural networks Artificial intelligence Medical diagnostic imaging X-ray imaging

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Multi-agent and Reinforcement Learning Schemes for Demand Response Estimation in Distributed Microgrids

Multi-agent and Reinforcement Learning Schemes for Demand Re...

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International Conference on Energy Conservation and Efficiency (ICECE)

作者： Muhammad Ikram Salman Ahmed Safdar Nawaz Khan Marwat Muhammad Nasir Dept. of Computer Systems Engineering University of Engineering and Technology Peshawar Pakistan Department of Physics Allama Iqbal Open University Islamabad Pakistan

Demand response (DR) is an approach that encourages consumers to shape consumption patterns in peak demands for the reliability of the power system and cost minimization. The optimal DR scheme has not only leverages the distribution system operators (DSOs) but also the consumers in the energy network. This paper introduced a multi-agent coordination control and reinforcement learning approach for optimal DR management. Each microgrid is considered an agent for the state and action estimation in the smart grid and programmed rewards and incentive plans. In this regard, the Multi-agent Markov game (MAMG) is utilized for the state and action. At the same time, the reward is articulated through reinforcement learning deep Q-network (DQN) and deep deterministic policy gradient (DDPG) schemes. The proposed DR model also encourages consumer participation for long-term incentivized benefits through integrating battery energy storage systems (BESS) in the SG network. The reliability of DQN and DDPG schemes is demonstrated and observed that the dynamically changing electricity cost is reduced by 19.86%. Moreover, the controllability of complex microgrids is achieved with limited control information to ensure the integrity and reliability of the network. The proposed schemes were simulated and evaluated in MATLAB and Python (PyCharm IDE) environments.

关键词： Costs Estimation Microgrids Reinforcement learning Mathematical models Power system reliability Smart grids

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Designing a NoSQL Database for Efficient Storage and Retrieval of Health Data 8

Designing a NoSQL Database for Efficient Storage and Retriev...

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8th International Conference on Future Internet of Things and Cloud, FiCloud 2021

作者： Sen, Poly Sil Mukherjee, Nandini Techno Main Salt Lake Dept. of Information Technology Kolkata India Jadavpur University Dept. of Computer Science Engineering Kolkata India

ISBN: (纸本)9781665425742

The role of Cloud to store and retrieve health data is felt more than ever before in this pandemic. In remote places, and in emergency situations, there is scarcity of medical personnel and proper medical infrastructure. Hand held devices like smart phones and other devices having sensing capabilities can be used to store health data in cloud. This health data containing audio, video, images, sensor data as well as text data can be easily stored in a cloud. A static data model does not have the capability to cope with changes in the requirements of a health care application. Ontology comes as a solution to incorporate the dynamic requirements of such an application. Also, there are multiple complicated health data standards to follow or to be interoperable with. Ontology has the capacity to bring different health data standards and relate these standards. Health data being Big data by its nature is stored in MongoDB cloud in this work. Designing a data model that stores health data so that queries can run in less time-is a challenge. An algorithm is used to generate the data model design for a set of queries. This data model design is used to store data in this work. The experience of storing and running some queries is discussed here. © 2021 IEEE.

关键词： Ontology

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Investigation of Musical Factors Affecting Walking Speed with the Same Tempo

Investigation of Musical Factors Affecting Walking Speed wit...

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Summer Virtual Conference on Software engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Summer), ACIS International

作者： Makoto Fukumoto Sakura Ichikawa Dept. of Computer Science and Engineering Fukuoka Institute of Technology Fukuoka Japan

ISBN: (纸本)9798350396386

One of the applications of listening to music pieces is walking. Previous studies suggested that musical tempo is an important factor in a listener’s walking. Leman et al. found the difference in walking distance in the fixed time by employing many music pieces with the same tempo. However, the other musical factors that affect walking have not been revealed. This study aims to investigate the effects of music factors on walking by employing musical stimuli having different musical factors with the same musical tempo. Three walking experiments were conducted with fourteen participants. They walked the same distance while listening to the musical stimuli composed of different factors: musical scale, beats, and key were focused in each experiment. The musical melody and other factors of these musical stimuli were composed to be similar to each other to conduct the experiments with the independence of the focused factor. The elapsed time, the number of footsteps, and three subjective evaluations related to impressions of musical stimuli and feelings evoked by the musical stimuli were employed as the experimental indices. The experimental results showed that the difference in the musical beats affects the elapsed time, the number of steps, and the subjective evaluations.

