检索结果-内蒙古大学图书馆

Computing, Applications and Systems (COMPAS), IEEE International Conference on

作者： Al-Amain Fatema Tuj Janin Faizul Ahmed Robin Shifat Ahmed Khandaker Mohammad Mohi Uddin Dept. of Computer Science and Engineering Southeast University Dhaka Bangladesh Dept. of Information and Electrical Engineering Hamburg University of Applied Sciences Hamburg Germany

ISBN: (数字)9798331529765

ISBN: (纸本)9798331529772

Chronic diseases, characterized by long-term effects and persistent symptoms, pose significant challenges to human health and well-being. The hepatitis C virus (HCV) is the cause of chronic hepatitis C, which affects 58 million people globally. It also causes 290,000 deaths annually due to liver cancer and cirrhosis, two conditions connected to HCV. Taking advantage of machine learning (ML) algorithms' ability to analyze large datasets and identify patterns and relationships that aid in diagnosis, this effort focuses on employing algorithms for machine learning to identify and forecast hepatitis C precisely. Various techniques were utilized, including Random Forest, Cat Boost, SVM, and others to create predictive models using blood values from 615 patients, including both hepatitis patients and healthy blood donors. The dataset underwent comprehensive preprocessing, including handling missing values, scaling, and dimensionality reduction via Principal Component Analysis (PCA). Various ML algorithms were evaluated, and the Cat Boost classifier achieved the highest accuracy of 99.17%, recall of 92.00%, precision of 100.00% and F1-score is 96.00%. This study demonstrates the potential of ML in enhancing HCV diagnosis, offering less invasive and cost-effective alternatives to traditional methods, and providing predictive insights for personalized treatment plans. The findings underscore the importance of advanced data preprocessing and feature selection in improving model efficiency. This study adds to the ongoing efforts to lessen the prevalence of hepatitis C worldwide, aligning with the World Health Organization's goal to significantly decrease new HCV cases and related deaths by 2030.

关键词： Support vector machines Machine learning algorithms Accuracy Liver diseases Predictive models Prediction algorithms Classification algorithms Viruses (medical) Medical diagnostic imaging Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Vehicle To Vehicle and Vehicle To Ground Communication - Speech Encryption Algorithm

Vehicle To Vehicle and Vehicle To Ground Communication - Spe...

引用

Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： Obaida M. Al-Hazaimeh Ma'moun A. Al-Smadi Dept. of Computer Science Al-Balqa Applied University Irbid Jordan Dept. of Electrical Engineering Al-Balqa Applied University Irbid Jordan

Vehicle to vehicle (V2V) communication has many applications in intelligent transportation system (ITS) like smart grid systems, fleet management and traffic light control. It aims to interconnect several components like road infrastructures, wireless networks, sensors, and vehicles. Therefore, it can be utilized to reduce congestion, accidents and fuel consumption. This paper propose a speech encryption system based on a one-dimensional logistic map for vehicle to vehicle communication (V2V) communication in intelligent transportation systems (ITS) to improve road safety and efficiency, where encryption and security play a major role. This study employs a symmetric key cryptography technique for chaotic ciphering. In this approach, a random key table lookup criterion was paired with a one-dimensional chaotic map in order to encrypt speech samples with a high level of security and acceptable speed. XOR encryption and speech row shuffling are used in the proposed technique. Using the difference between the old and new row locations, a combination of variable rotation and inversion was performed to each shuffled row in order to increase the level of security. As a consequence of the testing, the proposed approach was shown to be both efficient and usable. Combining key table and logistic map illustrates the advantages of both high-level security and large random key space. The encrypted speech produced is suitable for practical usage especially in vehicle to vehicle and vehicle to base transmission.

