Proceedings of the 3rd International Conference on Software Engineering and Information Management最新文献

TKM Ontology Integration and Visualization TKM本体集成与可视化

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378976

Suganya Selvaraj, Eunmi Choi

引用次数: 1

Energy Balanced Threshold Using Game Theory Algorithm for Wireless Sensor Networks Optimization 基于博弈论算法的能量平衡阈值无线传感器网络优化

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378952

N. Hendrarini, M. Asvial, R. F. Sari

{"title":"Energy Balanced Threshold Using Game Theory Algorithm for Wireless Sensor Networks Optimization","authors":"N. Hendrarini, M. Asvial, R. F. Sari","doi":"10.1145/3378936.3378952","DOIUrl":"https://doi.org/10.1145/3378936.3378952","url":null,"abstract":"The wireless sensor network (WSN) as a supporting monitoring system requires stable conditions. The clustering mechanism in wireless sensor networks has been implemented to reduce energy waste. Therefore, maintaining energy in a balanced cluster head is very important. Logically, the distance between the cluster member nodes and the cluster head, and the distance of the head to sink node can affect the stability of the network while it is related to energy resources. To maintain a balanced environment, head cluster energy configuration management is a priority. One effective way to extend network life is to maintain energy balance. The main objective of this paper is to optimize the sensor network by modifying the Distributed Energy Efficient Clustering (DEEC) protocol using the Game Theory algorithm. Here, game theory has been introduced into the solution of problems by finding threshold values. Nash Equilibrium, a concept of game theory is used to have a correlation between energy variables, and non-cooperative behaviour as a character of game theory. In this work, DEEC protocol - a heterogeneous cluster protocol - has been modified in terms of threshold factors to improve the performance of wireless sensor networks. The threshold will filter out nodes that are not suitable to be cluster heads, so the wrong cluster head selection will not occur.","PeriodicalId":304149,"journal":{"name":"Proceedings of the 3rd International Conference on Software Engineering and Information Management","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126228769","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: 8

Agile Project Management Challenges and Mapping Solutions: A Systematic Literature Review 敏捷项目管理的挑战和映射解决方案:系统的文献综述

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378949

T. Raharjo, B. Purwandari

{"title":"Agile Project Management Challenges and Mapping Solutions: A Systematic Literature Review","authors":"T. Raharjo, B. Purwandari","doi":"10.1145/3378936.3378949","DOIUrl":"https://doi.org/10.1145/3378936.3378949","url":null,"abstract":"The Project Management Institute reported that the Agile approach is widely being used for project management practices. This approach has a significant impact on business growth and project performance. However, its implementation is challenging. Therefore, a systematic literature review (SLR) is used to reveal the challenges faced in Agile project execution. The Project Management Body of Knowledge (PMBOK) knowledge areas were adopted to classify the challenges. A total of 23 papers from 400 were identified as the result of SLR extraction. The challenges from related studies were categorized into the PMBOK knowledge areas. A mapping from the challenges to the solutions was performed using the PMBOK Guide, Prince2 Agile, Agile Practice Guide, and other related references. This study provides a list of Agile challenges and their mapped solutions. The biggest challenge arises from stakeholder management, which includes challenges related to Agile adaption, Agile transition, and Agile transformation. Other challenges include project resource management, project integration management, project scope management, and project schedule management. For academicians, this study provides a new understanding of Agile challenges and their suitable solutions from the perspective of project management. For practitioners, the findings provide potential lessons learned and recommendations to deal with the challenges.","PeriodicalId":304149,"journal":{"name":"Proceedings of the 3rd International Conference on Software Engineering and Information Management","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121780789","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: 31

Efficient Semantic Segmentation through Dense Upscaling Convolutions 基于密集上尺度卷积的高效语义分割

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378941

Kurt Schoenhoff, Jason J. Holdsworth, Ickjai Lee

{"title":"Efficient Semantic Segmentation through Dense Upscaling Convolutions","authors":"Kurt Schoenhoff, Jason J. Holdsworth, Ickjai Lee","doi":"10.1145/3378936.3378941","DOIUrl":"https://doi.org/10.1145/3378936.3378941","url":null,"abstract":"Semantic segmentation is the classification of each pixel in an image to an object, the resultant pixel map has significant usage in many fields. Some fields where this technology is being actively researched is in medicine, agriculture and robotics. For uses where the resources or power requirements are restricted such as robotics or where large amounts of images are required to process, efficiency can be key to the feasibility of a technique. Other applications that require real-time processing have a need for fast and efficient methods, especially where collision avoidance or safety may be involved. We take a combination of existing semantic segmentation methods and improve upon the efficiency by the replacement of the decoder network in ERFNet with a method based upon Dense Upscaling Convolutions, we then add a novel layer that allows the fine tuning of the decoder channel depth and therefore the efficiency of the network. Our proposed modification achieves 20-30% improvement in efficiency on moderate hardware (Nvidia GTX 960) over the original ERFNET and an additional 10% efficiency over the original Dense Upscaling Convolution. We perform a series of experiments to determine viable hyperparameters for the modification and measure the efficiency and accuracy over a range of image sizes, proving the viability of our approach.","PeriodicalId":304149,"journal":{"name":"Proceedings of the 3rd International Conference on Software Engineering and Information Management","volume":"130 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124251554","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: 0

