2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)最新文献

{"title":"Impact of Load on Total Harmonic Distortion in a Photovoltaic System","authors":"S. K. Shah, A. Hellany, M. Nagrial, J. Rizk","doi":"10.1109/CSDE50874.2020.9411527","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411527","url":null,"abstract":"Environmental concerns are the biggest reasons for the rising interest in Renewable Energy sources. Rapid industrialization and urbanization have forced engineers to look at cost-effective sources. Power quality issues are increasing day by day. The introduction of sensitive equipment into an electrical grid is an essential factor for the introduction of these problems in the grid. The introduction of Renewable Energy (RE) sources into the system can increase PQ disturbances in the system. The addition of sensitive equipment in the electrical system can cause compatibility issues. The compatibility issues take centre stage if RE sources are part of the electrical system. These compatibility problems become complex if multiple sources are used to produce power. The type and size of the load in the electrical system play a vital role in the introduction of PQ disturbances. These PQ disturbances can bring changes in voltage or current value. The impact of the load should be studied in detail to understand its impact on the system. This paper presents the results of a study based on the impact of load on a PV system. The impact of different types of loads on the electrical system was investigated, and results were collected to facilitate future research. Total harmonic distortion (THD) was given more importance.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"675 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116105216","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 probabilistic approach to evaluate the relationship between visual and quantified pavement distress data using logistic regression","authors":"Tamina Tasmin, James Wang, H. Dia, David L. Richards, Quddus Tushar","doi":"10.1109/CSDE50874.2020.9411555","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411555","url":null,"abstract":"Detailed measurements along with visual ratings of major pavement distresses assist highway authorities in maintenance decision makings. The ratings are allocated by professional pavement engineers whereas the objectively collected measured data are collected through electronic or automated devices by trained personnel who may have a lack of experience. Therefore, data quality discrepancy from both types of surveys has gained attention in pavement maintenance management to find the reliability of pavement distress data to predict the overall pavement condition, both at the project and network level. This research employs probabilistic logistic modeling to evaluate the consistency in two types of survey data at the network level. The measured distress used in developing the logit models include crack (% area involved), rut depth (mm), and loss of surface texture (left wheel path %). Developed logistic models predict visual crack and deformation conditions from quantified distress data with a medium success rate (55% to 61%). However, deformation (sprayed sealed network) and texture loss (both asphalt surfaced and sprayed sealed network) data cannot be validated due to the failure of the logistic models. The gradual deterioration process of the pavement surface associated with loss of texture makes it difficult to detect visually. In the case of deformation ratings, assessors evaluate both longitudinal and local depressions. It appears that other local depressions dominate longitudinal depression (rutting) in the sprayed sealed network, and hence the data from both types of surveys are not related statistically significantly in this logistic approach. Data collection and synchronization error in the objective survey have potential influences as well, in creating this disagreement. The approach used in this study would help the state road authorities to ensure the data integrity in developing overall pavement condition models for the bituminous road network.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121662642","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":"Integrating Cloud ERP Systems with New Technologies Based on Industry 4.0: A Systematic Literature Review","authors":"Sunchai Tongsuksai, Sanjay Mathrani","doi":"10.1109/CSDE50874.2020.9411570","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411570","url":null,"abstract":"In the modern world, the fourth industrial revolution (Industry 4.0) has been introduced to the manufacturing sector. This strategy uses Internet-of-things (IoT) platforms and new technologies in order to provide integrated connectivity via the Internet. The purpose of this strategy is to enhance automation and communication in businesses to provide a comprehensive view of their processes in real-time. Cloud enterprise resource planning (ERP) is one of the new technologies that plays a vital role in this revolution and is a core part of the inter-connected data exchange in Industry 4.0 based companies. This paper presents a comprehensive literature review of current research on integration of cloud ERP systems with new technologies in the Industry 4.0 environment. This study evaluated 16 relevant articles to identify the core benefits of integrating cloud ERP systems with IoT based technologies as part of Industry 4.0 revolution.