检索结果-内蒙古大学图书馆

RETRACTED ARTICLE: Obstacles Uncovering System for Slender Pathways Using Unmanned Aerial Vehicles with Automatic Image Localization Technique

引用

International Journal of Computational Intelligence systems 2023年第1期16卷 1-14页

作者： Selvarajan, Shitharth Manoharan, Hariprasath Khadidos, Alaa O. Shankar, Achyut Khadidos, Adil O. Onyema, Edeh Michael Department of Computer Science Kebri Dehar University Kebri Dehar Ethiopia School of Built Environment Engineering and Computing Leeds Beckett University Leeds UK Department of Electronics and Communication Engineering Panimalar Engineering College Chennai India Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Center of Research Excellence in Artificial Intelligence and Data Science King Abdulaziz University Jeddah Saudi Arabia Secure Cyber Systems Research Group (SCSRG) WMG University of Warwick Coventry UK School of Computer Science Engineering Lovely Professional University Phagwara India Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Mathematics and Computer Science Coal City University Enugu Nigeria

In this study, unidentified flying machines are built with real-time monitoring in mid-course settings for obstacle avoidance in mind. The majority of the currently available methods are implemented as comprehensive monitoring systems, with significant success in monitored applications like bridges, railways, etc. So, the predicted model is developed exclusively for specific monitoring settings, as opposed to the broad conditions that are used by the current approaches. Also, in the design model, the first steps are taken by limiting the procedure to specific heights, and the input thrust that is provided for take up operation is kept to a minimum. Due to the improved altitudes, the velocity and acceleration units have been cranked up on purpose, making it possible to sidestep intact objects. In addition, Advanced Image Mapping Localization (AIML) is used to carry out the implementation process, which identifies stable sites at the correct rotation angle. Besides, Cyphal protocol integration improves the security of the data-gathering process by transmitting information gathered from sensing devices. The suggested system is put to the test across five different case studies, where the designed Unmanned aerial vehicle can able to detect 25 obstacles in the narrow paths in considered routs but existing approach can able to identify only 14 obstacle in the same routes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Based Fertilizer Recommendation System for Paddy and Wheat in West Bengal 3rd

A Machine Learning Based Fertilizer Recommendation System fo...

引用

3rd International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2021

作者： Sarkar, Uditendu Banerjee, Gouravmoy Ghosh, Indrajit National Informatics Centre Ministry of Electronics and Information Technology Government of India Jalpaiguri West Bengal735101 India Department of Computer Science Ananda Chandra College Jalpaiguri West Bengal735101 India

ISBN: (纸本)9783030755287

Agricultural soil provides the nutrients to the crop, and over time, the nutrient contents deplete with continued cultivation. The adequate quantity and quality of fertilizers provide the essential nutrients to the soil for the sustained production of crops. Paddy and wheat are the two major crops cultivated by most rural farmers in West Bengal, India. As the agricultural experts are very scarce and expensive, the layman farmers apply the chemical fertilizers with poor technical knowledge. To mitigate the lack of experts and assist the rural farmers, an intelligent machine learning based fertilizer recommendation system for paddy and wheat is very noteworthy. This work proposes a machine learning-based fertilizer recommendation system for this purpose. Instead of a single classifier, the machine learning component is designed with an assembly of multiple classifiers. Each classifier’s performance is evaluated in terms of two well established accuracy metrics;percentage accuracy and Cohen’s kappa. The output of the best performing classifier is always accepted as the final recommendation. The system incorporated the Soil Test Crop Response protocol suggested by the Indian Council of Agricultural Research for the recommendation of fertilizers. It allows the farmers to choose any one of four alternative combinations of fertilizers depending on the local availability and cost. To the best of the authors’ knowledge, no such comprehensive fertilizer recommendation system has been suggested using Soil Test Crop Response protocol. This work is a pioneer in this field. © 2021, Springer Nature Switzerland AG.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Non-repudiable Provenance for Clinical Decision Support systems 8th

Non-repudiable Provenance for Clinical Decision Support Syst...

