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A comparative study on factors used to predict dengue outbreaks using machine learning algorithm

AIP Conference Proceedings 2023年第1期2855卷

作者： Amiben Mehta Kajal Patel Research Scholar Department of Computer Engineering Gujarat Technological University Ahmedabad 382424 Gujarat India Associate Professor Department of Computer Engineering Government Engineering College Chandkheda Ahmedabad 382424 Gujarat India

Aedes mosquitoes spread Dengue which is a viral disease. Every year approximately 100 to 400 million people become victims of dengue all over the world. There is no particular treatment for dengue, just as for severe dengue. The basis for a dengue outbreak is mainly influenced by various weather parameters (such as rainfall, humidity, temperature, etc.) and geographical area. This study aims to analyze the factor that primarily affects the dengue outbreak. These factors can help to predict a dengue outbreak using machine learning algorithms. This study compares different machine learning algorithms and compares their predictions’ accuracy. It is not good to directly compare as not all models are used with the same dataset. But it does provide guidance on which algorithm can help predict dengue outbreaks with reasonable accuracy. In the end, it is concluded that the most common factors for predicting a dengue outbreak can be used in the future implementation and which algorithm is better to use in the model to predict.

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The Terms Estimation of S Robotics using MTRS as well as FEM

The Terms Estimation of S Robotics using MTRS as well as FEM

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： R. Gopal Mustafa Mudhafar Amjad Hashem Venkadeshan Ramalingam Dibyahash Bordoloi Muhammad Numan Ali Khan Myasar Mundher Adnan Zahraa N. Abdulhussain Assistant Professor Information and communication Engineering College of Engineering University of Buraimi Sultanate of Oman Department of Medical Physics Faculty of Medical Applied Sciences University of Kerbala Karbala Iraq Computer Engineer Department Al-kunooze University College Basra Iraq Network Computing College of Computing and Information Sciences University of Technology and Applied Sciences– Shinas Sultanate of Oman Dept of CSE Graphic Era Hill University Adjunct professor Graphic Era Deemed to be University Dehradun Uttarakhand Faculty – Network Computing College of Computing and Information Sciences University of Technology and Applied Sciences – Shinas Sultanate of Oman Department of computers Techniques engineering College of technical engineering The Islamic university Najaf Iraq College of Technical Engineering National University of Science and TechnologyDhi Qar Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

This look at addresses the critical project of reaching dependable and precise proprioception in soft robots, it really is essential for his or her effective deployment in complicated environments. By integrating multi-tap resistive sensors in the robot’s form, our technique lets in for the distinct sensing of nearby deformations at various factors throughout the robotics’ frame, moving beyond traditional techniques that anticipate steady curvature. We beautify the decision of these deformations and couple the sensory facts with a strong finite detail technique (FEM) model. This included framework allows the correct estimation of the smooth robot’s form and the significance of outside forces applied to it, attaining a mean relative inaccuracy of about 4%. Additionally, our technique proves its software program in tender manipulation structures, in which it achieves thirteen% relative mistakes in external force estimation inside diverse zero to five N. The approach gives a promising direction for enhancing robotic interactions in sensitive and dynamic responsibilities, providing massive enhancements in robotic proprioception without reliance on outdoor monitoring generation.

关键词： Deformable models Deformation Force Estimation Soft robotics Robot sensing systems Software

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nBLAST-JC: An accelerated deployment of nucleotide BLAST on high-performance cluster

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Heliyon 2025年第10期11卷

作者： Rani, Sita Kataria, Aman Gupta, O.P. Bhambri, Pankaj Min, Hong Department of Computer Science & Engineering Guru Nanak Dev Engineering College Punjab Ludhiana 141006 India University Centre for Research and Development Chandigarh University Gharuan Mohali 140413 India Associate Director IT Punjab Agricultural University Punjab Ludhiana 141004 India Department of Information Technology Guru Nanak Dev Engineering College Punjab Ludhiana 141006 India School of Computing Gachon University 1342 Seongnamdaero Sujeong-gu Gyeonggi-do Seongnam-si 13120 South Korea

