{"title":"Searching Overseas Taiwanese Nationals by Web Content Mining","authors":"C. Hsu, Yuh Tzong Liu, Jen-Shin Hong","doi":"10.1109/CCOMS.2018.8463239","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463239","url":null,"abstract":"This article proposes a novel approach to retrieve overseas nationals of a given country by using web content mining techniques. The approach includes a three-step process: (1) key phrases composition, (2) query constraint imposition, and (3) web search result filtering. Based on the proposed approach, we develop a framework to realize a web retrieval system for searching professional overseas nationals. The framework includes modules of (1) Query Agent, (2) Web Search Engine, (3) Snippet Parser, (4) Page Filter and (5) Metadata Generator. The prototype system implementation shows that the feasibility of the proposed approach to efficiently retrieve large number of pages containing potential overseas nationals. Experiments shows that the precision rate varies between different combination of key phrases and query constraints. In certain cases, the precision rate could reach as high as 29%, which is much better than typical web searches using simple query terms.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124206868","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}
Donata D. Acula, Louise Aster C. Oblan, Tracy B. Pedroso, Katrine Jee V. Riosa, Michelle Arianne R. Tolibas
{"title":"Implementing Fact-Checking in Journalistic Articles Shared on Social Media in the Philippines Using Knowledge Graphs","authors":"Donata D. Acula, Louise Aster C. Oblan, Tracy B. Pedroso, Katrine Jee V. Riosa, Michelle Arianne R. Tolibas","doi":"10.1109/CCOMS.2018.8463282","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463282","url":null,"abstract":"In the technology age, articles with fraudulent content are rampant, especially articles shared on social media. Misinformation could just be an inaccuracy at its best, or it could lead to normalizing false information at worst. To aid the predicament, the researchers created a system that will “fact check” suspicious articles against those articles that have been deemed credible, reliable, and more accurate, in order to help fight deceiving content that may be detrimental to society. The journal regarding computational fact checking that was published by Ciampaglia, et. al. (2015) from the Indiana University in the USA entitled Computational Fact Checking from Knowledge Networks, was used as the basis and inspiration for this thesis. The researchers made use of the undirected graph (UG) together with a part-of-speech (POS) tagging algorithm to create a knowledge graph (KG) that would serve as the center of the system. Five different POS tagging algorithms were paired with the UG to assess which combination would yield the best results, these are Conditional Random Fields, Logistic Regression, a Hybrid of CRF and LR, Random Forests, and K-Nearest Neighbors. Random Forests and K-Nearest Neighbors were classification algorithms used in Ciampaglia's study. It was concluded that among the 5 pairs of UG and POS Tagging algorithms, the Hybrid of CRF and LR used as a POS tagger, together with the UG, created the most efficient KG.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115994189","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}
Pannipa Chinakaew, Sakkarin Sinchai, P. Wardkein, J. Koseeyaporn
{"title":"Frequency Estimation of Short Range Radar Using Adaptive FIR Notch Filter and SAGC for Velocity Detection","authors":"Pannipa Chinakaew, Sakkarin Sinchai, P. Wardkein, J. Koseeyaporn","doi":"10.1109/CCOMS.2018.8463227","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463227","url":null,"abstract":"This research proposes the velocity detection for short range radar using an adaptive FIR notch filter and a sinusoidal automatic gain control scheme (SAGC). A HB 100 module with amplifying gain of 20 times produces Doppler signal and this signal is fed to a laptop through a sound card with sampling frequency of 8000 Hertz. The signal is processed by the SAGC to amplify the amplitude of the signal to be unity. To detect the frequency of the signal, an algorithm of indirect frequency estimation based on adaptive FIR notch filter is performed. After that, the resulting frequency is converted to velocity. All procedures in this work are processed by MATLAB program. The results of the proposed method have better signal to noise ratio compared with existing method. In addition, the presented work consumes low computational time.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128161528","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":"Web Service Based Food Additive Inventory Management with Forecasting System","authors":"Pikulkaew Tangtisanon","doi":"10.1109/CCOMS.2018.8463339","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463339","url":null,"abstract":"Recently, food industries have been growing rapidly due to the development of novel technology. Numerous research has been conducted to improve products to satisfy the needs of customers. As a result, various food additives have been used to compose the product and which makes it difficult in recognizing and managing food additive stock. To be able to survive in a competitive world, the industry must find a practical stock management solution since under-stocking causes the industry to lose an opportunity to sell while overstocking causes a deficit. This paper focuses on an inventory management and a stock forecasting system. Web service was implemented as a new approach for an inventory management system that helps to manage and to find the food additives that exist in the international food additive database authorized by Codex Alimentarius Commission. Using web services has many advantages than a traditional web base. The service provider does not have to reveal the database access method to the client, and the information or business model can be changed at any time, and no need to update the client side. The client can access the service via any platform. The web service has been developed through Hypertext Mark up Language 5 (HTML5), Node JavaScript (NodeJS), and My Structured Query Language (MySQL), Database Management System, Hypertext Preprocessor (PHP). The stock forecasting was done by Python with four machine learning models which are Naive Bayes, Decision Tree, Linear Regression and Support Vector Regression to predict stock of food additive. Accuracy is used to measure the performance of these techniques. The experimental result indicated that the most accurate model for stock forecasting is Linear regression.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132032388","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":"Extracting Attributes for Recommender Systems Based on MEC Theory","authors":"Yun-Shan Cheng, P. Hsu, Yu-Chin Liu","doi":"10.1109/CCOMS.2018.8463179","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463179","url":null,"abstract":"To retain consumer attention and increase their purchasing rates, many online e-commerce vendors have adopted content-based approaches in their recommender systems. However, except for text based documents, there is little theoretic background information guiding the selection of elements. On the other hand, Means-End Chain theory noted deciding elements that dictate product selection include attributes, benefits, and values. This study strives to establish a methodology to identify favorite attributes based on Means-End Chain theory. The experiment is conducted to compare and contrast the performance of the proposed method and two traditional content (attribute) based methodologies. The results show that the proposed system outperforms the two methods by 82% and 68%, respectively.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130836250","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}
