检索结果-内蒙古大学图书馆

Identification of spatial potential flood-prone area using topographic wetness index under the digital elevation model of Kr. Keureuto watershed, North Aceh. 5

Identification of spatial potential flood-prone area using t...

引用

5th Aceh International Symposium on Civil engineering 2024, AISCE 2024

作者： Rizalihadi, Maimun Meilianda, Ella Yulianur, Alfiansyah Away, Yuwaldi Doctoral Program Post Graduate Program Syiah Kuala University Banda Aceh Indonesia Civil Engineering Department Syiah Kuala University Banda Aceh Indonesia Electro and Computer Engineering Department Syiah Kuala University Banda Aceh Indonesia

Floods are the most frequent disaster events in Lhoksukon, resulting in significant losses and community and environmental damage. Floods are generated by several factors, consisting of hydrometeorological, topographical, geological, soil, and human activities. Topography is a key controlling factor in flood initiation. Topographic analysis for detecting flood susceptibility, especially flood inundation, can be conducted using the TWI. The research aims to identify the potential spatial distribution of flood-prone areas based on TWI and assess the model accuracy using the ROC-AUC method. A case study was conducted in the Kr. Keureuto watershed. of North Aceh. TWI analysis is based on the topography of an area denoted by extracting DEM using GIS to create slope, flow direction, and flow accumulation. Higher TWI values are associated with higher flood susceptibility. The results show that the value of TWI is approximately 1.571-27.147, showing that more than 20% of area are potentially flood inundations with high and very hight rating of flood susceptibility. Furthermore, based on the analysis using field observation flood is obtained the AUC value of 71,60%. It can be concluded that the spatial model of flood-prone using TWI is good and effective for determining flood prone region in the Kr. Keureuto River basin © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Watersheds

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis in Indonesian Trading using Lexicon-based and Support Vector Machine

Sentiment Analysis in Indonesian Trading using Lexicon-based...

引用

2023 International Conference on computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Oetama, Raymond Sunardi Yanfi, Yanfi Ikhsan Assiddiq Up, Masagus M. Muhamad Isa, Sani Universitas Multimedia Nusantara Information System DepartmentFaculty of Engineering and Informatics Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350320954

Many individuals now trade online utilizing trading software in the digital world. Binomo is one of Indonesia's most popular trading platforms. This is because some influencers made several promises to Binomo customers. Since many customers were deceived, this case became quite popular. This study was executed to see how Indonesians felt about the Binomo application after the case went viral. The solution taken was in the form of sentiment analysis because there had been no previous research on sentiment analysis that discussed the Binomo case. The data was scanned using Netlytic tools, a cloud-based text and social network analyzer capable of identifying any talks on social media sites such as Twitter. The sentiment analysis of Binomo trading tweets by using the Multi-Perspective Question Answering lexicon utilized the KNIME tool. But unfortunately, the accuracy of sentiment analysis results is low. Furthermore, the Support Vector Machine technique is also being conducted. The Term Frequency-Inverse Document Frequency method is applied to perform feature extraction whilst the chi-square approach is utilized to identify features that are thought to be useful for inclusion in the classification process and to exclude features that are irrelevant to the target class. The obtained accuracy is 86%. The study proposes that words from the algorithm's outputs can be utilized to improve the quality of sentiment analysis using the lexicon. As an outcome of the algorithm, positive and negative terms are added to the lexicon, increasing the accuracy of sentiment analysis using the new vocabulary from 58.984% to 71.146%. © 2023 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

An Extended Euclidean Algorithm Implementation over Ciphertext Space 2nd

An Extended Euclidean Algorithm Implementation over Ciphert...

