2022 14th International Conference on Knowledge and Smart Technology (KST)最新文献

SIREN! Detecting Burmese Hate Speech Comments on Social Media 警笛!在社交媒体上发现缅甸人的仇恨言论评论

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9729075

Khin Me Me Chit, Yi Yi Chan Myae Win Shein, Wai Yan, A. Khine

{"title":"SIREN! Detecting Burmese Hate Speech Comments on Social Media","authors":"Khin Me Me Chit, Yi Yi Chan Myae Win Shein, Wai Yan, A. Khine","doi":"10.1109/KST53302.2022.9729075","DOIUrl":"https://doi.org/10.1109/KST53302.2022.9729075","url":null,"abstract":"Hate Speech on Social Media is definitely an evolving threat for every nation, especially for countries like Myanmar. Lack of media and digital literacy is playing a huge role in making people insult to each other or misallocating their stresses to others without physical encounter. Moreover, disingenuous politicians fuel online hate speech campaigns backstage of the elections by targeting different religions in the regard of heretics and using racialism. To emphasize this matter, we scraped over 16,000 social media comments from the most popular social media platform in Myanmar and performed hate-speech research using those samples. With the precise definition of a hate speech labelling guideline, annotation on the sample dataset was done systematically and efficiently. Experiments and evaluations were conducted using different linear and non-linear deep-learning classification models. Performances of the models are at the peak in Logistic Regression among linear models with 0.8974 AUC score and XLM-RoBERTa among deep learning models with 0.8958 AUC score on the test dataset. We observed that it is more advantageous to use linear models on our dataset since they achieved comparable results to the deep learning models and have much lower computational cost.","PeriodicalId":433638,"journal":{"name":"2022 14th International Conference on Knowledge and Smart Technology (KST)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123120903","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

Neural Networks for Real-Time Digital Emulation of Guitar Speaker Cabinet Impulse Response 基于神经网络的吉他音箱箱体脉冲响应实时数字仿真

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9727233

Tantep Sinjanakhom, S. Chivapreecha

{"title":"Neural Networks for Real-Time Digital Emulation of Guitar Speaker Cabinet Impulse Response","authors":"Tantep Sinjanakhom, S. Chivapreecha","doi":"10.1109/KST53302.2022.9727233","DOIUrl":"https://doi.org/10.1109/KST53302.2022.9727233","url":null,"abstract":"This This paper presents a real-time signal processing system in which a neural network generates the impulse response (IR) of a Marshall 1960A guitar cabinet with 25W Celestion speakers based on user-specified parameters. The parameters include the microphone type, position of the speaker on which the microphone is mounted, distance between the microphone and the cabinet, and off-axis tilting angle. The trained model of neural network can generate the impulse response for a speaker cabinet, as well as the sound of settings not included in training set. Cross-correlation, error-to-signal ratio, power spectral density error, and magnitude-squared coherence were all utilized to assess the model's output. Mean Opinion Score listening tests were performed to determine the similarity of the convolved guitar signals. According to the results, the emulated cabinet sounds were perceived to be nearly identical to the original sounds. The performance of the real-time audio plugin implementation is proved to be computationally efficient. Because raw IR data for each microphone configuration does not need to be saved directly to the PC's memory, utilizing it in music production work can be more convenient, allowing the user to modify the parameters while hearing the differences without having to repeat the IR file loading procedure.","PeriodicalId":433638,"journal":{"name":"2022 14th International Conference on Knowledge and Smart Technology (KST)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126906713","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

Electronic Nose for Analysis of Coffee Beans Obtained from Different Altitudes and Origin 不同海拔和产地咖啡豆的电子鼻分析

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9729071

Wandee Aunsa-Ard, T. Kerdcharoen

{"title":"Electronic Nose for Analysis of Coffee Beans Obtained from Different Altitudes and Origin","authors":"Wandee Aunsa-Ard, T. Kerdcharoen","doi":"10.1109/KST53302.2022.9729071","DOIUrl":"https://doi.org/10.1109/KST53302.2022.9729071","url":null,"abstract":"The coffee industry is facing increasing challenges due to climate change, pests, diseases, which leads to the reduced production and negative impact on coffee qualities. Thus, quality assurance of coffee from production to roasting and brewing becomes more important, especially coffee flavor and aroma. This research aims to study the applicability of electronic nose (e-nose) and algorithm to detect coffee aroma obtained from different origins. The coffee beans used in this experiment were obtained from different areas in northern Thailand. These coffee beans have different growing conditions, altitude, processing and roasting condition. In this study, the three aspects of e-nose were investigated; (i) e-nose sensitivity to coffee odors, (ii) e-nose capability of correctly recognizing the detected odors and (iii) factors that influence coffee odors such as altitude, processing and roasting conditions. The e-nose system comprises of eight metal oxide semiconductor (MOX) gas sensors and in-house developed analysis software. Principal Component Analysis (PCA) is a classification algorithm for pattern recognition of different coffee aroma. Based on experimental results, the e-nose technology shows a capability to detect and distinguish the coffee odors caused by different altitude, processing and roasting process. E-nose is a suitable method for aroma detection in coffee industry to enhance the quality.","PeriodicalId":433638,"journal":{"name":"2022 14th International Conference on Knowledge and Smart Technology (KST)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122026471","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: 3

