2017 Intelligent Systems Conference (IntelliSys)最新文献_第10页

Development of intelligent tools for recognizing cockroaches in the forensic entomology context 在法医昆虫学背景下识别蟑螂的智能工具的发展

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324269

María F. Hernández Luquin, E. Santacruz, Rocío A. Lizárraga Morales, C. N. Vázquez, Mariano Gamboa Zúñiga

{"title":"Development of intelligent tools for recognizing cockroaches in the forensic entomology context","authors":"María F. Hernández Luquin, E. Santacruz, Rocío A. Lizárraga Morales, C. N. Vázquez, Mariano Gamboa Zúñiga","doi":"10.1109/INTELLISYS.2017.8324269","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324269","url":null,"abstract":"The study of insects in forensic Entomology is very important for forensic sciences in making certain decisions. The insect identification on forensic Entomology is carried out by the analysis of their taxonomic features. Currently, the insect identification is time-consuming, since it requires specific processes which can be complicated for experts or students who do not have knowledge in Entomology. Developments on computer vision and computational intelligence techniques have facilitated applications of new identification methods based on image processing. Therefore, in this work is proposed a new approach based on extracting features from the images of cockroaches pronotum, such as: texture, color and shape for the classification accuracy of three species of cockroaches — Blattella germanica, Periplaneta Americana, and Arenivaga sp which are common in different areas of Mexico City (Urban and outdoor areas) and due to their relation with humans are important in forensic Entomology cases. The percentage of accuracy of identification using images achieved in this research was 96.2687% using an Artificial Neural Network (ANN) algorithm. The results obtained for the analysis demonstrate that features extracted are useful for the identification of Cockroaches species used.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"114 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":"128210006","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

Multi-dimensional I-vector closed set speaker identification based on an extreme learning machine with and without fusion technologies 基于融合和不融合技术的极限学习机多维i向量闭集说话人识别

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324273

Musab T. S. Al-Kaltakchi, W. L. Woo, S. Dlay, J. Chambers

{"title":"Multi-dimensional I-vector closed set speaker identification based on an extreme learning machine with and without fusion technologies","authors":"Musab T. S. Al-Kaltakchi, W. L. Woo, S. Dlay, J. Chambers","doi":"10.1109/INTELLISYS.2017.8324273","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324273","url":null,"abstract":"In this article, I-vector Speaker Identification (SID) is exploited as a compact, low dimension, fixed length and modern state of the art system. The main structures for this study consist of four combinations of features which depend on Power Normalization Cepstral Coefficient (PNCC) and Mel Frequency Cepstral Coefficient (MFCC) features, with two different compensation approaches which have been previously proposed. The main system is modelled by I-vectors with low dimensions, and we also propose fusion strategies with different higher I-vector dimensions to improve the recognition rate. In addition, cumulative, concatenated, and interleaved fusion techniques are investigated to improve the conventional late fusion presented in our previous work. Moreover, the proposed system employs an Extreme Learning Machine (ELM) for classification purpose, which is efficient, less complex and less time consuming compared with traditional neural network based approaches. The system is evaluated on the TIMIT database for clean and AWGN environments and achieved a recognition rate of 96.67% and 80.83% respectively. The system shows improvements compared with the Gaussian Mixture Model-Universal Background Model (GMM-UBM) in our previously proposed scheme, with an improvement of 1.76% in clean speech and 2.1% for 30dB AWGN and with the highest improvement at 10dB with 43.81%.","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":"115798267","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

CAMABOT, An assistance device for Mexican society with motor disabilities CAMABOT，墨西哥社会运动障碍辅助装置

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324244

Rosaura Anaid Suarez-Santillan, Eduardo Vázquez-Santacruz, Mariano Gamboa-Zúñiga

引用次数: 0

FPGA based image de-hazing architecture for real time applications 基于FPGA的实时图像去雾架构

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324357

Muhammad Naseem Majoka, G. Raja

引用次数: 1

Dependency networks extractions from textual sources — A case study in criminology 依赖网络从文本来源提取-犯罪学案例研究

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324321

M. Trovati

引用次数: 0

An intervention detection framework for collaborative projects 协作项目的干预检测框架

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324300

Elizabeth Sokolowski, Samia Oussena

引用次数: 1

An intelligent system for forex trading: Hybrid ANN with GARCH and intrinsic mode functions 外汇交易智能系统：具有 GARCH 和内在模式函数的混合 ANN

