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Revolutionizing Digital Media Content using a Smart Drone and an Innovative ML Technique 22

Revolutionizing Digital Media Content using a Smart Drone an...

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22nd International Learning and technology Conference, L and T 2025

作者： Almalki, Faris A. Almarzouki, Rahaf A Technology Taif University College of Computers and Information Department of Computer Engineering Taif Saudi Arabia King Abdulaziz University Collage of Economics and Admissions Department of Management Information System Jeddah21589 Saudi Arabia

ISBN: (纸本)9798331532215

In the contemporary digital age, the fields of journalism and social media assume a pivotal role in disseminating information about current events and issues to the public. However, conventional techniques for gathering news and capturing images frequently encounter constraints and limitations. In recent years, technological advancements have transformed the creation and consumption of digital media content. This study presents an innovative solution that combines a smart drone with a reinforcement learning (RL) machine learning technique to enhance digital media content in a timely manner. The proposed framework has been subjected to validation and testing in a real-world scenario in Taif City through the transfer of rich digital media content. The results demonstrate promising outcomes, which support Saudi Arabia's efforts to enrich digital media content for tourism. © 2025 IEEE.

关键词： Adversarial machine learning

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Interoperability and Standardization in the Internet of Things 9

Interoperability and Standardization in the Internet of Thin...

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9th International Conference on Science, technology, engineering and Mathematics, ICONSTEM 2024

作者： Saidala, Ravi Kumar Haseeb, V.V. Padmapriya, G. Jayabalan, S. Priya, V. Kalai Shaikh, Anwar Ahamed Alliance University Department of Computer Science Engineering Karnataka Bangalore560076 India Nam College Department of Computer Science Kerala Tamil Nadu Kallikkandy 670693 India School of Computing Srm Institute of Science And Technology Department of Computing Technologies Chennai Tamil Nadu Kattankulathur603203 India Panimalar Engineering College Department of Computer Science And Business System Tamil Nadu Chennai600123 India Rmk College of Engineering And Technology Department of Computer Science And Engineering Puduvoyal601206 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram522502 India

ISBN: (纸本)9798350365092

This research highlights the importance of standards and interoperability in the IoT. An essential component of IoT ecosystems is interoperability, which refers to the ability for various systems and devices to converse and share data. Formats for data, methods of communication, and safeguards are all outlined by standards. Widespread adoption and scalability are made possible through interoperability and standards, which allow devices from many manufacturers to communicate with one another. This research investigates the alliances, regulatory authorities, and commercial associations that cooperate in the creation and advancement of open standards that can be embraced by other entities. The main objective of the research is to showcase the construction of an Internet of Things device capable of communicating with various embedded peripheral protocols utilizing Plug and Play (PnP) technology. Moreover, the research examines the impact of regulatory frameworks on the IoT ecosystem and their role in fostering interoperability. An IoT ecosystem necessitates a standardized and open environment to provide optimal performance in terms of connectivity, data exchange, and innovation. This research contributes to the progress of harmonizing and achieving interoperability among World Wide Web Things. © 2024 IEEE.

关键词： Interoperability

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Text to Image Generation Using Attentional Generative Adversarial Network 1

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1st International Conference on Advanced Computing, Machine Learning, Robotics and Internet Technologies, AMRIT 2023

作者： Rao, Supriya B. Shetty, Shailesh S. Singh, Chandra M, Srinivas P. Bekal, Anush Department of Artificial Intelligence and Machine Learning New Horizon College of Engineering Bangalore Karnataka Mangaluru India Department of Computer Science and Business System Srinivas Institute of Technology Karnataka Mangaluru India Department of Electronics & Communication Engineering Sahyadri College of Engineering & Management Karnataka Mangaluru India Department of Computer Science Engineering Sahyadri College of Engineering & Management Karnataka Mangaluru India