BLAST is the most practiced algorithm to perform the task of sequence alignment. To cope with the voluminous growth in molecular data and reduce processing time, several accelerated versions of BLAST have been proposed by researchers. In this paper, an expeditious design of nucleotide BLAST named nBLAST-JC for a high-performance cluster (HPC) is proposed. The proposed algorithm is implemented on the Hadoop framework using JCuda. It can run multiple query sequences in parallel. The proposed nBLAST-JC gave a speed-up ranging from 7.1 × to 9 × in comparison to HS-BLASN and 1.8 × to 2.3 × in comparison to G-BLASTN (‘blastn’ mode). This algorithm is highly scalable for huge-sized databases due to the fundamental characteristics of the Hadoop framework. The performance of nBLAST-JC can be further enhanced using available CPU cores along with the GPU of each client node. The reliability of the proposed model can further be improved using a two-server approach. © 2025 The Authors

关键词： Basic local alignment search tool (BLAST) Compute unified device architecture (CUDA) Hadoop High-performance cluster (HPC) JCuda Sequence alignment

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An Applied Time Series Forecasting Model for Yield Prediction of Agricultural Crop 1

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2nd International Conference on Soft Computing and Signal Processing, ICSCSP 2019

作者： Reddy, P. Chandra Shaker Sureshbabu, A. Research Scholar JNTUA AnanathapuramuAP India Department of Computer Science & Engineering CMR College of Engineering & Technology HyderabadTS India Professor of CSE Department JNTUA College of Engineering AnanathapuramuAP India

ISBN: (数字)9789811524752

ISBN: (纸本)9789811524745

Rice is an essential yield amongst the most essential food crops of India and it is grown everywhere throughout the nation. Rice is a major yield in the semi-arid district as Ananthapur is the part of Andhra Pradesh (AP) state in India. Precise and early forecasting of rice yield can give valuable information to inside season alteration of yield management. Time series data has been of incredible significance to investigate the area of forecasting strategies and times series models are used for rice yield forecasting from various investigators across the world, yet the forecast has not been precise. In this investigation, we proposed an effective approach to predict seasonal rice production of coming four years based on existing data. The model was build based on rice production data, which it is collected from agricultural department Andhra Pradesh. Rice production data of two seasons (Kharif and Rabi) was gathered in the period of 2008–2014 from Ananthapur district. In this article, we introduced Seasonal Adaptive Auto-Regressive Integrated Moving Average (ARIMA) time series model for prediction for rice crop production for next four years seasonalwise and give more precise outcomes than the previous existing models. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Forecasting

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Site reliability engineering for IOS mobile application in small-medium scale industries

Global Transitions Proceedings

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Global Transitions Proceedings 2021年第2期2卷 137-144页

作者： N Kavyashree Dr. Supriya M C Dr. Lokesh M R SSAHE Tumkur Assistant Professor Dr.AIT Bangalore Karnataka India Department of MCA SSIT Tumkur Karnataka India Department of computer Science and Engineering MITM Mandya Karnataka India

Software reliability is one and only the standard used to calculate the excellence of a software system. In this situation, we suggest a method to forecast software reliability in the primary creation of any process growth phases since from the designing stage only. Software mobile application has remained a significant tool in our lifetime, and several small-medium scale software progress companies capitalize the substantial resources to mark accessible prospects. The landscape of mobile atmospheres varies as of server environments owing to various issues, by means of the net, liveliness, battery-operated, and compatibility. Estimating and forecasting mobile application reliability remain the actual contests as of the variety of the mobile situations in which the applications are used, and the absence of widely available fault data. In addition, error information is optionally given in to the end-users. Hence, in what way to estimate reliability of mobile software application has remained more and more significant. In this paper, site reliability engineering (SRE) for mobile application is proposed for the reliability of software and is taken as a case study. Their failure is copied back to the exact features of mobile application is useful and powerful.

