检索结果-内蒙古大学图书馆

Annual Conference of Industrial Electronics Society

作者： André L. de S. Paula Eduardo K. Viegas Altair O. Santin Graduate Program in Computer Science Pontifical Catholic University of Parana Brazil

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Access point (AP) security has become increasingly important as wireless local area networks (WLANs) proliferate in industrial environments. Rogue APs are often used by attackers to conduct man-in-the-middle (MiTM) attacks. They can redirect users to malicious servers or do eavesdropping and manipulation of their *** this paper, we propose a novel one-class machine learning model to passively identify rogue APs in industrial environments. The implementation of the model is twofold. First, we passively extract the hardware and software characteristics of the evaluated AP according to its generated messages. This results in a comprehensive feature set that captures both low-level and high-level behaviors of the evaluated ***, we apply a one-class machine learning model to identify APs that significantly deviate from the previously known profile of legitimate APs. The combined evaluation of hardware and software behaviors integrated with an outlier detection scheme to effectively identify rogue APs is the insight of our proposal. We demonstrate the feasibility of our model, achieving an F1 score of 0.89 and a true positive rate of 0.9 in experiments conducted on our new publicly available dataset of 357 unique AP behaviors.

关键词： Wireless LAN Machine learning Network security Feature extraction Software Hardware Robustness Software reliability Servers Proposals

来源：评论

学校读者我要写书评

暂无评论

Towards a Feasible Palm Vein Verification Scheme Using Deep Autoencoder and Siamese Networks

Towards a Feasible Palm Vein Verification Scheme Using Deep ...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Mateus Nunes Eduardo K. Viegas Altair O. Santin Graduate Program in Computer Science Pontifical Catholic University of Parana Brazil

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

Palm vein pattern recognition offers a unique personal identification feature. Unfortunately, these techniques typically require a Near Infrared (NIR) camera sensor to extract the individual's venous pattern, challenging their wide deployment. This paper proposes a new feasible palm vein verification scheme using a Deep Autoencoder and a Siamese Network, implemented threefold. First, we capture the individual's palm using a traditional visible spectrum camera sensor and perform preprocessing tasks to correct imprecise positioning, easing palm support accessories requirements. Second, we eliminate NIR sensor requirement by fine-tuning a Deep Autoencoder model to convert images from the visible spectrum to their infrared counterparts. Third, generated images are processed by a lightweight Siamese network using a contrastive loss function for individual verification. Experiments conducted on a publicly available dataset with over a hundred individuals confirmed the feasibility of our proposal. Our scheme reaches up to 0.97 of true-negative rate, with only 0.01 decrease compared to traditional NIR-based approaches. In addition, individual identification can be conducted in less than 6 seconds in a resource-constrained environment thanks to our lightweight model's implementation.

关键词： Training Performance evaluation Image synthesis Databases Autoencoders Machine learning Cameras Feature extraction Pattern recognition Proposals

来源：评论

学校读者我要写书评

暂无评论

The Deep Learning Approach For American Sign Language Detection

The Deep Learning Approach For American Sign Language Detect...

引用

2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Pangestu, Gusti Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University School of Computer Science Computer Science Department Binus Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

Sign language has importance rule to deal with communication process especially with impairments hearing people. Sign language detection also attract lot of researchers to join the challenge of research to detect and recognize the sign language in the field of computer science. Hence, there is still no any standard approach and method to recognize the meaning in every pose of sign language. This research proposed a mechanism to detect Alphabet American Sign Language by utilizing Convolutional Neural Network (CNN) process. The CNN approach was chosen based on the ability and capability to recognize image. In this research, MNIST dataset is used for traning and testing process. The proposed CNN architecture produced 97% of accuracy that outperform the previous research using the same dataset which made this architecture promising. © 2022 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Serverless utilization in microservice e-learning platform

引用

Procedia computer science 2023年 216卷 204-212页

作者： Bryan Andreas Nday Gede Putra Kusuma Renaldy Fredyan Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Since cloud computing becoming the trend, the way servers being implemented slowly moves to the cloud. Companies did not need to buy a physical server machine to deploy an app. Having a private server on cloud infrastructure indeed already reduce some cost for on-premise server maintenance. However, there is still a cost for usage when the server is inactive or having low to no traffic at all. Serverless deployment offer function as a service where application is deployed as a function and cost is billed per function call. This paper proposed a solution where there are two deployment that works in turn between infrastructure as a service and function as a service deployment. This dual deployment offered the system to use the virtual private server or deployed instance on active hours, and switch to serverless functions on inactive hours. Switching to serverless on low traffic hours will cut the usage and cost of the microservice app by the least 25%, while having performance slightly comparable to microservice app deployed to instances.

