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International Conference on Contemporary Computing and informatics (IC3I)

作者： Kanwalpreet Kour Jhansi Bharathi Madavarapu Mudita Deepali Gupta Rajesh Kumar Dhanaraj Shilpa Saini Department of Computer Science and Engineering Lovely Professional University Punjab India University of Cumberlands United States Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Symbiosis Institute of Computer Studies and Research (SICSR) Symbiosis International (Deemed University) Pune India Department of CSE Chandigarh University Punjab India

Kashmir is a leading producer of walnuts in India. They are considered the healthiest nuts and are very costly owing to their nutritional value. Kashmir is one of the leading producers of walnuts, contributing to about 90% of production in India. However, the farmers don't get much higher rates for these organically produced walnuts as the separation of kernel and shell is a laborious task. This paper proposes an automatic device to separate walnut shells and their hulls making them market ready at a faster processing speed. The walnuts are passed through a conveyor belt where they are broken down by using automated hammer, applying the perfect pressure so as not to break the walnuts completely and ensure the kernel is taken out of the green and brown shell. The shell and the kernel are separated by the data from the color sensor and image processing technology with classification techniques. The device provides a sustainable solution for post harvest agricultural practices in walnut cultivation.

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Design of a Secure Machine Learning-Based Malware Detection and Analysis Scheme

Design of a Secure Machine Learning-Based Malware Detection ...

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2023 IEEE International Conference on Communications, Computing, Cybersecurity and informatics, CCCI 2023

作者： Kumar, Pankaj Obaidat, Mohammad S. Pandey, Piyush Wazid, Mohammad Das, Ashok Kumar Singh, Devesh Pratap Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India King Abdullah Ii School of Information Technology The University of Jordan Amman11942 Jordan School of Computing Srm University Jordan University of Science and Technology Beijing Beijing100083 China School of Computing Srm University TN Kattankulathur603203 India Algorithmic Research International Institute of Information Technology Center for Security Theory Hyderabad India

ISBN: (纸本)9798350302561

Today's world is rapidly growing towards the advanced concept of technology. technology nowadays is at its peak of development and has great advantages in all fields of work, whether it is in industrial automation, farming, weather forecasting, or disease detection and control. Despite its great advantages, it does have its negative side because a major population is using technology and general-purpose computing devices (i.e., desktops, laptops, smartphones, tablets, etc.). Therefore, most of their personal data is available online. The data is constantly in danger of getting stolen by malicious actors (i.e., hackers), who can find a way to get their hands on this data and then use it for their personal gain (i.e., money-making). The best-known technique to get this information is by using malware exploitation on the machine of the target. Malware is an executable or a binary that is malicious in nature. It may have various devastating effects, and in order to detect and make the system defensive, we need to propose a scheme to detect the malware in the system, analyze the particular file, and then mitigate it. In this paper, we propose a secure machine learning-based malware detection and analysis scheme (in short, SML-MDA). The conducted security analysis and formal security verification of the proposed SMLMDA prove its security against various types of potential attacks. The proposed SML-MDA is then compared with the other similar competing schemes, and its performance has been found to be better in terms of various performance metrics like accuracy and F1-score. © 2023 IEEE.

关键词： Machine learning

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Out Domain Data Augmentation on Punjabi Children Speech Recognition using Tacotron 1

Out Domain Data Augmentation on Punjabi Children Speech Reco...

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1st International Conference on Mechatronics and Artificial Intelligence, ICMAI 2021

作者： Hasija, Taniya Kadyan, Virender Guleria, Kalpna Centre of Excellence for Speech and Multimodal Laboratory Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Informatics School of Computer Science University of Petroleum and Energy Studies Dehradun India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

The performance of Automatic Speech Recognition (ASR) is directly proportional to the quality of the corpus used and the training data quantity. Data scarcity and more children's speech variability degrades the performance of ASR systems. As Punjabi is a tonal language and low resource language, less data is available for Punjabi children's speech. It leads to poor ASR performance for Punjabi children speech recognition. To overcome limited data conditions, in this paper, two corpora of different domains are evaluated for testing the feasibility of ASR performance. We have implemented Tacotron as an artificial speech synthesis system for Punjabi Language. The speech audios synthesized by Tacotron are merged with available speech corpus and tested on Punjabi children ASR using Mel Frequency Cepstral Coefficients (MFCC) + pitch feature extraction, and Deep Neural Network (DNN) acoustic modeling. It is noticed that the merged data corpus has shown reduced Word Error Rate (WER) of the ASR system with a Relative Improvement (RI) of 9-12%. © Published under licence by IOP Publishing Ltd.

关键词： Deep neural networks

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An Advanced Strategy for Efficient Agricultural Production using Machine Learning

An Advanced Strategy for Efficient Agricultural Production u...