Bayu Charisma Putra, Budi Sctiyono, D. Sulistyaningrum, Soetrisno, I. Mukhlash
{"title":"Moving Vehicle Classification Using Pixel Quantity Based on Gaussian Mixture Models","authors":"Bayu Charisma Putra, Budi Sctiyono, D. Sulistyaningrum, Soetrisno, I. Mukhlash","doi":"10.1109/CCOMS.2018.8463218","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463218","url":null,"abstract":"One problem of transportation that often happens is the traffic congestion. In order to address this problem, the information related to traffic are needed, such as type and total number of vehicles that passes certain road. This research discussed classification of the types of vehicles using pixel quantity. The Gaussian Mixture Models (GMM) used to extract foreground and background images. To classify vehicles, we use a quantity of pixels in which the amount is obtained based on the experiment. In the last stage, tracking and counting on vehicles passing through Region of Interest according to the classified type. The result is an algorithm capable for classifying type of vehicles with a high degree of accuracy. The experiments were carried out with two road conditions, namely a quiet and crowded road. On a quite road, the Kedung Cowek street and Wonokromo street, we obtained accuracy of 98.87% and 96.67% respectively. While on the crowded road, the Diponegoro street and Pemuda street, we get accuracy of 95.45% and 89.13%.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126326568","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":"Investigating an Adaptive Network Coding Control Protocol for Multihop-Multipath Networks for Network Reconfigurability","authors":"Zilole Simate, R. Kohno","doi":"10.1109/CCOMS.2018.8463217","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463217","url":null,"abstract":"One of the challenges in current designs of wireless networks is that of guaranteeing end to end delivery of high priority data or packets in multi-path multi-hop networks for medical use especially for nodes with mobility. There are various solutions based on traffic engineering which are applied in wired networks to guarantee end to end delivery of packets. With mobile wireless networks, the environment is highly dynamic, therefore with different scenarios having multiple paths or routes in the network, the node has to adapt to the network for dependable delivery of priority packets. In so doing, a level of Qos can at least be guaranteed. This paper reviews some of the techniques to achieve adaptive network coding, and the objective is to implement adaptive network coding in multi-hop, multipath network for high reliability and dependability. As a preliminary study we investigate an Adaptive Network coding scheme in a Binary tree fashion with the root being the convolution coder for its feasibility. The objective is to design a control protocol to be used to adapt to the error changes that occur in the network thereby increasing performance.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125232364","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 Study of the Z-Wave Protocol: Implementing Your Own Smart Home Gateway","authors":"Phan minh Linh An, Taehong Kim","doi":"10.1109/CCOMS.2018.8463281","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463281","url":null,"abstract":"Z-Wave is one of the most popular wireless protocols for home area networks. However, there have been few studies about this protocol in recent years. Unlike Wi-Fi, Z-Wave is not an IP-compatible protocol, thus a Z-Wave device cannot directly connect to the Internet or common user devices (e.g., smartphone, laptop). The Z-Wave network uses a controller to manage and control all devices. The controller also acts as a gateway and allows a user to interact with Z-Wave devices from smartphone or laptop via the Internet or a local network. In this paper, we designed and implemented a Z-Wave gateway controller for a smart home system. We proved the feasibility of the proposed gateway using a prototype and evaluated its performance by command execution time. We also discussed the limitations of the Z-Wave protocol based on our experience.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131256772","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":"Towards Academic Organizations Security","authors":"Nader Shahata","doi":"10.1109/CCOMS.2018.8463304","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463304","url":null,"abstract":"Organizations that have limited proper knowledge of network security infrastructure often struggle to design and implement effective network security plan for their websites. Such gap can lead to severe damages to the institution, for instance, the insecure website can lead to loss of data. The importance of having a security system in place is that it enables organizations to monitor their traffics and other security issues. The information discussed in this paper gives a detailed plan of a network security plan that is capable of optimizing the network security the university website from any malicious attack. Besides, the paper highlights the various steps that are essential when developing network security structure such as network segmentation, detection of intrusion, prevention mechanism, and security logging events as well as packet capturing strategies. In its entirety, this proposal gives a broad description of the background of the research, its significance and a methodology section presenting the approach used in carrying out this study. The research assumptions, limitations and delimitations are also highlighted in a broader manner, a detailed review of past literature work related to web network security. The network security infrastructure is also designed in a manner that allows other stakeholders to know how the system works so that they can participate in securing the network security of the University network.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114446803","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 New Learner Model in Adaptive Learning System","authors":"Wen-ling Ding, Zhengzhou Zhu, Qun Guo","doi":"10.1109/CCOMS.2018.8463316","DOIUrl":"https://doi.org/10.1109/CCOMS.2018.8463316","url":null,"abstract":"Learner model is the core of adaptive learning system and determines the quality of online teaching. Based on online learning norms and combined with learner characteristics of online learning in China, this paper proposes a new learner model. It includes four basic features: basic information, learning style, knowledge state, and cognitive ability. It gives a formal representation of these four feature elements and a method for initializing and updating the values. Finally, in the “Software Engineering” course adaptive learning system developed on the MoodIe platform, the learner model has good usability and validity.","PeriodicalId":405664,"journal":{"name":"2018 3rd International Conference on Computer and Communication Systems (ICCCS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124941045","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}