2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)最新文献

{"title":"Retail Analytics to anticipate Covid-19 effects Using Big Data Technologies","authors":"Jessica Sharma, Deepikesh Sharma, Krishneel Sharma","doi":"10.1109/CSDE53843.2021.9718390","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718390","url":null,"abstract":"Retail analytics helps a company gain a deeper understanding of customer demand, making shopping more relevant, personalized, and convenient and boosting sales using optimal pricing. This paper aims to demonstrate retail analytics through a prototype that uses big data technologies. Using the big data technologies, the raw data is stored, analyzed and visualized to get valuable decision-making insights. The project objective is to help companies get retail analytics from which they can make decisions to anticipate the Covid-19 effects. The design for the system includes Hadoop Distributed File System (HDFS), Apache Pig, Apache Hive, SparkSQL, Spark MLLib, and Apache Zeppelin. The prototype uses a dataset that contains information for the transactions in the United Kingdom. Therefore it does not relate to covid-19 retail data but helps answer relevant questions. The dataset is used to investigate revenue aggregate by the country for the top 5 countries, daily sales activity, hourly sales activity, basket size distribution, top 20 Items sold by frequency, and market basket analysis. This paper can be used to produce a production possibility curve, reduce shortage, avoid surplus, illustrate demand and supply curves, and detect current economic conditions. All these would help the decision-makers to develop strategies to help them anticipate the impacts of Covid-19.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133303888","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":"Prediction of Volumetric Drag Coefficient of Tri-Lobed Airship Envelopes using ML tools","authors":"Anudeep Peela, Manikandan Murugaiah, R. Pant","doi":"10.1109/CSDE53843.2021.9718376","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718376","url":null,"abstract":"Hybrid Airships use tri-lobed envelopes, which enable the installation of flatter solar panels on their upper surface to increase their efficiency. The envelope shape can be parameterized in terms of some geometrical parameters. Optimization of the envelope shape to reduce its volumetric drag coefficient (CDV) requires wind-tunnel tests or numerical investigations, both of which are expensive and time consuming. In this paper we describe an approximate model to predict the envelope CDV as a function of nine geometrical parameters. This model is built by applying six Machine Learning models, viz., Linear Regression (LR), K-Neighbors Regression (KNNR), Decision Trees (DT), Gradient Boosting Regressor (GBR), Elastic Net with Polynomial Terms (ENPT) and Neural Network (NN) on a dataset comprising of numerically computed values of CDV for 170 combinations of the shape parameters. Sensitivity of CDV to each of the envelope shape parameters was determined using Accumulated Local Effects (ALE) plots. It was found that ENPT performed the best in this dataset and resulted in predicting the CDV within an error band of ± 3%. Feature Importance Analysis was carried out to reveal that envelope fineness ratio had the largest contribution towards the prediction of CDV, followed by the inter lobe distance and envelope prismatic coefficient. Two additional parameters, viz., Total Surface Area and Cross-Sectional Area of the envelope were introduced, and the former was found to be significantly influencing CDV.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129533813","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":"Three - Dimensional Tunnel Passing Maneuvers of Mobile Robots","authors":"Madhur Verma, Sanjana Chetty, Praviserk Chand, Hafswa Bibi, J. Raj","doi":"10.1109/CSDE53843.2021.9718451","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718451","url":null,"abstract":"In this paper, we consider multiple point masses traversing in a 3-dimensional obstacle-ridden environment made up of cylindrical-shaped obstacles, which will act as tunnels. Each point mass will have different targets and avoiding each other and the cylindrical tunnels in its path. The motion of a robot is bounded within a workspace and its velocities are curtailed for safety reasons. Since the workspace is cluttered with 3-dimensional cylindrical shaped objects, we propose a collision-free path that can lead the mobile robot from the desired starting point to the desired location or target. A complete solution to this problem will use the Minimum Distance Technique (MDT) for the generation of the shortest, smoothest and safest path among all the collision-free paths between the initial position and the target. Here, the minimum distance between the center of the point mass, representing a mobile robot, and the surface wall of the cylinder is calculated; thus, only the avoidance of a point on the surface wall of the cylinder is considered. The simulations and derivations are verified by using Mathematica software.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115658831","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":"Customer Size Prediction Using Machine Learning Approach for Mobile Package","authors":"Desalegn Medhin Firdu, Rosa Tsegaye Aga","doi":"10.1109/CSDE53843.2021.9718375","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718375","url":null,"abstract":"Nowadays the telecom market is competitive and telecom operators launch various new service packages to meet customer needs and attract more customers as well. Ethio telecom is the only telecommunications service provider in Ethiopia. In the case of ethio telecom, as there is no an automated method for package preview, Machine Learning (ML) approach has been studied to predict customer size for new mobile packages. Three ML algorithms that are, ElasticNet regression, Extreme Gradient Boosting and Random Forest regression (RF) have been used to train the prediction models. To train the model, mobile package dataset has been constructed by integrating data from three different sources in ethio telecom. The sources are business support systems, marketing product catalog and mobile package post launch analysis results. As the study has showed, the RF model has outperformed the ElasticNet regression and Extreme Gradient Boosting models.