{"title":"A Framework for Word Segmentation in Images using Density-based Clustering","authors":"Hui Guo, Qin Ding","doi":"10.29007/hq3n","DOIUrl":"https://doi.org/10.29007/hq3n","url":null,"abstract":"Word recognition is to identify words in images of printed or handwritten documents. It is especially challenging to recognize words from cursive handwriting documents. In this paper, we present a framework of using density-based clustering for word segmentation in printed or handwritten documents, including cursive handwriting. First, we performed various strategies for data preprocessing, including converting images to B/W images, adjusting the tilted images, and removing the background noises. K-means clustering and/or neighborhood density are used in finding parameters for the preprocessing steps. The preprocessing has shown to be very effective. For the word segmentation, we proposed density-based clustering to segment the words using multiple steps, including blurring, plotting, and clustering. We also developed a system for the framework, including preprocessing and clustering functionalities. Our approach works very well for printed documents. It works reasonably well for handwriting documents if words are relatively far from each other. The performance on handwriting documents can be further improved by using line segmentation.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129706948","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":"Channel-Matched OFDM (CM-OFDM) for Enhanced Performance of Multiuser Systems Operating in Underwater Acoustic Channels","authors":"S. El-Khamy, Dalia Ibrahim","doi":"10.29007/kmzx","DOIUrl":"https://doi.org/10.29007/kmzx","url":null,"abstract":"The design of multiuser OFDM underwater acoustic (UWA) communication systems is very challenging due to the time-varying and frequency selective fading of UWA channels. The key for ensuring a reliable optimum transmission for every user is the suitable resource assignment for each. This paper proposes a new adaptive channelmatched OFDM scheme (CM-OFDM) to overcome the performance degradation caused by the frequency selective fading across the OFDM subcarriers. In the proposed scheme, the OFDM subcarriers are sorted depending on their corresponding channel gains. Then the resource assignment to the different users is accomplished according to their required quality of service (QOS). The user with the highest QOS is assigned the best subcarriers and the other users are similarly assigned the remaining subcarriers. This optimized resource assignment technique guarantees enhanced performance with no need of increasing the transmitted power or changing the modulation schemes. The performance of the proposed technique is investigated and is compared with uniform and random subcarriers’ assignment methods used for multiuser OFDM systems. The simulations are performed for a multipath frequency selective UWA channel model. The simulation results clearly show the advantages of CM-OFDM scheme for the users with high QOS on the expense of a slight degradation in the performance for the other user with lower QOS. EPiC Series in Computing Volume 69, 2020, Pages 345–354 Proceedings of 35th International Conference on Computers and Their Applications G. Lee and Y. Jin (eds.), CATA 2020 (EPiC Series in Computing, vol. 69), pp. 345–354","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129431420","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":"NRDC Data Visualization Web Suite","authors":"Andrew Munoz, F. Harris, S. Dascalu","doi":"10.29007/rkqh","DOIUrl":"https://doi.org/10.29007/rkqh","url":null,"abstract":"","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"10 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132640610","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":"Implementing Timed Petri net for Modeling and Simulation in Card Gameplay","authors":"Garrett Hope, Paul Brodhead, Seung-yun Kim","doi":"10.29007/htqb","DOIUrl":"https://doi.org/10.29007/htqb","url":null,"abstract":"Petri nets (PNs) are a form of directed graph that can be used to model and simulate systems. They are very useful tool for developing and analyzing algorithms, prior to implementation. Adding the component of time, allows for systems with prioritized actions to be modeled more effectively. This paper assesses a Texas Hold’em algorithm using Petri nets and uses them to develop an improved version of this algorithm. Both are implemented in Python scripts to obtain the results to show which is more effective.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129144619","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":"Reducing error propagation for long term energy forecasting using multivariate prediction","authors":"Maher Selim, Ryan Zhou, Wenying Feng, Omar Alam","doi":"10.29007/mbb7","DOIUrl":"https://doi.org/10.29007/mbb7","url":null,"abstract":"Many statistical and machine learning models for prediction make use of historical data as an input and produce single or small numbers of output values. To forecast over many timesteps, it is necessary to run the program recursively. This leads to a compounding of errors, which has adverse effects on accuracy for long forecast periods. In this paper, we show this can be mitigated through the addition of generating features which can have an “anchoring” effect on recurrent forecasts, limiting the amount of compounded error in the long term. This is studied experimentally on a benchmark energy dataset using two machine learning models LSTM and XGBoost. Prediction accuracy over differing forecast lengths is compared using the forecasting MAPE. It is found that for LSTM model the accuracy of short term energy forecasting by using a past energy consumption value as a feature is higher than the accuracy when not using past values as a feature. The opposite behavior takes place for the long term energy forecasting. For the XGBoost model, the accuracy for both short and long term energy forecasting is higher when not using past values as a feature.