2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS)最新文献_第7页

Using Decentralized Social Trust as an Alternative Way to Prove Someone’s Address 使用分散的社会信任作为证明某人地址的另一种方式

2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2022-10-21 DOI: 10.1109/ICSESS54813.2022.9930197

Suzana Mesquita de Borba Maranhão Moreno, J. Seigneur

{"title":"Using Decentralized Social Trust as an Alternative Way to Prove Someone’s Address","authors":"Suzana Mesquita de Borba Maranhão Moreno, J. Seigneur","doi":"10.1109/ICSESS54813.2022.9930197","DOIUrl":"https://doi.org/10.1109/ICSESS54813.2022.9930197","url":null,"abstract":"The traditional way to prove someone’s address using formal documents like utility bills may not be feasible for some people, like those living in very poor neighborhoods, because they do not have these documents. In this paper, we propose an alternative way to prove someone’s address using a decentralized social trust solution. Because our design choices, this solution is able to work offline and does not need a logically centralized repository of all issued proof-of-address, in oppose to what would be achieved by using existing accretionary ID solutions. We validated this proposal by building a mobile application, using it in a real experiment in a Brazilian favela, and collecting mobile data. We also interviewed 20 people to complement our validation and help to guide the next steps of this work. The experiment showed that the solution is viable and easy to use. It is possible to adopt an approach like the one proposed to prove other facts, like gender, sex and income. These proofs may be used for different initiatives, like social programs, purpose-driven lending or other decentralized finance services.","PeriodicalId":265412,"journal":{"name":"2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122352249","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

Model Optimization for Stock Market Prediction using Multiple Labelling Techniques 基于多重标签技术的股票市场预测模型优化

2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2022-10-21 DOI: 10.1109/ICSESS54813.2022.9930328

Hangjun Li, Yuzhe Cao, Xu Yang, Yapeng Wang

{"title":"Model Optimization for Stock Market Prediction using Multiple Labelling Techniques","authors":"Hangjun Li, Yuzhe Cao, Xu Yang, Yapeng Wang","doi":"10.1109/ICSESS54813.2022.9930328","DOIUrl":"https://doi.org/10.1109/ICSESS54813.2022.9930328","url":null,"abstract":"In the field of stock market prediction, various labelling techniques have been developed, aiming to improve the accuracy of stock prediction. However, few comparisons and evaluations of labelling techniques have been made in this field. To address this problem, the effectiveness of three labelling methods Raw Return (RR), Fixed Time Horizon (FTH), and Triple Barrier (TB) methods have been studied and compared on Nasdaq 100 Index (NDX) with Multivariate Long Short-term Memory (LSTM) Fully Convolutional Network (MLSTM-FCN) deep learning model. The results are then compared using the confusion matrix and classification report. Experiment results demonstrate that the TB method achieves the highest F1 score on buying signal due to TB being an advanced method that adds two horizontal barriers defined by stop-loss and take-profit. Additionally, the model utilizing the FTH method has the highest overall accuracy, and the model using the RR method generates more accurate predictions of selling signals. The result, therefore, demonstrates that TB method can utilize its additional two barriers to improve price prediction accuracy.","PeriodicalId":265412,"journal":{"name":"2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127542323","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

An Interactive Chatbot for University Open Day 大学开放日的互动聊天机器人

2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2022-10-21 DOI: 10.1109/ICSESS54813.2022.9930277

Fengyu Liu, Xu Yang, Yapeng Wang

{"title":"An Interactive Chatbot for University Open Day","authors":"Fengyu Liu, Xu Yang, Yapeng Wang","doi":"10.1109/ICSESS54813.2022.9930277","DOIUrl":"https://doi.org/10.1109/ICSESS54813.2022.9930277","url":null,"abstract":"Macau Polytechnic University (MPU) welcomes many visitors on its open day, and it is therefore necessary to provide them with excellent service and guidance. However, there are many difficulties in providing information to visitors, such as the occupation of human resources, language barriers and inaccurate answers, etc. By developing a chatbot to answer the questions from visitors instantly and consistently, helps to save human resources and increase the efficiency of work. An intelligent chatbot can not only provide accurate and appropriate responses but also bring a great communication experience to the visitors. This research uses Natural Language Processing (NLP) and Deep Learning (DL) techniques to develop a chatbot that can engage in interactive conversations with visitors for the MPU open day. A high-performance neural network is built to learn from the given dataset and can accurately answer questions about the MPU open day. Besides, STT (Speech-to-Text) and TTS (Text-to-Speech) APIs are used in this work to assist the communication between computers and humans. This work can be used as a reference framework of fast implementation of a chatbot for any knowledge area with an easy-to-adapt web interface.","PeriodicalId":265412,"journal":{"name":"2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130648544","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 Many-Objective Evolutionary Algorithm with Pareto Front Estimation and Angle-Based Selection 基于Pareto前估计和角度选择的多目标进化算法

2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2022-10-21 DOI: 10.1109/ICSESS54813.2022.9930253

Changshun Chen, Maowei He

引用次数: 0

Recognizing Stationary and Locomotion Activities using LSTM-XGB with Smartphone Sensors 使用LSTM-XGB与智能手机传感器识别静止和运动活动

2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2022-10-21 DOI: 10.1109/ICSESS54813.2022.9930285

Narit Hnoohom, Pitchaya Chotivatunyu, S. Mekruksavanich, A. Jitpattanakul

{"title":"Recognizing Stationary and Locomotion Activities using LSTM-XGB with Smartphone Sensors","authors":"Narit Hnoohom, Pitchaya Chotivatunyu, S. Mekruksavanich, A. Jitpattanakul","doi":"10.1109/ICSESS54813.2022.9930285","DOIUrl":"https://doi.org/10.1109/ICSESS54813.2022.9930285","url":null,"abstract":"Nowadays, stationary and locomotion activity recognition, also known as SLAR, is becoming increasingly important in a variety of domains, such as indoor localization, fitness activity tracking, and elderly care. Currently used methods typically involve handcrafted feature extraction, a process that is both difficult and requires specialized knowledge, and results can still be subpar. We proposed a deep learning technique for SLAR called LSTM-XGB that uses data from inertial sensors in smartphones to reduce the effort required for feature development and selection. The proposed LSTM-XGB consists of multiple stacked LSTM layers to automatically learn the temporal features of the input, followed by XGBoost for label prediction in the final layer. The results showed that the proposed LSTM-XGB technique, which automatically extracts features, outperforms conventional machine learning that requires manual feature extraction. We also showed that sensor data from three sensors (accelerometer, linear acceleration, and gyroscope) can be combined. This achieved higher accuracy than other combinations or single sensors.","PeriodicalId":265412,"journal":{"name":"2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115892411","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

Application of Fuzzy Query Technology in Data Analysis of Mongolian Medicine Prescriptions 模糊查询技术在蒙药处方数据分析中的应用

2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2022-10-21 DOI: 10.1109/ICSESS54813.2022.9930234

Lin Qingming, Lan Zhanjiang, Z. Chunsheng

引用次数: 0

A Weighted Kernel-based Possibilistic Fuzzy Clustering With Its Applications in Aerospace Image Segmentation 基于加权核的可能性模糊聚类及其在航空图像分割中的应用

2022 IEEE 13th International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2022-10-21 DOI: 10.1109/ICSESS54813.2022.9930181

Yun Wang, Fuli Qu, Xijie Yin

引用次数: 0