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"72 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116563192","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":"Numerical Investigation of the Fracture Pattern in Cedar Wood by Finite Element Method by Considering Grain Direction","authors":"Raviduth Ramful","doi":"10.1109/CSDE53843.2021.9718449","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718449","url":null,"abstract":"The transverse strength of wood is influenced by numerous naturally inherited factors such as grain direction, proportion of latewood and earlywood and microstructural arrangement. The mechanisms of transverse fracture in such material is thus a function of the combined effect of the aforementioned structural features. The aim of this study is to explore the influence of structural features, namely grain direction and variation in orthotropic properties on the transverse fracture of Japanese cedar (Cryptomeria japonica) by considering 3point bending investigation in finite element method (FEM). To this end, three types of Japanese cedar specimen with varying grain distribution, namely longitudinal-radial (LR), longitudinal-tangential (LT) and radial-longitudinal (RL) were considered. The selected specimens were modelled on finite element modelling and post processing software (FEMAP) and simulation was conducted on LS-DYNA. In comparison to LR and RL specimens, FEM results revealed a unique transition in fracture pattern of LT specimens with varying material properties. From results of this study, it has been deduced that the unrestricted mechanisms of crack propagation observed in natural materials like Japanese cedar predominantly occurred as a result of inferior transverse strength. Lessons learned about the transverse fracture in natural materials are beneficial when crafting advanced composite materials with enhanced ability to resist transverse fracture.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123524554","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 Color Vision Approach Considering Weather Conditions Based on Autoencoder Techniques Using Deep Neural Networks","authors":"Mohammad Mainuddin Raj, Samaul Haque Tasdid, Maliha Ahmed Nidra, Jobaer Noor, Sanjana Amin Ria, Md. Ashraful Alam","doi":"10.1109/CSDE53843.2021.9718453","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718453","url":null,"abstract":"Color machine vision is a riveting technology crucial in pioneering innovations like autonomous vehicles, autonomous drone deliveries, automated stores, robots, infrastructure and surveillance monitoring programs for security, manufacturing defect monitoring and more. When it comes to real life applications of automated machines, safety is a major concern and to ensure utmost safety the unpredictable has to be taken into consideration. We propose and demonstrate a color vision approach that allows image normalization hinged on autoencoder techniques employing deep neural networks. The model is composed of image preprocessing, encoding and decoding. The images are resized in preprocessing portion the images go through a cognitive operation where the input image becomes suitable to enter the autoencoding technique section. The autoencoder is comprised of two core components – encoder and decoder. To employ this system deep neural network is applied which generates a code of an image in the encoding process. Sequentially, the code changes over to decoding. Decoder portion decodes it and regenerates the initial image extracting it from the code of the encoder portion. It allows normalizing color images under different weather conditions such as images captured during rainy or foggy weather conditions. We devise it such that rainy and foggy images are normalized concurrently and in real time. The autoencoder is trained with numerous rainy and foggy datasets utilizing CNN. In this research we investigate the model normalizing images in two different weather conditions – rainy and foggy conditions in real time. We used SSIM and PSNR to verify the accuracy of the model and confirm its capability reconstructing images in real time for advanced real life color vision implementations.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124844878","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":"Application of Gaussian Process Preference Learning for Visualizing Facial Features Related to Personality Traits","authors":"Keito Shiroshita, Masashi Komori, Koyo Nakamura, Maiko Kobayashi, Katsumi Watanabe","doi":"10.1109/CSDE53843.2021.9718431","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718431","url":null,"abstract":"People automatically make inferences about other people’s personality traits based on their facial features. This study aims to apply a sequential experimental design based on Bayesian optimization (BO) in order to elucidate the relationship between impressions of personality and faces and facial features. We used a BO that incorporates Gaussian process preference learning (GPPL) which allows us to estimate a utility function based on a pairwise comparison task. One hundred and six Japanese university students provided photographs and each male and female facial image was embedded into a latent representation (18 x 512 dimensions) in the StyleGAN2 network using the Flickr-Faces-HQ (FFHQ) dataset. Using PCA, the dimensions of the latent representations were reduced to an 8-dimensional subspace, which we refer to as the Japanese face space. The participants were asked to select which faces were more trustworthy from among the images in the first session and the more dominant faces in the second session. The stimulus images were synthesized using the pre-trained StyleGAN2 model within the face space. Each session consisted of 100 trials. The stimuli for each session of the first 95 trials were created based on randomly generated parameters in the face subspace, while the stimuli for the remaining five trials were created based on the parameters calculated using the acquisition function. Facial traits related to trustworthiness and dominance were estimated based on the averaged utility functions. The impression of trustworthiness was found to be associated with facial aversion, while dominance was associated with sexual dimorphism. The results suggest that GPPL is an effective method for elucidating average psychological evaluations of complex stimuli.