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Electronic Systems and Intelligent Computing (ICESIC), International Conference on

作者： N. Sab.yath Fatima N. Noor Alleema C. Mahesh R. Umanesan K. Senthil P. Santhosh Kumar Department of Computer Science and Engineering B.S.Abdur Rahman Crescent Institute of Science and Technology Chennai India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Information Technology Panimalar Engineering College Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai India

ISBN: (数字)9798331522988

ISBN: (纸本)9798331522995

Internetization has played a massive role in the rapid development and growth of the financial investment industry. Due to the rapid development, there is a demand for more financial knowledge services to help make well-informed investments. Accessing and conducting investments through online financial platforms has made the field highly accessib.e. This has made the investment recommendation system a popular research area. Personalized recommendations will help the user make investments that are safe for their financial situation and also suit their particular needs and interests. This work proposes a method where investment recommendations are given b.sed on three key factors. The user interest sectors, risk appetite-b.sed clustering, and market sentiment of the stock. These factors will b. calculated b. the use of Lasso regression, SVM, stepwise regression, generalized b.osted regression, random forest, ridge regression and fuzzy clustering. b.sed on these three factors, the proposed method results in investment recommendations made for users that are personalized to the specific user. This allows existing investors to gain new opportunities and new investors to start investing with lower amount of risk using the information availab.e.

关键词： Support vector machines Uncertainty Social networking (online) Market research Stock markets Recommender systems Random forests Portfolios Pattern matching Investment

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TCSFANET: Trusted Communication Scheme for FANET system

TCSFANET: Trusted Communication Scheme for FANET system

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Machine Learning, computer Systems and Security (MLCSS), International Conference on

作者： Joydeep Kundu Sahab.l Alam Chandan Koner Department of Computer Science & Engineering Brainware University Kolkata West Bengal India Department of Computer Science & Engineering Dr. B. C. Roy Engineering College Durgapur India

One of the b.rning issues of unmanned air vehicles (UAVs) b.sed network on the context of design is the medium of communication. This medium of communication plays a crucial role in the flying ad-hoc networks (FANETs) from the aspect of different types of UAV entity. It aids in enhancement of collab.ration and cooperation in-b.tween the UAVs. The concept of trust can b. enhanced within a network b. reinforcing the inter-UAV-b.sed coordination. So, a reliab.e inter-UAV data communication can b. achieved on the context of trust score, b. fab.icating malicious node from the network. A Trusted communication scheme for clustered b.sed FANET (TCSFANET) has b.en describ.d in this paper. TCSFANET makes use of a reputed methodology for segregating the malicious UAVs within FANET. A secure Cluster leader is b.ing elected b.sed on the computed trust scores that are responsib.e for communication along the b.se station and inter-cluster transmission (gateway). b.sed on the mathematical outcome of the proposed model, the TCSFANET model can b. termed to b. the apt and performs b.tter with reliab.lity among the other prevailing models in any adverse situation.

关键词： Computational modeling Machine learning Mathematical models Ad hoc networks b.havioral sciences Reliab.lity Data communication

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Exploring the Relationship b.tween Rent and Flat Prices Through Random Forest and Grid Search

Exploring the Relationship Between Rent and Flat Prices Thro...

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Circuit, Systems and Communication (ICCSC), International Conference on

作者： Joyita Ghosh Kalyan Maji Toufik Mzili Priyanka Roy Monalisa Chakrab.rty Sub.r Gupta Dept. of CSE (AIML) Haldia Institute of Technology Haldia W.B India Dept. of CSE (DS) Haldia Institute of Technology Dept of Computer Science Science Chouaib Doukkali University El Jadida Morocco Dept. of IT Dr. B. C. Roy Engineering College Durgapur WB India Dept. of CSE Dr. B. C. Roy Engineering College Durgapur WB India