关键词：

来源：评论

学校读者我要写书评

暂无评论

EVALUATION OF PERFORMANCE OF A CI ENGINE FUELED WITH BIODIESEL PRODUCED FROM UNUSED ALGAE

Journal of Solid Waste Technology and Management

引用

Journal of Solid Waste Technology and Management 2023年第4期49卷 359-364页

作者： Karmakar, Rachan Kumar, Nitin Rajor, Anita Kundu, Krishnendu Kumar, Rajesh Gahlot, Dinesh Chaudhury, Bhaskerpratap Ragit, S.S. Kumar, Amit Gorai, Sanjoy Gangwar, Pavan SInghal, Rishabh Bhattacharya, Sourish Sharma, Rachna Savita Singh, Narpinder Kumar, Neeraj Graphic Era Deemed to be University Uttarakhand Dehradun India Dept. of Mechanical Engineering Roorkee Institute of Technology Uttarakhand Roorkee India School of Energy and Environment Thapar University Punjab Patiala India Dept. of Biofuel CSIR CMERI CoEFM Punjab Ludhiana India Dept. of Chemistry S.S.J. University Campus Almora Uttarakhand India Dept. of Physics Chandigarh Group of Colleges Punjab Jhanjheri India Dept. of Mechanical Engineering Guru Nanak Institute of Technology Maharashtra Nagpur India Dept. of Computer Application Quantum University Uttarakhand Roorkee India Dept. of Electronics and Communication Engineering IMS Engineering College U.P. Gaziabad India Dept. of Electrical Engineering COER University Uttarakhand Roorkee India Process Design and Engineering Cell Discipline CSIR Central Salt and Marine Chemicals Research Institute Gujrat Bhavnagar India Dept. of Applied Science Roorkee Institute of Technology Uttarakhand Roorkee India School of Agriculture Graphic Era Hill University Uttarakhand Dehradun India Dept. of Food Science and Technology Graphic Era Deemed to be University Uttarakhand Dehradun India

Abundant availability and easy culture process of algae make it a better resource than other vegetable crops for biodiesel production. The oil (with 21% FFA content) extracted from the unused, mixed culture of algae in this experiment was used to produce biodiesel by an ‘acid esterification followed by alkaline esterification’ procedure. After confirming the properties of the biodiesel to be within the limit of ASTM standard, three biodiesel blends (B10, B20 and B30) were used in an internal combustion engine (Four stroke single cylinder VCR engine) and the performance of the engine was observed at different engine loads (0%, 20%, 40%, 80%, 100%, 120%). The little higher brake specific fuel consumption (0.22kg/KWh, 0.25 kg/KWh, 0.26kg/KWh and 0.21kg/KWh respectively for B10, B20, B30 and petro-diesel at overload condition), lower brake power (3.41 kW, 3.37 kW, 3.25 kW, 3.39 kW for diesel, B10, B20 and B30 respectively for B10, B20, B30 and petro-diesel) and mechanical efficiency (63.34, 51.43%, 52.06% and 51.43% for petro-diesel, B10, B20 and B30 respectively) for biodiesel blends took place which might be the results of lower calorific value (40800 kJ/kg), higher density (875.27kg/m3) and viscosity (3.14 mm2/s) of the algal biodiesel than diesel. © 2023 Widener University School of Civil Engineering. All rights reserved.

关键词： Biodiesel

来源：评论

学校读者我要写书评

暂无评论

The Use of Encryption to Preserve the Privacy and Security of Electronic Health Records

The Use of Encryption to Preserve the Privacy and Security o...

引用

Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Naila Samar Naz Dept. of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan

Cloud computing is the storage of data over the Internet rather than locally on a user's device, and it is one of the most extensively used applications of computers and related technologies in today's world. Since cloud computing became publicly available, its popularity has risen. End customers may be able to obtain a better application that is more convenient, less expensive, and both effective and efficient because of cloud computing. When storing and managing sensitive data, it is critical to select a storage and management solution that provides security and privacy safeguards. Patients have long been maintained on the cloud, but the data has always been protected by ciphertext encryption. One of the most challenging challenges in a cloud computing environment is the need to protect users' online activities as well as their personal information. The healthcare system was created with the intention of addressing the demands of medical practitioners by providing a solid foundation, simple means to obtain patient information, and efficient ways to use the system. This work describes, with implementation details, an innovative approach for establishing a reliable and effective e-health cloud model employing identity-based encryption. This approach is suggested in this article. The time, power, and energy requirements for encryption and decryption of the suggested strategy were estimated and compared to those of the currently used method. It has been demonstrated that the cryptographic approach presented can reduce the time required for data decoding by up to 50%. Because the decryption process is quicker, the cryptographic procedures may be conducted with less power.