Massively Scalable Image Processing on the HPCC Systems Big Data Platform 基于HPCC系统大数据平台的大规模可扩展图像处理

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378978

Tanmay Sanjay Hukkeri, G. Shobha, Shubham Milind Phal, Jyothi Shetty, R. YatishH., Naweed Mohammed

{"title":"Massively Scalable Image Processing on the HPCC Systems Big Data Platform","authors":"Tanmay Sanjay Hukkeri, G. Shobha, Shubham Milind Phal, Jyothi Shetty, R. YatishH., Naweed Mohammed","doi":"10.1145/3378936.3378978","DOIUrl":"https://doi.org/10.1145/3378936.3378978","url":null,"abstract":"Today's fast-moving world sees an abundance of image data in everyday life. From messages to insurance claims to even judicial systems, image data plays a pivotal role in facilitating several critical Big Data applications. Some of these applications such as automatic license plate recognition (ALPR) use CCTV cameras to capture snapshots of traffic from real-time video, inadvertently resulting in the generation vast amounts of image data on a daily basis. This brings with it the herculean task of processing these images to extract the essential information as efficiently as possible. The conventional method of processing images in a sequential manner can be very time consuming on account of the vast multitude of images and the intensive computation involved in order to process these. Distributed image processing seeks to provide a solution to this problem by splitting the computations involved across multiple nodes. This paper presents a novel framework to implement distributed image processing via OpenCV on HPCC Systems distributed node architecture*, a set of high-performance computing clusters. The proposed approach when tested on the Indian License Plates Dataset was found to be 85 percent accurate. Additionally, a 30 percent decrease in computation time was observed when executed on a multi-node setup without any impact to accuracy.","PeriodicalId":304149,"journal":{"name":"Proceedings of the 3rd International Conference on Software Engineering and Information Management","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126206043","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

IP Traceback method by OpenFlow 使用OpenFlow的IP回溯方法

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378965

N. Yoshiura, Hayata Yano

引用次数: 1

A Novel Graph-Based Program Representation for Java Code Plagiarism Detection 一种新的基于图的Java代码抄袭检测方法

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378960

Hayden Cheers, Yuqing Lin

引用次数: 4

Research on Differential Particle Swarm Optimization Algorithm for Wireless Network Location in Seismic Exploration 地震勘探无线网络定位的差分粒子群优化算法研究

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378964

XianHua Kong, Ju-Rak Kang, Mingliang Li, Jingting Li

引用次数: 1

Feature Selection for the Classification of Alzheimer's Disease Data 阿尔茨海默病数据分类的特征选择

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378982

Hany Al Ashwal, Areeg S. Abdalla, M. E. Halaby, A. Moustafa

引用次数: 1

Buying the Unreal: Drivers of Virtual Item Purchase in Video Games 购买虚幻:电子游戏中虚拟物品购买的驱动因素

Proceedings of the 3rd International Conference on Software Engineering and Information Management Pub Date : 2020-01-12 DOI: 10.1145/3378936.3378948

Andy Syahrizal, B. Purwandari, M. Mishbah, M. Dzulfikar

{"title":"Buying the Unreal: Drivers of Virtual Item Purchase in Video Games","authors":"Andy Syahrizal, B. Purwandari, M. Mishbah, M. Dzulfikar","doi":"10.1145/3378936.3378948","DOIUrl":"https://doi.org/10.1145/3378936.3378948","url":null,"abstract":"In the past couple of years, video games have become one of the biggest platforms for the consumption of virtual goods. In addition to the advancement of video game markets, virtual items in gaming industries have grown significantly. There is a substantial amount of money going into the purchase of virtual items. However, most of it is spent on aesthetic virtual goods. They give a better look to the game characters, but they do not grant any direct advantages to the character owners in gameplay. Why do people buy these items? Do they want to attract more attention from other players? Hence, an investigation was conducted to address these questions. A systematic literature review was performed to identify factors that influence individuals to purchase virtual goods in video games. The analysis of selected references was mapped into two models. The first one is the stimulus-organism-response model to explain the purchase behavior. The second one is the attention, interest, desire, and action model to reflect the monetization behind the purchase. The findings improve the understanding of the driving factors to purchase a virtual item. It gives a potential contribution to the gaming industry as well as to regulators.","PeriodicalId":304149,"journal":{"name":"Proceedings of the 3rd International Conference on Software Engineering and Information Management","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128006672","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: 4