ISBN: (数字)9783031472213

ISBN: (纸本)9783031472206

AttnGan – Attentional Generative Adversarial Network (GAN) is a type of GANs that is used for text to image generation. Unlike other art models, it focuses on fine-grained word level information and once the model is trained by mapping the images and the corresponding text in the dataset, the model will generate image part-by-part using the image description given by the user as an input to the model. Current paper, focuses on the conversion of text into images based on the description provided by the user. This enables them to translate their ideas in the form of text into images of their required choices. The model is initially trained by the description of the text and images and when the user provides the text as an input to the system, it is used as a testing data. By analyzing the text word-by-word, the respective images pertaining to the text is generated part-by-part by considering the text description into account. This can heavily help the users in a applications such as in editing aids, documental archives, etc. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Generative adversarial networks

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Ethiopic Cryptography: An Efficient Hybrid Encryption Algorithm for Reducing Cybersecurity Attack 11th

Ethiopic Cryptography: An Efficient Hybrid Encryption Algori...

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11th EAI International Conference on Advancement of Science and technology, ICAST 2023

作者： Akele, Tadesse Birara Bahiru, Tadesse Kebede Molla, Tibebu Legesse Fentie, Shambel Dessale Belay, Tadesse Destaw Marye, Almaz Yemataw Getaneh, Mersha Derese Department of Information System Kombolcha Institute of Technology Wollo University Kombolcha Ethiopia Department of Information Technology Kombolcha Institute of Technology Wollo University Kombolcha Ethiopia Deparment of Software Engineering Kombolcha Institute of Technology Wollo University Kombolcha Ethiopia Department of Computer Science Kombolcha Institute of Technology Wollo University Kombolcha Ethiopia

ISBN: (纸本)9783031641503

Cryptography is an essential tool in ensuring the security of data during network communication. Network and service providers prioritize data security to ensure secure data exchanges. Ethiopic cryptography is a unique encryption method that utilizes the Amharic language, prevalent in Ethiopia. Unlike Latin alphabets, Amharic consists of 287 characters, making decryption challenging. The encryption process involves converting the text to Amharic and then mapping it to a pair of randomly chosen two-bit English alphabets, creating an intermediate cipher. The Ethiopic cryptography algorithm employs a hybrid approach, using the RSA algorithm for secure key exchange and the Advanced Encryption Standard algorithm for text confidentiality. The algorithm comprises three phases—translation, mapping, and encryption—contributing to its effectiveness in securing data over the network. Decryption requires familiarity with the Amharic language and mapping details. The algorithm demonstrates a stronger avalanche effect (97%) in comparison with Blowfish and DES. The algorithm is proposed and evaluated using the design science research methodology, and its performance is validated through simulation using MATLAB and BunnaScript tools, considering factors like the avalanche effect, time complexity, and memory consumption. The evaluation shows that the suggested solution operates faster, requires lesser time for data encryption, and uses less memory than other methods in use. Overall, the proposed Ethiopic cryptography algorithm proves to be an efficient and effective method for securing data during network communication, offering stronger text confidentiality and an improved avalanche effect. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： MATLAB

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Honeypot Comparison of Attack Detection and Mitigation of SSH Attack 3

Honeypot Comparison of Attack Detection and Mitigation of SS...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Ali, Wasif Sajid, Ahthasham Ghodke, Tanvi Ajit Malik, Rida Malik, Neeru Kaushik, Keshav Riphah Institute of System Engineering Riphah International University Department of Cyber Security Islamabad Pakistan Pimpri Chinchwad University Department of Computer Science and Engineering Maharashtra India School of Engineering & Technology Pimpri Chinchwad University Maharashtra Pune India Amity School of Engineering and Technology Amity University Mohali India

ISBN: (纸本)9798331518592

This research study addresses the importance of honeypots at multiple levels, which includes but not limited to placement in network or group of networks working alongside in an organization. This paper talks about the usage of multiple honeypots working alongside to log useful data for the mitigation of ongoing bot or actual attack this approach helps the organization better understand the threat they are dealing and the techniques which they can use to overcome the gap of the unseen security risks. The comparison will shed better light to the working and attack patterns of the ongoing attacks, gaining more confidence on using the honeypot for better protection. This allows strategic, optimized and critical insight to the evolving attack patterns. © 2024 IEEE.

关键词： Network intrusion

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Multi Attributes Recognition from Human Gait Analysis using MotionSense Dataset

Multi Attributes Recognition from Human Gait Analysis using ...