GSAP: A Hybrid GRU and Self-Attention Based Model for Dual Medical NLP Tasks GSAP:基于GRU和自注意的双重医学NLP任务混合模型

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9727234

Huey-Ing Liu, Meng-Wei Chen, Wei-Chun Kao, Yao-Wen Yeh, Cheng Yang

引用次数: 1

RaaS (Robot-as-a-Service) focusing on the human-robot collaboration in industrial sites RaaS (Robot-as-a-Service)专注于工业现场的人机协作

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9729068

Hahyeon Kim, Chen Li

{"title":"RaaS (Robot-as-a-Service) focusing on the human-robot collaboration in industrial sites","authors":"Hahyeon Kim, Chen Li","doi":"10.1109/KST53302.2022.9729068","DOIUrl":"https://doi.org/10.1109/KST53302.2022.9729068","url":null,"abstract":"In this paper, we present the concept of a robot service that interacts with a human operator through speech. Service-oriented architectures and cloud computing are now the dominant computer paradigms. Research on using robots as a service (Robot-as-a-Service. RaaS) is a new trend based on the integration of robots and embedded devices and web and cloud computing. However, while the demand for RaaS utilization within the industry is high, it has not successfully acquired many users. One of the reasons is that the accuracy of the robot's recognition-judgment-action process does not reach a level that users can trust, and the other reason is that it is challenging to learn how to control the robot. Therefore, this study focused on services that allow users to control robots easily within industrial sites. Speech recognition was implemented using RESTful API and Server-Client communication, and a mobile manipulator robot, what we call Little-Helper (LH), is used for implementation. According to the human operators, communicate with the robot by voice speech, increasing collaboration efficiency and productivity of the industry is expected.","PeriodicalId":433638,"journal":{"name":"2022 14th International Conference on Knowledge and Smart Technology (KST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134006789","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

Comparison of Prediction Models for Road Deaths On Road Network 路网道路死亡预测模型的比较

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9729086

Thaninthorn Whasphutthisit, Watchareewan Jitsakul

引用次数: 2

Unsupervised and Ensemble-based Anomaly Detection Method for Network Security 基于集成的无监督网络安全异常检测方法

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9729061

Donghun Yang, Myunggwon Hwang

引用次数: 5

Explainable Digital Currency Candlestick Pattern AI Learner 可解释的数字货币烛台模式人工智能学习者

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9727231

Jun-Hao Chen, Cheng-Han Wu, Yun-Cheng Tsai, Samuel Yen-Chi Chen

{"title":"Explainable Digital Currency Candlestick Pattern AI Learner","authors":"Jun-Hao Chen, Cheng-Han Wu, Yun-Cheng Tsai, Samuel Yen-Chi Chen","doi":"10.1109/KST53302.2022.9727231","DOIUrl":"https://doi.org/10.1109/KST53302.2022.9727231","url":null,"abstract":"More and more hedge funds have integrated AI techniques into the traditional trading strategy to speculate on Digital Currency. Among the conventional technical analysis, candlestick pattern recognition is a critical financial trading technique by visual judgment on graphical price movement. A model with high accuracy still can not meet the demand under the highly regulated financial industry that requires understanding the decision-making and quantifying the potential risk. Despite the deep convolutional neural networks (CNNs) have a significant performance. Especially in a highly speculative market, blindly trusting a black-box model will incur lots of troubles. Therefore, it is necessary to incorporate explainability into a DNN-based classic trading strategy, candlestick pattern recognition. It can make an acceptable justification for traders in the Digital Currency market. The paper exposes the black box and provides two algorithms as following. The first is an Adversarial Interpreter to explore the explainability. The second is an Adversarial Generator to enhance the model's explainability. To trust in the AI model and understand its judgment, the participant adopts powerful AI techniques to create more possibilities for AI in the Digital Currency market.","PeriodicalId":433638,"journal":{"name":"2022 14th International Conference on Knowledge and Smart Technology (KST)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122607339","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

Continuity of line detection methods based on the Radon transform 基于Radon变换的连续性线检测方法

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9729056

Pat Vatiwutipong

引用次数: 0

Unsupervised concept identification from a large corpus of research documents 从大量研究文献的语料库中进行无监督概念识别

2022 14th International Conference on Knowledge and Smart Technology (KST) Pub Date : 2022-01-26 DOI: 10.1109/KST53302.2022.9729060

Watcharachat Plangsri, Nalina Phisanbut, P. Piamsa-nga

引用次数: 0