关键词： Cloud Computing E-Learning Function as a Service Hybrid Deployment REST API

来源：评论

学校读者我要写书评

暂无评论

A Multi-View Android Malware Detection Model Through Multi-Objective Optimization

A Multi-View Android Malware Detection Model Through Multi-O...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Philipe Fransozi Jhonatan Geremias Eduardo K. Viegas Graduate Program in Computer Science Pontifical Catholic University of Parana Brazil

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

Over the past few years, several highly accurate Machine Learning (ML) techniques have been proposed for Android malware detection. Unfortunately, proposed schemes are rarely used in production, a situation usually caused by their limited generalization capabilities, leading to low accuracies when deployed. This paper proposes a new multi-view Android malware detection model, implemented in two stages. First, we extract multiple feature sets from an analyzed Android application package. The feature sets provide a complementary Android app behavioral vector for the classification task, enhancing the system's generalization. Secondly, we conduct a multi-objective optimization to select the optimal feature subset from each view for subsequent ensemble-based classification. Our proposal's insight is to proactively select each feature subset that simultaneously improves accuracy and reduces processing requirements in a multi-view setting. Experiments on our new dataset, comprising over 40 thousand Android app samples, demonstrated the feasibility of our proposal. Our scheme can improve true-positive rates by an average of 4.4 while demanding only up to 65% of inference processing costs.

关键词： Accuracy Costs Computational modeling Production Machine learning Feature extraction Malware Vectors Proposals Optimization

来源：评论

学校读者我要写书评

暂无评论

Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

引用

2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Yanfi, Yanfi Heryadi, Yaya Lukas, Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University Binus Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy. © 2022 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Intelligence Tutorial System for Learning Cultures and Local Languages in Indonesia 2

Intelligence Tutorial System for Learning Cultures and Local...

引用

2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Veron, Juan Sebastian Tantry, Calvin Fladico, Naxwell Warnars, Harco Leslie Hendric Spits Bina Nusantara University School of Computer Science Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665400527

Indonesia has so many local cultures and languages that spread from Sabang to Merauke, and most Indonesians do not know how to speak two or more regional languages in Indonesia. Most Indonesians only know familiar tribes that are only commonly heard. Because of this problem, governments in the Indonesian provinces have included lessons on Indonesian culture. The lesson will explain Indonesia's national and local culture for their area. In this way, the government can also help Indonesians learn more about their local language. This paper proposes a solution to create a learning portal website for users, both from Indonesia and other countries, to learn Indonesian culture and regional languages. In this way, the author hopes that users can learn about Indonesian local culture and language and contribute to preserving Indonesian local culture and language. This application was built on a web-based basis by applying the following HTML, CSS, and javascript using Personal Home Pages (PHP) for database connection using MySQL. The built application was designed using a use case diagram and class diagram to describe the database relations. © 2022 IEEE.

关键词： Websites

来源：评论

学校读者我要写书评

暂无评论

An Object-Driven Fuzzy Decision Model for Determining Fuel in Boiler Machines

An Object-Driven Fuzzy Decision Model for Determining Fuel i...

引用

Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Ditdit Nugeraha Utama Jeremia Widyanto Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

There are many alternative fuel types that can be used by a particular type of engine. Determining which fuel alternative is optimal for an engine presents its own challenges. This is especially true in an industrial setting, where certain standards are necessary to select the best fuel alternative to be used and operated. This study aims to develop a decision model for selecting a fuel type for boiler engines based on specific parameters or criteria. The decision model is designed using an object-oriented approach, utilizing three types of diagrams: object, activity, and sequence. An object-oriented model design approach allows for the decision model to be depicted transparently and very close to reality. Additionally, the analytical hierarchical process (AHP) and fuzzy logic are the core methods employed in constructing the decision model. Then, in developing this decision model, four main criteria or parameters are considered: cost, heating value, safety, and emissions. These four parameters were derived from a literature review and interviews with experts. Among the three evaluated fuel types (i.e., natural gas, industrial diesel oil or IDO, and coal), coal received the highest decision score of 0.78. Thus, based on this decision value―the outcome of the model's recommendation―it can be concluded that coal remains an objective choice as a fuel for use in boiler engines.

关键词： Fuzzy logic Object oriented modeling Oils Coal Analytic hierarchy process Boilers Safety Engines Standards Systematic literature review

来源：评论

学校读者我要写书评

暂无评论

News Classification Based On News Headline Using SVC Classifier 16

News Classification Based On News Headline Using SVC Classif...

引用

16th International Conference on Telecommunication Systems Services and Applications, TSSA 2022

作者： Leonard, Goldius Sisnadi, Fukriandy Wardhana, Nicholas Vigo Aziz Al-Ghofari, Muhammad Abdul Girsang, Abba Suganda School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Binus Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665455947

News gives new insight and information from all over the world. News has many categories, such as politic, economy, science, and other common news categories. Every news will have their own category based on its content. The classification of news is usually done manually by inputting the category during the news posting. Some of the categories may be inputted incorrectly. The news classifier can be the solution for problem, but the news classifications out there are usually based on the news content. The classifier will receive the word vector inputs that are taken from the news content and try to classify it into one of certain categories. Unfortunately, news contents can be longer and harder to be processed rather than processing the news headline. The news headline is shorter and packs a decent information for the classifier to find out what category it is. Besides the news headline usage, the classifier also needs to be chosen correctly. In this paper, the SVC model will be tested using the news headline data to classify the news and compare with several other models, such as Linear Regression, Multinomial Naive Bayes, Decision Tree, and Random Forest. The common variables to be compared are the accuracy, recall, and precision to evaluate the SVC model. © 2022 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

引用

IEEE Transactions on Services Computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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：