2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)最新文献_第2页

Identifying digital investing services using design thinking methodology 使用设计思维方法识别数字投资服务

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982477

P. Fehér, Krisztián Varga

{"title":"Identifying digital investing services using design thinking methodology","authors":"P. Fehér, Krisztián Varga","doi":"10.1109/SKIMA47702.2019.8982477","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982477","url":null,"abstract":"Incumbent financial institutions are continuously challenged by small fintech startups and big technology enterprises in finding ways to offer new, customer centric, and most importantly digital services. This paper is focusing on the investing services. The presented research is using Design Thinking methodology to identify challenges of investing activities and finding digital ways to answer these challenges. Our target customer group were those, who are not investing right now, as we wanted to identify what are their barriers of entering the investment market. The research sample focuses on educated, young generations. Although the financial background of the sample provides a good opportunity of investments, alternate use of savings is more widespread, and the general behavior of the analyzed generation requires liquid assets. The qualitative answers highlight the necessity of knowledge, trust and external expertise for investing decisions. The research generated four main possible products for the non-investing segment in order to gain their trust, educate them or to offer them an opportunity that does not need huge amount of money in investment.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116794075","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}

引用次数: 2

SKIMA 2019 Welcome

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/skima47702.2019.8982537

引用次数: 0

A Supply Chain Model with Blockchain-Enabled Reverse Auction Bidding Process for Transparency and Efficiency 具有区块链支持的透明度和效率的反向拍卖招标过程的供应链模型

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982476

R. Koirala, K. Dahal, S. Matalonga, Rameshwar Rijal

引用次数: 11

Big Data with Decision Tree Induction 基于决策树归纳的大数据

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982419

Shabnam Sabah, Sara Anwar, Sadia Afroze, Md. Abulkalam Azad, Swakkhar Shatabda, D. Farid

{"title":"Big Data with Decision Tree Induction","authors":"Shabnam Sabah, Sara Anwar, Sadia Afroze, Md. Abulkalam Azad, Swakkhar Shatabda, D. Farid","doi":"10.1109/SKIMA47702.2019.8982419","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982419","url":null,"abstract":"Big data mining is one of the major challenging research issues in the field of machine learning for data mining applications in this present digital era. Big data consists of 3V’s: (1) volume - massive amount of data/too many bytes, (2) velocity - high speed streaming data/too high a rate, and (3) variety - data are coming from different sources/too many sources. Collecting and managing real-life big data is a difficult task, as big data is so big that we cannot keep all the data together in a single machine. Therefore, we need advanced relational database management systems with parallel computing to deal with big data. Knowledge mining from big data employing traditional machine learning and data mining techniques is a big issue and attract computational intelligent researcher in this area. In this paper, we have used the decision tree (DT) induction method for mining big data. Decision tree induction is one of the most preferable and well-known supervised learning technique, which is a top-down recursive divide and conquer algorithm and require little prior knowledge for constructing a classifier. The traditional DT algorithms like Iterative Dichotomiser 3 (ID3), C4.5 (a successor of ID3 algorithm), Classification and Regression Trees (CART) are generally built for mining relatively small datasets. So, we need a more scalable decision tree learning approach for mining big data. In this paper, we have engendered several trees employing two scalable decision tree algorithms: RainForest Tree and Bootstrapped Optimistic Algorithm for Tree construction (BOAT) using seven benchmark datasets from Keel Repository and UCI Machine Learning repository. We have compared the performance of RainForest and BOAT algorithms. Also, we have proposed a decision tree merging approach, as decision tree merging is a very complex and challenging task.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114477331","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}

引用次数: 5

The Computer Nose Best 电脑鼻子最好

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982474

S. Jilani, H. Ugail, Andrew Logan

{"title":"The Computer Nose Best","authors":"S. Jilani, H. Ugail, Andrew Logan","doi":"10.1109/SKIMA47702.2019.8982474","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982474","url":null,"abstract":"The nose is the most central feature on the face which is known to exhibit both gender and ethnic differences. It is a robust feature, invariant to expression and known to contain depth information. In this paper we address the topic of binary ethnicity classificiation from images of the nose, using a novel dataset of South Asian, Pakistani images. To the best of our knowledge, we are one of the first to attempt demographic (ethnicity) based identification based solely on information from the nose.A two-category (Pakistani vs Non-Pakistani) task was used in combination with Deep learning (ResNet) based and VGG-based pre-trained models. A series of experiments were conducted using ResNet-50, ResNet-101, ResNet-152, VGG-Face, VGG-16 and VGG-19, for feature extraction and a Linear Support Vector Machine for classification. The experimental results demonstrate ResNet-50 achieves the highest performance accuracy of 94.1%. In comparison, the highest score for the VGG-based models (VGG-16) was 90.8%. These results demonstrate that information from the nose is sufficient for deep learning models to achieve >90% accuracy on judgements of ethnicity.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134239790","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}