引用

2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Chi, Po-Wen Lin, Yuan-Pang Wang, Ming-Hung Chuang, Yun-Hsin Department of Computer Science and Information Engineering National Taiwan Normal University Taiwan Taipei Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Taiwan Chiayi Taiwan Engineering Management Graduate Program College of Engineering National Cheng Kung University Taiwan Tainan Taiwan

ISBN: (纸本)9789819777853

Fully homomorphic encryption (FHE) is a useful cryptographic primitive. It makes a third-party manipulate data in the ciphertext space and therefore is a key technology for privacy-preserving outsourcing services. Theoretically, FHE can evaluate any circuits. However, the implementation is not trivial. The reason it lacks lots of basic operations like conditional check and branch control. In this paper, we focus on extended Euclidean algorithm operation over FHE. We introduce the problems we encounter and show how we solve these issues. We implement our design and evaluate its performance on a real computer. Finally, we propose some research directions for our future work. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ciphertext

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Inference Engine to Predict Uncertain Sugar Content for Sugar Industry 9th

A Hybrid Inference Engine to Predict Uncertain Sugar Content...

引用

9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Asrol, Muhammad Napthaleni Utama, Ditdit Nugeraha Suharjito Harito, Christian Syafrudin, Muhammad Industrial Engineering Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Department of Artificial Intelligence and Data Science Sejong University Seoul05006 Korea Republic of

The sugar industry is facing challenges in increasing productivity to meet consumer demand. One opportunity for productivity improvement lies in ensuring sugar content. This study proposes a hybrid model to predict sugar content by considering uncertainty factors. A hybrid model combining fuzzy subtractive clustering, and a fuzzy inference system is proposed to predict sugar content. The clustering results using silhouette and fuzzy subtractive clustering successfully identified 6 cluster centres from 2225 datasets collected in a sugar industry in East Java Province. The hybrid inference engine model is designed with fuzzy rules derived from the clustered data. Two inference models are developed: triangular and Gaussian fuzzy numbers. The testing results indicate that the hybrid model with triangular fuzzy numbers shows the smallest error with an R2 value of 0.95. This model is possible to applied in the sugar industry for decision makers in improving productivity with taking attention into uncertain factors influencing sugar content. © 2024 The Authors.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

ForTT-Gen: Network Traffic Generator for Malware Forensics Analysis Training 12

ForTT-Gen: Network Traffic Generator for Malware Forensics A...

引用

12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Bistene, Jonas Vasconcelos Das Chagas, Clayton Escouper Dos Santos, Anderson Fernandes Pereira De Souza Dias, Gabriela Moutinho Salles, Ronaldo Moreira Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil Military Institute of Engineering Department of Computer Engineering Rio de Janeiro Brazil Ciicesi Estg Polytechnic of Porto Porto Portugal

ISBN: (纸本)9798350330366

The generation and replication of network traffic are essential tasks for testing, analyzing, simulating, and evaluating the behavior and efficiency of systems, protocols, applications, and network services. However, it faces various challenges and limitations when generating or replicating network traffic in a realistic, responsive, and scalable manner, using appropriate models. This work proposes a modeling of a program for generating and replicating network traffic, called Forensic Training Traffic Generator (ForTT-Gen), aims to address the challenge associated with generating and replicating network traffic generated by malware by creating files that can be used in the analysis of network packets inherent to forensic analysts' training. ForTT-Gen is a tool that can generate and replicate network traffic using a hybrid model that combines the replication of real data and the generation of synthetic data through statistical techniques. Experimental results demonstrate the model's ability to reliably. Accurately reproducing the statistical patterns of the original traffic, is evidenced by a determination coefficient of 1 and a Pearson coefficient of 0.9, all within a 0,58 confidence interval with 95% certainty. © 2024 IEEE.

关键词： Malware

来源：评论

学校读者我要写书评

暂无评论

Improving Supplier Evaluation Model using Ensemble Method-Machine Learning for Food Industry 8

Improving Supplier Evaluation Model using Ensemble Method-Ma...

引用

8th International Conference on computer Science and Computational Intelligence, ICCSCI 2023

作者： Asrol, Muhammad Wahyudi, Sofyan Suharjito Harito, Christian Utama, Ditdit N. Syafrudin, Muhammad Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Artificial Intelligence Sejong University Seoul05006 Korea Republic of

Supplier evaluation has a crucial role in maintaining efficiency in the food industry supply chain. Machine learning approaches can be employed to formulate models aimed at analyzing and evaluating supplier performance. Previous research has successfully designed decision tree and neural network models for assessing suppliers in the food industry with accuracies of 84.2% and 92.8% separately. Recognizing the opportunity to improve the model's performance, this study aims to advancing the machine learning models accuracy for analyzing and evaluating suppliers in the food industry. Two main models are proposed to enhance model accuracy: ensemble methods and support vector machine. This research has successfully designed a supplier evaluation model and demonstrated that the ensemble method - gradient boosting model outperforms other ensemble methods and support vector machine which is achieved a accuracy of 93.6% on a cross-validation dataset. The development of a dashboard is required to implement the supplier evaluation model using machine learning, facilitating decision-makers in evaluating and controlling supplier performance. © 2023 The Authors. Published by Elsevier B.V.

