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ADMT: ACO-based Data Management Technique for IoT 3

ADMT: ACO-based Data Management Technique for IoT

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3rd International Conference on Trends in Electrical, Electronics and Computer engineering, TEECCON 2024

作者： Pruthvi, C.N. Sandhya, K. Shreyas, J. Arpitha, T. Amutha, S. Babu, D R Ramesh Dayananda Sagar College of Engineering Dept. of Cse Bengaluru India Manipal Academy of Higher Education Dept. of Information Technology Manipal Bengaluru India Uvce Dept. of Cse Bangalore Bengaluru India

ISBN: (纸本)9798331505714

Context: ICN (information Centric Network) is a content-centric network that enables communication in the network by using content names. Each content is retrieved and cached inside the network using the content name rather than the address of the content. This enables content retrieval from the neighbor nodes and decreases the burden of reaching the content producer every time. Objective: Objective of the proposed work is to improve the cache hit ratio and reduce the content retrieval delay of IoT networks by using ICN in-network caching and placing content at the efficient ***: Proposed work uses an ACO (Ant Colony Optimization) based caching technique, which enables the caching of the content at the efficient node by considering the node capabilities and position. This technique uses pheromone level and heuristic information to select the best path to reach the cache node. Resulsts: Proposed work is evaluated using the ndnSIM simulator, and the results are evaluated regarding CHR (Cache Hit Ratio) and CRD (Content Retrieval Delay). The proposed work approximately achieves 5 to 8% efficiency in CHR and reduces 7% of CRD. Conclusion: The proposed work is an efficient caching technique that uses ACO to enhance cache node selection and path section in IoT. © 2024 IEEE.

关键词： Ant colony optimization

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Steganographic Encryption and Decryption Using Duality Preserving GANs 22

Steganographic Encryption and Decryption Using Duality Prese...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Shah, Aaryak Kamal, Alok Kumar Neeraj Dept. of Information Technology ABV-IIITM Gwalior Gwalior India Dept. of Electrical/Electronics ABV-IIITM Gwalior Gwalior India Dept. of Computer Science and Engineering Mahindra University Hyderabad India

ISBN: (纸本)9798331527471

Image steganography has been a significant research area in the security sphere. The core idea revolves around embedding secret messages in existing images (covers) such that the resultant image displays no noticeable detectable artifacts of the secret while also being statistically similar to the original cover. Various steganographic techniques have been developed and tested. However, these traditional techniques often exploit some specific property of the image and are often easy to detect with the right tools. In recent times, generative adversarial networks, or GANs for short, have shown massive promise in their capability to modify and synthesize data. They are now ubiquitous in image synthesis and image translation tasks. With various recent advancements in this technology allowing these models to generate, in many cases, human-imperceptible data, GAN-based steganographic systems have become a significant focus of security research. This report analyzes and compares some existing models and attempts to provide a new solution that performs better on multiple well-defined metrics. A DualGAN-based architecture is proposed that trains both the encoder and decoder processes simultaneously while maintaining the underlying dual relationship of these tasks. The proposed scheme reports better results on the selected metrics (SBR, DER, PSNR) at three values of embedding capacity set at 0.3, 0.6, and 0.9. © 2024 IEEE.

关键词： Generative adversarial networks

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Automated Bengali Sign Language Character Classification with Deep Learning Techniques 15

Automated Bengali Sign Language Character Classification wit...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Akter, Tahmina Mahmud, Tanjim Barua, Tikle Naher, Sultana Rokeya Hossain, Mohammad Shahadat Andersson, Karl Port City International University Dept. of Computer Science and Engineering Chittagong Bangladesh Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati4500 Bangladesh University of Information Technology and Sciences Dept. of Computer Science and Engineering Dhaka Bangladesh University of Chittagong Dept. of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Luleå97187 Sweden