关键词： Cloud computing Privacy Identity-based encryption Public key Medical services Solids Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Software Defect Predictor and Classifier Tool Using Machine Learning Techniques

Software Defect Predictor and Classifier Tool Using Machine ...

引用

Network, Multimedia and Information Technology (NMITCON) International Conference on

作者： Sahana P. Shankar Divyansh Pushp Nemi Makadia Raghav Dubey Anusha Nayak Shilpa Shashikant Chaudhari Dept. of Computer Science and Engineering Ramaiah University of Applied Sciences Bangalore Karnataka Dept. of Computer Science and Engineering M S Ramaiah Institute of Technology Bangalore Karnataka

The Software testing is critical for ensuring the quality of software, but it can consume more than half of a software project's total expenses. This research can help software development teams identify potential bugs early on, leading to efficient and effective software creation. To improve the efficiency of software testing, this report presents research on software defect prediction using a hybrid machine learning algorithm that combines supervised and unsupervised learning techniques. The study used publicly available datasets to train and evaluate various machine learning models, including an ensemble learning model. A comparative analysis was conducted among KNN, Random Forest, Adaboost, Multilayer Perceptron, CNN, and Gaussian Naïve Bayes on different datasets. Feature selection was performed using various methods, including Recurrent Feature Elimination (RFE), SelectKBest, and Correlation, implemented by a tool created to select any feature selection algorithm and compare the results for various combinations with the above mentioned classifiers. The results achieved by the model are showed in detail for each of the algorithms on the selected datasets. The main objectives of the research are to create a tool to apply various machine learning techniques to the datasets and determine the most effective ones, as well as to explore different feature selection methods for improving the accuracy of defect prediction.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Adaptive optical interconnect for digital systems using integrated MOEMS technology

Adaptive optical interconnect for digital systems using inte...

引用

2021 IEEE International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2021

作者： Lohmann, Ulrich Jahns, Jurgen University of Applied Administrative Science Dept. of Computer Science Münster48161 Germany FernUniversität in Hagen Dept. of Mathematics and Computer Science Hagen58097 Germany

ISBN: (纸本)9781665412629

Rapid growth in computing and communications, novel computing concepts and applications require permanent advances and increasing flexibility in data networks and data centers. Here, we discuss architecture and physical implementation of an adaptive interconnect using a Clos-based spine-leaf architecture. At the center of the discussion is the optimization of the interconnection network by using redundancy. The physical implementation is based on integrated micro-optics combined with micro-mechanical device technology. In a top-down approach, we consider the various aspects of the interconnect at the systems and at the physical level. © 2021 IEEE.

关键词： Redundancy

来源：评论

学校读者我要写书评

暂无评论

Pre-processing Blood-Volume-Pulse for In-the-wild Applications

arXiv

引用

arXiv 2023年

作者： Fromberg, Laurits Das, Sneha Clemmensen, Line Katrine Harder Dept. Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark

Blood-volume-pulse (BVP) is a biosignal commonly used in applications for non-invasive affect recognition and wearable technology. However, its predisposition to noise constitutes limitations for its application in real-life settings. This paper revisits BVP processing and proposes standard practices for feature extraction from empirical observations of BVP. We propose a method for improving the use of features in the presence of noise and compare it to a standard signal processing approach of a 4th order Butterworth bandpass filter with cut-off frequencies of 1 Hz and 8 Hz. Our method achieves better results for most time features as well as for a subset of the frequency features. We find that all but one time feature and around half of the frequency features perform better when the noisy parts are known (best case). When the noisy parts are unknown and estimated using a metric of skewness, the proposed method in general works better or similar to the Butterworth bandpass filter, but both methods also fail for a subset features. Our results can be used to select BVP features that are meaningful under different SNR conditions. Copyright © 2023, The Authors. All rights reserved.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Evaluation of the Effectiveness of Vulnerable Road User Clustering in C-V2X Systems

Evaluation of the Effectiveness of Vulnerable Road User Clus...