关键词： Ensemble Method Food Machine Learning Supply chain Supplier evaluation

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Deep Convolutional Neural Network-Based Tattoo Detection 7

Evaluation of Deep Convolutional Neural Network-Based Tattoo...

引用

7th International Congress on Ambient Intelligence, Software engineering, and e-Health and Mobile Health, AmITIC 2024

作者： Jiménez-Delgado, E. Quesada-López, C. Méndez-Porras, A. Lara-Petitdemange, A. Alfaro-Velasco, J. Graduate Program in Computer Science and Informatics University of Costa Rica Costa Rica Technological Institute of Costa Rica Computer Engineering Department Costa Rica School of Computer Science and Informatics University of Costa Rica Costa Rica

ISBN: (纸本)9798350364538

In this study, two deep learning models for automatic tattoo detection were analyzed;a modified Convolutional Neural Network (CNN) and pre-trained ResNet-50 model. In order to achieve this, ResNet-50 uses transfer learning with fine-tuning. The purpose of this study was to evaluate the accuracy, precision, recall, F1-score, and computational efficiency of the system being considered. To augment the dataset included 1000 photos that were equally divided between those showing tattoos and those that did not show tattoos. A k-fold cross-validation approach was employed in training and testing the models. Although custom CNNs are effective, utilizing pre-trained ones like ResNet-50 can offer even better outcomes. Specifically, ResNet-50 attained a higher accuracy (0.86 compared to 0.79), precision (0.85 versus 0.78), recall (0.91 against 0.86), and F1-score (0.91 vis-a-vis 0.86) as compared to custom CNNs. In selecting these models for examination, two main motivations were considered. The first motivation is to see whether transfer learning with a pre-trained ResNet-50 model does well when compared with a customized CNN designed specifically for tattoo detection. Secondly,the intent of this study is to know what advantages can be derived from each approach and their demerits too. Furthermore, it seeks to determine if transfer learning can provide an alternative in contrast to the common CNN techniques with regards to precision and computational efficiency. In this research, two models will be evaluated in order to answer the question of what is better for tattoo detection: transfer learning or designing custom architectures. © 2024 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Overview of Versatile Video Coding (H.266/VVC) and Its Coding Performance Analysis

引用

IEIE Transactions on Smart Processing and Computing 2023年第2期12卷 122-154页

作者： Lee, Minhun Song, HyeonJu Park, Jeeyoon Jeon, Byeungwoo Kang, Jungwon Kim, Jae-Gon Lee, Yung-Lyul Kang, Je-Won Sim, Donggyu Department of Computer Engineering Kwangwoon University Seoul Korea Republic of Department of Computer Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Kyunggi-do Korea Republic of Communication and Media Research Laboratory Electronics and Telecommunications Research Institute Deajeon Korea Republic of School of Electronics and Information Engineering Korea Aerospace University Kyunggi-do Korea Republic of Department of Electronic and Electrical Engineering Graduate Program in Smart Factory Ewha Womans University Seoul Korea Republic of

Versatile Video Coding (H.266/VVC) is the newest video coding standard jointly developed by the Joint Video Experts Team (JVET), which is organized by the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). H.266/VVC provides about 40% bitrate reduction compared with High Efficiency Video Coding (H.265/HEVC) for the same visual quality. This paper introduces in detail the core structure of H.266/VVC by highlighting its features within block partitioning structure, intra/inter prediction, transform, quantization, and in-loop filtering, compared to its predecessor (H.265/HEVC). H.266/VVC yields significantly improved the coding performance, but it increased the computational complexity, particularly for the encoder side, which remains a problem to be tackled for successful commercialization in the future. This paper examined the statistical performance of H.266/VVC coding tools from the bitstreams encoded by the VVC test model (VTM12.0) encoder through rate-distortion optimization under the JVET common test conditions. In addition, the complexity and performance analyses are conducted on the block partitioning structure and group of picture structure. It is expected that an optimized H.266/VVC encoder can be designed and developed by minimizing the coding loss based on the analysis data. © 2023 Institute of Electronics and Information Engineers. All rights reserved.

