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Anuvaadika: Implementation of Sanskrit to Hindi translation tool using rule-based approach

Recent Advances in computer science and Communications 2020年第6期13卷 1136-1151页

作者： Agrawal, Prateek Jain, Leena Department of Computer Science Engineering Lovely Professional University Jalandhar India Department of Computer Science Engineering IKG-Punjab Technical University Kapurthala India Department of Computer Applica-tions Global Institute of Management and Emerging Technologies Amritsar India

Background: Sanskrit is claimed as the second oldest language of the world and in ancient days, Sanskrit was considered as mother tongue in the larger part of India. But now, it is strug-gling for its acceptance in common people. Objective: Objective of the work is to develop algorithms for stemming of Sanskrit words, implement semantic analysis, discourse integration and pragmatic analysis. Another objective is to implement a translation tool that is able to translate Sanskrit text into Hindi. Methods: Rule Based Method is used to prepare the corpora and implement the proposed work. Results: An interface is made available through which step by step translation can be seen and understood. Conclusion: This tool will be helpful to those who are familiar in Hindi language but unable to learn Sanskrit due to the scarcity of language experts. More than 60 million people from India and abroad who are active Hindi users and work on computer, can get themselves connected with Sanskrit and also can learn the Sanskrit fundamentals by self. © 2020 Bentham science Publishers.

关键词： Semantics

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Exploring Local Governance and Sustainability Challenges in Community Reserves: A Data science Perspective with Global Insights

Exploring Local Governance and Sustainability Challenges in ...

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Electrical Power Engineering, Communication and Computing Technology(ODICON), Odisha International Conference on

作者： Sachin Pavithran A P Anurima Banerjee G S Pradeep Ghantasala Rajesh Sharma R U Ananthanagu Suresh Kumar Natarajan Pellakuri Vidyullatha Department of Humanities and Social Sciences Jain (Deemed-to-beUniversity) Ramanagara India Department of Humanities and Social Sciences (HCIMT Kozhikode) Department of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bengaluru India Center of Excellence in Immersive Technologies Alliance University Bengaluru India School of Computer Science and Engineering Jain (Deemed-to-beUniversity) Ramanagara India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur Andhra Pradesh India

ISBN: (数字)9798350354379

ISBN: (纸本)9798350354386

As one of the furthermost noticeable industries, tourism strives for to magnify the situation in numerous forms, effectually addressing the dissimilar matters and concerns into the world nowadays. Frequently, these issues disturb the ecologically momentous areas and the local communities on a higher note. It's the need of the hour to check the forecasts of sustainable and community-based coastal tourism, whichever targets to promote the area's tourism potential over vigorous involvement by the local community although preservative the aboriginal ecological balance. Kerala, a classic tourism destination in India, provides significant opportunities for livelihood options to the local community who depend on natural resources. The contemporaneous research paper was centered on a case study of Kadalundi- Vallikkunnu Community Reserve in Kerala, the local authority and several influences it could need onto the local community then the recommendations whichever could be measured to discourse a interrelated issues. A vast portion of the respondents, having tourism activities as their primary source of income, have identified the problem of environmental degradation as prevalent in the area. In contrast, the rest are unaware of the harmful effects happening to the natural ecosystem, primarily because of waste disposal and water pollution. The paper is an endeavor to shed graceful on the local governance system of community reserve and socio-economic aspects of the local communities on the development of tourism initiatives in Kerala.

关键词： Ecosystems Sea measurements Livelihood Environmental degradation Water conservation Water pollution Time measurement Pollution measurement Waste disposal Sustainable development

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Sum Computation Rate Maximization in Self-Sustainable RIS-Assisted MEC

Sum Computation Rate Maximization in Self-Sustainable RIS-As...

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2023 IEEE INFOCOM Conference on computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Li, Han Liu, Ming Gao, Bo Xiong, Ke Fan, Pingyi Letaief, Khaled B. School of Computer and Information Technology Eng. Res. Center of Network Management Technology for High Speed Railway of Ministry of Education Beijing Jiaotong University Beijing100044 China Beijing Jiaotong University Collaborative Innovation Center of Railway Traffic Safety Beijing100044 China Tsinghua University Department of Electronic Engineering Beijing100084 China Hong Kong University of Science and Technology Department of Electrical and Computer Engineering Hong Kong Hong Kong

ISBN: (纸本)9781665494274

This paper studies a self-sustainable reconfigurable intelligent surface (SRIS)-assisted mobile edge computing (MEC) network, where a SRIS first harvests energy from a hybrid access point (HAP), and then enhances the users' offloading performance with the harvested energy. To improve computing efficiency, a sum computation rate maximization problem is formulated. Based on the alternating optimization (AO) method, an efficient algorithm is proposed to solve the formulated non-convex problem. Simulations show that when the SRIS is deployed closer to the HAP, a higher performance gain can be achieved. © 2023 IEEE.

