2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)最新文献

Spreading of Corona Virus in Central Europe: The Cases of Italy and Spain and the Very Beginning of Pandemic 冠状病毒在中欧的传播:意大利和西班牙的案例和大流行的开始

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9704918

H. Nieto-Chaupis

引用次数: 1

Face-recognition System Design and Manufacture 人脸识别系统设计与制造

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9705014

Menq-Jiun Wu, Ye Chen, Yi-Sheng Liao, Jun-An Chen, Hao-Han Lin

{"title":"Face-recognition System Design and Manufacture","authors":"Menq-Jiun Wu, Ye Chen, Yi-Sheng Liao, Jun-An Chen, Hao-Han Lin","doi":"10.1109/SNPD51163.2021.9705014","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9705014","url":null,"abstract":"The theory of face recognition is mainly from the idea of feature vectors. The face image is converted into a series of numbers to form a feature vector. For a feature vector of a face image, its content includes various features, such as: face height, face width, average face color, lips width, and nose height. The face-recognition operation is to compare the input of the feature vector of a face image with a large number of feature vectors in a dataset to identify the personal identity.The face recognition system in this paper is mainly implemented in the Python environment. Face generation is achieved by selfie of face. The image is cut to retain the part of the face, and stored in the database. Comparing the face image input with those saved in the dataset, if the similarity value passes the threshold value of true. The program will show the face image identification. Otherwise, the system will display a false message. The face recognition system is completed and the experimental results show the correct face-recognition. Finally the laptop Webcam is used to take the face image, and the result of comparison is also correct.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125328181","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

Effectiveness of Explaining a Program to Others in Finding Its Bugs 向他人解释程序发现bug的有效性

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9704932

Toshihiro Nakamura, Akito Monden, Mariko Sasakura, H. Uwano

引用次数: 0

Implementation of Tire Status Estimation Using Hall Sensor and G-Sensor 利用霍尔传感器和g传感器实现轮胎状态估计

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9704975

W. Chang, Rong-Terng Juang, Min-Hsiang Huang, M. Sung

{"title":"Implementation of Tire Status Estimation Using Hall Sensor and G-Sensor","authors":"W. Chang, Rong-Terng Juang, Min-Hsiang Huang, M. Sung","doi":"10.1109/SNPD51163.2021.9704975","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704975","url":null,"abstract":"Vehicles are one kind of human’s transport tools that can carry us to anywhere. Safety is an important issue for vehicle applications. Tire is an important element of the vehicle, because the vehicle only has four points connect on the road through tires. Many accidents are caused the tire problems. There are more and more researches in intelligent tire base on safety issues. Tire pressure monitor system (TPMS) can be called an application of intelligent tires that are currently a very popular tire monitoring device, it provides pressure and temperature information for drivers. The information can let drivers understand their tire’s status through simple information. Not only pressure and temperature can affect safety, but also tire’s use mileage. The tire wear has some relation to safety. The mileage has been defined by tire spec. The different tires have different specs and the tire wear status cannot be defined clearly. The wear status is hard to get that is because the vehicle condition, use scenario and situation are complicated. Drivers can’t understand how many miles did the tire use and what status the tire. This paper proposed a method to estimate and monitor tire mileage and wear base on simple sensors. G-sensor and hall sensors are common sensors in applications. The method will use these simple sensors to implement the method. Drivers can accord information to evaluate the tire status and decide the timing to replace the tire. It can help drivers to increase safety during the drive and provide a solution to support intelligent tire function.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128274342","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

Reversible Data Hiding for SMVQ Compressed Images Based on De-Clustering Rules 基于去聚类规则的SMVQ压缩图像可逆数据隐藏

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9704947

Kunpeng Sun, Ji-Hwei Horng, C. Chang

引用次数: 1

How to Enlighten Novice Users on Behavior of Machine Learning Models? 如何让新手了解机器学习模型的行为?

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9704891

Hiroto Mizutani, Masateru Tsunoda, K. Nakasai

{"title":"How to Enlighten Novice Users on Behavior of Machine Learning Models?","authors":"Hiroto Mizutani, Masateru Tsunoda, K. Nakasai","doi":"10.1109/SNPD51163.2021.9704891","DOIUrl":"https://doi.org/10.1109/SNPD51163.2021.9704891","url":null,"abstract":"Background: Machine learning models are sometimes embedded in software to implement the required functions. As a result, non-experts in machine learning are becoming familiar with the models. However, the interpretability of the built models is often low in machine learning, such as deep learning, and the recognition process of such models is very different from that of humans. Therefore, it is not easy for novice users, such as end-users and beginners, to anticipate the behavior of models that they will use or build. Aim: We assist novice users to realize an aspect of the behavior of machine learning models relating to robustness intuitively. Method: We formalized and evaluated quiz-based analysis, which is often applied by practitioners to test the robustness of machine learning models arbitrarily. To generate test cases of the models, the analysis converts images towards the boundary of classification for both machine learning and humans. It can be regarded as a type of boundary value analysis of software development. Results: In the experiment, we evaluated whether the analysis quantitatively clarified the aspects of the models. The analysis clarified the robustness of the model for image conversion and misclassification quantitatively. Conclusion: The analysis is expected to enlighten novice users on the behavior of machine learning models. This may promote behavioral changes in the evaluation of models for novice users.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114796269","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

A Reversible Database Watermark Scheme for Textual and Numerical Datasets 文本和数字数据集的可逆数据库水印方案

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9704991

Chinchen Chang, T. Nguyen, Chia-Chen Lin

引用次数: 5

Geometrical Schemes as Probabilistic and Entropic Tools to Estimate Duration and Peaks of Pandemic Waves 几何格式作为估计大流行波持续时间和峰值的概率和熵工具

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9704981

H. Nieto-Chaupis

引用次数: 0

Automated Eight-Arm Maze Trajectory Tracking System for Feature Extraction of TBI Animals TBI动物特征提取的自动八臂迷宫轨迹跟踪系统

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9704966

Shu-Cing Wu, Chi-Yuan Lin, Liang-Jyun Hong, Chi-Chun Chen

引用次数: 0

Conditional Data Augmentation For Sky Segmentation 天空分割的条件数据增强

2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) Pub Date : 2021-11-24 DOI: 10.1109/SNPD51163.2021.9705011

Zheng-An Zhu, Chien-Hao Chen, Chen-Kuo Chiang

引用次数: 0