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125443900","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":"Analysis of technology-mediated pedagogies: Experiences from a BYOD initiative in New Zealand","authors":"Janak Adhikari, A. Mathrani, C. Scogings","doi":"10.1109/CSDE53843.2021.9718393","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718393","url":null,"abstract":"A longitudinal study was conducted in a New Zealand secondary school to investigate the immediate and longer-term challenges and opportunities of a technology-supported learning initiative. A ‘bring your own device’ (BYOD) initiative called for a stronger connect with digital technology in formal educational settings in 2012. This was indeed much ahead of its time, as now evident from worldwide move towards digital education in the aftermath of the COVID-19 pandemic. In this study, we tracked transformations within learning and teaching for over five years. At the inception of the idea, there was much resistance from parents and other stakeholders; however, the BYOD initiative ultimately showcased a very successful example of technology-supported teaching and learning initiative for other New Zealand schools. Our investigation primarily focused on one of the critical indicators for the success of such an initiative, the digital divide. The digital divide is particularly important because of the level of attention and dialogue this BYOD topic gathered across New Zealand. Initial discourses (over newspapers, radio and television) suggested that this initiative would be damaging in view of existing digital divides across societies and the overall public opinion outweighed the potential positives from such an initiative. As part of our five-year study, we investigated some of the key concerns around the digital divide issue in the context of such a technology-supported learning initiative. One of the key enablers of this study was integration of two frameworks, to enable the cross-examination of relationships between various sources of social cognitive abilities related to an individual’s information literacy, motivational and behavioral aspects. That is, how skill development, knowledge acquisition, and changes in personal and behavioral aspects impact self-efficacy levels as a consequence of BYOD strategies. The resulting framework is especially relevant in post-COVID-19 times, since technology-driven remote education delivery formats are now being touted as the new norm. Our framework will therefore provide much value to policy-makers in establishing inclusive educational policies.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128938107","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":"The impact of demographics on user satisfaction in cloud-based payment systems in Australia","authors":"Domingos Mondego, E. Gide","doi":"10.1109/CSDE53843.2021.9718383","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718383","url":null,"abstract":"Over the past decade, payments conducted over the Internet, or cloud-based payments, have significantly increased. Cloud-based payment systems (CBPS) represent an evolution of the payment process due to ubiquity and versatility. Yet, notwithstanding the benefits of using the CPBS are undeniable the adoption rates by Australian users are still very low compared to other countries. This might indicate that the users are not satisfied with the current payment systems, or they do not know the benefits of using them. In this sense, the aim of this study was to investigate the effect of personal characteristics of users (age, gender and income) on user satisfaction, and their impact on the adoption of cloud-based payment systems (CBPS) in Australia. This study used a quantitative approach through an online questionnaire survey was conducted to measure the data collected. The raw data of 411 respondents were collected using Qualtrics and the results were imported into SPSS (Statistical Package for the Social Sciences) system, where the sample homogeneity took place. The findings of sample homogeneity pointed out that there are major differences between mean values in some responses, which may suggest that age, gender and income have influence on user satisfaction.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"66 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133588146","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":"Determine the optimum operating conditions for black pepper drying in a tray dryer to minimize the total drying energy","authors":"Ishan Virantha, A. Wijewardane","doi":"10.1109/CSDE53843.2021.9718440","DOIUrl":"https://doi.org/10.1109/CSDE53843.2021.9718440","url":null,"abstract":"Open sun drying is the widely used passive method for black pepper drying, but due to its limitations, artificial dryers have become popular. Among these dryers, convective hot air tray dryers are extremely popular in black pepper processing industries. It is extremely important to identify the optimum drying temperature and the hot air velocity for black pepper drying process on a convective type tray dryer to minimize the total drying energy while improving the quality of the black pepper. During this study, the drying characteristics of black pepper were investigated in a convective type tray dryer. An experimental apparatus which was fabricated in-house was used to understand the variation of the moisture ratio with the drying time. The experiments were conducted for three different temperatures of 50°C, 55°C and 60°C and, for three different air velocities of $0.4 text{ms}^{-1},0.8text{ms}^{-1}$ and $1.2 text{ms}^{-1}$. The observed experimental data were fitted with existing drying models. Model coefficients and constants were evaluated by using the MS Excel Solver software. The Logarithmic model was found to be the most suitable drying model describing the black pepper drying on a convective type tray dryer with an average RMSE (root mean square deviation) of 0.0140. The total drying time required to reduce the moisture content to 12% (minimum safe storage moisture content) in dry basis under different drying conditions was calculated using the logarithmic model equation. The total drying energy required to dry 1 kg of raw black pepper in different drying conditions was calculated and a surface plot of total drying energy against temperature and hot air velocity was generated. Based on the contours of the surface plot, the drying conditions which minimize the total drying energy required were determined.","PeriodicalId":166950,"journal":{"name":"2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134362862","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}