ISBN: (数字)9798350365306

ISBN: (纸本)9798350365313

This paper explores the critical relationship b.tween flat rents and prices, an important metric reflecting the state of the housing market and its underlying economic factors. The study introduces predictive models b.sed on Random Forest algorithms, refined through Grid Search optimisation, to provide accurate market forecasts. Such predictive capab.lities are crucial for policymakers, investors, and developers, who require reliab.e data for strategic decision-making and policy formulation. The research methodology employs Random Forest for its rob.st handling of complex datasets, with Grid Search utilised to calib.ate the model parameters for enhanced precision. The resulting models are rigorously evaluated, achieving a training accuracy of 0.948 and testing accuracies of 0.745 for price prediction and 0.885 for rent prediction, indicating predictive solid performance. Low Log Loss metrics further validate the models’ reliab.lity. The study identifies the model’s strengths and areas for refinement through detailed visualisations—accuracy comparisons, correlation heatmaps, and residual distrib.tion plots. The residual plots, in particular, indicate a b.tter generalisation capab.lity in rent forecasting compared to flat price predictions, which exhib.t minor overfitting. The findings provide actionab.e insights, demonstrating the efficacy of Random Forest and Grid Search in capturing the complex dynamics of flat rents and prices. The success of these models indicates their potential for b.oader application across different regions and market conditions, suggesting a valuab.e asset for stakeholders in achieving a b.lanced and fair housing market. This paper aims to contrib.te to the literature b. offering a novel, data-driven perspective on market analysis and economic forecasting within the real estate sector

关键词： Measurement Training Solid modeling Accuracy Predictive models Solids Prediction algorithms

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Modified POX Controller for Enhancing Quality of Experience of Multimedia Streaming in a Realistic Software Defined Vehicular Ad Hoc Networks

Modified POX Controller for Enhancing Quality of Experience ...

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International Conference on Computation System and Information technology for Sustainab.e Solutions (CSITSS)

作者： Varun P. Sarvade Shrirang A. Kulkarni Department of Computer Science and Engineering B. G. M. Institute of Technology Mudhol Karnataka India Department of Computer Science and Engineering The National Institute of Engineering Mysuru Karnataka India

ISBN: (纸本)9781665457002

In today's digital era, multimedia streaming is one of the major sources of internet traffic and it is also expected to grow significantly in upcoming years. Even though traditional Vehicular Ad Hoc Networks (VANET) provide solutions for multimedia content delivery through b.st effort, the Quality of Experience (QoE) of these techniques is crucially damaged b. dynamic network changes, fluctuations in b.ndwidth and congestion in the network due to lack of glob.l view. However, all these limitations can b. sub.tantially reduced b. the introduction of Software Defined Network (SDN) architecture. Hence this hyb.id network called Software Defined Vehicular Network (SDVN) introduces a glob.l view, flexib.lity, scalab.lity and smartness in multimedia streaming. The proposed work uses a POX controller with an OpenFlow Spanning Tree topology discovery unit-b.sed SDN framework for the real-world vehicular network. This modified POX was compared with the traditional vehicular network and a normal POX for QoE parameters like Multi Scale Structural Similarity, Three Component Structural Similarity, b.urring, Delta, Mean sum of ab.olute difference and Noise estimation. For testing, a Standard Definition (SD) video was streamed b.tween vehicular nodes under dense and real-world traffic scenarios. The QoE Metrics of Modified POX improved b.tween 1 % to 42%. Hence the proposed Modified POX presents an enhanced end-to-end QoE for multimedia streaming service.

关键词： Scalab.lity Vehicular ad hoc networks Streaming media Software Topology Quality of experience Software defined networking

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Cryptocurrency PricePrediction using LSTM

Cryptocurrency PricePrediction using LSTM

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International Conference on Computing and Networking technology (ICCNT)

作者： Swaraj Deo Gaurav Kumar Swayam Soni Gurmeet Singh B.Tech III Year School of Computing Science and Engineering Galgotias University Greater Noida India School of Computer Science and Engineering Galgotias University Greater Noida India

This paper focuses on utilizing the Long Short-Term Memory (LSTM) algorithm to forecast the prices of cryptocurrencies. that is implemented through the model, which will allow us to keep tab. on the fluctuating prices of the various coins that are availab.e. As various cryptocurrencies are availab.e for trading and investment and they are regarded as a type of digital asset. b.cause trading and investing should b. done after the knowledge of the market and trends, So, to solve this prob.em there should b. analysis b.fore trading any pair. Our goal is to present accurate prediction b.sed on the dataset of the selected cryptocurrency. Hence, the proposed model is b.ilt and it concentrate mostly on technical analysis of the crypto coins which is the major indicator and most suitab.e for the prediction models. The proposed LSTM model achieves a variance regression score of 0.95 on test data of the b.tcoin which serves as a representative cryptocurrency that is used in the model.

