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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Revathi, B. Usharani, C. Kezial Elizabeth, S.K. Nagaraj, P. Nithya, D. Ramco Institute of Technology Department of Artificial Intelligence And Data Science Virudhunagar India Mangayarkarasi College of Engineering Department of Computer Science And Engineering Madurai India Kalasalingam Academy of Research And Education Department of Computer Science And Engineering Virudhunagar Krishnankoil India Theni Kammavar Sangam College of Technology Department of Computer Science And Engineering Theni India

ISBN: (纸本)9798350359299

Deep learning algorithms can summarize images to understand how to carry out necessary tasks. The purpose of this study is to compare several deep learning methods. Both experience-based and explanation-based learning are possible in deep learning. The most widely utilized algorithms, such as Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), Generative Adversarial Networks (GAN), Radial Basis Function Networks (RBFN), and Deep Belief Networks (DBN), and the Diabetic Retinopathy dataset is utilized in this study to evaluate the effectiveness of the algorithms. A comparative study of the classifiers reveals that CNN performs more accurately than the other approaches. © 2024 IEEE.

关键词： Classification (of information)

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Energy-Aware Scheduling for Tasks with Target-Time in Blockchain based Data Centres

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computer Systems science & engineering 2022年第2期40卷 405-419页

作者： I.Devi G.R.Karpagam Department of Computer Science and Engineering PSG College of TechnologyCoimbatore641004India

Cloud computing infrastructures have intended to provide computing services to end-users through the internet in a pay-per-use *** extensive deployment of the Cloud and continuous increment in the capacity and utilization of data centers(DC)leads to massive power *** intensifying scale of DCs has made energy consumption a critical *** paper emphasizes the task scheduling algorithm by formulating the system model to minimize the makespan and energy consumption incurred in a data ***,an energy-aware task scheduling in the Blockchain-based data center was proposed to offer an optimal solution that minimizes makespan and energy *** estab-lished model was analyzed with a target-time responsive precedence scheduling *** observations were analyzed and compared with the traditional scheduling *** outcomes exhibited that the developed solution incurs better performance with a response to resource utilization and decreasing energy *** investigation revealed that the applied strategy considerably enhanced the effectiveness of the designed schedule.

关键词： Cloud computing taskscheduling blockchain energy-aware virtual machine

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Malware Analysis of Cryptojacks: Crackonosh and Winstar Nss Miner

Malware Analysis of Cryptojacks: Crackonosh and Winstar Nss ...

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2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Raj, Sparsh Basta, Aditya Laksha, S. Sinha, Samarth Asha, S. Vellore Institute of Technology School of Computer Science and Engineering Chennai India National Institute of Technology Department of Computer Science and Engineering Rourkela India

ISBN: (纸本)9798350319200

Malware analysis is an essential process for understanding the behaviour and purpose of a piece of malware. Cryptojacks are malware designed to exploit the computational resources of a machine to mine cryptocurrency. The year of 2017 saw the rise of Cryptocurrency which led to the rise of Cryptojacks. Despite being a very deadly piece of malware, Cryptojacks aren't researched much because unlike other pieces of malware, they don't cause any damage to the data or ask for any ransom. In 2018, with the end of Coin-hive project, browser based Cryptojacks disappeared but machine based Cryptojacks are still in the wild. In our work, we are analysing 2 Cryptojacks one taken from 2017 era (WinstarNssMiner) and another (Crackonosh) which was released recently(last week of June). We aim to find out how these Cryptojacks work and also about how they have changed over time. In turn, we can understand how the attitude of hackers has changed towards Cryptojacks. © 2023 IEEE.

关键词： crackonosh cryptojacks dynamic analysis Malware analysis static analysis winstarnssminer

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Machine Learning for the Exposure of Malicious URLs 1

Machine Learning for the Exposure of Malicious URLs

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1st International Conference on Recent Advances in Information technology for Sustainable Development, ICRAIS 2023

作者： Hanji, Bhagyashri R. Kanagavalli, R. Dayananda Sagar Academy of Technology and Management Computer Science and Engineering Bangalore India Global Academy of Technology Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350306637

In today's era, as per the statistics for world-wide internet users or digital population as on April 2023, there are 5.18 billion internet users worldwide, which goes to 64.6 percent of global population. Of this total, 4.8 billion, or 59.9 percent of the world's population are social media users. [***/statistics617136/digital-population-worldwide]. Enhancement in technology and internet usage increases the scope for cyber-criminal activities. As the connectivity and the number of users grow, there is a proportional increase in attackers. Vindictive sites or URLs become one of the significant dangers for network protection. Malevolent URLs are most risky danger prompting phishing assault, malware dissemination, Drive-by Downloads, Program Exploits, Data fraud in this computerized world. It's critical to remain cautious and safeguard us on the web. It is vital to be sufficiently mindful and have the option to identify and act against these dangers by not visiting such destinations or giving any private data. In this work we will focus on attacks through malicious URLS, working, preventions and machine learning algorithms used to detect malicious URLs. © 2023 IEEE.