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121595229","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":"On relationships between imbalance and overlapping of datasets","authors":"Waleed Almutairi, R. Janicki","doi":"10.29007/h71z","DOIUrl":"https://doi.org/10.29007/h71z","url":null,"abstract":"The paper deals with problems that imbalanced and overlapping datasets often encounter. Performance indicators as accuracy, precision and recall of imbalanced data sets, both with and without overlapping, are discussed and compared with the same performance indicators of balanced datasets with overlapping. Three popular classification algorithms, namely, Decision Tree, KNN (k-Nearest Neighbors) and SVM (Support Vector Machines) classifiers are analyzed and compared.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"80 2-3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123568737","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}
Huda Aldosari, Raafat S. Elfouly, R. Ammar, Mohammad Alsulami
{"title":"New Monitoring Architectures for underwater oil/Gas Pipeline using Hyper sensors","authors":"Huda Aldosari, Raafat S. Elfouly, R. Ammar, Mohammad Alsulami","doi":"10.29007/c84d","DOIUrl":"https://doi.org/10.29007/c84d","url":null,"abstract":"In this paper we propose new real time architectures for monitoring underwater oil and gas pipelines by using underwater wireless sensor network (UWSN). New monitoring architectures for underwater oil/gas pipeline inspection system combine a real time UWSN with nondestructive In Line Inspection (ILI) technology. These architecture will help in reducing or detecting the pipeline’s defects such as cracks, corrosions, welds, pipeline’s wall thickness ...etc by improving data transfer from the pipeline to the processor to extract useful information and deliver it to the onshore main station. Hence, decreasing delays in default detection.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127647927","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":"SOC and SOH Monitoring Algorithms for Lithium Batteries Using Multilayer Neural Networks","authors":"Jong-Hyun Lee, Hyun-Sil Kim, Insoo Lee","doi":"10.29007/m89x","DOIUrl":"https://doi.org/10.29007/m89x","url":null,"abstract":"This paper presents a battery monitoring system using a multilayer neural network (MNN) for state of charge (SOC) estimation and state of health (SOH) diagnosis. In this system, the MNN utilizes experimental discharge voltage data from lithium battery operation to estimate SOH and uses present and previous voltages for SOC estimation. From experimental results, we know that the proposed battery monitoring system performs SOC estimation and SOH diagnosis well.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129162526","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":"New Approach to Teaching Computer Programming to Freshmen","authors":"Jacob Sukhodolsky","doi":"10.29007/sl43","DOIUrl":"https://doi.org/10.29007/sl43","url":null,"abstract":"Freshmen who take an introductory computer programming course often ask their classmates for help. In some cases, they even copy each other’s programs. That is being considered as cheating. The problem of cheating in Computer Science students’ homework assignments so far has been handled mainly through administrative punishment of the cheaters. The success of such an approach depends to a large degree on the ability of the instructor to recognize the fact of cheating, which is a complicated task. With a large number of students taking the course, identifying the cheaters sometimes requires considerable time. The author of this paper suggests a way of solving the cheating problem by encouraging students’ cooperation rather than trying to fight it. He also suggests the way of changing the course grading policy emphasizes the importance of regular checking the students’ understanding of the course material.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133525382","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":"Age-group Classification Using 3DHOG Descriptor Applied to Depth Maps","authors":"Nabila Mansouri, Hana Bougueddima, Y. Jemaa","doi":"10.29007/rvq6","DOIUrl":"https://doi.org/10.29007/rvq6","url":null,"abstract":"Age estimation has lots of real-world applications, such as security control, biometrics, customer relationship management, entertainment and cosmetology. In fact, facial age estimation has gained wide popularity in recent years. Despite numerous research efforts and advances in the last decade, traditional human age-group recognition with the sequence of 2D color images is still a challenging problem. The goal of this work is to recognize human age-group only using depth maps without additional joints information. As a practical solution, we present a novel representation of global appearance of aging-effect such as wrinkles’ depth. The proposed framework relay, first-of-all, on an extended version of Viola-Jones algorithm for face and region of interest (most affected by aging) extraction. Then, the 3D histogram of oriented gradients is used to describe local appearances and shapes of the depth map, for more compact and discriminative aging effect representation. The presented method has been compared with the state-of-the-art 2D-approaches on public datasets. The experimental results demonstrate that our approach achieves a better and more stable performances.","PeriodicalId":264035,"journal":{"name":"International Conference on Computers and Their Applications","volume":"144 46","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133086925","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}