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2023 International Conference on computer Communication and informatics, ICCCI 2023

作者： Harish, K.P. Dhivyanchali, M.N. Devi, K.Nirmala Krishnamoorthy, N. Dhana Sree, R. Dharanidharan, R. Kongu Engineering College Department of Computer Science & Engineering Erode India Swamy Vivekanandha Medical College Hospital and Research Institute Elayampalayam Tamilnadu Tiruchengode637 205 India Vellore Institute of Technology Vellore Campus School of Information Technology and Engineering Department of Software Systems and Engineering Tamilnadu 632014 India

ISBN: (纸本)9798350348217

PCOS are the serious condition which affects female ovaries during their reproductive age of 15 to 45. This disease affects 5 to 10% of reproductive-age females. Although it is difficult to fully resolve this issue,the PCOS affected women can be mitigated through proper exercise, by taking proper nutritious diet and maintaining the healthy BMI. Until they take a pregnancy test, the majority of women are unaware of the disease. The clinical dataset has the 541 instances and 45 attributes of unbalanced classes of 0 and 1 (no and yes) which has 364 instances of 0 (no) class and 177 instances of 1 (yes) class. Preprocessing is done for the unbalanced dataset by filling the null values and changing the datatype of all attributes to numeric datatypes. The unbalanced dataset is balanced by the balancing techniques of SMOTE and Random Over Sampling. Comparing the both balanced techniques through the accuracy the random oversampling gives the *** supervised learning algorithms are Decision tree, KNN,Random Forest,AdaBoost, Logistic regression,Gradient boosting, cat boosting, XGBoosting, Linear SVM, Radial SVM, Linear discriminant analysis and Quadratic discriminant analysis are *** supervised learning algorithms are trained and tested by splitting the dataset to 70% for training and 30% for testing. The ensemble stacking techniques are used by implementing the all models at the cross validation of *** xgboost gives the accuracy of 96% for the balanced dataset. © 2023 IEEE.

关键词： Adaptive boosting

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Fixed-Parameter Sensitivity Oracles 13

Fixed-Parameter Sensitivity Oracles

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13th Innovations in Theoretical computer Science Conference, ITCS 2022

作者： Bilò, Davide Casel, Katrin Choudhary, Keerti Cohen, Sarel Friedrich, Tobias Lagodzinski, J.A. Gregor Schirneck, Martin Wietheger, Simon Department of Humanities and Social Sciences University of Sassari Italy Hasso Plattner Institute University of Potsdam Germany Department of Computer Science and Engineering Indian Institute of Technology Delhi India School of Computer Science Tel-Aviv-Yaffo Academic College Israel

ISBN: (纸本)9783959772174

We combine ideas from distance sensitivity oracles (DSOs) and fixed-parameter tractability (FPT) to design sensitivity oracles for FPT graph problems. An oracle with sensitivity f for an FPT problem Π on a graph G with parameter k preprocesses G in time O(g(f, k) · poly(n)). When queried with a set F of at most f edges of G, the oracle reports the answer to the Π - with the same parameter k - on the graph G − F, i.e., G deprived of F. The oracle should answer queries in a time that is significantly faster than merely running the best-known FPT algorithm on G − F from scratch. We design sensitivity oracles for the k-Path and the k-Vertex Cover problem. Our first oracle for k-Path has size O(kf+1) and query time O(f min{f, log(f) + k}). We use a technique inspired by the work of Weimann and Yuster [FOCS 2010, TALG 2013] on distance sensitivity problems to reduce the space to O ((Eqaution presented) fk · log n) at the expense of increasing the query time to O((Eqaution presented) f min{f, k} · log n). Both oracles can be modified to handle vertex-failures, but we need to replace k with 2k in all the claimed bounds. Regarding k-Vertex Cover, we design three oracles offering different trade-offs between the size and the query time. The first oracle takes O(3f+k) space and has O(2f) query time, the second one has a size of O(2f+k2+k) and a query time of O(f+k2);finally, the third one takes O(fk + k2) space and can be queried in time O(1.2738k + f). All our oracles are computable in time (at most) proportional to their size and the time needed to detect a k-path or k-vertex cover, respectively. We also provide an interesting connection between k-Vertex Cover and the fault-tolerant shortest path problem, by giving a DSO of size O(poly(f, k) · n) with query time in O(poly(f, k)), where k is the size of a vertex cover. Following our line of research connecting fault-tolerant FPT and shortest paths problems, we introduce parameterization to the computation of distance preserve

