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arXiv 2024年

作者： Akpanya, Reymond Rivkin, Adi Stock, Frederick RWTH Aachen University Aachen Germany Dept. of Computer Science Technion-Israel Institute of Technology Haifa Israel Miner School of Computer & Information Sciences LowellMA United States

In this work we study inside-out dissections of polygons and polyhedra. We first show that an arbitrary polygon can be inside-out dissected with 2n+1 pieces, thereby improving the best previous upper bound of 4(n - 2) pieces. Additionally, we establish that a regular polygon can be inside-out dissected with at most 6 pieces. Lastly, we prove that any polyhedron that can be decomposed into finitely many regular tetrahedra and octahedra can be inside-out *** Codes 68U05 Copyright © 2024, The Authors. All rights reserved.

关键词： Geometry

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Effect of Ultra Violet Light on Planar Field Emitters

Effect of Ultra Violet Light on Planar Field Emitters

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International Conference on Vacuum Electronics

作者： Ranajoy Bhattacharya Marco Turchetti P. Donald Keithley Karl K. Berggren Jim Browning Dept. of Electrical & Computer Engineering Boise State University Boise ID USA Dept. of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge MA USA Dept. Of Electrical Engineering and Computer Science and Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge MA USA

Two different types of planar nano-scale (4–5 nm) field emitters, bowtie and diode devices, were characterized for use as electron sources for vacuum nano-transistors. I-V measurements were performed before and after Ultra-violet (UV) light exposure. Experiments showed that the field emission current was $\approx 2.7 \text{nA}$ before the UV exposure and was $\approx 1.8\text{nA}$ after the exposure for the bow-die devices. Experiments also showed that the field emission current was $\approx 5.6\text{nA}$ before the UV exposure and was $\approx 3.6 \text{nA}$ after the exposure for the diode devices. This reduction in current could be attributed to the removal of water vapor by UV exposure resulting in the reduction in the surface leakage current. A long-term stability tests conducted after the UV exposure showed both the bow-tie and diode devices emitted a stable current (<5% drop) for > 1100 hrs. of continuous operation at a DC bias of 5 V.

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Steganographic Encryption and Decryption Using Duality Preserving GANs

Steganographic Encryption and Decryption Using Duality Prese...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Aaryak Shah Alok Kumar Kamal 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: (数字)9798331527471

ISBN: (纸本)9798331527488

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.

关键词： Measurement Steganography Image synthesis Generative adversarial networks Distortion Data models Decoding Encryption Security Informatics

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User Interface Design’s Impact on Customer Satisfaction and Loyalty in SaaS E-Commerce

User Interface Design’s Impact on Customer Satisfaction and...

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Creative Communication and Innovative technology (ICCIT), IEEE

作者： Eka Purnama Harahap Pandu Hermawan Dhiyah Ayu Rini Kusumawardhani Nina Rahayu Maulana Arif Komara Harry Agustian Master of Technology Information University of Raharja Tangerang Indonesia Dept. of Information System Bina Bangsa University Serang Indonesia Dept. of Information System Pandawan Sejahtera Indonesia Tangerang Indonesia Dept. of Computer Systems University of Raharja Tangerang Indonesia Dept. of Digital Bussiness CAI Sejahtera Indonesia Tangerang Indonesia Dept. of Computer Systems Sesindo Tangerang Indonesia

ISBN: (数字)9798350367492

ISBN: (纸本)9798350367508

This study aims to analyze the impact of user interface (UI) design on customer satisfaction and loyalty in SaaS e-commerce applications, using a quantitative approach to measure the perceptions of SaaS e-commerce application users and determine how visual aspects and interface functionality contribute to the user experience, with data analysis conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, indicating that an intuitive and responsive interface design significantly influences increased customer satisfaction, which in turn strengthens their loyalty to the application; the study seeks to provide insights that developing an effective user interface is crucial for building long-term relationships with customers and reaffirms the importance of integrating good interface design in e-commerce application development strategies, and further suggests that incorporating user-centered design principles and continuously collecting user feedback can enhance the user experience, thereby allowing developers to create interfaces that not only attract users but also retain them, essential for e-commerce businesses aiming to improve user engagement and loyalty in a highly competitive market.