引用次数: 1

Modelling and Simulation of Lily flowers using PDE Surfaces 百合花的PDE曲面建模与仿真

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982402

Ehtzaz Chaudhry, A. Noreika, L. You, Jian-Jun Zhang, Jian Chang, H. Ugail, Alexander Malyshev, A. Carriazo, A. Iglesias, Z. Habib, Allah Bux Sargano, H. Haron

引用次数: 1

Real-Time Video Dehazing for Industrial Image Processing 用于工业图像处理的实时视频去雾

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982486

Hayat Ullah, I. Mehmood

{"title":"Real-Time Video Dehazing for Industrial Image Processing","authors":"Hayat Ullah, I. Mehmood","doi":"10.1109/SKIMA47702.2019.8982486","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982486","url":null,"abstract":"In today’s industries, automation, reliability, robustness and accuracy are pivotal problem to cut costs and increase productivity and quality. Visual sensor networks are vital control and monitoring tools for continues, on-line imaging and real time image processing in production and plant process. Most of the industrial videos are captured in hazy weather and usually degraded by suspended particles of atmosphere, such as smoke, fog, rain, and snow, which limits the visual quality of image. This hinders the ability of artificial intelligent driven systems to achieve automation, reliability and accuracy. Recovery of the clear visuals from the input hazy videos is challenging problem. Instead of relying on explicitly estimating the key component of atmospheric scattering model, we present end-to-end CNN model, which directly recovers the clear images from hazy images. This end-to-end architecture makes it an ideal pre-processing tool into other deep models for increasing the efficiency of various computer vision tasks in real time systems, such as Retina-Net for object detection, ResNet for object recognition. Experimental results demonstrate the effectiveness and robustness of proposed framework by outperforming the stat-of-the-art approaches in terms of time complexity and visual quality.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124301752","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}

引用次数: 1

Evolutionary Behavioral Design of Non-Player Characters in a FPS Video Game Through Particle Swarm Optimization 基于粒子群优化的FPS电子游戏非玩家角色进化行为设计

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982467

Guillermo Díaz, A. Iglesias

引用次数: 2

Novel Technique for Isolated Sign Language Based on Fingerspelling Recognition 基于指纹拼写识别的孤立手语新技术

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982452

Ahmad Yahya Dawod, N. Chakpitak

{"title":"Novel Technique for Isolated Sign Language Based on Fingerspelling Recognition","authors":"Ahmad Yahya Dawod, N. Chakpitak","doi":"10.1109/SKIMA47702.2019.8982452","DOIUrl":"https://doi.org/10.1109/SKIMA47702.2019.8982452","url":null,"abstract":"Sign language is used by deaf and hard hearing people to exchange information between their own community and with other people. Fingerspelling recognition method from isolate sign language has attracted research interest in computer vision and human-computer interaction based on a novel technique. The essential for real-time recognition of isolate sign language has grown with the emergence of better-capturing devices such as Kinect sensors. The purpose of this paper is to design a user independent framework for automatic recognition of American Sign Language which can recognize several one-handed dynamic isolated signs and interpreting their meaning. We built datasets as a raw data for alphabets (A–Z) or numbers (1–20) by used left-hand the 3D point (XL, YL, ZL) or switch by right-hand (XR, YR, ZR) centroid as one of contribution. The proposed approach was tested for gestures that involve left-hand or right-hand and was compared with other approach and gave better accuracy. Two machine learning methods are involved like Hidden Conditional Random Field (HCRF), and Random Decision Forest (RDF) for the classification part. The third contribution based on low lighting condition and cluttered background. In this research work is achieved for recognition accuracy over 99.7%.","PeriodicalId":245523,"journal":{"name":"2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"1117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116066356","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}

引用次数: 5

Remodeling Hospitality Industry through Artificial Intelligence 通过人工智能重塑酒店业

2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) Pub Date : 2019-08-01 DOI: 10.1109/SKIMA47702.2019.8982488

A. Imad

引用次数: 3