引用

8th and 9th International Provenance and Annotation Workshop, IPAW 2020 and IPAW 2021 held as part of ProvenanceWeek in 2020 and 2021

作者： Fairweather, Elliot Wittner, Rudolf Chapman, Martin Holub, Petr Curcin, Vasa Department of Population Health Sciences King’s College London London United Kingdom BBMRI-ERIC Graz Austria Institute of Computer Science and Faculty of Informatics Masaryk University Brno Czech Republic

ISBN: (纸本)9783030809591

Provenance templates are now a recognised methodology for the construction of data provenance records. Each template defines the provenance of a domain-specific action in abstract form, which may then be instantiated as required by a single call to the provenance template service. As data reliability and trustworthiness becomes a critical issue in an increasing number of domains, there is a corresponding need to ensure that the provenance of that data is non-repudiable. In this paper we contribute two new, complementary modules to our template model and implementation to produce non-repudiable data provenance. The first, a module that traces the operation of the provenance template service itself, and records a provenance trace of the construction of an object-level document, at the level of individual service calls. The second, a non-repudiation module that generates evidence for the data recorded about each call, annotates the service trace accordingly, and submits a representation of that evidence to a provider-agnostic notary service. We evaluate the applicability of our approach in the context of a clinical decision support system. We first define a policy to ensure the non-repudiation of evidence with respect to a security threat analysis in order to demonstrate the suitability of our solution. We then select three use cases from within a particular system, Consult, with contrasting data provenance recording requirements and analyse the subsequent performance of our prototype implementation against three different notary providers. © 2021, Springer Nature Switzerland AG.

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

Fistnet: Fusion of Style-Path Generative Networks for Facial Style Transfer

SSRN

引用

SSRN 2024年

作者： Khowaja, Sunder Ali Nkenyereye, Lewis Mujtaba, Ghulam Lee, Ik Hyun Fortino, Giancarlo Dev, Kapal Faculty of Engineering and Technology University of Sindh Sindh Jamshoro76080 Pakistan Sejong University Korea Republic of Department of Computer Science West Virginia University MorgantownWV26506 United States IKLab Inc. Gyeonggi-do Siheung15073 Korea Republic of Department of Mechatronics Tech University of Korea Gyeonggi-do Siheung15073 Korea Republic of Department of Informatics Modeling Electronics and Systems University of Calabria Calabria Italy Department of Computer Science ADAPT Centre Munster Technological University Cork Ireland

With the surge in emerging technologies such as Metaverse, spatial computing, and generative AI, the application of facial style transfer has gained a lot of interest from researchers as well as startups enthusiasts alike. StyleGAN methods have paved the way for transfer-learning strategies that could reduce the dependency on the huge volume of data that is available for the training process. However, StyleGAN methods have the tendency of overfitting that results in the introduction of artifacts in the facial images. Studies, such as DualStyleGAN, proposed the use of multipath networks but they require the networks to be trained for a specific style rather than generating a fusion of facial styles at once. In this paper, we propose a FusIon of STyles (FIST) network for facial images that leverages pre-trained multipath style transfer networks to eliminate the problem associated with lack of huge data volume in the training phase along with the fusion of multiple styles at the output. We leverage pre-trained styleGAN networks with an external style pass that use residual modulation block instead of a transform coding block. The method also preserves facial structure, identity, and details via the gated mapping unit introduced in this study. The aforementioned components enable us to train the network with very limited amount of data while generating high-quality stylized images. Our training process adapts curriculum learning strategy to perform efficient, flexible style and model fusion in the generative space. We perform extensive experiments to show the superiority of FISTNet in comparison to existing state-of-the-art methods. © 2024, The Authors. All rights reserved.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

A Fuzzy Logic-Based Crop Recommendation System

A Fuzzy Logic-Based Crop Recommendation System

引用

International Conference on Frontiers in Computing and systems, COMSYS 2020

作者： Banerjee, Gouravmoy Sarkar, Uditendu Ghosh, Indrajit Department of Computer Science Ananda Chandra College JalpaiguriWest Bengal735101 India National Informatics Centre Ministry of Electronics & Information Technology Government of India JalpaiguriWest Bengal735101 India

ISBN: (纸本)9789811578335

Soil, geographical and meteorological parameters have major impacts on sustained crop production. Most of the rural farmers have no adequate knowledge about the effects of these parameters on crop production. The rural farmers generally rely on their traditional knowledge to select a crop which often leads to huge economic loss. A scientific system considering these site-specific parameters along with the traditional knowledge of the farmers may be an effective solution. This paper suggests a fuzzy logic-based crop recommendation system to assist rural farmers. The proposed model has been designed to deal with eight major crops grown in the state of West Bengal. Separate fuzzy rule bases were created for each crop to achieve faster parallel processing. The performance of the model has been validated by a diverse dataset and achieved an accuracy of about 92%. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

Using HLPC for parallelization of autonomous tests of WEB applications from its GUI 34

Using HLPC for parallelization of autonomous tests of WEB ap...