关键词： Customer satisfaction Buildings Psychology Virtual reality User interfaces User experience Mathematical models Electronic commerce Usability Business

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A Fair Federated Learning Framework for Collaborative Network Traffic Prediction and Resource Allocation

arXiv

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arXiv 2025年

作者： Panda, Saroj Kumar Panayiotou, Tania Ellinas, Georgios Behera, Sadananda Dept. of Electronics and Communication Eng. National Institute of Technology Rourkela Odisha India KIOS CoE Dept. of Electrical and Computer Eng. University of Cyprus Nicosia Cyprus

In the beyond 5G era, AI/ML empowered real-world digital twins (DTs) will enable diverse network operators to collaboratively optimize their networks, ultimately improving end-user experience. Although centralized AI-based learning techniques have been shown to achieve significant network traffic accuracy, resulting in efficient network operations, they require sharing of sensitive data among operators, leading to privacy and security concerns. Distributed learning, and specifically federated learning (FL), that keeps data isolated at local clients, has emerged as an effective and promising solution for mitigating such concerns. Federated learning poses, however, new challenges in ensuring fairness both in terms of collaborative training contributions from heterogeneous data and in mitigating bias in model predictions with respect to sensitive attributes. To address these challenges, a fair FL framework is proposed for collaborative network traffic prediction and resource allocation. To demonstrate the effectiveness of the proposed approach, non-iid and imbalanced federated datasets based on real-word traffic traces are utilized for an elastic optical network. The assumption is that different optical nodes may be managed by different operators. Fairness is evaluated according to the coefficient of variations measure in terms of accuracy across the operators and in terms of quality-of-service across the connections (i.e., reflecting end-user experience). It is shown that fair traffic prediction across the operators result in fairer resource allocations across the connections. © 2025, CC BY.

关键词： Federated learning

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Covid-19 Vaccine Certificate Verification using Sha Algorithm and IPFS in Blockchain technology

Covid-19 Vaccine Certificate Verification using Sha Algorith...

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Advances in Computing, Communication Control and Networking (ICAC3N), International Conference on

作者： Naitik Agrawal Yash Veer Singh Vishnu Sharma Vikas Kumar Bedi Sumit Chhonker Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida India Dept. of Computer Science and Engineering Galgotias College of Engineering and Technology Greater Noida India

ISBN: (数字)9798350330861

ISBN: (纸本)9798350330878

The COVID-19 pandemic has suddenly arisen as a global health emergency requiring concerted international action. Governments are working to stop the virus from spreading and health organizations rushed to create vaccines that would protect people. Reduce Covid-19 morbidity, reduce strain on healthcare systems, and let economies to expand. The Vaccine Certificate has been adopted as a way forward after the COVID-19 vaccination to assist authorities in formulating policies by restricting cross-border travel. In this work, we employ blockchain technology to construct a safe and verifiable vaccination certificate, which alleviates substantial privacy concerns and eliminates the need for third parties to maintain trust and control the user’s data. Different modern technologies, such as smart contracts, are used in our approach.

关键词： COVID-19 Data privacy Pandemics computer viruses Smart contracts Government Vaccines

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Energy-Optimized with Multi-Population Differential Annealed Optimization in Mobile Edge Computing

Energy-Optimized with Multi-Population Differential Annealed...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Wu, Ruixuan Shi, Yuliang Yuan, Haitao Bi, Jing Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9798350337020

Mobile devices (MDs) cannot fully run all computation/delay-sensitive tasks due to their limited computing resources. Mobile edge computing (MEC) meets the demand by providing massive resources for MDs and offloading task partitions to MEC servers. However, task offloading also brings communication delay and energy consumption. Therefore, it is challenging to associate resource-constrained MDs with appropriate MEC servers to minimize power consumption. To address this problem, a constrained mixed integer nonlinear program is formulated to optimize the total energy consumption of the system including MDs and MEC servers. To solve this problem, this work designs an improved meta-heuristic optimization algorithm called Self-adaptive and Multi-population Differential Annealed Optimization (SMDAO). Experimental results demonstrate that compared with its two state-of-the-art peers, the proposed SMDAO yields the best solution with the smallest total energy consumption in the least time. © 2023 IEEE.

关键词： computation offloading energy optimization Mobile edge computing multi-population optimization simulated annealing

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A Quantitative Analysis and Mapping of Soluble Solids Content with Interior Regions of `Hayward' Kiwifruit from Centre to Pericarp Using Hyperspectral Imaging and Chemometric Algorithms

SSRN

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SSRN 2024年

作者： Francis, Jobin George, Sony Devassy, Binu M. George, Sudhish N. Dept. of Computer Science Norwegian University of Science and Technology Innlandet Gjøvik2815 Norway Dept. of Electronics and Communication Engineering National Institute of Technology Calicut Kerala Calicut673601 India

