检索结果-内蒙古大学图书馆

14th International Conference on Education Technology and computers, ICETC 2022

作者： Souza, Adriana Freitas, Diamantino Bahia Federal Institute of Education Science and Technology Porto Seguro Bahia Brazil Doctoral Program in Digital Media Faculty of Engineering Faculty of Engineering of University of Porto Porto Portugal Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Porto Portugal

ISBN: (纸本)9781450397766

Voice synthesizers still present several challenges in the speech of mathematical content, as spoken mathematics has quite peculiar rules. In the synthesized speech, pauses help blind and visually impaired students identify the limits of mathematical operators and subexpressions. However, most studies on pauses define them uniformly or use simple punctuation marks to force the synthesizer to introduce pauses in certain parts of the expression. Speech is a dynamic process and pauses in expressions also need to be dynamic to make the synthetic speech of expressions more natural, as this can help in memorizing this type of content. This work proposed a dynamic model of pauses for mathematical expressions. Collected math expressions spoken by teachers were used to create the model. These expressions were useful for identifying patterns and creating a linear regression model. Blind and visually impaired students evaluated the model. Some improvements were observed when we compared the synthesized mathematical expressions with the model and Audiomath, the parameter tool used in this study. © 2022 ACM.

关键词： Dynamic models

来源：评论

学校读者我要写书评

暂无评论

Development of mechanisms for MAC channel selection to improve the performance of IEEE 802.15.4 beacon-enabled network

Development of mechanisms for MAC channel selection to impro...

引用

2010 3rd IEEE International Conference on Broadband Network and Multimedia Technology, IC-BNMT2010

作者： Hsiang, Chang Chen, Ai-Wei Chang, Chin-Jui Shih, Bih-Yaw Chen, Chen-Yuan Department of Computer Science National Pingtung University of Education Pingtung Taiwan Department of Information Management Transworld University No. 1221 Jen-Nang Road Chia-Tong Li Douliou Yunlin 64063 Taiwan Doctoral Program in Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan

ISBN: (纸本)9781424467709

An improved mechanism called Scan First 3 Channels (SF3C) is developed to reduce the communicating frequency among devices and PAN Coordinator. The throughput and energy consumption are major performance indexes for it. Meanwhile, the beacon-enabled mode for broadcast transmissions in WPAN has higher flexibility than the non-beacon -enabled mode. In the research, a new analytic mode of the IEEE 802.15.4 beacon-enabled mode is developed to improve throughput. Furthermore, the MAC performance in the simple star topology is evaluated. © 2010 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Support Vector Machine and Neural Network Algorithm Approach to Classifying Facial Expression Recognition

Support Vector Machine and Neural Network Algorithm Approach...

引用

International Conference on Informatics and Computing (ICIC)

作者： Muhamad Fatchan Mauridhi Hery Purnomo Affandy Ahmad Zainul Fanani Linda Marlinda Doctoral Program of Computer Science Universitas Dian Nuswantoro Semarang Indonesia Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9781728180472

ISBN: (纸本)9781728180489

One of the obstacles to detecting facial emotions is the lack of analysis in the process of emotional expression on human faces based on a photo camera. Identifying features and implementing different feature combinations can improve accuracy, in most cases. Trial detection through the use of feature vectors with higher dimensions that contain facial emotions can provide a lot of information on the accuracy of the data. The purpose of this study is to determine the highest accuracy results from the comparison of Support Vector Machine and Neural Network Algorithms. It can be seen that the Support Vector Machine has the highest accuracy value, which is 87%, while the Neural Network algorithm only has an accuracy of 85%. The results of the ROC Curve show that the Support Vector Machine achieves the best AUC value, namely 0.97. Comparison between Neural Network algorithm and Support Vector Machine for prediction of emotions using data types with many variations of emotions including anger, sadness, happy and surprise. The Support Vector Machine method is an accurate algorithm and this method is also very dominant over other methods. Based on the Accuracy, AUC, and T-test method, this method falls into the best classification.