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Automation, Computing and Renewable Systems (ICACRS), International Conference on

作者： S. Athinarayanan R Selvi K Rajakumari R Arunadevi M Robinson Joel Department of CSE School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Tamil Nadu India Department of Information Technology Dr MGR Educational and Research Institute Chennai Department of Computer Science BIHER (Bharath University) Chennai Department of Computer Science and Engineering Prince Shri Venkateshwara padmavathy Engineering College Chennai Tamil Nadu Department of Information Technology Kings Engineering College Chennai India

Agriculture is very important to the prosperity of the country. Climate change has created a variety of problems for the agricultural academic system. Since machine learning (ML) provides effective and affordable solutions, it is the most effective method for solving problems. Crop yield prediction involves estimating the crop yield based on historical data and a variety of other factors, including the climate, sometimes the environment, the water source, and warmth. This study analyses and discusses the use of the linear regression technique for evaluating agricultural production based on data from the earlier study. This study uses geographic and meteorological data to anticipate winter wheat production. It is motivated by this data science issue. The project’s goal is to find a solution to the cost loss issue. Actual agricultural data is used to build the models, which are then evaluated on samples. Using the vegetable yield forecasting model, end users (agriculturalist) may foresee crop production as they plant crops on agricultural land. The Linear Regression Algorithm method is used to forecast results with accuracy. The decision-making model’s creation will be aided by the availability of a sizable dataset.

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Nondestructive Chicken Egg Fertility Detection Using CNN-Transfer Learning Algorithms

arXiv

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arXiv 2023年

作者： Saifullah, Shoffan Drezewski, Rafal Yudhana, Anton Pranolo, Andri Kaswijanti, Wilis Suryotomo, Andiko Putro Putra, Seno Aji Khaliduzzaman, Alin Prabuwono, Anton Satria Japkowicz, Nathalie Institute of Computer Science AGH University of Krakow Krakow30-059 Poland Department of Informatics Universitas Pembangunan Nasional Veteran Yogyakarta Yogyakarta55281 Indonesia Center of Knowledge Engineering and Data Science Department of Electrical Engineering and Informatics Universitas Negeri Malang Malang65145 Indonesia Department of Electrical Engineering Universitas Ahmad Dahlan Yogyakarta55191 Indonesia College of Computer and Information Hohai University Nanjing211100 China Department of Informatics Faculty of Industrial Technology Universitas Ahmad Dahlan Yogyakarta55166 Indonesia Faculty of Agricultural Engineering and Technology Sylhet Agricultural University Sylhet3100 Bangladesh Faculty of Computing and Information Technology in Rabigh King Abdulaziz University Jeddah21589 Saudi Arabia Department of Computer Science American University WashingtonDC20016 United States

This study explored the application of CNN-Transfer Learning for nondestructive chicken egg fertility detection for precise poultry hatchery practices. Four models, VGG16, ResNet50, InceptionNet, and MobileNet, were trained and evaluated on a dataset (200 single egg images) using augmented images (rotation, flip, scale, translation, and reflection). The training results demonstrated that all models achieved high accuracy, indicating their ability to learn and classify chicken eggs’ fertility. However, variations in accuracy and performance were observed when these models were evaluated on the testing datasets. The InceptionNet exhibited the best overall performance, accurately classifying fertile and non-fertile eggs. It demonstrated excellent performance in all parameters of the evaluation metrics for both training and testing datasets. When evaluated on the testing datasets, it achieved an accuracy of 0.98, a sensitivity of 1 for detecting fertile eggs, and a specificity of 0.96 for identifying non-fertile eggs. The higher performance is attributed to its unique architecture, efficiently capturing features at different scales, which leads to improved accuracy and robustness. Further optimization and fine-tuning of the models might be necessary to address the limitations in accurately detecting fertile and non-fertile eggs using other models. This study highlighted the potential of CNN-transfer learning for nondestructive fertility detection and emphasized the need for further research to enhance the models’ capabilities and to ensure accurate *** Codes CS-Class: 68T07, 68T45, 68U10, ICT-Class: 94A08 © 2023, CC BY-SA.

关键词： Image classification

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Energy Preservation in MANET Using Self-Adaptive CH Selection with Advanced Genetic Algorithm 1

Energy Preservation in MANET Using Self-Adaptive CH Selectio...