关键词： Fault report Mobile application Site reliability engineering Software forecast Software reliability SRGM Model

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Fresh, mechanical and durability properties of sustainable cement grouts incorporating dredged materials from UAE dams

Results in Engineering

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Results in engineering 2025年 27卷

作者： Samer Al Martini Reem Sabouni Mohamed Elhakeem Mahmoud Masri Associate Professor of Civil Engineering at Department of Civil Engineering College of Engineering Abu Dhabi University Abu Dhabi 59911 United Arab Emirates Affiliate Associate Professor Faculty of Applied Science School of Engineering at the Okanagan Campus University of British Columbia Canada Professor of Civil Engineering at Department of Civil Engineering College of Engineering Abu Dhabi University Abu Dhabi 59911 United Arab Emirates Research Assistant College of Engineering Abu Dhabi University Abu Dhabi 59911 United Arab Emirates

The paper proposes the use of dam dredged materials (DDM) in the construction industry in the United Arab Emirates (UAE). The used DDM in this study were collected from a prominent dam in UAE. Four cement grout mixes were prepared by replacing aggregates with the following percentages of DDM: 0 %, 3 %, 5 % and 10 %. The fresh, mechanical and durability performance of the grout mixes were examined. The slump and rheology of the prepared grout mixes were measured over two hours, with one-hour intervals between two successive measurements. The rheology was assessed by conducting shear flow and stress growth tests. Further, air content, fresh bulk density and initial setting time were measured for all mixes. The mechanical properties were evaluated through measuring the compressive strength and hardened density at 7, 28, 56 and 90 days. Additionally, shrinkage, electrical conductivity and electrical resistivity were measured to assess the durability of the prepared mixes. The results showed that the dam dredged materials enhanced the mechanical and durability of the tested grouts. For example, the 28-day strength increased by approximately 40 % when DDM content was increased from 0 % to 10 %. Further, the DDM offset the shrinkage of the grouts, and shrinkage decreased with higher content of DDM. On the other hand, the cement grouts incorporating DDM were rated as medium resistance to chloride penetration after 90 days of curing. The cement grout mixes were implemented in two construction applications: tile adhesive and plaster. The samples for both applications showed favourable behaviour with no observed cracks after 11 months of exposure to harsh environmental conditions. The promising results of this study would contribute towards reducing the environmental impacts of dam dredged materials and preserving natural resources, leading to sustainable and economic benefits to the UAE.

关键词： Dam dredged materials (DDM) Rheology Cement grouts Compressive strength Thixotropy

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The 27th international conference on case-based reasoning

The 27th international conference on case-based reasoning

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作者： Althoff, Klaus-Dieter Bach, Kerstin Bergmann, Ralph Marling, Cindy Institute of Computer Science University of Hildesheim Hildesheim Germany Department of Computer Science Norwegian University of Science and Technology Trondheim Norway University Professor for Business Information Systems University of Trier Trier Germany School of Electrical Engineering and Computer Science Ohio University AthensOH United States

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AGRO-GAIN - AN ABSOLUTE AGRICULTURE BY SENSING AND DATA-DRIVEN THROUGH IOT PLATFORM

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Procedia computer science 2020年 172卷 534-539页

作者： Dinesh Manikandan Arjun Manoj Skl T. Sethukarasi Student Department of Computer Science Engineering RMK Engineering College Kavaraipettai - 601206 India Professor and Head Department of Computer Science Engineering RMK Engineering College Kavaraipettai - 601206 India