关键词： Mobile edge computing

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Avian abundance and diversity in three urbanized university campuses at different elevations in Northern Mindanao, Philippines

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Biodiversity 2025年第1期26卷 62-73页

作者： Pedrera, Joven A. Ascaño, Cordulo P. Piloton, Queenilyn A. Relox, Richel E. Cagurin, Giovanni B. Mugot, Dennis A. Palma, Richmund A. Maglunsod, Jessica G. Gonzaga, Apolinario B. Taylaran, Renante D. Quirino, John Preach C. Acma, John Mikel M. Valdez, Ruthy Mae B. Getuaban, Geisha Mae V. Agbas, Jessa Marie A. Acosta, Pelmar M. Roa, Mitchie M. Cardoza, Marjho Mae S. Calvis, Liza H. Llevado, Jomar C. Landicho, Junar A. Moncada, John David O. Handag, Sansen A. Walag, Angelo Mark P. Department of Environmental Science and Technology University of Science and Technology of Southern Philippines–Cagayan de Oro Cagayan de Oro Philippines Department of Science Education University of Science and Technology of Southern Philippines–Cagayan de Oro Cagayan de Oro Philippines Mathematics and Science Service Unit University of Science and Technology of Southern Philippines–Claveria Claveria Philippines Department of Agroforestry University of Science and Technology of Southern Philippines–Claveria Claveria Philippines Department of Agronomy University of Science and Technology of Southern Philippines–Claveria Claveria Philippines Department of Technology and Livelihood Education University of Science and Technology of Southern Philippines–Claveria Claveria Philippines Department of Manufacturing Engineering Technology University of Science and Technology of Southern Philippines–Jasaan Jasaan Philippines Department of Technology Communication Management University of Science and Technology of Southern Philippines–Jasaan Jasaan Philippines Department of Information Technology University of Science and Technology of Southern Philippines–Villanueva Villanueva Philippines Department of Electro-Mechanical Technology University of Science and Technology of Southern Philippines–Villanueva Villanueva Philippines Arts and Sciences Unit University of Science and Technology of Southern Philippines–Oroquieta Oroquieta Philippines Department of Food Processing and Technology University of Science and Technology of Southern Philippines–Oroquieta Oroquieta Philippines Department of Marine Biology University of Science and Technology of Southern Philippines–Panaon Panaon Philippines Department of Information Technology University of Science and Technology of Southern Philippines–Cagayan de Oro Cagayan de Oro Philippines Department of Computer Science University of Science and Technology of Southern Philippines–Cagayan de Oro Cagayan de Oro Philippines

This study investigates the impact of urbanization and elevation on avian diversity across three university campuses in the Philippines. Urbanization, a significant driver of global environmental change, negatively affects biodiversity by altering natural habitats. Birds, frequently used as bioindicators, are vital subjects for studying urban impacts due to their visibility and sensitivity to environmental changes. This research compares the abundance of bird families across campuses at different elevations, revealing significant variations influenced by urban structure, vegetation, and resource availability. Line transect, point count, and mist-netting methods were employed to survey the birds in the study area following established methods. The family Pycnonotidae is most abundant in the low-elevation urban campus (University of science and Technology of Southern Philippines - Cagayan de Oro), while families like Nectariniidae and Cuculidae are more prevalent in the high-elevation campus (USTPClaveria). These findings underscore the importance of habitat diversity and resource availability in supporting avian communities. The study highlights the potential of urbanized university campuses to serve as refuges for biodiversity if managed appropriately. Enhancing habitat complexity, maintaining green spaces, and ensuring diverse food resources are crucial for sustaining bird populations. The results emphasize the need for targeted conservation efforts within urban campuses to preserve and promote avian diversity in increasingly urbanized landscapes. © 2024 Biodiversity Conservancy International.

关键词： Avian diversity conservation strategies urban campuses urban spaces urbanization

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The Smart Application of Data Mining in the Detection of Fraudulent Transactions 3

The Smart Application of Data Mining in the Detection of Fra...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Bodhankar, Aniruddha Aswal, Upendra Singh Arivazhagn, D. Pund, Sachin S. Kulkarni, Nandini Chaturvedi, Sudhir Kumar Dr. Ambedkar Institute of Management Studies and Research- Nagpur Department of Data Science & Information Systems Nagpur India Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Symbiosis International University Department of Symbiosis School of Planning Architecture and Design Nagpur Nagpur India Business School Academy of Maritime Education and Training Deemed to Be University Department of Amet Chennai India Upes Department of School of Engineering Dehradun India

