2017 Intelligent Systems Conference (IntelliSys)最新文献_第3页

A tourist advisor based on a question answering system 基于问答系统的旅游顾问

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324280

Antonio Guerrieri, G. Ghiani, Andrea Manni

引用次数: 1

A review of technician and task scheduling problems, datasets and solution approaches 回顾技术人员和任务调度问题，数据集和解决方案

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324306

Amy Khalfay, Alan Crispin, Keeley A. Crockett

{"title":"A review of technician and task scheduling problems, datasets and solution approaches","authors":"Amy Khalfay, Alan Crispin, Keeley A. Crockett","doi":"10.1109/INTELLISYS.2017.8324306","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324306","url":null,"abstract":"This paper aims to provide a review of technician and task scheduling problems. A technician and task scheduling problem requires the creation of timetables for employees in order to serve customers, each having skill requirements. Optimised scheduling can reduce the cost of a workforce and save the employer's significant amount of money whilst maintaining customer and workforce satisfaction. This problem is an NP-hard combinatorial optimisation problem. Over the years, many technician and task scheduling problems have been studied. This is due to the real world nature of the problem, that occurs in many industries such as service maintenance, home healthcare, call centres, forest management and housing development projects. Each problem studied has included a diverse range of constraints such as teaming, priority levels, outsourcing, precedence, routing, time windows and tools and spare parts. We present a study of the problems in the literature, datasets and solution approaches. This review aims to identify promising areas for further research such as focusing on multi-period problems, technician unavailability, teaming and precedence constraints.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"34 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":"123355055","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

Decision support in condition-based maintenance of a fleet of cyber-physical systems: A fuzzy logic approach 网络物理系统舰队基于状态维护的决策支持:一种模糊逻辑方法

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324362

John Mbuli, D. Trentesaux, J. Clarhaut, G. Branger

引用次数: 8

Content analysis of MOOC forums: The characteristics of the learners' discourse in forums MOOC论坛内容分析:论坛中学习者话语的特点

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324235

Anat Cohen, Udi Shimony, Rafi Nachmias

引用次数: 3

A heuristic attack detection approach using the “least weighted” attributes for cyber security data 基于“最小加权”属性的网络安全数据启发式攻击检测方法

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324260

Loubna Dali, Kato Mivule, H. El-Sayed

{"title":"A heuristic attack detection approach using the “least weighted” attributes for cyber security data","authors":"Loubna Dali, Kato Mivule, H. El-Sayed","doi":"10.1109/INTELLISYS.2017.8324260","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324260","url":null,"abstract":"The continuous advance in recent cloud-based computer networks has generated a number of security challenges associated with intrusions in network systems. With the exponential increase in the volume of network traffic data, involvement of humans in such detection systems is time consuming and a non-trivial problem. Secondly, network traffic data tends to be highly dimensional, comprising of numerous features and attributes, making classification challenging and thus susceptible to the curse of dimensionality problem. Given such scenarios, the need arises for dimensional reduction, feature selection, combined with machine-learning techniques in the classification of such data. Therefore, as a contribution, this paper seeks to employ data mining techniques in a cloud-based environment, by selecting appropriate attributes and features with the least importance in terms of weight for the classification. Often the standard is to select features with better weights while ignoring those with least weights. In this study, we seek to find out if we can make prediction using those features with least weights. The motivation is that adversaries use stealth to hide their activities from the obvious. The question then is, can we predict any stealth activity of an adversary using the least observed attributes? In this particular study, we employ information gain to select attributes with the lowest weights and then apply machine learning to classify if a combination, in this case, of both source and destination ports are attacked or not. The motivation of this investigation is if attributes that are of least importance can be used to predict if an attack could occur. Our preliminary results show that even when the source and destination port attributes are used in combination with features with the least weights, it is possible to classify such network traffic data and predict if an attack will occur or not.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"12 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":"123616987","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

From data exploration to semantic model of customer 从数据挖掘到客户语义模型

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324322

Ilona Pawełoszek, J. Korczak

引用次数: 4

An evolutionary computing approach to diabetic foot analysis 糖尿病足分析的进化计算方法

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324342

J. Neves, H. Vicente, D. Couto, João Azevedo, J. Pereira, Filipa Ferraz, Victor Alves, J. Neves

引用次数: 0

Hybrid functional networks for PVT characterisation 用于PVT表征的混合功能网络

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324242

Munirudeen A. Oloso, M. G. Hassan, M. Bader-El-Den, J. Buick

引用次数: 1

Toward learning intracranial hypertension through physiological features: A statistical and machine learning approach 通过生理特征学习颅内高压:统计学和机器学习方法

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324324

Parisa Naraei, Mohsen Nouri, Alireza Sadeghian

{"title":"Toward learning intracranial hypertension through physiological features: A statistical and machine learning approach","authors":"Parisa Naraei, Mohsen Nouri, Alireza Sadeghian","doi":"10.1109/INTELLISYS.2017.8324324","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324324","url":null,"abstract":"Intracranial pressure (ICP) monitoring is one of the most routinely conducted procedures in neurocritical care units to monitor comatose patients having Traumatic Brain Injuries (TBI). The existing clinical standard of care using insertion of a transducer or catheter is based on an invasive method which always has certain risks. This study found some significant correlations between ICP and routinely monitored physiological signals in TBI patients. The results indicate that Heart Rate, Pulse, Diastolic Arterial Blood Pressure, Respiration, Mean Arterial Blood Pressure and ECG ST segment levels are significantly correlated with ICP and have the potential to be reliable predictors of intracranial hypertension (ICH). In this paper an algorithm is presented to extract increased ICP episodes and the corresponding physiological signals from large datasets. Episodes of “Intracranial hypertension onset”, “Intracranial Hypertension” and “Severe Intracranial Hypertension” were detected and differentiated based on the ICP levels. It was discovered that there is a potential predictive power in the dynamical information of routinely monitored physiological signals in TBI patients.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"52 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":"129384705","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: 6

A new technique for saving water trapped inside home water networks 一种新技术，用于节约困在家庭供水系统中的水

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324284

Y. Osais, J. Alsadah, M. Siddiqui

引用次数: 1