The Soluble Solids Content (SSC) of kiwifruit is an essential internal quality attribute that represents its consumption of eating and post-harvest shelf life. This paper presents the findings of a feasibility study that aimed at improving the mapping of SSC values with different regions at the interior part of the kiwifruit from its center to the outer pericarp. Hyperspectral images of 495 kiwifruit were acquired in reflectance mode between 400 and 1000 nm wavelengths. Further, the interior of each kiwifruit has been divided into five regions (Region I to Region V), from the center to the outer pericarp, and an algorithm is proposed to automatically select spectral points from those regions. A third-order tensor framework is employed in this work, where spectral measurements from the respective locations of the kiwifruit are effectively arranged into its frontal slices. This study then employed Partial Least Square Regression (PLSR) as a chemometric model and Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), and second derivative (D2) as the pre-processing methods. Among these, Region III which comprises the fleshy part of the kiwifruit between the center and the pericarp delivers the calibration and prediction outcomes with MSC+D2+PLS combination as $\mbox{R}_{C}^2=0.485$, $\mbox{RMSEC}=1.216$ and $\mbox{R}_{P}^2=0.349$, $\mbox{RMSEP}=1.349$ respectively. This study also attempted to compare the evaluation results of SSC values with spectral measurements taken from hyperspectral images of kiwifruit with its skin. Overall, the proposed study can be effectively used to find the correlation of the SSC values of the kiwifruit with their spectral measurements and, thereby, can be employed for the non-invasive prediction of the SSC values of the kiwifruit. © 2024, The Authors. All rights reserved.

关键词： Mapping

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Essay Rating System Using Machine Learning 5

Essay Rating System Using Machine Learning

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5th International Conference on Information Systems and computer Networks, ISCON 2021

作者： Pathak, Pooja Raghav, Shilpy Jain, Shubhanshu Jalal, Sunita GLA University Dept. of Mathematics Mathura India GLA University Dept. of Computer Engineering and Applications Mathura India Govind Ballabh Pant University of Agriculture and Technology Dept. of Computer Engineering Pantnagar India

ISBN: (纸本)9781665403412

Essay Rating is the process of assigning grades to the essays written for professional purposes. Automating this process implies the use of specified machine learning algorithms over the standard manual methods to evaluate the essays through Natural Language Processing. Essays can be termed as a large set of textual entities. Grading these essays involves distributing them into a fewer number of distinct categories based on certain constraints and standards. These categories are then used to assign the possible grades. Because of numerous factors like cost, time, biasness, and delay in results, there is a need to switch from manually checking the essays to automated grading. It is a very tedious task to evaluate a bulk of essays while probing every kind of error. Henceforth, this model of Automated Essay Grading System models seems quite assuring. It takes text input from the user and generates grades conforming to the pre-defined standards. After evaluating its useful attributes, an output is obtained in the form of a grade for the given essay. This project comprises of grammar-based Checking (Checking Unique Word count, Sentence Count, Grammatical Mistakes, Spelling Errors) and Context Based Checking (Application of NLP to categorize the essays). © 2021 IEEE.

关键词： Text processing

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DEAL-YOLO: Drone-based Efficient Animal Localization using YOLO

arXiv

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arXiv 2025年

作者： Naidu, Aditya Prashant Gosalia, Hem Gakhar, Ishaan Rathore, Shaurya Singh Didwania, Krish Verma, Ujjwal Dept. of Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India Dept. of Mechatronics Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India Dept. of Information and Communication Technology Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India Dept. of Data Science and Computer Applications Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India Dept. of Electronics and Communication Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India

Although advances in deep learning and aerial surveillance technology are improving wildlife conservation efforts, complex and erratic environmental conditions still pose a problem, requiring innovative solutions for cost-effective small animal detection. This work introduces DEAL-YOLO, a novel approach that improves small object detection in Unmanned Aerial Vehicle (UAV) images by using multi-objective loss functions like Wise IoU (WIoU) and Normalized Wasserstein Distance (NWD), which prioritize pixels near the centre of the bounding box, ensuring smoother localization and reducing abrupt deviations. Additionally, the model is optimized through efficient feature extraction with Linear Deformable (LD) convolutions, enhancing accuracy while maintaining computational efficiency. The Scaled Sequence Feature Fusion (SSFF) module enhances object detection by effectively capturing inter-scale relationships, improving feature representation, and boosting metrics through optimized multiscale fusion. Comparison with baseline models reveals high efficacy with up to 69.5% fewer parameters compared to vanilla Yolov8-N, highlighting the robustness of the proposed modifications. Through this approach, our paper aims to facilitate the detection of endangered species, animal population analysis, habitat monitoring, biodiversity research, and various other applications that enrich wildlife conservation efforts. DEAL-YOLO employs a two-stage inference paradigm for object detection, refining selected regions to improve localization and confidence. This approach enhances performance, especially for small instances with low objectness scores. © 2025, CC BY.

关键词： Unmanned aerial vehicles (UAV)

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