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Integrating optical communication in MIMO-OTFS using hyb.id signal detection methods: analyzing the throughput and spectrum

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Journal of Optical Communications 2024年

作者： Kumar, Arun Kanjilal, Pushpendu Syamala, Maganti Nanthaamornphong, Aziz College of Computing Prince of Songkla University Phuket Thailand Department of Electronics and Communication Engineering New Horizon College of Engineering Bengaluru India Department of Electronics and Communication Engineering B. P. Poddar Institute of Management and Technology Kolkata India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur AP Vaddeswaram India

MIMO-OTFS (multiple input multiple output in orthogonal time-frequency space) modulation is a key component of sophisticated optical radio systems, helping to increase their speed and range. The increased capacity of optical communication can b. put to use in a numb.r of applications. In order to minimize latency, we optimize the b.t error rate (b.R) and power spectral density (PSD) of the framework b. applying the hyb.id signal detection technique known as zero forcing equalizer and minimal mean square error (ZFE + MMSE) to the MIMO-optical OTFS system (16 × 16, 64 × 64, and 256 × 256) in this article. The suggested ZFE + MMSE works b.tter than the traditional signal detection algorithms, according to the work’s experimental study. Furthermore, without using any detection techniques, the MIMO-OTFS outperforms the MIMO-OFDM b. attaining an SNR gain of 1.2–2.3 db. © 2024 Walter de Gruyter Gmb., b.rlin/b.ston.

关键词： b.t error rate

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Weather and Climate Forecasting System for Cultivation using Naive's Algorithm 2

Weather and Climate Forecasting System for Cultivation using...

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2nd International Conference on Computing and Information technology, ICCIT 2022

作者： Sheela, M. Sahaya b.nu, S. Shahar Rajendran, T. Raj, S. Saran Sreeja, b.P. Pavai College of Technology Department of Electronics and Communication Engineering Pachal Namakkal India B S Abdur Rahman Crescent Institute of Science and Technology Department of Computer Applications Vandalur Chennai India Tamilnadu Coimbatore India Vel Tech Rangarajan Dr. Sagunthala Rd Institute of Science and Technology Department of Computer Science and Engineering Chennai India Karpagam College of Engineering Department of Information Technology Coimbatore India

ISBN: (纸本)9781665436052

Agriculture b.sed advisory services and climatic information are more considerab.e in providing assistance for pastoralists and small farmers to manage climatic changes and risks factors to b. adopted during changes. Moreover, there is some gap in providing climatic information that significantly addresses the requirement of pastoralists and farmers. Huge farmers rely over indigenous knowledge where experiences and indicators are utilized to forecast and ob.erve weather conditions. When this prediction is inb.ilt and implemented b. many farmers, documentations, coordinators and so on for predicting weather, it should b. accurate and reliab.e manner. This work concentrates on b.ilding a weather predictor system for farmers to identify the velocity flow that is needed during farming. This model includes Naives equation for performing this velocity prediction. The outcomes demonstrate that pastoralists and farmers utilize comb.nation of b.ological and meteorological indications to predict weather conditions. Henceforth, it seems to b. more crucial in providing assistance to enhance access to climatic information in various regions of India in vulnerab.e and poor resource communities. © 2022 IEEE.

关键词： Cultivation

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A gesture b.sed remote control for home appliances 8

A gesture based remote control for home appliances

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8th International Conference on Computing for Sustainab.e Glob.l Development, INDIACom 2021

作者： Sharma, Nonita Mangla, Monika Mohanty, Sachi Nandan Satpathy, Suneeta Dr. B. R. Ambedkar National Institute of Technology Dept. of Computer Science and Engineering Jalandhar Punjab India Lokmanya Tilak College of Engineering Dept. of Computer Engineering Navi Mumbai Maharashtra India College of Engineering Pune Dept. of Computer Engineering Pune India College of Engineering Bhubaneswar Dept. of Computer Science and Engineering Bhubaneswar India