关键词： Fault tolerance

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CHEMFUZZ: Large Language Models-Assisted Fuzzing for Quantum Chemistry Software Bug Detection 23

CHEMFUZZ: Large Language Models-Assisted Fuzzing for Quantum...

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23rd IEEE International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2023

作者： Qiu, Feng Ji, Pu Hua, Baojian Wang, Yang School of Software Engineering University of Science and Technology of China China Suzhou Institute for Advanced Research University of Science and Technology of China China The Johns Hopkins University Computer Science Department United States

ISBN: (纸本)9798350359398

Quantum chemistry software implements the first principle quantum computation and is indispensable in both scientific research and chemical industries. Any bugs in such software will lead to serious consequences, thus defeating its trustworthiness and reliability. However, bug detection techniques for such software have not been fully investigated. In this paper, to fill this gap, we propose a novel approach to fuzz quantum chemistry software with the aid of Large Language Models (LLMs). Our basic idea is utilize LLMs to mutate and generate syntactic and semantic valid input files from seed inputs, by proving valuable domain-specific knowledge of chemistry. With this basic idea, we have designed and implemented CHEMFuzz, a fully automatic fuzzing framework to fuzz quantum chemistry software for bugs. Our evaluation of CHEMFUZZ leverages popular LLMs including GPT3.5, Claude-2, and Bart as test oracles to generate parameters to mutate inputs and analyze computation results. CHEMFUZZ detected 40 unique bugs, which have been classified and reported to developers, with a code coverage of 17.4%. © 2023 IEEE.

关键词： Quantum chemistry

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Robust Transmission Design in Multiobjective RIS-Aided SWIPT IoT Communications

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IEEE Internet of Things Journal 2024年第10期11卷 18605-18618页

作者： Sharma, Vaibhav Allu, Raviteja Singh, Sandeep Kumar Singh, Keshav Duong, Trung Q. Tsiftsis, Theodoros A. Institute of Communications Engineering National Sun Yat-sen University Kaohsiung804 Taiwan Motilal Nehru National Institute of Technology Allahabad Electronics and Communication Engineering Department Prayagraj211004 India Memorial University of Newfoundland Faculty of Engineering and Applied Science St. John'sNLA1B 3X5 Canada Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece

This work investigates the performance of simultaneous wireless information and power transfer (SWIPT) in a reconfigurable intelligent surface (RIS)-aided Internet of Things (IoT) communications under imperfect channel state information (CSI). We formulate a multiobjective optimization problem (MOOP) to design a transmit precoding vector (TPV) at the base station (BS) and phase shift matrix (PSM) at the RIS that jointly maximizes energy efficiency (EE) and harvested power (HP) under the norm-bounded CSI error model. Due to the conflicting objective functions and nonconvex nature of the above optimization problem, the MOOP is simplified using the ϵ-constraint method and subsequently adopting advanced optimization tools, such as the Dinkelbach method, S-procedure, general sign-definiteness, semidefinite programming and convex-concave procedure. Thereafter, we propose an alternating optimization-based algorithm which determines optimal TPV and PSM iteratively that jointly maximizes the EE and HP of the considered system. Through numerical simulations, we validate the robustness, optimality, convergence, accuracy, and effectiveness of our proposed algorithm. Furthermore, we assess the impact of several key parameters, such as the number of RIS elements, available transmit power at BS, and the minimum HP on the performance of the considered system. © 2014 IEEE.