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121694983","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 Algorithm of Ship Trajectory Based on Machine Learning Techniques","authors":"Haocheng Wang, Y. Zuo, Tie-shan Li, Zhenyu Wang","doi":"10.1109/CSDE50874.2020.9411551","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411551","url":null,"abstract":"In order to solve the problem of identifying ship trajectories with different motion patterns in waterways, a ship trajectory classification algorithm based on machine learning techniques is proposed. First, the area of waterways is divided and the trajectory selection rules are formulated to construct the label matrix. Then, the piecewise cubic Hermite interpolation algorithm is used to extract the feature points of the original trajectory data from the perspectives of the equal time interval in recording time and the equal space interval in spatial distribution to construct the trajectory feature matrices. Finally, in order to train and test the classification model, the label matrix and trajectory feature matrices are put into the model and the parameters are optimized. The AIS trajectory data in Huaian section of the Beijing-Hangzhou Canal are selected for the trajectory classification experiment. In this research, the broad learning system (BLS), the back propagation neural network (BPNN) and the support vector machine (SVM) are chosen as the machine learning classification methods. The results show that the trajectory classification model based on BLS is superior to those based on BPNN and SVM in classification accuracy and training time.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"299 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121455507","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":"Deep Machine Learning Digital library recommendation system based on Metadata for Arabic and English Languages","authors":"M. Almaghrabi, G. Chetty","doi":"10.1109/CSDE50874.2020.9411525","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411525","url":null,"abstract":"During the last three decades, information technologies are adopted by many libraries. It provides public access to their material in digital form to improve service. Metadata are the key aspect that must be considered to achieve a proper integration of digital library. It is data about data and has many purposes: data description, data browsing and data transfer. The advanced search engine for text documents allowed retrieving text information in an efficient way. For the organization structured digital collections on internet scale, metadata is an approach for retrieval improvement, preservation, and interoperability. However, such engines experienced low accuracy when documents had unique properties that need specialized and deeper semantic extraction. By Combining the strengths of the deep learning models with that of word embedding is the key to high-performance metadata classification in digital library recommendation system. Throughout this article, we aim at providing a proposed method on the utilization of the deep machine learning approaches to build digital library recommendation system based on Metadata for Arabic and English languages.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127605362","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":"Covid-19 Pandemic: A New Era Of Cyber Security Threat And Holistic Approach To Overcome","authors":"Jabber Ahmed, Quddus Tushar","doi":"10.1109/CSDE50874.2020.9411533","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411533","url":null,"abstract":"In this paper, we present cyber security threat created worldwide has been discussed during the current COVID-19 situation. To stop the spread of Coronavirus, almost all the countries of the world declared lockdown. People are now doing their office, schooling, and business remotely. For that reason, the use of computers and the internet has increased a lot and made cyber criminals more active. Recently the number of cyber-attacks has increased a lot, and everyone has become a target the cyber criminals. Lack of personal safety precautions in using the internet is causing significant damage to everyone. COVID-19 has made it easy for cyber criminals to have easy access to everyone’s data. Many banking sectors and government and non-government organizations have faced several cyberattacks during this time. This paper focuses on some safety precautions to safeguard the personal and organizational data from cyber criminals.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133442601","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":"Piecewise Linear Optimization for Public EV Charging Depots in Different Utility Environments","authors":"A. Brissette, David Coats, D. Scoffield","doi":"10.1109/CSDE50874.2020.9411610","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411610","url":null,"abstract":"With the proliferation of electric vehicles (EVs), EV supply equipment technology is being pushed to increasingly higher power levels, such as extreme fast charging (XFC) at 300kW or more. As more public XFC depots are connected to electric distribution systems, utility operators will mitigate their impact with pricing schemes and programs such as demand response, demand charges, and time-varying prices. In this paper we describe an XFC management system that combines an on-site battery energy storage system and an optimization application that minimizes the cost to operate the depot in light of the utility pricing programs. We have designed the optimizer specially to use fast and simple linear programming so that it can be deployed to low-cost computing platforms. We also describe how several utility pricing schemes are integrated into a single piecewise model, reducing the engineering effort to implement the optimizer in different utility environments.