引用

Omni-layer Intelligent Systems (COINS), International Conference on

作者： Matthias Rupp Lars Wischhof Dept. of Computer Science and Mathematics Munich University of Applied Sciences HM Munich Germany

Vulnerable Road Users (VRUs) are at special risk in road traffic. The dissemination of information about VRUs in Intelligent Transportation Systems (ITS) can help to protect VRUs from various risks. The Vulnerable Road User Awareness Message (VAM) format has been specified by ETSI as a way of distributing VRU-related information. The standard also describes a clustering mechanism that can help to reduce the number of generated messages and therefore prevent computing overload and network congestion in certain situations. This paper presents initial results on the effectiveness of the clustering approach proposed in the ETSI standard as well as its impact on position accuracy. Therefore, the clustering schemes are implemented in coupled network- and mobility simulations, modeling traffic situations with pedestrians and vehicles. In addition, the impact of one of the most relevant parameters for forming clusters, the maxClusterVelocityDifference, on clustering is assessed. The results indicate that VRU clustering can signifi-cantly reduce the number of VAM messages but also leads to a larger position error between the actual- and received position of individual VRUs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Development of Anomaly Detection with Variable Contexts on Refrigeration Data

Development of Anomaly Detection with Variable Contexts on R...

引用

International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Melina Meyer Martin Gergeleit Dirk Krechel Dept. of Design Computer Science Media RheinMain University of Applied Sciences Wiesbaden Germany

Anomaly detection in time series data is a well-known research topic and of great interest to the industry. However, industrial systems are complex due to the nature of real world plants and their interrelationships in the overall system. Industrial plants often cannot be considered in isolation because their environment affects them. Thus, industrial plants have variable contexts in which they are embedded. The combination of a variable context with the information of the plant poses a challenge in modeling AI approaches for anomaly *** the field of refrigeration, machine learning approaches are still in their early stages. In live systems, simple threshold values are often still used. There are only a few published approaches to detect error situations using machine learning on such *** this work, the challenges to such a model architecture are analyzed and a dataset of real refrigeration plants is built. Then, models for detection and classification are explored and their applicability to this type of data is evaluated. Furthermore, models are combined to add context to improve the results compared to models without context information.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimization of Liver RNA-Seq Analysis through HRNet: Bridging Computational Techniques and Biological Understanding

Optimization of Liver RNA-Seq Analysis through HRNet: Bridgi...

引用

International Conference on computer and Information Technology (ICCIT)

作者： Mejbah Ahammad Nourin Zaman Rishan Hasan Tenis Abdullah Al Mamun Sakib Tasnim Niger Tithee Chakma Mama Dept. of Physical Sciences Independent University Dhaka Bangladesh Dept. of Statistics and Data Science Jahangirnagar University Dhaka Bangladesh Dept. of Computer Science & Technology Southwest Petroleum University Chengdu China Applied Chemistry & Chemical Engi. University of Dhaka Dhaka Bangladesh Dept. of Computer Science & Engi. Islamic University of Technology (IUT) Dhaka Bangladesh Dept. of Computer Science & Engi. Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

In the digital era, the rapid proliferation of RNA sequencing (RNA-Seq) has uncovered vast datasets, particularly in liver-specific gene expression, yet the complexity of such high-dimensional data often obscures actionable insights. This research focuses on optimizing the analysis of liver RNA-Seq data through the innovative application of the Human RNA Network (HRNet) architecture, renowned for its proficiency in handling complex image and data patterns. Employing a refined dataset from the All RNA-seq and ChIP-seq sample and signature search (ARCHS4) platform, this study evaluates the effectiveness of HRNet alongside traditional machine learning and emerging deep learning techniques. The introduction of enhanced preprocessing, feature selection, and dimensionality reduction methods tailored to the intricacies of liver RNA-Seq data marks a pivotal advance in computational biology. Rigorous testing against conventional models demonstrates the superior capability of HRNet, achieving remarkable precision in identifying and analyzing gene expressions critical to understanding liver functions and disorders. The results showcase not only HRNet’s robust performance, with accuracy rates exceeding 98.5% in complex gene expression patterns, but also its potential in transforming the landscape of genomic research, facilitating more precise diagnostic and therapeutic strategies. This study underscores the necessity of integrating advanced computational models to effectively decipher the voluminous data generated by RNA-Seq, thereby enhancing the accuracy and applicability of genomic analyses in medical research.

关键词： Analytical models RNA Computational modeling Biological system modeling Liver Genomics Feature extraction Gene expression Bioinformatics Computational biology

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：