Proceedings of the 4th International Conference on Information Technology and Computer Communications最新文献_第2页

Memory Usage Comparison in an Android Application: Basic Object-Oriented Programming vs Decorator Design Pattern: Coding styles for keeping low memory usage in a mobile application. Android应用程序中的内存使用比较:基本面向对象编程与装饰设计模式:在移动应用程序中保持低内存使用的编码风格。

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548655

Wasana Ngaogate

{"title":"Memory Usage Comparison in an Android Application: Basic Object-Oriented Programming vs Decorator Design Pattern: Coding styles for keeping low memory usage in a mobile application.","authors":"Wasana Ngaogate","doi":"10.1145/3548636.3548655","DOIUrl":"https://doi.org/10.1145/3548636.3548655","url":null,"abstract":"This paper explores how an Android application consumes memory when it is developed by two approaches: basic object-oriented programming versus decorator design pattern. Somehow programmers develop applications based on their coding experience without concern of memory usage especially in mobile applications which memory consumption is a critical issue. The deployed Android application of a list of temples which join a Candle Festival is selected as a case study. New functions are assumingly required by users so that the application could provide more services. Two class diagrams are designed based on basic object-oriented programming and based on decorator design pattern before implementation of the two approaches. The problem is what is the better approach for handling an increasing number of services after the application has been deployed. So that the application still consumes less memory as possible. The case-study applications retrieve information from a free REST API. Memory usage is measured by using an emulator and a physical device. The result shows that an Android application which developed by using decorator design pattern consumes more memory although its codes are cleaner and easier to read. Therefore, when a developer applies decorator design pattern, they should pay more attention on unexpected effect of the design pattern. Research in impact of design patterns should also be investigated more.","PeriodicalId":384376,"journal":{"name":"Proceedings of the 4th International Conference on Information Technology and Computer Communications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121744720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two-path Android Malware Detection Based on N-gram Feature Weighting 基于N-gram特征加权的双路径Android恶意软件检测

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548651

Min Sun, Danni Zhang

引用次数: 0

Hybrid approach for text similarity detection in Vietnamese based on Sentence-BERT and WordNet 基于Sentence-BERT和WordNet的越南语文本相似度检测混合方法

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548645

Son Cao, Huy V. Vo, Hang Le, D. Dinh

引用次数: 0

An Attack Impact and Host Importance based Approach to Intrusion Response Action Selection 基于攻击影响和主机重要性的入侵响应动作选择方法

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548649

Tazar Hussain, Chris D. Nugent, Jun Liu, Alfie Beard, Liming Chen, A. Moore

{"title":"An Attack Impact and Host Importance based Approach to Intrusion Response Action Selection","authors":"Tazar Hussain, Chris D. Nugent, Jun Liu, Alfie Beard, Liming Chen, A. Moore","doi":"10.1145/3548636.3548649","DOIUrl":"https://doi.org/10.1145/3548636.3548649","url":null,"abstract":"Selecting appropriate actions is crucial for building effective Intrusion Response Systems (IRS) that can counter intrusions according to their priority level. Currently, the priority level of intrusions is determined manually, in a static manner, which is time consuming, ineffective and cannot scale with the growing number of attacks. In this paper we present an effective event prioritization methodology by encoding domain knowledge, namely attack impact and host importance, into features in terms of the confidentiality, integrity and availability (CIA). The proposed approach is demonstrated using a testbed architecture where a total of six features are generated from the domain knowledge and are labeled with appropriate response options. One set of features encodes attack impact in terms of its potential damage and its ability to propagate and another set of features encodes host importance in terms of data sensitivity, service criticality, number of connections and vulnerabilities on the basis of the CIA factors. The case study results indicate that the generated features help security analysts to select appropriate response options according to the priority level of events. Additionally, as a result of the methodology a labelled Intrusion Response (IR) dataset is generated. In future work we aim to use machine learning to analyze this dataset to infer actions automatically.","PeriodicalId":384376,"journal":{"name":"Proceedings of the 4th International Conference on Information Technology and Computer Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127797708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart Conveyor Belt Sushi Bill Payment with a Mobile Shot 智能传送带寿司账单支付与移动拍摄