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1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Indriyono, Bonifacius Vicky Pamungkas, Natalinda Abbas, Fatima Hashim Mintorini, Ery Almohamadi, Mohammed Mahmood, Sarmad Nozad Alani, Sameer Alkhayyat, Ahmed H. Rachmawanto, Eko Hari University of Dian Nuswantoro Information System Kediri Indonesia Al-Mustaqbal University College Medical Laboratories Techniques Department Hillah51001 Iraq University of Dian Nuswantoro Visual Communication Design Kediri Indonesia College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna66002 Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq University of Mashreq Research Center Medical Laboratories Techniques Baghdad Iraq College of Technical Engineering University of Mashreq the Islamic University Najaf Iraq University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia

ISBN: (纸本)9798350306484

Mobile Adhoc Networks (MANETs) is an emerging technology in both the industrial and academic research. The major drawback in MANETs is improving the battery capacity. MANETs are dynamic in nature therefore during communication it consumes more energy that reduces the overall energy efficiency of the network. Many past and present researches are concern about this problem. In this paper, Energy Preservation in MANETs using Self-Adaptive Cluster Head Selection with Advanced Genetic Algorithm (EPMSA-CHAG) approach is proposed where the CH selection is performed using two segments;they are initial parameter based on CH selection and Advanced Genetic Algorithm (AGA) based CH selection. At the initial stage the parameters which are considered for the CH selection are node degree, node stability, distance, residual energy, and speed and delivery rate. Using these parameters are the best fit for CH selection is chosen then in order to find the optimal best fit from the best fit calculation, Advanced Genetic Algorithm (AGA). The proposed EPMSA-CHAG approach is simulated using NS2 and the parameters which are considered for the performance analysis are packet delivery rate, energy efficiency, end to end delay, routing overhead and throughput. The methods that are taken for the comparative analysis are HLSPM-CHSR and HAMBO-CHLD. From the results calculated it is proven that the proposed EPMSA-CHAG approach achieved high packet delivery rate, energy efficiency and throughput as well as lower end to end delay and routing overhead when compared with the earlier methods HLSPM-CHSR and HAMBO-CHLD. © 2023 IEEE.

关键词： Energy efficiency

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VILMA: A ZERO-SHOT BENCHMARK FOR LINGUISTIC AND TEMPORAL GROUNDING IN VIDEO-LANGUAGE MODELS

arXiv

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arXiv 2023年

作者： Kesen, Ilker Pedrotti, Andrea Dogan, Mustafa Cafagna, Michele Acikgoz, Emre Can Parcalabescu, Letitia Calixto, Iacer Frank, Anette Gatt, Albert Erdem, Aykut Erdem, Erkut Koç University KUIS AI Center 2 Koç University Department of Computer Engineering Turkey University of Pisa Department of Computer Science Italy Institute of Information Science and Technologies "Alessandro Faedo" Italy Hacettepe University Department of Computer Engineering 6 Aselsan Research Turkey University of Malta Institute of Linguistics and Language Technology Malta Heidelberg University Department of Computational Linguistics Germany Amsterdam UMC University of Amsterdam Department of Medical Informatics Netherlands Amsterdam Public Health Methodology & Mental Health Amsterdam Netherlands Utrecht University Department of Information and Computing Sciences Netherlands

With the ever-increasing popularity of pretrained Video-Language Models (VidLMs), there is a pressing need to develop robust evaluation methodologies that delve deeper into their visio-linguistic capabilities. To address this challenge, we present VILMA1 (Video Language Model Assessment), a task-agnostic benchmark that places the assessment of fine-grained capabilities of these models on a firm footing. Task-based evaluations, while valuable, fail to capture the complexities and specific temporal aspects of moving images that VidLMs need to process. Through carefully curated counterfactuals, VILMA offers a controlled evaluation suite that sheds light on the true potential of these models, as well as their performance gaps compared to human-level understanding. VILMA also includes proficiency tests, which assess basic capabilities deemed essential to solving the main counterfactual tests. We show that current VidLMs’ grounding abilities are no better than those of vision-language models which use static images. This is especially striking once the performance on proficiency tests is factored in. Our benchmark serves as a catalyst for future research on VidLMs, helping to highlight areas that still need to be explored. © 2023, CC BY.

关键词： Computational linguistics

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Problems in NP Can Admit Double-Exponential Lower Bounds When Parameterized by Treewidth or Vertex Cover 51

Problems in NP Can Admit Double-Exponential Lower Bounds Whe...

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51st International Colloquium on Automata, Languages, and Programming, ICALP 2024

作者： Foucaud, Florent Galby, Esther Khazaliya, Liana Li, Shaohua Mc Inerney, Fionn Sharma, Roohani Tale, Prafullkumar Université Clermont Auvergne CNRS Mines Saint-Étienne Clermont Auvergne INP LIMOS Clermont-Ferrand63000 France Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden University of Gothenburg Sweden Technische Universität Wien Austria CISPA Helmholtz Center for Information Security Saarbrücken Germany University of Bergen Norway Indian Institute of Science Education and Research Pune India