关键词： Cybersecurity

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Gloss-Free Sign Language Translation using Sign2gpt-Next Technique

Gloss-Free Sign Language Translation using Sign2gpt-Next Tec...

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2024 International Conference on Computing and Intelligent Reality Technologies, ICCIRT 2024

作者： Babisha, A. Umarani Srikanth, G. Angel Kiruba, D.R. Sundar, R. Department of Artificial Intelligence and Data Science Panimalar Engineering College Chennai India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer Science and Engineering DMI College of Engineering Chennai India Department of Computer Science and Engineering School of Computing Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9798331510299

This work proposes a new approach to convert the data from sign language to spoken language without exposing the data to a gloss layer. Whenever gloss annotations are used which frequently are incomplete and act as an intermediate representation, it is usually found to be a bottleneck in translating sign language videos. In order to avoid this, the authors use a combination of modern machine learning algorithms to arrive at the conclusion. They use Dino-V2 Vision Transformer to implement the function of extracting the spatial features of the input sign language video frames. This model is particularly suitable for learning and visual patterns in general and particularly for capturing fine details of these patterns. Further, a spatio-temporal transformer layer is added to automate the temporal processing of the Sign-Language which helps in the arrangement of the body gestures and limb movements needed at a specific temporal frame. It is then translated into the desired spoken language using a multilingual Generative Pre-trained Transformer (GPT) model. The approach can be said to be a big leap forward in sign language transliteration especially for such situations where few Gloss annotations are available, and making way for better and improved tools for the Deaf and the hard-of-hearing. © 2024 IEEE.

关键词： Audition

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A versatile acoustically active surface based on piezoelectric microstructures

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Microsystems & Nanoengineering 2022年第3期8卷 51-60页

作者： Jinchi Han Mayuran Saravanapavanantham Matthew R.Chua Jeffrey H.Lang Vadimir Bulovic Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMA 02139USA

We demonstrate a versatile acoustically active surface consisting of an ensemble of piezoelectric microstructures that are capable of radiating and sensing acoustic waves.A freestanding microstructure array embossed in a single step on a flexible piezoelectric sheet of polyvinylidene fluoride(PVDF)leads to high-quality acoustic performance,which can be tuned by the design of the embossed *** high sensitivity and large bandwidth for sound generation demonstrated by this acoustically active surface outperform previously reported thin-flm loudspeakers using PVDF,PVDF copolymers,or voided charged polymers without *** further explore the directivity of this device and its use on a curved *** addition,high-fidelity sound perception is demonstrated by the surface,enabling its microphonic application for voice recording and speaker *** versatility,high-quality acoustic performance,minimal form factor,and scalability of future production of this acoustically active surface can lead to broad industrial and commercial adoption for this technology.

关键词： surface. piezoelectric versatile

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Web Scraping and Job Recommender System 2

Web Scraping and Job Recommender System

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2nd International Conference on Informatics, ICI 2023

作者： Sinha, Koustubh Sharma, Priyansh Sharma, Harshit Asawa, Krishna Jaypee Institute of Information Technology Computer Science Engineering Delhi India Jaypee Institute of Information Technology Computer Science Engineering Noida India

ISBN: (纸本)9798350343830

Web scraping is the process of autonomously obtaining data from webpages using computer software or tools. It has grown in popularity in recent years because of the volume of data available on the internet and the necessity for organizations and individuals to analyze and utilize this data to get the necessary and important information out of it for further analysis and application. Web scraping, together with automation tools, can create wonders. In this paper, we have focused on the latest web scraping techniques and their applications. One of the ideas is to assist those looking for employment on different firm job portals, which is discussed in this paper. Job tracking and scraping collect data from multiple platforms and are web-based tools that help job searchers locate the ideal job for them based on their categories and organize their job search more effectively. People are always on the lookout for a place where they can get their desired information so that they can easily apply for a job. After the collection of data based on user profile attributes, we recommend their success rate based on previous records and an appropriate machine learning model, and we also suggest what skills they can improve to land that job. Web scraping tools allow us to extract the necessary data from different websites in real time and present it to the user. We have discussed various ways to implement scraping and propose a job algorithm to process the extracted data and make it into meaningful information to help users land the best job. © 2023 IEEE.

