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XML-Relational mapping using production rule system 使用生产规则系统的xml -关系映射
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324328
A. Lyamin, Elena N. Cherepovskaya
{"title":"XML-Relational mapping using production rule system","authors":"A. Lyamin, Elena N. Cherepovskaya","doi":"10.1109/INTELLISYS.2017.8324328","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324328","url":null,"abstract":"The most efficient information systems are based on the relational data model. extensible Markup Language (XML) structures are machine- and human-readable. XML data can be easily analyzed and exchanged between different systems. Though, XML data is simply understandable, it has hierarchical model, which is quite redundant. Modern systems frequently apply various methods of XML-Relational Database Management System (RDBMS) transformation that assume different degrees of data compression and processing time of the method. However, the existing methods are not always effective. This paper defines new rules of XML-relational mapping, which provides more efficient data representation in both models, and describes the method based on them that lies upon the basic rules-driven principles of artificial intelligence and production system. This method is applied in learning management system of ITMO University, called AcademicNT, which contains a huge amount of educational data and materials.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130424599","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
A compact, low-cost unmanned surface vehicle for shallow inshore applications 一种小型，低成本的无人水面车辆，用于浅海应用
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324246
B. Metcalfe, B. Thomas, Alfie Treloar, Zuhayr Rymansaib, A. Hunter, Peter Wilson
{"title":"A compact, low-cost unmanned surface vehicle for shallow inshore applications","authors":"B. Metcalfe, B. Thomas, Alfie Treloar, Zuhayr Rymansaib, A. Hunter, Peter Wilson","doi":"10.1109/INTELLISYS.2017.8324246","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324246","url":null,"abstract":"This paper describes the preliminary design, implementation, and testing of a Police Robot for Inspecting and Mapping underwater Evidence (PRIME), an Unmanned Surface Vehicle (USV) developed to aid and support police search teams in shallow-water and inshore reconnaissance operations. Manual processing of such areas can be time consuming and difficult, with dangerous debris and low visibility causing further hindrance in some scenarios. PRIME uses a combination of MultiBeam EchoSounder (MBES) and Side Scan Sonar (SSS) systems for high resolution underwater imaging. Additional navigational sensors provide PRIME with further data allowing for position control, path planning and autonomous navigation within complex environments such as inland waterways. Such applications pose significant design constraints, with the USV required to be compact and portable, relatively inexpensive and scenario-configurable. We present some approaches taken to address these challenges, based around a modular hardware and software architecture using the Robot Operating System (ROS) framework. Data gathered from field tests using initial prototypes for the detection of body-shaped test targets is also discussed.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122328519","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: 14
IoT enabled smart buildings: A systematic review 物联网智能建筑:系统回顾
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324283
M. R. Bashir, A. Gill
{"title":"IoT enabled smart buildings: A systematic review","authors":"M. R. Bashir, A. Gill","doi":"10.1109/INTELLISYS.2017.8324283","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324283","url":null,"abstract":"There is an increasing interest in the Internet of Things (IoT) enabled smart buildings. The main question is: what are the key challenges, which must be addressed to effectively manage and analyze the big data for IoT enabled smart buildings. There is a need for the systematic literature review to understand the challenges and the solutions to overcome such challenges. Using the SLR approach, 22 relevant studies were identified and reviewed in this paper. The data from these selected studies were extracted to identify the challenges and relevant solutions. The findings from this research paper will serve as a knowledge base for researchers and practitioners for conducting further research and development in this important area.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129500873","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: 16
Improving open-domain event schema discovery with casual english normalization for noisy text 改进开放域事件模式发现的随机英语规范化噪声文本
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324323
Assia Mezhar, A. Mzabi, M. Ramdani
{"title":"Improving open-domain event schema discovery with casual english normalization for noisy text","authors":"Assia Mezhar, A. Mzabi, M. Ramdani","doi":"10.1109/INTELLISYS.2017.8324323","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324323","url":null,"abstract":"Social media enable people to share significant events from their daily life. Social data mining evolves the challenge of dealing with casual language extraction due to the unstructured social media content: social media users often prefer communicating unconventionally with informal language using abbreviations, slang, misspelled words, or non-standard short-forms. Thereby, this paper proposes a new open-domain event schema discovery approach using casual language normalization to normalize, extract events and discover their adequate schemas (event types and argument roles) from noisy corpus. The proposed approach exploits casual language normalization to improve both tasks of event schema discovery and event extraction. This approach can automatically normalize and generate high-quality schemas from the extracted events with unknown types. The introduced approach promises better results in terms of accuracy and quality of the discovered schemas.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127625133","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
Knowledge extraction from software engineering repositories 从软件工程存储库中提取知识
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324320
G. N. V. Ramana Rao, V. Balaram, B. Vishnuvardhan
{"title":"Knowledge extraction from software engineering repositories","authors":"G. N. V. Ramana Rao, V. Balaram, B. Vishnuvardhan","doi":"10.1109/INTELLISYS.2017.8324320","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324320","url":null,"abstract":"Software engineering processes are hard to understand, and related tasks frequently produce lot of information which can be used for development of strategy for future Projects. In the last decade, a large number of software data sets have been created for different purposes, however as the challenges in the development and maintenance of software are increased the need for novel approaches to make use of the collected data is also increased. The demands for reduced development time and increased reliability of software also necessitated the need for knowledge extraction from the previously collected data sets. In this paper a detailed survey is conducted on the available methods for the knowledge extraction from the software engineering data bases to forecast and aid in improved development and maintenance phases of software.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130854784","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