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548637

Rangrak Maitriboriruks, Patchariya Piya-Aromrat, Y. Limpiyakorn

{"title":"Smart Conveyor Belt Sushi Bill Payment with a Mobile Shot","authors":"Rangrak Maitriboriruks, Patchariya Piya-Aromrat, Y. Limpiyakorn","doi":"10.1145/3548636.3548637","DOIUrl":"https://doi.org/10.1145/3548636.3548637","url":null,"abstract":"Organization must automate wherever and whenever they can, particularly during today's global changes in daily lifestyles. Trends regarding the use of technology, especially AI has emerged as a key enabler for disruptive innovation. This paper thus presents the application programming interface of object detector implemented with YOLOv4 and OpenCV for classifying the prices of sushi plates distinguished by colors. The object detector is part of the smart cross-platform mobile application to facilitate billing process for conveyor belt sushi business. The frontend is developed with Flutter to build single codebase for UIs. To handle the variants of image colors resulting from the use of different mobile cameras, color transfer is used for transferring the image dataset colors to images captured by users. Microservices architecture is adopted for the backend. Orchestration of YOLOv4, OpenCV and Spring Boot REST API will create APIs to calculate food cost, generate QR code for bill payment, and maintain customer membership benefits. The constructed object detection model achieved the precision of 97%, recall of 97%, F1-score of 97% and mAP of 97.3%. The smart billing system presented in this work would accelerate the workflow, increase productivity, reduce waste and drive moving for contactless society.","PeriodicalId":384376,"journal":{"name":"Proceedings of the 4th International Conference on Information Technology and Computer Communications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130483140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Combining Latent Semantic Analysis and Pre-trained Model for Vietnamese Text Readability Assessment: Combining Statistical Semantic Embeddings and Pre-trained Model for Vietnamese Long-Sequence Readability Assessment 结合潜在语义分析和预训练模型的越南文文本可读性评估:结合统计语义嵌入和预训练模型的越南文长序列可读性评估

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548643

Nam T. Doan, Thi-Anh-Thi Le, An-Vinh Lương, Dinh Dien

{"title":"Combining Latent Semantic Analysis and Pre-trained Model for Vietnamese Text Readability Assessment: Combining Statistical Semantic Embeddings and Pre-trained Model for Vietnamese Long-Sequence Readability Assessment","authors":"Nam T. Doan, Thi-Anh-Thi Le, An-Vinh Lương, Dinh Dien","doi":"10.1145/3548636.3548643","DOIUrl":"https://doi.org/10.1145/3548636.3548643","url":null,"abstract":"Together with the rapid development of text processing, readability assessment is an important and challenging task of measuring how easy or difficult it is to read a text. Despite the foundation and enhancement of this task in high-resource languages such as English where there are a ton of NLP tools and corpus, this task is not an advantage for low-resource languages, especially Vietnamese. Most previous studies for Vietnamese text readability assessment focus on shallow text characteristics, which have yet to address deeper readability features. In our study, we propose a novel finding in Vietnamese to create the construction of features reflecting in terms of semantics. In view of this, we notice that the difficulty level of terms affects the difficulty level of knowledge that strongly involves text comprehension. Particularly, our approach based on the difficulty distribution of terms in a text generated by Latent Semantic Analysis (LSA) technique decreases the dependence of experts in annotating and discovering the typical feature in a narrow domain. Our proposed feature is efficient to be considered as a new and automatic feature for Vietnamese text readability assessment. Furthermore, LSA is a statistical approach that is more stable and feasible for low-resource languages. In addition, we also integrate PhoBERT, a pre-trained language model for Vietnamese, to generate the bidirectional contextual representation of a word for Vietnamese long-sequence as a semantic feature. Through the experiments in Vietnamese readability dataset, our proposed approach achieves promising performance against the strong competitive baselines. The best performance with up to an accuracy of 94.52% and a weighted F1 score of 94.09%.","PeriodicalId":384376,"journal":{"name":"Proceedings of the 4th International Conference on Information Technology and Computer Communications","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126886989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Stock price prediction under multi-frequency model - based on attention state-frequency memory network 基于注意状态-频率记忆网络的多频模型下股价预测