关键词： Image compression

来源：评论

学校读者我要写书评

暂无评论

A Multifunctional Hydrogel with Multimodal Self-Powered Sensing Capability and Stable Direct Current Output for Outdoor Plant Monitoring Systems

引用

Nano-Micro Letters 2025年第4期17卷 1-24页

作者： Xinge Guo Luwei Wang Zhenyang Jin Chengkuo Lee Department of Electrical&Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117576Singapore Center for Intelligent Sensors and MEMS(CISM) National University of Singapore5 Engineering Drive 1Singapore 117608Singapore NUS Graduate School-Integrative Sciences and Engineering Program(ISEP) National University of SingaporeSingapore 119077Singapore Research Center for Sustainable Urban Farming(SUrF) National University of SingaporeSingapore 117558Singapore

Smart farming with outdoor monitoring systems is critical to address food shortages and sustainability *** systems facilitate informed decisions that enhance efficiency in broader environmental *** outdoor systems equipped with energy harvesters and self-powered sensors often struggle with fluctuating energy sources,low durability under harsh conditions,non-transparent or non-biocompatible materials,and complex ***,a multifunctional hydrogel is developed,which can fulfill all the above requirements and build selfsustainable outdoor monitoring systems solely by *** can serve as a stable energy harvester that continuously generates direct current output with an average power density of 1.9 W m^(-3)for nearly 60 days of operation in normal environments(24℃,60%RH),with an energy density of around 1.36×10^(7)J m^(-3).It also shows good self-recoverability in severe environments(45℃,30%RH)in nearly 40 days of continuous ***,this hydrogel enables noninvasive and self-powered monitoring of leaf relative water content,providing critical data on evaluating plant health,previously obtainable only through invasive or high-power consumption *** potential extends to acting as other self-powered environmental *** multifunctional hydrogel enables self-sustainable outdoor systems with scalable and low-cost production,paving the way for future agriculture.

关键词： Self-powered sensor Hydrogel Energy harvester Outdoor farming Self-sustainable IoT

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Analysis and Remediation of Insecure Direct Object References (IDOR) Vulnerabilities in Android APIs 1

Comprehensive Analysis and Remediation of Insecure Direct Ob...

引用

1st IEEE International Conference on Cryptography, Informatics, and Cybersecurity, ICoCICs 2023

作者： Yulianto, Semi Abdullah, Roni Reza Soewito, Benfano Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia National Institute of Science and Technology Faculty of Informatics Engineering Jakarta12630 Indonesia Bina Nusantara University Binus Graduate Program. Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339437

The escalating visibility of secure direct object reference (IDOR) vulnerabilities in API security, as indicated in the compilation of OWASP Top 10 API Security Risks, highlights a noteworthy peril to sensitive data. This study explores IDOR vulnerabilities found within Android APIs, intending to clarify their inception while evaluating their implications for application security. This study combined the qualitative and quantitative approaches. Insights were obtained from an actual penetration test on an Android app into the primary reasons for IDOR vulnerabilities, underscoring insufficient input validation and weak authorization methods. We stress the frequent occurrence of IDOR vulnerabilities in the OWASP Top 10 API vulnerability list, highlighting the necessity to prioritize them in security evaluations. There are mitigation recommendations available for developers, which recognize its limitations involving a possibly small and homogeneous selection of tested Android applications, the testing environment that could cause some inaccuracies, and the impact of time constraints. Additionally, the study noted insufficient threat modeling and root cause analysis, affecting its generalizability and real-world relevance. However, comprehending and controlling IDOR dangers can enhance Android API security, protect user data, and bolster application resilience. © 2023 IEEE.

关键词： Sensitive data

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：