Proceedings of the 3rd International Conference on Information Science and Systems最新文献

{"title":"Analysis of Key Criteria for Selecting ERP Systems in Croatian Companies","authors":"R. Picek","doi":"10.1145/3388176.3388203","DOIUrl":"https://doi.org/10.1145/3388176.3388203","url":null,"abstract":"Selection of an ERP system is extremely important and complex process about whose outcome directly depends the company's success. The goal of this research is to identify, analyze and classified key criteria for selecting ERP systems and then via study apply those results to Croatian companies. The study is based on the comprehensive literature review, where key criteria for selecting ERP systems were systematized in two categories. Then, the online survey was designed and conducted for two target groups: Croatian companies that have implemented ERP system (Users) and companies that implement ERP systems (Consultant). Survey results gives the perception of the importance of certain key criteria per categories from different perspectives. Also, for Croatian companies that have implemented the ERP system, study analyze the importance of particular defined criteria per additional dimensions: years of experience in using ERP systems, enterprise size and type of business.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130859290","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}

{"title":"Instance Segmentation of Water Body from Aerial Image using Mask Region-based Convolutional Neural Network","authors":"Sangdaow Noppitak, Sarayut Gonwirat, Olarik Surinta","doi":"10.1145/3388176.3388184","DOIUrl":"https://doi.org/10.1145/3388176.3388184","url":null,"abstract":"Land use is constantly changing, and water plays a critical role in the process. If changes are noticed quickly or are predictable, land use planning and policies can be devised to mitigate almost any problem. Accordingly, researchers present a mask region-based convolutional neural network (Mask R-CNN) for water body segmentation from aerial images. The system's Aerial image water resources dataset (AIWR) was tested. The AIWR areas were agricultural and lowland areas that require rainwater for farming. Many wells were spotted throughout the agricultural areas. The AIWR dataset presents two types of data: natural water bodies and artificial water bodies. The two different areas appear as aerial area images that are different in color, shape, size, and similarity. A pre-trained model of Mask R-CNN was used to reduce network learning time. ResNet-101 was used as backbone architecture. The information gathered in the learning process is limited, and only 720 pictures were produced, Researchers used data augmentation to increase the amount of information for training by using affine image transformation, including scale, translation, rotation, and shear. The experiment found that mask R-CNN architecture can specify the position of the water surface. Measuring method in this case is mAP value. The mAP value is at 0.30 without data augmentation. However, if using the R-CNN mask with data augmentation, the mAP value increased to 0.59.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126408169","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}

{"title":"Classification of Medical Data using Character-level CNN","authors":"K. Miyazaki","doi":"10.1145/3388176.3388191","DOIUrl":"https://doi.org/10.1145/3388176.3388191","url":null,"abstract":"It is necessary to handle an enormous amount of electronic data in medical practice. Therefore, a support system using information technology is desired to analyze the data. In this paper, we propose a preliminary system using character-level convolutional neural networks in order to improve the classification performance of text data on medical practice. The effectiveness of the proposed system is confirmed by the testbed called the NTCIR-13 MedWeb task [15].","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114145488","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}

{"title":"Comparative Study between Texture Feature and Local Feature Descriptors for Silk Fabric Pattern Image Recognition","authors":"Thananchai Khamket, Olarik Surinta","doi":"10.1145/3388176.3388201","DOIUrl":"https://doi.org/10.1145/3388176.3388201","url":null,"abstract":"Thai silk fabrics have unique patterns in different regions of Thailand. The designers may have been inspired and took ideas from the natural environment to create new silk patterns. Hence, many new silk patterns are modified from the original silk pattern. It is challenging for people to recognize a pattern without any prior knowledge and expertise. This paper aims to present a comparative study between texture feature and local feature descriptor for silk pattern image recognition. First, two feature extraction techniques: texture feature and local feature descriptors are proposed to create robustness features from sub-regions that are divided by the grid-based method. Second, the robust features are then classified using the well-known and effective classifier algorithms: K-nearest neighbor (KNN) and support vector machine (SVM) with the radial basis function. We experimented with silk pattern image recognition on two silk fabric pattern image datasets: the Silk-Pattern and Silk-Diff-Pattern. The evaluation results show that the texture feature called the local binary pattern (LBP) when combined with the KNN and SVM algorithms outperforms other feature extraction methods, even deep learning architectures.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116266102","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}

{"title":"Unrolled PRINCE Cipher based Glitch Physically Unclonable Function","authors":"Y. Nozaki, M. Yoshikawa","doi":"10.1145/3388176.3388207","DOIUrl":"https://doi.org/10.1145/3388176.3388207","url":null,"abstract":"Physically unclonable functions (PUFs) have attracted attention as authentication technologies in integrated circuits (ICs). A PUF utilizes IC manufacturing variation as a unique device's ID. Several PUFs have been proposed, and a glitch PUF is superior to other PUFs in terms of resistance against malicious attacks. A glitch PUF uses the variation of glitch waveforms in AES's S-BOX circuit which requires large area to embed, while IoT devices have strict area constraint. It is important to satisfy the area constraints when a glitch PUF is applied to IoT devices. This study proposes a new glitch PUF using a lightweight cipher which can be embedded into small area. The proposed PUF is based on an unrolled PRINCE low-latency cipher. Experiments using a field programmable gate array (FPGA) prove the validity of the proposed PUF.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125639010","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}