ISBN: (纸本)9783959773225

Treewidth serves as an important parameter that, when bounded, yields tractability for a wide class of problems. For example, graph problems expressible in Monadic Second Order (MSO) logic and Quantified SAT or, more generally, Quantified CSP, are fixed-parameter tractable parameterized by the treewidth of the input’s (primal) graph plus the length of the MSO-formula [Courcelle, Information & Computation 1990] and the quantifier rank [Chen, ECAI 2004], respectively. The algorithms generated by these (meta-)results have running times whose dependence on treewidth is a tower of exponents. A conditional lower bound by Fichte, Hecher, and Pfandler [LICS 2020] shows that, for Quantified SAT, the height of this tower is equal to the number of quantifier alternations. These types of lower bounds, which show that at least double-exponential factors in the running time are necessary, exhibit the extraordinary level of computational hardness for such problems, and are rare in the current literature: there are only a handful of such lower bounds (for treewidth and vertex cover parameterizations) and all of them are for problems that are #NP-complete, Σp2-complete, Πp2-complete, or complete for even higher levels of the polynomial hierarchy. Our results demonstrate, for the first time, that it is not necessary to go higher up in the polynomial hierarchy to achieve double-exponential lower bounds: we derive double-exponential lower bounds in the treewidth (tw) and the vertex cover number (vc), for natural, important, and well-studied NP-complete graph problems. Specifically, we design a technique to obtain such lower bounds and show its versatility by applying it to three different problems: Metric Dimension, Strong Metric Dimension, and Geodetic Set. We prove that these problems do not admit 22o(tw) ·nO(1)-time algorithms, even on bounded diameter graphs, unless the ETH fails (here, n is the number of vertices in the graph). In fact, for Strong Metric Dimension, the double-expo

关键词： Parameterization

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Design and Fabrication Challenges of Integrated Optical Circuits for Quantum Computing Applications

Design and Fabrication Challenges of Integrated Optical Circ...

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International Conference on Transparent Optical Networks

作者： Simeon I. Tsintzos Konstantinos Tsimvrakidis Alexandra Sinani Adonis Bogris James C. Gates Peter G.R. Smith Ali W. Elshaari Val Zwiller Christos Riziotis National Hellenic Research Foundation Theoretical & Physical Chemistry Institute Athens Greece Department of Informatics and Computer Engineering University of West Attica Egaleo Greece Optoelectronics Research Centre University of Southampton Southampton United Kingdom Department of Applied Physics Royal Institute of Technology (KTH) Stockholm Sweden Institute for Advanced Modelling and Simulation University of Nicosia Nicosia Cyprus

The paper presents current design issues, limitations, and fabrication challenges towards the development of hybrid integrated optical circuits with embedded single photon sources, which are critical components for future quantum computing, sensing, and communication systems. Optical nanowires with embedded quantum dots (NWQD) are very promising single photon sources, with several reported results of integration in high index platforms like silicon or silicon nitride. Silica on silicon is a favorable platform for optical computing, providing the high degree of customization when combined with direct laser writing techniques for definition of optical structures with refractive index modification. However, the low ~10 -3 achievable refractive index contrast imposes strict limitations on the compatibility with NWQD resulting in general in low coupling efficiency as shown in this work. Consideration of several design and fabrication issues demonstrates the potential for NQWD integration in laser written silica based optical circuits with adequate efficiency for practical applications.

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Full-Duplex Wireless for 6G: Progress Brings New Opportunities and Challenges

arXiv

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arXiv 2023年

作者： Smida, Besma Sabharwal, Ashutosh Fodor, Gabor Alexandropoulos, George C. Suraweera, Himal A. Chae, Chan-Byoung The Department of Electrical and Computer Engineering University of Illinois Chicago ChicagoIL77005 United States The Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Ericsson Research KTH Royal Institute of Technology Stockholm Sweden The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens15784 Greece The Department of Electrical and Electronic Engineering University of Peradeniya Peradeniya20400 Sri Lanka The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of

The use of in-band full-duplex (FD) enables nodes to simultaneously transmit and receive on the same frequency band, which challenges the traditional assumption in wireless network design. The full-duplex capability enhances spectral efficiency and decreases latency, which are two key drivers pushing the performance expectations of next-generation mobile networks. In less than ten years, in-band FD has advanced from being demonstrated in research labs to being implemented in standards, presenting new opportunities to utilize its foundational concepts. Some of the most significant opportunities include using FD to enable wireless networks to sense the physical environment, integrate sensing and communication applications, develop integrated access and backhaul solutions, and work with smart signal propagation environments powered by reconfigurable intelligent surfaces. However, these new opportunities also come with new challenges for large-scale commercial deployment of FD technology, such as managing self-interference, combating cross-link interference in multi-cell networks, and coexistence of dynamic time division duplex, subband FD and FD networks. © 2023, CC BY-NC-ND.

关键词： Wireless networks

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