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2022 Mohammad Ali Jinnah University International Conference on Computing, MAJICC 2022

作者： Ibrar, Kainat Shaikh, Anam Zafar, Shakeel University of Wah Wah Department of Computer Science Pakistan Mehran University of Engineering and Technology Department of Computer System Engineering Jamshoro Pakistan UET Taxila Department of Computer Engineering Taxila Pakistan

ISBN: (数字)9781665475198

ISBN: (纸本)9781665475198

Human Gait analysis is a very prodigious and flourishing field of research nowadays, due to its immense importance in clinical and medical studies, rehabilitation, security and surveillance, crime investigation, health, sports, development of marketing applications and product optimization etc. Every human has a distinctive gait pattern, which with critical scrutiny may exhibit a lot of information about his identity and personal traits. Although researchers have made remarkable efforts in this field of research but there is a lack of work regarding sensorial gait analysis for identifying multi-attributes of a person. This paper proposes a novel framework to recognize multi-attributes i.e., user, gender, age and weight of a person based on gait analysis using smartphone built-in sensors including accelerometer, gyroscope and motion sensor. We have used an existing dataset named 'MotionSense' for human activity and attributes recognition. Multi-class machine learning algorithms are applied for training the dataset. We have achieved the accuracy of 99.75% for User, 99.74% for gender, 99.61% for age and 99.74% for weight recognition respectively. Experimental results and performance evaluation of the applied machine learning classifiers reveals the efficacy of the proposed scheme. © 2022 IEEE.

关键词： Classification (of information)

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Investigating the Effectiveness of Artificial Intelligence in Watermarking and Steganography for Digital Media Security 21

Investigating the Effectiveness of Artificial Intelligence i...

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21st International Multi-Conference on systems, Signals and Devices, SSD 2024

作者： Abdalwahid, Shadan M.J.A Hashim, Wassan Adnan Saeed, Mohammed Ganim Altaie, Sarmad A. Kareem, Shahab Wahhab Engineering College Erbil Polytechnic University Information System Engineering Dept. Erbil Iraq AIQAlam University College Medical Instruments Techniques Dept Kirkuk Iraq Dohuk Polytechnic University Department of Information Technology Dohuk Iraq University of Technology Computer Engineering Department Baghdad Iraq Erbil Technical Engineering College Erbil Polytechnic University Information System Engineering Dept. Erbil Iraq

ISBN: (纸本)9798350374131

Watermarking and Steganography are methods of embedding digital information within images or other media, such as text or audio, for the purpose of Copyright Protection or covert communication. This field of study is not recent and has been ongoing for several years, culminating in its current advanced stage. The utilization of Artificial Intelligence algorithms has played a pivotal role in revolutionizing various aspects, including security concerns and the precision of outcomes, as compared to traditional methods. This paper focuses on doing an in-depth analysis of cutting-edge research, techniques, and methodologies employed in the domain of Watermarking and Steganography, specifically in conjunction with Artificial Intelligence. By thoroughly examining and evaluating a collection of recent studies in this domain, we have scrutinized the outcomes of each study with respect to its research goal, the acquired results, the employed algorithm, and the research's robustness in terms of susceptibility to various forms of attacks and the technique of data embedding. Our findings indicate that the use of Artificial Intelligence algorithms has a substantial influence on enhancing result precision, system resilience, and establishing data ownership. Deep Neural Networks (DNN) are essential in Watermarking and Steganography due to their robustness, effectiveness, and accuracy. Novel methodologies and systems improve security, incorporation rates, precision of detection, and speed of convergence. Deep learning is being investigated in techniques such as data concealment, information hiding, and steganography to improve security. © 2024 IEEE.

关键词： Embeddings

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Multi-Speaker Diarization using Long-Short Term Memory Network 3

Multi-Speaker Diarization using Long-Short Term Memory Netwo...