ISBN: (纸本)9798350370249

Recognition of Bengali sign language characters is crucial for facilitating communication for the deaf and hard-of-hearing population in Bengali-speaking regions, which encompass approximately 430 million people worldwide. Despite the significant number of individuals requiring this support, research on Bengali sign language character recognition remains underdeveloped. This article presents a novel approach to categorize Bengali sign language characters using the Ishara-Lipi dataset, based on convolutional neural networks (CNNs) and pretrained models. We evaluated our approach using metrics such as accuracy, precision, recall, F1-score, and confusion matrices. Our findings indicate that the CNN model achieved the highest performance with an accuracy of 98%, followed by VGG19 with 94% and ResNet variants achieving around 88%. The proposed model demonstrates robust and efficient classification capabilities, significantly bridging the gap in existing literature. This study holds substantial promise for enhancing assistive technology, thereby improving social inclusion and quality of life for Bengalispeaking deaf and hard-of-hearing individuals. © 2024 IEEE.

关键词： Bengali sign language CNNs Deaf and hard-of-hearing community Image classification

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A Low Noise Bandgap Reference Voltage Source for CMOS Temperature Sensors 3

A Low Noise Bandgap Reference Voltage Source for CMOS Temper...

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3rd International Conference on Electronic information engineering and Computer Science, EIECS 2023

作者： Jin, Ao Wei, Qi Zhang, Jing Liang, Jiaxuan North China University of Technology Dept. Information Beijing China Tsinghua University Dept. Precision Instrument Beijing China Shandong Agricultural University Dept. Information Science and Engineering China

ISBN: (纸本)9798350316674

This design is based on the SMIC180nm CMOS process, with a power supply voltage of 1.8V, a sampling frequency of 800kHz, a temperature measurement range of -45 to 125 , an ADC with 12 significant bits, and a chip core area of 880um × 620um. The power consumption is 0.2916mW, and the bandgap reference voltage source output reference voltage is 1.2V with a noise level of 0.02nV/√ Hz. This article presents a new self-start circuit for a low noise bandgap reference voltage source in integrated temperature sensors. The bandgap reference voltage source itself utilizes bias to generate a starting current, which is then used to initiate the operational amplifier in the Bandgap. Compared to using individual capacitors and resistors to achieve the opening and closing of the starting circuit. This design fully realizes the multiplexing of notch filters, handles the ripple caused by the chopper and also achieve a negative feedback effect through self-capacitor charging and discharging, thereby turning off the starting current and achieving the self-start of the entire circuit. © 2023 IEEE.

关键词： bandgap low noise notch filter Start

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An Overview of Protocols-Based Security Threats and Countermeasures in WLAN 4

An Overview of Protocols-Based Security Threats and Counterm...

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4th International Conference for Emerging technology, INCET 2023

作者： Ojha, Nitish Kumar Baray, Elyas Indian Institute of Information Technology Dept. of Information Technology Allahabad211012 India Sharda University Knowledge Park - III Dept. of Computer Science and Engineering Greater Noida201310 India

ISBN: (纸本)9798350335750

WLAN security protocols are the most important section for wireless networks which controls all the security-related issues by securing the network with some pre-defined rules made by wireless-protected access organizations, further which makes it the main target of hacking and threats by interested parties and to be safe from such threats. There should be countermeasures for such threats where there will be a solution for any threat encountered and to mention. WIFI or wireless local area Network is a cost-effective easy deployment Network that makes users take advantage of vast data shared on the internet and by the network without the need for any cable for connections. Here in this overview paper by reviewing many researchers' techniques and works on the WLAN security topic, there are shared threats to WLAN and the ways of taking precautions against those threats as countermeasures and for which the tables are used. For comparison of techniques used by authors and some famous and highly dangerous threats are also defined further. WPA3's new security protocol is also defined with its newly found vulnerabilities and countermeasures except there is a conclusion on the downgrade attack problem with WPA3. Further, there are also countermeasures for that as well, nowadays people think the network is secured with standards defined by the IEEE organization but some know this is not the case so it makes it a more important area for research. © 2023 IEEE.