The Agro-gain provides an end-to-end lot platform for data-driven agriculture, that gives an seamless data collection from various sensor type like drones, cameras and sensors. Agro-gain can ensure the availability of system even when the power and internet outages caused by bad weather. First, to enable connectivity within the farm, Agro-gain leverages recent work in unlicensed TV White Spaces (TVWS) to setup a high band width link from the farmer’s home Internet connection to an IoT base station on the farm. Sensors, cameras and drones can connect to this base station over a Wi-Fi frontend. This ensures high bandwidth connectivity within the farm. However, due to the lack of power on the farm, the base station is powered by battery- backed solar power which suffers from power unreliability depending on weather conditions. As shown in past work, cloudy weather can reduce solar power output significantly and drain the batteries of the base station to shut it down. To solve this problem, Agro-gain uses a novel weather-aware IoT base station design. Specifically, it uses weather forecasts to appropriately duty cycle different components of the base station. To the best of our knowledge, this is the first weather-aware IoT base station design. Second, internet connection to the farm is typically weak and it is not sufficient to ship high bandwidth drone videos to the cloud. The Agro-gain uses a Gateway based design, where in a PC at the farmer’s home serves as a gateway for the farm data.

关键词： agrogain agro-gain precision agriculture data driven farming farming with IoT complete agriculture

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Centralized and Reliable Digital Twin Models for Smart City's Buildings Protection during Disaster

Centralized and Reliable Digital Twin Models for Smart City'...

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Computational Modelling, Simulation and Optimization (ICCMSO), International Conference on

作者： Md.Sameeruddin Khan R. Chinnaiyan S Balachandar S.Jafar Ali Ibrahim N.S.Kalyan Chakravarthy C. Kalaiarasan R Divya Dean School of CSE & IS Presidency University Bengaluru INDIA Professor School of CSE&IS Presidency University Bengaluru INDIA VTU-RC Department of MCA CMR Institute of Technology Bengaluru INDIA Department of IoT School of Computer Science and Engineering Vellore Institute of Technology Vellore Tamilnadu India School of CSE QIS College of Engineering & Technology Ongole AP Associate Dean School of CSE & IS Presidency University Bengaluru INDIA

Digital Twin is one of the fast-growing technology digitalization space which needs to complete Smart City's problem areas. Digital twin is virtual representation of physical things or assets or process in a connected network. The data from Physical asset or things IOT Devices, Sensors, Cameras needs to be collected in a large cloud store which contains the engineering data like machine diagrams or flow charts, building blueprint, building electrical map or waterline map, Building information Model, 3D images, computer Aided Design (CAD), controls data IOT Sensors, IOT Gateway, Drones, Cameras, etc. and supporting data. This research paper narrates the different types of digital twin with a use case of Smart Building and how it should be protected during disaster time with different technologies and dataset

关键词： Solid modeling Three-dimensional displays Smart buildings Computational modeling Urban areas Data models Digital twins

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Hybrid CNN-SVM Classifier for Handwritten Digit Recognition

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Procedia computer science 2020年 167卷 2554-2560页

作者： Savita Ahlawat Amit Choudhary Reader Deptt. of Computer Science and Engineering Maharaja Surajmal Institute of Technology New Delhi Associate Professor Deptt. of Computer Science Maharaja Surajmal Institute New Delhi

The aim of this paper is to develop a hybrid model of a powerful Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) for recognition of handwritten digit from MNIST dataset. The proposed hybrid model combines the key properties of both the classifiers. In the proposed hybrid model, CNN works as an automatic feature extractor and SVM works as a binary classifier. The MNIST dataset of handwritten digits is used for training and testing the algorithm adopted in the proposed model. The MNIST dataset consists of handwritten digits images which are diverse and highly distorted. The receptive field of CNN helps in automatically extracting the most distinguishable features from these handwritten digits. The experimental results demonstrate the effectiveness of the proposed framework by achieving a recognition accuracy of 99.28% over MNIST handwritten digits dataset.

关键词： Handwritten digit recognition Hybrid model Convolutional Neural Network Support Vector Machine

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