MCS: Multiple classifier system to predict the churners in the telecom industry MCS:电信行业流失预测的多分类系统
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324367
Mehreen Ahmed, I. Siddiqi, H. Afzal, Behram Khan
{"title":"MCS: Multiple classifier system to predict the churners in the telecom industry","authors":"Mehreen Ahmed, I. Siddiqi, H. Afzal, Behram Khan","doi":"10.1109/INTELLISYS.2017.8324367","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324367","url":null,"abstract":"Multiple classifiers for prediction or classification has gained popularity in recent years. Ensemble Technique perform best predictions as compared to traditional classifiers. This has resulted in the experimentation with new ways of ensemble creation. This paper presents a multiple classifier system (MCS) that can outperform traditional classifiers. Experiments are performed on a benchmark Customer Churn Dataset (available on UCI repository) and a newly created dataset from a South Asian wireless telecom operator. MCS achieved accuracies of 97% and 86% on the UCI churn dataset and private dataset, respectively. MCS as compared to existing best approaches realized the best results on the private and public datasets.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133298115","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
Dataset designing of software architectures styles for analysis through data mining clustering algorithms 数据集设计的软件架构风格，通过数据挖掘聚类算法进行分析
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324325
Qadeem Khan, Usman Qamar, Wasi Haider Butt, S. Rehman
{"title":"Dataset designing of software architectures styles for analysis through data mining clustering algorithms","authors":"Qadeem Khan, Usman Qamar, Wasi Haider Butt, S. Rehman","doi":"10.1109/INTELLISYS.2017.8324325","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324325","url":null,"abstract":"Software architecture is an important part of the software systems which states that how multiple components of the system interact with each other. There are multiple architecture styles in software engineering, such as Object Oriented, Client-Server, CORBA, Repository, Event-based, Interpreter. This research article provides a concept of a novel data set designing which defines the architectures of software systems based on architecture styles. As there is no such data set available so hence this article will enable researchers and software industrialists to define their own data set of their organizations for analyzing the projects through data mining approaches. The research also performs clustering algorithms on the proposed data set with RapidMiner Studio tool for interesting analysis.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114747537","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
Development of a control system for electric wheelchairs based on head movements 基于头部运动的电动轮椅控制系统的研制
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324250
Guilherme M. Marins, D. Carvalho, A. Marcato, I. Junior
{"title":"Development of a control system for electric wheelchairs based on head movements","authors":"Guilherme M. Marins, D. Carvalho, A. Marcato, I. Junior","doi":"10.1109/INTELLISYS.2017.8324250","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324250","url":null,"abstract":"This paper presents an economic solution for individuals with disabilities in the legs and arms. The goal is to use an IMU (Inertial Measurement Unit) to capture movements from the user's head and through this movement be able to move an electric wheelchair. For the extraction and data processing an Arduino Uno is used for data classification and the MatLab® software for simulating the movement. Euclidean distance, Mahalanobis distance, and artificial neural network was used for data classification. In this way, we seek an alternative to wheelchair users with greater limitations and minimizing costs for development.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121898369","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: 12
Unsupervised image segmentation using lab color space 使用实验室色彩空间的无监督图像分割
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324217
Erum Fida, Junaid Baber, Maheen Bakhtyar, Rabia Fida, Muhammad Javid Iqbal
{"title":"Unsupervised image segmentation using lab color space","authors":"Erum Fida, Junaid Baber, Maheen Bakhtyar, Rabia Fida, Muhammad Javid Iqbal","doi":"10.1109/INTELLISYS.2017.8324217","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324217","url":null,"abstract":"Image segmentation helps computer to understand visual information. A number of techniques are proposed for image segmentation that are either interactive or automatic. Interactive techniques provide satisfactory result but user interaction is the biggest limitation when large number of images are considered. On the other hand automatic image segmentation is difficult to acquire satisfactory results. We propose an unsupervised approach for automatic image segmentation that employ image color information to segment an image into foreground and background. The results confirm the effectiveness of the approach.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126188766","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
Utilizing high-performance embedded computing, agile condor, for intelligent processing: An artificial intelligence platform for remotely piloted aircraft 利用高性能嵌入式计算，敏捷秃鹰，用于智能处理:远程驾驶飞机的人工智能平台
2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324277
Darrek Isereau, C. Capraro, Éric Côté, Mark D. Barnell, Courtney Raymond
{"title":"Utilizing high-performance embedded computing, agile condor, for intelligent processing: An artificial intelligence platform for remotely piloted aircraft","authors":"Darrek Isereau, C. Capraro, Éric Côté, Mark D. Barnell, Courtney Raymond","doi":"10.1109/INTELLISYS.2017.8324277","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324277","url":null,"abstract":"A newly invented, high performance, pod-based computer architecture, called Agile Condor (patent pending), has been designed and developed. Agile Condor is supporting autonomous operations by providing a platform for the innovative use of artificial intelligence, machine learning, and decision making algorithms upstream, near the information source, where the data is collected. In September 2016, experimental tests successfully demonstrated the ability to implement advanced neural networks and deep learning techniques on Agile Condor. We continue to use this new processing architecture, algorithms and bio-inspired computing methods to demonstrate existing, refine emerging and invent new artificial intelligence techniques that are highly applicable and needed for sensor platforms. For the first time ever, and in real-time, the system demonstrated: image processing, video processing and pattern recognition through the use of deep convolutional neural networks. Because of Agile Condor's modular architecture and performance characteristics, the system is providing flexible computational resources that will continue to bring new artificial intelligence (AI) capabilities closer to sensor platforms.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128827617","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: 7
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