关键词： Energy efficiency

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Solar Wind Density Forecasting with U-Net and LSTM-based Neural Networks 8

Solar Wind Density Forecasting with U-Net and LSTM-based Neu...

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8th International Conference of Yearly Reports on informatics, Mathematics, and engineering, ICYRIME 2023

作者： Iacobelli, Emanuele Fiani, Francesca Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Roma00185 Italy Department of Computational Intelligence Czestochowa University of Technology Czestochowa42-201 Poland

Forecasting changes in solar wind properties accurately is crucial for predicting space weather, as it significantly impacts the majority of space operations and the telecommunication system. To meet this challenge, we introduce an architecture that combines U-Net’s capabilities for segmenting coronal holes from high-resolution sun images with the predictive abilities of Long Short-Term Memory (LSTM) and ConvLSTM models. This architecture predicts solar wind density using sun surface images obtained from the AIA 193 Å dataset (provided by NASA) and historical electron and proton density data from the OMNI and ELM2 datasets (also provided by NASA), covering the entire year 2012. Our findings demonstrate the system’s ability to generate reliable coronal hole segmentation maps and achieve good accuracy in forecasting solar wind density. © 2023 Copyright for this paper by its authors.

关键词： NASA

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Dynamic Disaster Management with Real-Time IoT Data Analysis and Response

Dynamic Disaster Management with Real-Time IoT Data Analysis...

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2024 IEEE International Conference on Automation and Computation, AUTOCOM 2024

作者： Dankan Gowda, V. Sharma, Avinash Prasad, K.D.V. Saxena, Rini Barua, Tarkeshwar Mohiuddin, Khalid Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Department of Computer Science and Engineering Punjab Mohali140307 India Symbiosis Institute of Business Management Hyderabad India Pune India King Khalid University College of Business Department of Business Informatics PO Box-3247 Abha61471 Saudi Arabia

ISBN: (纸本)9798350382723

As natural and manmade disasters grew in number, as a result the problem of how to quickly and effectively respond to disaster has become fresh. This is precisely the purpose of this research: Using IoT technologies and powerful data analysis techniques, to integrate them into existing disaster management systems. The beginning of the article contains a broadcasted statement to the effect that traditional methods are insufficient, and real-time data and preemptive response systems are needed. With the application of Internet of Things, an integrated system is proposed in which countless types of information such as weather conditions and seismic activity are gathered by sensors and actuators. Advanced machine learning algorithms and predictive modeling are used to analyze the gathered data. This allows us to make real-time decisions. The design and construction of an IoT-based disaster management system is the methodology behind the research. In particular, we will evaluate how effective it is at reducing response times and increasing overall resilience to disasters. The results show a high efficiency in response, which reflects the feasibility of the method. Finally, the paper discusses the problems encountered in implementing IoT and advanced data analysis of disaster risk and suggests future research avenues. There is no doubt that they will change the present disaster management practice forever. © 2024 IEEE.

关键词： Remote sensing

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Improving bot detection of fake followers on Twitter via a hybrid B-HC optimisation algorithm

Improving bot detection of fake followers on Twitter via a h...

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International Conference on Electronics, Communication and Computing Technologies (ICECCT)

作者： Haider Alzeyadi Fecir Duran Department of Computer Science Informatics Institute Gazi University Ankara Turkey Department of Computer Engineering Engineering Faculty of Technology Gazi University Ankara Turkey

Sophisticated cyber threats are seen on Online Social Networks (OSNs) social media accounts automated to imitate human behaviours has an impactful effect on distorting public thoughts and opinions. OSNs are weaponized to diffuse deception, misinformation, and malicious activities, that forms a serious threat to society. The deceptive nature of imitating human behaviour has become a challenging and crucial task to detect automated accounts (socialbots). This research, however, proposes a hybrid metaheuristic optimisation algorithm for socialbot detection. Specifically, a hybrid B-Hill Climbing (B-HC) optimisation algorithm works in tandem with a k-NN nearest neighbour classifier to accurately select a relevant feature subset. It is applied to be tested for fake followers account on Twitter data. Experimental results showed that the proposed method is better than the traditional and the latest feature selection techniques as well as the rule-set methods. The B-HC alongside with k-NN method achieved promising results using only relevant feature subset.