关键词： Wireless local area networks (WLAN)

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A Systematic Study on Ransomware Attack: Types, Phases and Recent Variants 5

A Systematic Study on Ransomware Attack: Types, Phases and R...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Krishna Prasad, D.S. Prasanna Kumar, H.R. Dept. of Computer & Communication Engineering. Karnataka574110 India Visvesvaraya Technological University Belagavi590018 India Pes Institute of Technology and Management Dept. of Information Science and Engineering Shivamogga India

ISBN: (纸本)9798350385649

The rise of ransomware attacks presents a major cybersecurity threat, leading to considerable financial losses and disrupting crucial operations across diverse sectors. In-dept. research on the field of ransomware assaults is presented in this study, with particular attention to the various kinds and variations that have appeared throughout time. This research includes a thorough examination of the strategies, processes, and methods that ransomware perpetrators use to carry out their operations. The study outlines the many stages in the lifecycle of ransomware attacks, including the introduction of infection vectors, the use of encryption tools, and the last step of extortion. The research also explores the terrain of ransomware variations, recognizing the evolution and diversity of these threats throughout time. With a taxonomy that categorizes variations depending on their dissemination methods, encryption algorithms, and evasion approaches. © 2024 IEEE.

关键词： Cybersecurity

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Leveraging Cross Lingual Speech Representations To Build ASR For Under-resourced Languages 26

Leveraging Cross Lingual Speech Representations To Build ASR...

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26th Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardization of Speech Databases and Assessment Techniques, O-COCOSDA 2023

作者： Mukherjee, Sougata Bannulmath, Prashant Deepak, K.T. Prasanna, S. R. Mahadeva Indian Institute of Technology Dharwad Dept. of Electrical Electronics and Communication Engineering Dharwad India Indian Institute of Information Technology Dept. of Electronics and Communication Engineering Dharwad India Indian Institute of Technology Dept. of Electrical Electronics and Communication Engineering Dharwad India

ISBN: (纸本)9798350344028

Automatic speech recognition (ASR) technology can help document and preserve under-resourced tribal languages by converting spoken words into text. But building robust Automatic Speech Recognition(ASR) models for tribal languages is challenging due to scarcity of annotated data. This work shows the building of text and speech corpora for two tribal languages namely Lambani and Kui and attempts to develop an ASR system for those. Wav2vec2.0 is known to learn higher dimensional powerful representation directly from raw audio data and boost the performance of under-resource data. In order to overcome the limitation of scarce annotated data for under-resourced languages, wav2vec2.0 framework has been used along with data augmentation techniques like Gaussian noise addition, Pitch variation and Reverberation which increases the data synthetically. As Kui and Lambani are both indic languages, so in the wav2vec2.0 framework a model which has been pretrained on 10k hours of data and 23 indic languages has been used to leverage the cross lingual representations for the development of ASR for these languages. Using wav2vec2.0 framework a WER of 41.55% and 49.57% and a CER of 12.49% and 12.52% has been achieved for 5 hours of Lambani and Kui respectively. The data augmentation techniques gives a relative improvement of 8.64% and 3.73% in terms of WER for Lambani and Kui. Besides this, this work also compares the performance of English language with the other two tribal languages which has already been used during pre-training with same amount of data setting and framework. © 2023 IEEE.

关键词： Speech recognition

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Real Time Human Assisted Path Planning for Autonomous Agent using VR 2

Real Time Human Assisted Path Planning for Autonomous Agent ...

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2nd Edition of IEEE Delhi Section Owned Conference, DELCON 2023

作者： Khemchandani, Vineeta Khan, Mohd Anas Barkaa, Mohd Usman Chandra, Sushil Wadalkar, Nachiket Milind Jss Academy of Technical Education Dept. of Information Technology Noida India Inmas Drdo Dept. of Biomedical Engineering Delhi India Inmas Drdo Cognitive Control and Machin Learning Division Delhi India