关键词： Recommender systems

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Forensic Analysis and Detection of Spoofing Based Email Attack Using Memory Forensics and Machine Learning 1

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18th EAI International Conference on Security and Privacy in Communication Networks, SecureComm 2022

作者： Shukla, Sanjeev Misra, Manoj Varshney, Gaurav Department of Computer Science and Engineering Indian Institute of Technology Roorkee India Department of Computer Science and Engineering Indian Institute of Technology Jammu India

ISBN: (数字)9783031255380

ISBN: (纸本)9783031255373

Emails encounter many types of cyber-attacks and email spoofing is one of the most common and challenging investigation problems. This paper identifies spoofing-based email attacks in an organization by analyzing received and replied emails. The detection works by capturing the email traces via memory forensics. Unlike the traditional approaches of capturing the entire physical memory, we only capture the memory of relevant processes for email header extraction. It significantly reduces the size of the memory dump and makes detection faster. We suggest a novel mechanism called URL extractor, which uses seven novel features from URL to identify the live running email message process by applying ML that traces received emails and captures their header fields for analysis. The authentication header fields of SPF, DKIM, DMARC, and ARC are examined closely to develop a detection algorithm for received emails. Similarly, novel header fields of Reference along with MX record are applied for the detection of replied emails. The MX record is fetched to verify the domain name by sending a forward ns-lookup query to DNS. It also includes an email attack alert mechanism for intimating IT admins of an organization regarding suspected attacks. The results thus obtained show that email detection takes 35 secs (apprx.) to complete with high accuracy and low false positives. © 2023, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Cybersecurity

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Selective sampling and temporal positional encoding for monocular video based 3D human pose and shape estimation 5

Selective sampling and temporal positional encoding for mono...

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5th International Conference on Signal Processing and computer science, SPCS 2024

作者： Hou, Yupeng Wen, Han Zeng, Guangping School of Computer & Communication Engineering University of Science and Technology Beijing Beijing100083 China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

This study introduces a novel framework for video-based 3D human pose and shape estimation, termed Selective sampling and Temporal Positional Encoding (STPE). Our method leverages selective sampling and advanced positional encoding to tackle the temporal complexities of video data and the high cost and scarcity of annotated datasets. Inspired by the Masked Autoencoder (MAE), our approach adopts a selective sampling strategy that efficiently captures the essential dynamics of human motion from partial views, significantly reducing reliance on continuous frames. The framework incorporates Rotary Position Embedding (RoPE), using rotational angles to simplify positional encoding. This innovation decreases model complexity and boosts learning effectiveness. We also introduce randomized index positions during training, introducing variability and enhancing generalization across various datasets and motion patterns. Our model, validated on standard datasets like 3DPW, MPI-INF-3DHP, and Human3.6M, shows enhanced performance in accurate and robust 3D pose and shape capture compared to existing methods. Our results demonstrate that strategic frame sampling and sophisticated positional encoding can significantly improve accuracy and robustness of video-based pose estimation systems. © 2025 SPIE.

关键词： Video recording

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DISTANCE BETWEEN SPECIES BY CONFUSION OPERATORS OF MULTI-CLASS CLASSIFIERS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2025年第1期2025卷 171-182页

作者： Tarbă, Nicolae Irimescu, Ionela N. Pleavă, Ana M. Scarlat, Eugen N. Mihăilescu, Mona Doctoral School Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania Applied Sciences Doctoral School National University of Science and Technology POLITEHNICA Bucharest Romania CAMPUS Research Center National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept Research Center for Applied Sciences in Engineering National University of Science and Technology POLITEHNICA Bucharest Romania

We introduce a method to evaluate the similarities between classes of objects based on the confusion matrices coming from the multi-class machine learning (ML) predictors that operate in the vector space generated by the classes. Operation in the confusion domain allows us to use the distance as evaluation metric of the closeness of the relevant properties carried by the classes. We applied the method to semiquantitatively evaluate the effects of X-ray and carbon ion radiation on cultured SW1353 chondrosarcoma cells with respect to the non-irradiated reference. We prove that it is possible to draw useful information on the strength of cells nuclei changes. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Radiation effects

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