ISBN: (纸本)9798350319125

Records mining is a powerful analytical device used to find out styles, correlations, and traits in large facts sets. Smart application of data mining methods within the detection of fraudulent transactions has finished an extensive quantity of success. It normally entails statistical algorithms, facts evaluation, and machine getting to know techniques to stumble on suspicious sports associated with fraud. Using statistics mining techniques, it's far possible to music the behaviour of clients, discover anomalous transaction styles and developments in huge datasets, come across frauds and generate signals on suspicious activities. It also allows to identify which forms of merchandise are frequently centered, which price methods are used, which places are problem to danger, and which traders have capacity credit card fraud. The utility of facts mining within the detection of fraudulent sports entails principal techniques. The first method makes use of conventional techniques used by banks, credit groups and other retailers, which includes account reconciliation, annualized billing and complex question processing. Those methods are used to generate reviews that are used by investigators to perceive probably suspicious activities. The second technique entails the usage of superior analytical techniques such as neural networks, decision timber, and clustering algorithms. These strategies have the functionality to stumble on facts irregularities in several conditions that were formerly unseen or unknown. © 2023 IEEE.

关键词： developments entails reconciliation statistics transaction

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An Overview of Natural Language Processing Techniques for Information Analysis 3

An Overview of Natural Language Processing Techniques for In...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Al-Sarori, Mokhtar Hussein Pund, Sachin S. Charitha, Bondili Bhavya Kaushal, Ashish Lal, Bechoo Chaturvedi, Sudhir Kumar University of Saba Region Department of Copmute Science Yemen Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Gitam University Department of Gitam School of Business India Jindal Global Business School O P Jindal Global University Haryana Sonipat India Konenru Lakshmaiah Education Foundation Department of Computer Science and Engineering AP Vaddeswaram India Department of School of Engineering Upes Dehradun India

ISBN: (纸本)9798350319125

natural Language Processing (NLP) is an increasingly essential and rapidly advancing discipline of laptop technological know-how and artificial intelligence, centered on the development of algorithms and methods for analyzing big our bodies of natural language textual content. Records analysis entails extracting applicable records from natural language files, knowing how to interpret the textual content, and the way to practice the evaluation to diverse obligations. NLP strategies for data evaluation can consist of entity recognition, part-of-speech tagging, sentiment analysis, textual content type, summarization, query processing, and topic detection. Entity reputation is the method of tagging and assigning semantic labels to words or phrases in a text, frequently with the purpose of categorizing them by kind or class. The give up result is a set of entities that could then be in addition analyzed with other NLP strategies. Component-ofspeech tagging is the process of labeling words in a text primarily based on their part of speech. This can help become aware of vital phrases in a frame of text, helping in semantic or syntactic analyses. © 2023 IEEE.

关键词： assigning categorizing frequently strategies summarization

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Enhancing Fingerprint Security Using CNN for Robust Biometric Authentication and Spoof Detection

Enhancing Fingerprint Security Using CNN for Robust Biometri...

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Technological Advancements in Computational sciences (ICTACS), International Conference on

作者： Munish Kumar Ankita Tiwari Shilpa Choudhary Monali Gulhane Bhawna Kaliraman Rashmi Verma Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram India Department of Mathematics Koneru Lakshmaiah Education Foundation Vaddeswaram India Department of Computer Science and Engineering (AI & ML) Neil Gogte Institute of Technology Hyderabad India Department of CSE Symbiosis Institute of Technology (SIT) Nagpur Symbiosis International (Deemed University) (SIU) Pune India Department of Computer Science and Engineering DPG Institute of Technology and Management Gurugram India

Fake fingerprint recognition needs to pose a significant problem in the quickly developing field of biometric security. The creation of creative and effective spoof detection systems has become crucial as weaknesses in traditional authentication methods have been revealed. To solve this problem, this research employs Convolutional Neural Networks (CNNs) for next-generation biometric security, a ground-breaking approach. The proposed CNN-based fingerprint spoof detection approach utilizes deep learning inherent capabilities to extract complex patterns and information from fingerprint photos. The CNN model trains on a broad dataset containing multiple spoofing attempts to distinguish precisely between authentic and fake fingerprints. There are two significant contributions from this study. First, in order to fully train and assess the CNN model, we provide two datasets covering a wide range of fingerprint spoofing scenarios. Second, by successfully adjusting to the always-changing environment of spoofing tactics, our custom-built architecture outperforms traditional approaches and establishes new standards in detection accuracy. These results highlight CNNs' better capacity to discriminate between authentic and false fingerprints, placing them as a key component of future biometric security systems. This study highlights the value of utilizing cutting-edge technologies, like CNNs, to strengthen biometric security against new threats. By combining cutting-edge deep learning algorithms with the complexities of fingerprint spoof detection, we enter a new age of next-generation biometric security that promises enhanced accuracy and resilience in the face of shifting challenges. Comparing the suggested system to earlier methods, accuracy is 98.99%.