关键词： Support vector machines Face recognition Neural networks Support vector machine classification Prediction algorithms Classification algorithms Informatics

来源：评论

学校读者我要写书评

暂无评论

Reversible JPEG Data Hiding Based on EMD

引用

通讯和计算机（中英文版） 2012年第10期9卷 1135-1141页

作者： Wen-Chung Kuo Shao-Hung Kuo Department of Computer Science and Information Engineering National Yunlin University of Science & Technology Yunlin 672 Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Yunlin 640 Taiwan

来源：评论

学校读者我要写书评

暂无评论

Intrusion Detection using Deep Neural Network Algorithm on the Internet of Things 11

Intrusion Detection using Deep Neural Network Algorithm on t...

引用

11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022

作者： Ikhwan, Syariful Wibowo, Adi Warsito, Budi School of Postgraduate Studies Diponegoro University Doctoral Program of Information System Semarang Indonesia Institut Teknologi Telkom Purwokerto D3 Telecommunication Engineering Banyumas Indonesia Diponegoro University Computer Science Informatics Department of Science and Mathematics Faculty Semarang Indonesia Diponegoro University Statistics Department of Science and Mathematics Faculty Semarang Indonesia

ISBN: (纸本)9781665460309

The increasing use of IoT devices on future networks is very helpful for humans in their lives. However, the increase in devices connected to IoT networks also increases the potential for attacks against those networks. Vulnerabilities in Internet of Things (IoT) networks can be exposed at any time. Artificial intelligence can be used to protect the IoT network by being able to detect attacks on the network so that they can be prevented. In this study, network detection was carried out using the Deep Neural Network (DNN) algorithm. The test was carried out using the UNSW Bot-IoT dataset with a comparison of training data of 75% of the overall data. The results obtained show the ability of the algorithm to detect attacks on average with 99.999% accuracy. The validation loss and training loss look very small. In this study, there is a validation loss that still occurs in overfitting, but the difference is very small. © 2022 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

AI-Driven Market Demand Prediction: An Artificial Neural Network Model for Horticultural Commodities

AI-Driven Market Demand Prediction: An Artificial Neural Net...

引用

International Conference on Information Technology (INCIT)

作者： Petrus Wolo Aina Musdholifah Sri Mulyana Doctoral Program in Computer Science Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Gadjah Mada University Yogyakarta Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Gadjah Mada University Yogyakarta Indonesia

ISBN: (数字)9798350366303

ISBN: (纸本)9798350366310

The annual increase in population drives a corresponding rise in demand for goods and services, which in turn directly impacts agricultural needs at both regional and national levels. In Sikka Regency, the demand for horticultural commodities has grown alongside population expansion and increasing prosperity. However, the lack of proper planting distance management has disrupted efficient distribution, leading to logistical inefficiencies. As a result, it is crucial to develop an optimal market demand plan for horticultural commodities to prevent surplus accumulation. To address this challenge, this study proposes a predictive model for monthly market demand in 2024, focusing on 12 types of horticultural commodities in Sikka Regency. Food consumption time series data from 2019 to 2023 are used in the model. A back-propagation algorithm is utilized by an Artificial Neural Network (ANN) to make this prediction. With a Mean Absolute Error (MAE) of 0.166 and a Root Mean Square Error (RMSE) of 0.201, the model's performance evaluation showed an average training accuracy. The average testing accuracy, on the other hand, had an MAE of 0.303 and an RMSE of 0.338. These experimental results show that the suggested strategy might be a useful tool for horticulture commodities market participants and provide insightful information about market dynamics.

关键词： Training Performance evaluation Accuracy Time series analysis Weather forecasting Artificial neural networks Predictive models Prediction algorithms Root mean square Testing

来源：评论

学校读者我要写书评

暂无评论

A soft set approach for fast clustering attribute selection

A soft set approach for fast clustering attribute selection

引用

International Conference on Informatics and Computing (ICIC)

作者： Dedy Hartama Iwan Tri Riyadi Yanto Muhammad Zarlis USU Computer Science Doctoral Program Medan Universitas Ahmad Dahlan Yogyakarta Daerah Istimewa Yogyakart ID Department of Computer Science Universitas Sumatera Utara Medan Indonesia