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Performing Aerobatic Maneuver with Imitation Learning 23rd

Performing Aerobatic Maneuver with Imitation Learning

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23rd International Conference on Computational Science, ICCS 2023

作者： Freitas, Henrique Camacho, Rui Silva, Daniel Castro Department of Informatics Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias s/n. Porto4200-465 Portugal LIAAD/INESC TEC - Artificial Intelligence and Decision Support Laboratory/Institute for Systems and Computer Engineering Technology and Science Porto Portugal LIACC - Artificial Intelligence and Computer Science Laboratory Porto Portugal

ISBN: (纸本)9783031359941

The work reported in this article addresses the challenge of building models for non-trivial aerobatic aircraft maneuvers in an automated fashion. It is built using a Behavioural Cloning approach where human pilots provide a set of example maneuvers used by a Machine Learning algorithm to induce a control model for each maneuver. The best examples for each maneuver were selected using a set of objective evaluation metrics. Using those example sets, robust models were induced that could replicate (and in some cases outperform) the human pilots that provided the examples (the clean-up effect). Complete complex maneuvers were performed using a meta-controller capable of sequencing the basic ones learned by imitation. This endeavor was rewarded by the results that show several Machine Learning models capable of performing highly complex aircraft maneuvers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloning

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Automatic and Adaptive Segmentation of Customer in R framework using K-means Clustering Technique 12

Automatic and Adaptive Segmentation of Customer in R framewo...

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12th International Conference on computer Communication and informatics, ICCCI 2022

作者： Nagaraj, P. Birunda, S. Selva Venkatesh, R. Muneeswaran, V. Narayanan, S. Krishna Shree, U. Dhannu Sunethra, B. Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Virudhunagar Krishnankoil India Sri Shakthi Institute of Engineering and Technology Department of Computer Science and Engineering Chinniyampalayam Coimbatore India Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Virudhunagar Krishnankoil India

ISBN: (纸本)9781665480352

In the past few years, e-commerce business has placed a greater emphasis on delivering the better customer service. Building stronger customer relationships aids businesses in generating profits as well as customer happiness and retention. Customer segmentation is a useful tool for identifying unmet customer demand. This work solves the customer segmentation problem by improving the performance of K-means clustering algorithm by optimizing Sum of Squared Error using Elbow method. To aid K-means Clustering in calculating the optimal number of clusters, the Sum of Squared Error is used. © 2022 IEEE.

关键词： K-means clustering

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Enhancing Object Detection Robustness for Cross-Depiction Through Neural Style Transfer 8

Enhancing Object Detection Robustness for Cross-Depiction Th...

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8th International Conference of Yearly Reports on informatics, Mathematics, and engineering, ICYRIME 2023

作者： Fiani, Francesca Puglisi, Adriano Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Roma00185 Italy Department of Computational Intelligence Czestochowa University of Technology Czestochowa42-201 Poland

Modern neural networks models for computer vision are trained on millions of images. The idea is that models are able to increase generalization when the dataset contains well diversified images, e.g. with varied illumination and environmental conditions of the same objects. Generalization is particularly relevant in object detection, especially for what concerns the cross-depiction problem. In this work we explore the use of Neural Style Transfer as a novel technique to morph the original data, with the aim to enhance model generalization. To verify the effect on performances for object detection models, we selected the Faster R-CNN model to be applied on the Pascal VOC 2012 dataset. A number of tests were performed through style variations on images and by tuning Neural Style Transfer parameters to maintain the content of the original images. The experiments showed promising results, which effectively provide a foundation for future studies on cross-depiction via Neural Style Transfer. © 2023 Copyright for this paper by its authors.

关键词： Object detection

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