{"title":"A Verification Method for Security and Safety of IoT Applications Through DSM Language and Lustre","authors":"Wentao Tang, Hao Feng, K. Hisazumi, Akira Fukuda","doi":"10.1145/3388176.3388211","DOIUrl":"https://doi.org/10.1145/3388176.3388211","url":null,"abstract":"Development of Internet of Things (IoT) brings a variety of IoT applications that involve housing, navigation, payment, and healthcare. Since IoT applications play an important role in our lives, security is critical to these applications and must be guaranteed. In order to realize this, the paper proposes a pre-execution verification method for downloaded IoT applications, which meets security and safety requirements of users using model checking. The model checking requires special models for verification, which is difficult to describe for developers. So we introduce a domain-specific modeling language (DSML) to describe IoT application and a generator from the DSML into the model to pre-execution verification and execution. Also, as a case study, we provide a study of our method used in a smart house application, which is one of the most representative examples in IoT applications.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124698360","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}

{"title":"Role Identification of Domain Name Server Using Machine Learning based on DNS Response Features","authors":"Hailing Li, Hui Zhang, Longtao He, Kai Zhang, Chenghai He, Bingjie Wei","doi":"10.1145/3388176.3388205","DOIUrl":"https://doi.org/10.1145/3388176.3388205","url":null,"abstract":"The Domain Name System (DNS) plays an important role in the Internet by mapping domains to IP addresses. Numerous authoritative name servers and recursive resolvers form the DNS service infrastructure. Accurate identifying the role of the DNS server is of great importance for understanding the DNS infrastructure and performing security analysis. Previous research has proposed some methods for DNS server identification. Most of them are active methods which bring additional bandwidth and security risks; the non-negligible complex configuration of DNS servers in the actual network makes the results of passive approach using the DNS message header fields \"AA\" and \"RA\" unsatisfactory. This paper proposes a machine learning method to classify the typical role of the DNS server in a passive manner. Classifiers are trained by three categories of features extracted solely from passive DNS response records (removing the user information) and the experiment results show that the proposed method can achieve high accurate and low false positive rate.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134143787","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}

{"title":"Improving Recognition of Thai Handwritten Characters with Deep Convolutional Neural Networks","authors":"Sarayut Gonwirat, Olarik Surinta","doi":"10.1145/3388176.3388181","DOIUrl":"https://doi.org/10.1145/3388176.3388181","url":null,"abstract":"For handwritten character recognition, a common problem is that each writer has unique handwriting for each character (e.g. stroke, head, loop, and curl). The similarities of handwritten characters in each language is also a problem. These similarities have led to recognition mistakes. This research compared deep Convolutional Neural Networks (CNNs) which were used for handwriting recognition in the Thai language. CNNs were tested with the THI-C68 dataset. This research also compared two training methods, Train from scratch and Transfer learning, by using VGGNet-19 and Inception-ResNet-v2 architectures. The results showed that VGGNet-19 architecture with transfer learning can reduce learning time. Moreover, it also increased recognition efficiency up to 99.20% when tested with 10-fold cross-validation.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124923823","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}

{"title":"Virtue Ethics as a Solution to the Privacy Paradox and Trust in Emerging Technologies","authors":"A. Bilal, Stephen C. Wingreen, Ravishankar Sharma","doi":"10.1145/3388176.3388196","DOIUrl":"https://doi.org/10.1145/3388176.3388196","url":null,"abstract":"Despite concerns over the collection of personal information by technologies, society's use of such has increased rapidly. This attitude is termed the privacy paradox. This research-in-progress explores the root causes of this privacy paradox, the role of personal information privacy threats on trust in emerging technologies, and the influence of unconscious decision-making (based on virtue ethics traditions) on conscious decision-making. To understand the duality and subjectivity embedded in the above issues, this study applies Q-methodology for data collection, analysis, and interpretation. The study proposes that virtue ethics is the best approach to solve such subjective issues. This study enhances our understanding, on the basis of prior literature, of the importance of virtue ethics as a solution to the privacy paradox.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132826702","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}

{"title":"Development of Portable Air Quality Index (AQI) and Emergency Vehicles Preemption Prototype Based on Internet of Mobile Things (IoMT)","authors":"Shaik Shabana Anjum, R. M. Noor, I. Ahmedy, Norazlina Khamis, M. Anisi","doi":"10.1145/3388176.3388194","DOIUrl":"https://doi.org/10.1145/3388176.3388194","url":null,"abstract":"The technological advancements of the Internet of Things (IoT) in the recent past have facilitated immense progress towards mitigation of environmental pollution through smart transportation systems and solutions. In particular, communication to the commuters about the traffic ahead or occurrences of congestion has been envisioned to play a major role in outsmarting traffic through mobile applications giving rise to the emergence of the Internet of Mobile Things (IoMT). However, the existing mobile applications that serve as traffic reporting solutions still face major issues such as fixed route suggestions, longer delays during busy hours or emergencies, inefficient prompting of road accidents and heavy traffic en route to a particular destination. This research aims at providing solutions for notifying the commuters with updates on the traffic based upon the Air Quality Index (AQI) of the routes towards the destination and also about the approach of emergency vehicles. The cross-platform mobile application in this way enables the user to opt for a route with good air quality so that the more congested routes are avoided thereby mitigating the air pollution induced by road traffic. The experimental testing and validation of the proposed methodology are applied for areas belonging to Greater Kuala Lumpur. The various timings divided according to peak and non-peak hours are experimentally tested for analyzing the parameters of traffic usage and pattern through the mobile application. The outcome of the experiments has showed that when traffic flow is modelled and governed through vehicular emissions and concentrations of air pollutants, nearly 75% of the congested traffic is reduced thereby, giving rise to pollution-free environment as well as mitigation of urban heat island (UHI) effect that is formed through vehicular heat generation and difference in temperatures. On the other hand, the approach of emergency vehicles also prompts the commuters to avoid panic.","PeriodicalId":187568,"journal":{"name":"Proceedings of the 3rd International Conference on Information Science and Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128253671","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}