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Video Anomaly Detection with Spatio-Temporal Inspired Deep Neural Networks (DNN)

Video Anomaly Detection with Spatio-Temporal Inspired Deep N...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Anil Kumar Gupta Rupak Sharma Rudra Pratap Ojha Department of Computer Science and Engineering SRMIST Modinagar Ghaziabad U.P. Department of Computer Science and Engineering Government Polytechnic (Affiliated to Board of Technical Education U.P) Bareilly Uttar Pradesh India Department of Computer Science and Engineering Ghaziabad U.P. Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management (GLBITM) (Affiliated to AKTU) Greater Noida Uttar Pradesh India

Intelligent surveillance systems must be able to detect anomalies promptly to prevent malicious activity. It is common for deep learning methods to be used in video anomaly detection to focus on analyzing video streams from just one camera with a single scenario. Using large-scale training data with high complexity is necessary for these deep learning methods. This paper uses a spatiotemporal-inspired Deep Neural Network (DNN) to detect video anomalies. Rather than expensive optical flow calculations, a Deep Neural Network (DNN) is used for motion information in the proposed approach to achieve high recognition accuracy at a low computational cost. Experimental results on publicly available datasets demonstrate that the proposed model provides better input frame generation performance and is more accurate than existing approaches.

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Wide Range Data Transmission In Deep Water Sensor Network With Waves Via Wireless 2

Wide Range Data Transmission In Deep Water Sensor Network Wi...

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2nd International Conference on Advance Computing and Innovative technologies in Engineering, ICACITE 2022

作者： Someswararao, Ksnv Umamaheswaran, S.K. Umrao, Dhananjay Lal, Sujesh P Narayana, M Srinivasa Shukla, Surendra Kumar Electronics and Communication Engineering Dadi Institute of Engineering and Technology Anakapalle India Sri Sai Ram Engineering College Department of Mathematics TN Chennai India Computer Science and Engineering Naraina Vidya Peeth Engineering & Management Institute U.P. Kanpur India Federal Institute of Science and Technology Department of Computer Applications Ernakulam India Kl Business School K L University Koneru Lakshmaiah Education Foundation Vijayawada India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9781665437899

The study explores about the Wireless communication is one of the fastest growing and most active technology regions of the world of telecommunication. Wireless communication is the transmission of data from one location to another without the use of cables, cables, and other physical media. Information is conveyed from source to recipient across a defined distance in a communications network using general. The transmitter may be positioned anywhere within a few metres while using Wireless Communication. Our lives are responding to diverse stimuli, and the digital network, in particular, is an integral component of our daily existence. Cellphones, GPS, remotes, Bluetooth radio, and Wi-Fi are some of the most often utilised Wireless Communication Networks in our daily lives.. In this paper, a study of UWSNs is conducted. Underwater communication channels, environmental considerations, localization, medium access, routing methods, and the influence of packet size on communication. We examined currently known approaches and explored their benefits and drawbacks in order to identify new research avenues for future advancements in underwater sensor networks. © 2022 IEEE.

关键词： Data acquisition

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Automatic Vehicle License Plate Recognition Using Optimal Deep Learning Model

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computers, Materials & Continua 2021年第5期67卷 1881-1897页

作者： Thavavel Vaiyapuri Sachi Nandan Mohanty M.Sivaram Irina V.Pustokhina Denis A.Pustokhin K.Shankar College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science&Engineering IcfaiTechICFAI Foundation for Higher EducationHyderabadIndia Assistant professor Research Research CenterLebanese French UniversityErbil44001Iraq Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia Department of Computer Applications Alagappa UniversityKaraikudiIndia

The latest advancements in highway research domain and increase in the number of vehicles everyday led to wider exposure and attention towards the development of efficient Intelligent Transportation System(ITS).One of the popular research areas i.e.,Vehicle License Plate Recognition(VLPR)aims at determining the characters that exist in the license plate of the *** VLPR process is a difficult one due to the differences in viewpoint,shapes,colors,patterns,and non-uniform illumination at the time of capturing *** current study develops a robust Deep Learning(DL)-based VLPR model using Squirrel Search Algorithm(SSA)-based Convolutional Neural Network(CNN),called the SSA-CNN *** presented technique has a total of four major processes namely preprocessing,License Plate(LP)localization and detection,character segmentation,and *** Transform(HT)is applied as a feature extractor and SSA-CNN algorithm is applied for character recognition in *** SSA-CNN method effectively recognizes the characters that exist in the segmented image by optimal tuning of CNN *** HT-SSA-CNN model was experimentally validated using the Stanford Car,FZU Car,and HumAIn 2019 Challenge *** experimentation outcome verified that the presented method was better under several *** projected HT-SSA-CNN model implied the best performance with optimal overall accuracy of 0.983%.

关键词： Deep learning license plate recognition intelligent transportation segmentation

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