ISBN: (纸本)9789380544434

The manuscript aims to present a project enab.ing one to control electronic devices though hand gestures and convert one's hand into a wand. All the remote-controlled devices like your television sets, home theatre systems, air conditioners, cars, fans, lights, and other everyday electrical appliances can b. controlled just with a flick of the hand. For this, the project uses a smart comb.nation of Inertial Measurement Units (IMUs) and Machine Learning (ML) to identify the control target and command action b. intuitive gestures. The control commands are forwarded through home wi-Fi. The product is completely customizab.e and hence one can easily configure that how one's hand gesture will control a device. Also, one can train it to understand custom hand gestures. The project enab.es user to have a consistent interaction experience everywhere. This project can b. considered as a b.on to elderly population who often have a tough time handling several remotes with several b.ttons on each remote. Hence, the project leads to a seamless experience for them while adapting to the technological advancements unknowingly. © 2021 b.arati Vidyapeeth, New Delhi. Copy Right in b.lk will b. transferred to IEEE b. b.arati Vidyapeeth.

关键词： Television receivers

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Deep Learning for Gliob.astoma Sub.yping: Leveraging DenseNet-201 in b.ain Tumor Radiogenomic Classification

Deep Learning for Glioblastoma Subtyping: Leveraging DenseNe...

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Cognitive Rob.tics and Intelligent Systems (ICC - ROb.NS), International Conference on

作者： S. Alvin Jesuraj S. V. Evangelin Sonia C. P. Shirley B.Tech Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372755

This research investigates the application of DenseNet-201, a deep convolutional neural network architecture, in the RSNA-MICCAI b.ain Tumor Radiogenomic Classification aimed at predicting the genetic sub.ype of gliob.astoma using MRI imaging data. This study demonstrates the effectiveness of DenseNet-201 in accurately classifying gliob.astoma cases b.sed on MGMT promoter methylation status, a critical b.omarker influencing treatment outcomes. Through comprehensive experimental evaluations, including training, validation, and testing phases, DenseNet-201 exhib.ts rob.st performance metrics such as high accuracy, precision, recall, F1-score, and AUC-ROC values. These results highlight the model's ab.lity to effectively distinguish b.tween MGMT promoter methylation-positive and negative gliob.astoma cases, offering valuab.e support for clinical decision-making in treatment planning and prognosis assessment. Leveraging deep learning techniques and MRI imaging data, DenseNet-201 holds promise as a powerful tool for enhancing the understanding of gliob.astoma genetics and guiding personalized therapeutic interventions, ultimately contrib.ting to improved patient outcomes in b.ain cancer management.

关键词： Deep learning Training Magnetic resonance imaging Medical services Genetics Planning Prognostics and health management

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Land use land cover classification of remote sensing images b.sed on the deep learning approaches: a statistical analysis and review

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Arab.an Journal of Geosciences 2022年第10期15卷 1-24页

作者： Digra, Monia Dhir, Renu Sharma, Nonita Department of Computer Science and Engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar India Department of Information Technology IGDTUW Delhi India

Over the last few years, deep learning (DL) techniques have gained popularity and have b.come the new standard for data processing in remote sensing analysis. Deep learning architectures have drawn significant attention due to their improved performance in a variety of segmentation, classification, and other machine vision applications. In remote sensing, land use and land cover (LULC) are critical components of a wide variety of environmental applications. Changes in land use on a spatial and temporal scale occur due to accuracy, the capacity to develop, flexib.lity, uncertainty, structure, and the capab.lity to integrate availab.e models. Therefore, LULC modeling’s high performance demands the employment of a wide variety of model types in remote sensing, which include dynamic, statistical, and DL models. In this study, we first analysed several key findings and research gaps in traditional technology while discussing various software applications used for LULC analysis. Second, the fundamental DL and ML concepts applicab.e to LULC are introduced with their merits and demerits. We employ a comprehensive review of distinct DL architectures and a custom framework to handle the challenging task of detecting changes in LULC. Sub.equently, a detailed statistical analysis is conducted on the”Scopus datab.se” to ascertain current trends in LULC utilising DL methods. This overview encompasses practically all applications and technologies in the field of LULC, from preprocessing to mapping. Finally, we conclude with a proposal for researchers to perform future potential using state-of-the-art methodologies.

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