ISBN: (纸本)9798350322064

Path Planning is a term used in robotics that comprises motion planning approaches that can acclimate to real-time changes in the environment. Many problems in various fields are solved by proposing path planning which is widely applied in partially and unknown structured environments. Autonomous systems made up of mobile agents have established themselves as effective, durable, and adaptable instruments for military (such as search and rescue missions), commercial (such as Google self-driving cars), and exploration (such as space robots). When a target area needs to be rapidly searched (observed) by several military units (scouts, UAVs, UGVs), it is a very difficult issue for the defense to solve. This work is done considering problems faced by the defense in performing various operations in remote areas where path planning is essential. The main goal is to help defense to provide training in virtual reality and a better understanding of situations and to help making decisions in difficult times and increase performance. To overcome the risk and limitations this game is introduces actual (Real World) scenarios and provide the facility to present the whole operation virtually and perform various task remotely. It also includes situations like traffic light systems, AI car navigation algorithms, Swarm of vehicles and Rescue operations. Training in a virtual environment brings down the cost drastically because the replicas of simulate vehicles and tools that are simulated cost way less than actual inventory. © 2023 IEEE.

关键词： Motion planning

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Revealing the Potential of Hotel Improvements in Bali Based on Sentiment Analysis and Tourist Characteristics 11

Revealing the Potential of Hotel Improvements in Bali Based ...

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11th International Conference on Electrical engineering, Computer Science and Informatics, EECSI 2024

作者： Sumartini Saraswati, Ni Wayan Gede Darma Putra, I Ketut Sudarma, Made Sukarsa, I Made Yanti, Christina Purnama Tri Juniartini, Ni Komang Institute Bisnis Dan Teknologi Indonesia Faculty of Technology and Informatics Denpasar Indonesia Udayana University Dept. of Information Technology Denpasar Indonesia Udayana University Dept. of Engineering Science Denpasar Indonesia

ISBN: (纸本)9798350355314

Bali is a tourist destination with the largest market share in Indonesia. So the progress of Bali tourism has a major contribution to the country's foreign exchange earnings. This of course cannot be separated from the support of the Bali hotel industry. This research intends to reveal the potential for hotel development in Bali based on sentiment analysis and analysis of tourist characteristics through data analytic processes. From the results of the sentiment analysis, several aspects were obtained that can be used as references to strengthen and maintain the positive image, such as the friendliness of the staff and improving aspects that cause tourist dissatisfaction, such as room replacement. So hotel services in Bali will get better. The potential for hotel improvement in Bali can also be supported by understanding the characteristics of the guests. This research uses a clustering method to group tourists who stay in star hotels and budget hotels. Understanding the characteristics of each tourist cluster can be a reference for marketing strategies and decision-making in this industry. © 2024 IEEE.

关键词： Hotels

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Predictive Analysis of Jordan Road Accidents Severity Using Machine Learning

Predictive Analysis of Jordan Road Accidents Severity Using ...

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2023 International Symposium on Networks, Computers and Communications, ISNCC 2023

作者： Mustafa, Dheya Sawaged, Layan Khabour, Safaa M. The Hashemite University Faculty of Engineering Dept. of Computer Engineering Zarqa13133 Jordan Yarmouk University Faculty of Information Technology and Computer Sciences Dept. of Information Systems Irbid21163 Jordan

ISBN: (纸本)9798350335590

Jordan has a high and growing level of traffic accidents reaching 160,600) accidents in 2021, (11,241) of them had human injuries, (589) deaths, and (320) million JOD losses. Road traffic accidents are currently the 8th leading cause of death worldwide, accounting for about 1.35 million fatalities annually. Understanding the primary causes of these accidents and the circumstances in which they occur is essential if governments throughout the world are to put policies in place to limit the number of fatalities brought on by traffic accidents. This project has two objectives: (i) to learn more about Jordan's present road accident situation by performing an exploratory study on several road accident datasets, and (ii) to investigate the effectiveness of various machine-learning techniques in predicting the severity of road accidents in Jordan. The dataset entities were collected, collated, explored, and prepared for use in the model. To assess their predictive performance, five different classification algorithms were trained and tested. The findings of the present study demonstrate that the best algorithm was Logistic Regression, which had an accuracy of 98.1%. © 2023 IEEE.

关键词： Machine learning

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