ISBN: (纸本)9781509016495

Attribute-based data clustering has been proven as one of the efficient methods in data clustering. Set theory approaches for data clustering exist to handle attribute-based data clustering. The MDDS, a soft set based technique has proven its applicability in data clustering. However, in reviewing MDDS, where its calculations are based on comparing all constructed multi-soft sets, it still suffers from high computational time. This research presents a modification of the MDDS by generating an alternative technique to reduce its computational complexity. To provide alternative solutions from MDDS algorithm, we derive a new algorithm that can lesser response time. It is using theory of soft set by selecting and excluding the set having no effect domination on other sets. The experiments are implemented in MATLAB software thought to UCI benchmark datasets. The computation experiment illustrate that the time response can be speed up to 67.56 % by proposed algorithm compared with MDDS.

关键词： MATLAB Automobiles Algorithm design and analysis Knowledge based systems Genetics Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Systematic Literature Review of Text Feature Extraction

Systematic Literature Review of Text Feature Extraction

引用

International Conference on Informatics and Computing (ICIC)

作者： Agus Mulyanto Sri Hartati Retantyo Wardoyo Doctoral Program in Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (纸本)9798350345728

Text data has essential information in it depending on a party who can process the data. Text feature extraction techniques have opened various ways to carry out the analysis process from structured to unstructured data. Based on the development of text extraction, which is widely used today. This Systematic Literature Review (SLR) paper analyzes the methods widely used in current text extraction research studies. Writing this SLR implements the PICOC method. Trends in previous studies regarding text extraction have been analyzed in this study. The total publications used are 23 articles that have been carefully observed in a systematic literature review to answer the research questions that have been formulated.

关键词： Systematics Bibliographies Feature extraction Market research Informatics

来源：评论

学校读者我要写书评

暂无评论

Authenticated secret sharing scheme based on GMEMD

Lecture Notes in Computer Science (including subseries Lectu...

引用

Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9569卷 395-405页

作者： Kuo, Wen-Chung Kuo, Shao-Hung Chang, Hong-Yi Wuu, Lih-Chyau Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Douliu Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Douliu Taiwan

ISBN: (纸本)9783319319599

In secret image sharing schemes, all legal participants provide legitimate shared images and then they can extract the correct secret message. Recently, Wu et al. proposed a high quality data hiding secret sharing scheme with authentication ability. The major contribution of this scheme maintains good stego image quality while being able to verify secret message integrity. However, to ensure the process can work, the secret image’s pixel values larger than 250 must be changed to 250 for Wu’s scheme. Otherwise, extracting the secret image may fail. In other words, for a secret image, a few errors do not make the big difference but it could be distorted severely for some sensitive secrets. In order to improve this shortcoming, a secret image sharing scheme based on General Multi-Exploiting Modification Direction (GMEMD) data hiding technology will be proposed in this paper. According to simulation results and analysis, we can show that the stego image quality in Wu et al.’s scheme or our proposed scheme is larger than 43dB. We also demonstrate the authentication capability to find unauthorized participants. Furthermore, if all participants are legitimate, then the proposed scheme can extract the secret completely without any distortion. © Springer International Publishing Switzerland 2016.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Comparison of Hybrid Intrusion Detection System

Comparison of Hybrid Intrusion Detection System

引用

International Conference on Information Technology and Electrical Engineering (ICITEE)

作者： Aditya Nur Cahyo Anny Kartika Sari Mardhani Riasetiawan Doctoral Program of Computer Science FMIPA Universitas Gadjah Mada Yogyakarta Indonesia FMIPA Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9781728110974

ISBN: (纸本)9781728110981

IDS have an important role in dispelling and preventing an intrusion or abuse of access rights. In its development, research on IDS is growing. IDS consist of several detection models, one of which is hybrid-based, which in IDS detection combines the signature and anomaly models. This method is considered more effective because it combines the advantages of the speed of signature detection and the ability to analyze new attacks from the anomaly model. However, from existing models and frameworks hybrid-based IDS still needs to be further developed to be implemented in the industry. From a number of existing IDS-based studies, this paper intends to conduct a review with the aim that researchers who wish to develop hybrid-based IDS know which methods and architecture are best to be implemented. This paper reviews hybrid IDS research in the last five years.

关键词： Testing Security Intrusion detection computer crime Companies Handwriting recognition Feature extraction

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：