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134120022","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":"Automatic detection of ironic expressions based on the Implicit Display Theory","authors":"Akinori Sato, I. Tanev, K. Shimohara","doi":"10.1109/CSDE50874.2020.9411597","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411597","url":null,"abstract":"It is not easy for a computer to automatically detect irony. Because in order to understand the irony in a sentence, it is necessary to infer the meaning hidden behind the word from the branch. Common sense and common understanding of reality are required as background knowledge for detecting irony. The literal meaning and the meaning intended by a speaker do not often match, and this makes it a difficult task in natural language processing. In this research, the effectiveness of automatic detection of irony based on the Implicit Display Theory was verified. The Implicit Display Theory was proposed in 1997 as a comprehensive irony theory, and its validity and superiority have been shown as a theory representing irony research. We selected ironic sentences for which the Implicit Display Theory holds from a large-scale ironic corpus, and performed two-class classification using the deep learning model to evaluate the application of implicit display theory to natural language processing.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125363845","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":"Detection and 3D Visualization of Brain Tumor using Deep Learning and Polynomial Interpolation","authors":"Md. Akram Hossan Tuhin, Tarunya Pramanick, Humayoun Kabir Emon, Wasiur Rahman, Md. Muzahidul Islam Rahi, Md. Ashraful Alam","doi":"10.1109/CSDE50874.2020.9411595","DOIUrl":"https://doi.org/10.1109/CSDE50874.2020.9411595","url":null,"abstract":"Among different imaging techniques MRI, MRSI and CT scans are some of the widely use techniques to visualize brain structures to point out brain anomalies especially brain tumor. Identification of brain tumor accurately in clinical practices has always been a hard decision for neurologist as multiple exceptions might present in images which may lead dubious suggestion from neurologist. In our proposed model we are aiming towards brain tumor detection and 3d visualization of tumor more accurately in effcient way. Our proposed model composed of three stages such as classification of image using CNN whether any tumor exists of not; segmentation using multi-thresholding to extract the detected tumor; and 3d visualization using polynomial interpolation. the proposed model enables enhancing the accuracy of tumor detection as compare to existing models as well as segmenting and 3d visualizing the detected tumor. we get 85% accuracy on our model comparing with others which is slightly more efficient in terms of classification and detection.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125398330","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":"Novel Tidal Energy Harnessing System Utilizing Quadruple Bi-directional Turbine Arrangement","authors":"A. S. Weerakoon, H. Young, Wonwoo Kim, Young-Ho Lee","doi":"10.1109/csde50874.2020.9411578","DOIUrl":"https://doi.org/10.1109/csde50874.2020.9411578","url":null,"abstract":"In the modern era global power demand rises implicitly with exponentially growing power needs. As the global warming becomes a critical factor, emission regulations are set to minimize and eventually seize the traditional power production methods in near future. As a solution, this research aims on presenting a novel methodology for harnessing energy from tidal current streams. In hydro-power sector Cross Flow Turbine (CFT) or “Banki-Michell Turbine” have become a popular choice over the years. But in ocean renewable energy field, limited amount of research has being done to assess the capability of this particular turbine. CFT is a bi-directional turbine, as the turbine runner imparts unidirectional behavior regardless of the flow direction. In this study, tidal passage with cross sectional area of 756.25 m2 having length of 87.5 m consists of equally spaced, 6.1 m diameter four CFT’s housed within separate augmentation channels. These specially shaped augmentation channels act as turbines converging and diverging (vice-versa) nozzles passages for the fluid passage. Each turbine runner consists of 18 blades having thin profile. The turbine setup was computer modeled and meshed. The volumetric mesh combines of 28 million, Hexahedral and Tetrahedral mesh elements. Runner blades were extra fined with close mesh elements to capture the boundary layer effect accurately. The quad-turbine setup was simulated with an open sea domain to gain accurate flow field behavior also to eliminate abrupt turbulence behavior pass the tidal passage. Numerical calculations of the turbine setup was carried out using commercial computational fluid dynamics (CFD) code ANSYS CFX. The turbine cluster yields a maximum power output of about 500 kW at optimum tip speed ratio (TSR) of 0.4 for the designed average tidal flow velocity of 2.5 ms-1, with a maximum of about 18% efficiency. As the previous research studies suggests, the efficiency values of tidal current turbines are generally being lower becomes a bearable factor in this study as well. Compared with prevailing tidal turbines designs, the CFT system requires no mechanical or electrical interactions to change the turbine runner blade directions. The simple design of CFT system economically beneficial due to low manufacturing cost and requires considerably less maintenance.","PeriodicalId":445708,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129666697","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}