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3rd IEEE International Conference on Artificial Intelligence, ICAI 2023

作者： Aafaq, Nayyer Qamar, Usama Khan, Sohaib Ali Khan, Zeashan Hameed Department of Avionics Engineering College of Aeronautical Engineering National University of Sciences and Technology NUST Islamabad Pakistan N.E.D UET Department of Computer & Information System Engineering Karachi Pakistan

ISBN: (纸本)9798350322125

The task of multi-speaker diarization involves de-tection of number of speakers and segregate the audio seg-ments corresponding to each speaker. Despite the tremendous advancements in deep learning, the problem of multi-speaker diarization is still far from achieving acceptable performance. In this work, we address the problem by first getting the timestamps employing voice activity detection and sliding window techniques. We further extract the Mel-Spectrograms / Mel-frequency Cepstral Coefficients (MFCC). We then train a Long Short-Term Memory (LSTM) network to get the audio embed dings named d-vectors. Subsequently, we employ K-Means and Spectral clustering techniques to segment all the speakers in the given audio file. We evaluate the proposed framework on publically available VoxConverse dataset and report results comparing with similar benchmarks in the existing literature. The proposed model performs better / at par with exisiting techniques despite simpler framework. © 2023 IEEE.

关键词： Long short-term memory

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A Comparative Analysis of Joomla, Drupal, Wordpress and ***: Exploring Features, Performance, and Suitability

A Comparative Analysis of Joomla, Drupal, Wordpress and ***:...

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2023 IEEE Asia-Pacific Conference on computer Science and Data engineering, CSDE 2023

作者： Prasad, Ashwin Ashika Sharma, Neeraj Anand Kumar, Anal School of Science and Technology The University of Fiji Department of Computer Science and Mathematics Fiji College of Engineering Science and Technology Fiji National University Department of Computing Sciences and Information System Fiji

ISBN: (纸本)9798350341072

In the dynamic landscape of web development, the judicious choice of platform and structure plays a pivotal role. This comprehensive study conducts a thorough comparison of four prominent web development technologies: ***, Joomla, Drupal, and WordPress. With a primary focus on scrutinizing features, performance, and overall suitability, the research aims to provide valuable insights for developers, businesses, and decision-makers. By objectively evaluating the merits and limitations of each technology, this study seeks to empower stakeholders with essential knowledge, enabling them to make informed decisions at the onset of web development projects. © 2023 IEEE.

关键词： Decision making

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Bat Algorithm: A Review on Theory, Modifications and Applications 3

Bat Algorithm: A Review on Theory, Modifications and Applica...

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3rd International Conference on Intelligent Cybernetics technology and Applications, ICICyTA 2023

作者： Singh, Hakam Witarsyah, Deden Misra, Alok Tiwari, Raj Gaurang Chitkara University School of Engineering and Technology Department of Computer Science and Engineering Himachal Paradesh Baddi India Telkom University School of Industrial and System Engineering Information System Departement Bandung Indonesia Lovely Professional University School of Computer Application Punjab Phagwara India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350394559

Due to its many applications in a variety of domains, including clustering, cloud computing, and power systems, metaheuristic algorithms have attracted a lot of interest from the scholarly community. By using their self-explorative and adaptive processes, these algorithms provide certain benefits over conventional methods. One well-known metaheuristic approach is effective in resolving optimization problems with constraints and without constraints. This technique was inspired by nature, notably the echolocation ability of bat species. The Bat Algorithm (BA) makes use of a powerful search mechanism to provide the best results when compared to other algorithms of the same class. The theoretical underpinnings of the BA are explored in depth in this research, along with several changes and advancements that have improved its functionality. These enhancements include adjustments to search tactics as well as other developments. The report also thoroughly examines how the BA may be used across a variety of fields, demonstrating its competence and adaptability. The BA has been effectively used in several real-world applications, from cloud computing to clustering, and each one is carefully investigated. The study also offers a thoughtful examination of the BA's possible advancements and future possibilities. It also entails investigating novel modifications and tactics that might improve its effectiveness in handling challenging optimization issues. This study seeks to direct practitioners and academics toward more effective and efficient metaheuristic algorithms, thereby stimulating improvements in optimization approaches. It does this by summarising the present state of the BA and imagining its future development. © 2023 IEEE.

关键词： Cloud computing

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