关键词： Legged locomotion Music Artificial intelligence Software engineering

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BERTops: Studying BERT Representations under a Topological Lens

arXiv

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arXiv 2022年

作者： Chauhan, Jatin Kaul, Manohar Dept. of Computer Science & Engineering Indian Institute of Technology Hyderabad India

Proposing scoring functions to effectively understand, analyze and learn various properties of high dimensional hidden representations of large-scale transformer models like BERT can be a challenging task. In this work, we explore a new direction by studying the topological features of BERT hidden representations using persistent homology (PH). We propose a novel scoring function named "persistence scoring function (PSF)" which: (i) accurately captures the homology of the high-dimensional hidden representations and correlates well with the test set accuracy of a wide range of datasets and outperforms existing scoring metrics, (ii) captures interesting post fine-tuning "per-class"level properties from both qualitative and quantitative viewpoints, (iii) is more stable to perturbations as compared to the baseline functions, which makes it a very robust proxy, and (iv) finally, also serves as a predictor of the attack success rates for a wide category of black-box and white-box adversarial attack methods. Our extensive correlation experiments demonstrate the practical utility of PSF on various NLP tasks relevant to BERT. © 2022, CC BY.

关键词： Machine learning

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Multi mode Selection Sending Messages to Prioritize Nodes using WiFi Direct in Post Disaster Situation

Multi mode Selection Sending Messages to Prioritize Nodes us...

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Sustainable Energy, Signal Processing and Cyber Security (iSSSC), IEEE International Symposium on

作者： Balaram Pal Ashok Kumar Turuk Bibhudatta Sahoo Sourabh Debnath Jitendra Kumar Dept. of Computer Science Engineering National Institute of Technology Rourkela Odisha

ISBN: (纸本)9781665490573

In recent times WiFi Direct is a technology that can enable direct-to-direct device communication, single-group communication, or multi-group communication with each other device without any access point or without any internet access point. This paper expresses the WiFi Direct based multi-mode selection mobile ad hoc network. Basically here is a gateway layer and routing layer developed for supporting single group communication or multi-group communication between each WiFi direct supported device. This paper describes how to optimize the redundancy, how to select random group owners through WiFi Direct, and how to give priority to messages and among nodes also. Priority nodes have been selected from random nodes.

关键词： Databases Redundancy Software performance Signal processing Logic gates Routing Hardware

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Effect of Picture Prime on the Response Time and Error Rate Among Bilingual Children

Effect of Picture Prime on the Response Time and Error Rate ...

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Interdisciplinary Approaches in technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Java Banerjee Hrishikesh Roy Baisakhi Chakraborty Anupam Basu Dept. of Computer Science and Engineering National Institute of Technology Durgapur India

The Priming phenomena establishes a positive result in response to various word or picture naming tasks due to preceding manifestation in the form of a word or picture. The response time in identifying the words is less in the context of words appearing after a semantically connected word or picture compared to the words in segregation or words anteceded by a semantically unconnected word or picture. In order to investigate this phenomenon in the context of Bengali-speaking children, fifteen primary school children with ages ranging between 7 to 10 years were involved in the picture priming experiment. The experiment comprised of 25 words to be read by the children under two conditions consisting of without prime and with picture prime. Error rates of the participants are measured based on their performance during the experiment. The reaction time of the participants is also computed in seconds with reference to the two conditions that is the availability of prime and no prime. Analysis of the student's performance during the above experiment showed that the response time and error rate are comparatively reduced while identifying the target word in the condition of the presence of picture prime. To the best of our knowledge, this is the first-ever investigation regarding the effect of the presence of picture prime among Bengali-speaking children.

关键词： Visualization Technological innovation Error analysis Atmospheric measurements Semantics Measurement uncertainty Particle measurements

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