引用

34th European Modeling and Simulation Symposium, EMSS 2022

作者： Rossainz-López, Mario Islas-Fuentes, Jesús A. Pineda-Torres, Ivo Capel-Tuñón, Manuel Faculty of Computer Science Autonomous University of Puebla Av. San Claudio and 14 Sur Street San Manuel PueblaC.P. 72570 Mexico Software Engineering Department College of Informatics and Telecommunications ETSIIT University of Granada Daniel Saucedo Aranda s/n Granada18071 Spain

A proposal for parallelization of autonomous tests of Web applications from its graphical user interface (GUI) is presented to reduce its execution time since these increases exponentially due to the number of combinations that are generated with the different states of the fields, of the forms on the web application pages by creating a tree-like structure. It is proposed to use the model of high-level parallel compositions or HLPC as a suitable model of semi-automatic parallelization that defines a Treelike structure as a communication pattern between processes. The proposed HLPC, which we call HLPC-Tree, uses reinforcement learning that associates each node of the process tree as a slave object using the Q-Learning (QL) algorithm and achieves autonomous recognition of the fields of the forms and valid-invalid options to identify failures and display them with HTTP status codes. In addition, the Mechanize library is used to find the number of possible combinations through the states of the fields of the forms and to know how many nodes are generated at each level of the process tree in the HLPC-Tree when it grows in depth. Finally, the performance analysis of the proposed HLPC is shown with an analysis of the speedup and execution times in an 8-core machine to demonstrate good scalability in its accelerations compared to Amdahl's Law. © 2022 The Authors.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

FUTURE INDUSTRIAL APPLICATIONS: EXPLORING LPWAN-DRIVEN IOT PROTOCOLS

arXiv

引用

arXiv 2023年

作者： Islam, Mahbubul Mubashshir Jamil, Hossain Pranto, Samiul Ahsan Amin, Al Das, Rupak Kumar Khan, Arshia Department of Computer Science United International University Dhaka Bangladesh Department of Electrical and Electronic Engineering Islamic University of Technology Dhaka Bangladesh Department of Information Systems University of Maryland - Baltimore BaltimoreMD United States College Of Information Sciences and Technology Pennsylvania State University University Park State College PA United States Department of Computer Science University of Minnesota - Duluth DuluthMN United States

The Internet of Things (IoT) will bring about the next industrial revolution in Industry 4.0. The communication aspect of IoT devices is one of the most critical factors in choosing the suitable device for the suitable usage. So far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. Moreover, most of them are wireless protocols due to the sheer number of device requirements for IoT. This paper summarizes the network architectures of some of the most popular IoT wireless communications protocols. It also presents a comparative analysis of critical features, including power consumption, coverage, data rate, security, cost, and Quality of Service (QoS). This comparative study shows that Low Power Wide Area Network (LPWAN) based IoT protocols (LoRa, Sigfox, NB-IoT, LTE-M) are more suitable for future industrial applications because of their energy efficiency, high coverage, and cost efficiency. In addition, the study also presents an industrial Internet of Things (IIoT) application perspective on the suitability of LPWAN protocols in a particular scenario and addresses some open issues that need to be researched. Thus, this study can assist in deciding the most suitable protocol for an industrial and production field. Copyright © 2023, The Authors. All rights reserved.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Value-Compressed Sparse Column (VCSC): Sparse Matrix Storage for Single-cell Omics Data

Value-Compressed Sparse Column (VCSC): Sparse Matrix Storage...

引用

IEEE International Conference on Big Data

作者： Seth Wolfgang Skyler Ruiter Marc Tunnell Timothy Triche Erin Carrier Zachary DeBruine Department of Intelligent Systems Engineering University of Indiana Bloomington IN USA Department of Computer Science Purdue University West Lafayette IN USA Department of Epigenetics Van Andel Institute Grand Rapids MI USA College of Computing Grand Valley State University Allendale MI USA

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Genomics datasets, such as single-cell transcriptomics, are often very large and highly sparse, posing significant challenges for both storage and computation. As the scale of data generation accelerates, efficiently compressing these datasets becomes crucial. Current compression methods, like the popular Compressed Sparse Column (CSC) format, capitalize only on sparsity but overlook other properties like redundancy, which can offer additional opportunities for compression. Genomics data, especially single-cell assays, often exhibit high redundancy within columns, making traditional sparse formats inefficient for in-core computation. In this paper, we present two extensions to CSC: (1) Value-Compressed Sparse Column (VCSC) and (2) Index-and Value-Compressed Sparse Column (IVCSC). VCSC takes advantage of high redundancy within a column to further compress data up 1.9-fold over CSC on real data, without significant negative impact to performance characteristics. IVCSC extends VCSC by compressing index arrays through delta encoding and byte-packing, achieving up to a 4.4-fold decrease in memory usage over CSC on real data. Our benchmarks show that VCSC and IVCSC can be used in compressed form with little added computational cost. These formats represent a step forward in balancing the growing demands of data storage and processing in the era of large-scale genomics.