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548654

Wei Zhou, Yuting Pan, Zhaoxia Wu

{"title":"Stock price prediction under multi-frequency model - based on attention state-frequency memory network","authors":"Wei Zhou, Yuting Pan, Zhaoxia Wu","doi":"10.1145/3548636.3548654","DOIUrl":"https://doi.org/10.1145/3548636.3548654","url":null,"abstract":"Stock price forecasting is the most typical forecasting task in financial time series. However, stock prices are influenced by a variety of factors, with short-term and long-term trading activity being among the most important factors affecting price changes. The trading activity in these different frequency patterns is eventually reflected in the stock price data. Therefore, if the model identifies information about the potential multiple frequencies of the time series data in the process of prediction, it can enable the model to better learn the features of the time series data. In addition, stock price data are non-linear and non-stationary in nature, which makes it a challenging task to predict future trends. We used the attention state-frequency memory neural network (A-SFM) to accomplish the above objectives. The A-SFM realizes the decomposition of frequency by Fourier transform, and learns the state and frequency information by the powerful learning ability of neural network. In addition, we add an attention mechanism to the structure of the model to extract and learn the important parts of the price information. In this paper, we use the A-SFM model to capture the state and frequency information inherent in the series from past financial market data and use this information to make short- and long-term forecasts.","PeriodicalId":384376,"journal":{"name":"Proceedings of the 4th International Conference on Information Technology and Computer Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130113653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Simple and Efficient Object-Capability Revocation Method 一种简单有效的对象能力撤销方法

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548656

Liang-Jui Shen, Yusong Tan, Pan Dong, Jun Ma, Xiaoling Li

引用次数: 0

Multi-label Learning with User Credit Data in China Based on MLKNN 基于MLKNN的中国用户信用数据多标签学习

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548652

Zhu-Jin Zhang, Lu Han, Muzi Chen

引用次数: 0

Quality Changes of Image from Total Variation to Nonlinear Sparsifying Transform for Sparse-view CT Reconstruction 稀疏视图CT重建中图像质量从全变分到非线性稀疏化变换的变化

Proceedings of the 4th International Conference on Information Technology and Computer Communications Pub Date : 2022-06-23 DOI: 10.1145/3548636.3548641

Jian Dong, Siyuan Zhang, Lin He

{"title":"Quality Changes of Image from Total Variation to Nonlinear Sparsifying Transform for Sparse-view CT Reconstruction","authors":"Jian Dong, Siyuan Zhang, Lin He","doi":"10.1145/3548636.3548641","DOIUrl":"https://doi.org/10.1145/3548636.3548641","url":null,"abstract":"Sparse-view CT has been widely studied as an effective strategy for reducing radiation dose to patients. Total variation (TV) minimization, which is most extensively studied among the existing compressed sensing (CS) techniques, has been recognized as a powerful tool for dealing with the inverse problem of sparse-view image reconstruction. However, in recent years, the drawbacks of TV are being increasingly reported, such as appearance of patchy artifacts, depict of incorrect object boundaries, and loss in image textures. In order to address these drawbacks, a series of advanced algorithms using nonlinear sparsifying transform (NLST) have been proposed very recently. The NLST-based CS is based on a different framework from the TV, and it achieves an improvement in image quality. Since it is a relatively newly proposed idea, within the scope of our knowledge, there exist few literatures that discusses comprehensively how the image quality improvement occurs in comparison with the conventional TV method. In this study, we investigated the image quality differences between the conventional TV minimization and the NLST-based CS, as well as image quality differences among different kinds of NLST-based CS algorithms in the sparse-view CT image reconstruction. More specifically, image reconstructions of actual CT images of different body parts were carried out to demonstrate the image quality differences. Through comparative experiments, we conclude that the NLST-based CS method is superior to the TV method in the task of image reconstruction for sparse-view CT.","PeriodicalId":384376,"journal":{"name":"Proceedings of the 4th International Conference on Information Technology and Computer Communications","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122855055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0