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324331

H. Pathberiya, C. Tilakaratne, L. L. Hansen

{"title":"An intelligent system for forex trading: Hybrid ANN with GARCH and intrinsic mode functions","authors":"H. Pathberiya, C. Tilakaratne, L. L. Hansen","doi":"10.1109/INTELLISYS.2017.8324331","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324331","url":null,"abstract":"Time series forecasting can be viewed as an indispensable topic under discussion in a wide range of fields including, medicine, engineering, finance and economics, etc. As assumed by the conventional time series models static environmental conditions are rare to exist in real life situations. This study addressed this issue in case of financial markets by proposing an intelligent decision support system for Forex (Foreign Exchange) trading which can be used even under dynamic environmental conditions. The study proposes to identify clusters of time points relevant to dynamic environments defined by the release of scheduled news items. Then the proposed system utilizes the relevant database of time points to derive the forecast. The proposed intelligent system is supported with a hybrid neural network approach which combines generalized autoregressive conditional heteroskedasticity (GARCH) volatility estimates and intrinsic mode functions derived from Empirical Mode Decomposition. The incorporation of clustering of time points found significance in the forecasting process utilized in the proposed intelligent system over the method which ignores clustering. Moreover, the proposed system is efficient enough in delivering the trading decision yielding instant profitable opportunities, 57% of times and aggregated profit over hundred trading positions remained positive at almost all the time points.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"23 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":"126617600","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

Developing video games with elementary adaptive artificial intelligence in unity: An intelligent systems approach 用基本自适应人工智能开发视频游戏:一种智能系统方法

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324230

A. Meliones, Ioannis Plas

{"title":"Developing video games with elementary adaptive artificial intelligence in unity: An intelligent systems approach","authors":"A. Meliones, Ioannis Plas","doi":"10.1109/INTELLISYS.2017.8324230","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324230","url":null,"abstract":"Video games have increasingly demonstrated a great deal of audiovisual realism, in par with the massive performance improvement of computer systems. At the same time, their Artificial Intelligence (AI) component falls short in terms of realism because it is usually based on non-adaptive methods. Adaptive AI mechanisms can help increase video game realism allowing the game to adapt in real-time to the game progress and the user behavior. Following a short overview of the progress of AI in video games in the past years, this paper highlights the creation of modern video games with basic and elementary adaptive game AI using the Unity game development framework. Particular emphasis is on the details of the AI component. First, a shooter game with basic AI is created. Finally, an action-adventure video game is created featuring elementary case-based adaptive AI. The objective in this game is to create enemies which are able to perceive changes in the environment and adapt their strategies accordingly. Proposed AI practices can migrate into relevant real world applications, such as video surveillance and intrusion detection systems, mission critical autonomous networked patrolling and/or save and rescue robots, vision and hearing assistive applications, intelligent video and behavioral analytics to detect and predict threats etc.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"6 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":"127059438","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

Microrecording of writer's cramp signals with indigenously developed advanced real-time multi-channel intelligent-EMG-system 国产先进实时多通道智能肌电系统对作家痉挛信号的微记录

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324216

V. R. Raju, B. Roopam, K. Rukmini, G. R. Chakravarthy, Anuradha Boya

引用次数: 0

Features extracted from APPES to enable the categorization of heavy-duty vehicle drivers 从APPES中提取的特征，用于对重型车辆驾驶员进行分类

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324336

Iulian Carpatorea, Sławomir Nowaczyk, Thorsteinn S. Rögnvaldsson, J. Lodin

{"title":"Features extracted from APPES to enable the categorization of heavy-duty vehicle drivers","authors":"Iulian Carpatorea, Sławomir Nowaczyk, Thorsteinn S. Rögnvaldsson, J. Lodin","doi":"10.1109/INTELLISYS.2017.8324336","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324336","url":null,"abstract":"Improving the performance of systems is a goal pursued in all areas and vehicles are no exception. In places like Europe, where the majority of goods are transported over land, it is imperative for fleet operators to have the best efficiency, which results in efforts to improve all aspects of truck operations. We focus on drivers and their performance with respect to fuel consumption. Some of the relevant factors are not accounted for in available naturalistic data, since it is not feasible to measure them. An alternative is to set up experiments to investigate driver performance but these are expensive and the results are not always conclusive. For example, drivers are usually aware of the experiment's parameters and adapt their behavior. This paper proposes a method that addresses some of the challenges related to categorizing driver performance with respect to fuel consumption in a naturalistic environment. We use expert knowledge to transform the data and explore the resulting structure in a new space. We also show that the regions found in APPES provide useful information related to fuel consumption. The connection between APPES patterns and fuel consumption can be used, for example, cluster drivers in groups that correspond to high or low performance.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"18 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":"121357554","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