关键词： Redundancy Transcriptomics Memory Big Data Benchmark testing Encoding Computational efficiency Sparse matrices Indexes Bioinformatics

来源：评论

学校读者我要写书评

暂无评论

Knee Osteoarthritis Detection And Classification Using Transfer Learning

Knee Osteoarthritis Detection And Classification Using Trans...

引用

Computing and Information Technology (ICCIT-1441), 2020 International Conference on

作者： Naeem Ahmed Muhammad Saeed Muhammad Aftab Abid Mehmood Qazi Mudassar Ilyas Department of Computer Science University of Engineering and Technology Taxila Pakistan Department of MIS College of Business Administration King Faisal University Al-Ahsa Saudi Arabia Department of Information Systems College of CS & IT King Faisal University Al-Ahsa Saudi Arabia

Knee osteoarthritis (OA) is a common disease that causes pain, stiffness, and decreased mobility by wearing down the cartilage between the bones in the knee joint. Early and automatic detection of knee OA is important for ensuring effective treatment for patients. The aim of this article is to develop a deep learning model using ResNet50 architecture for the accurate classification of knee osteoarthritis (OA) from images of X-rays originally labeled using the Kellgren–Lawrence (KL) Scale. The dataset used in the current study involves images taken from 4796 participants of ages between 45 and 79 years, with approximately nine thousand knee X-ray images. The ResNet50 model is trained on this dataset, and various evaluation metrics were used to evaluate its performance. A flask-based web application was also developed for using the trained model. Our model achieved a high degree of accuracy (97.4%) in classifying knee OA, suggesting that it could be a valuable tool for diagnosing this condition quickly and accurately.

关键词：

来源：评论

学校读者我要写书评

暂无评论

CNN segmentation of skin melanoma in pre-processed dermoscopy images

引用

Procedia computer science 2024年 235卷 2775-2782页

作者： Seifedine Kadry Elena Verdú Robertas Damasevicius Laith Abualigah Vijendra Singh Venkatesan Rajinikanth Department of Applied Data Science Noroff University College Kristiansand Norway Artificial Intelligence Research Center (AIRC) Ajman University Ajman 346 United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon Higher School of Engineering and Technology Universidad Internacional de La Rioja Logroño 26006 Spain Department of Applied Informatics Vytautas Magnus University 53361 Kaunas Lithuania Computer Science Department Al al-Bayt University Mafraq 25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan MEU Research Unit Middle East University Amman 11831 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang 11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya 27500 Malaysia School of Computer Science University of Petroleum and Energy Studies Dehradun 248007 India Department of Computer Science and Engineering Division of Research and Innovation Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602105 India

Using medical data to improve diagnosis accuracy has recently become common practice in hospitals. A modern computing environment has enabled real-time diagnosis of medical data using Convolutional Neural Networks (CNNs). To extract and evaluate skin melanoma recorded with digital dermatoscopy images (DDI), we developed a CNN segmentation framework. In this proposal, four phases are proposed: (i) DDI collection and resizing, (ii) DDI enhancement using pre-processing techniques, (iii) CNN segmentation for lesion extraction, (v) Comparing the extracted sections to the ground truth images, and (v) Verifying whether the framework is valid. Using DDI pre-processed with (i) Traditional procedures, (ii) Otsu’s thresholding, (iii) Kapur’s thresholding, and (iv) Fuzzy-Tsallis thresholding, this proposal examines the different CNN segmentation schemes presented in the literature. For mining skin lesions, the Moth-Flame Algorithm (MFA) combined with tri-level thresholding achieves an optimal threshold for the DDI. With Fuzzy-Tsallis thresholding images, the VGG-UNet performs better than the alternatives. This framework helps to achieve better values of Jaccard (88.47±2.13%), Dice (93.08±1.17%), and Accuracy (98.64±0.71%) on the chosen DDI database.

关键词： Watershed-algorithm skin melanoma segmentation Fuzzy-Tsallis entropy Moth-Flame algorithm evaluation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：