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Recognition of air-conditioner operation from indoor air temperature and relative humidity by a data mining approach

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ENERGY AND BUILDINGS 2016年 111卷 233-241页

作者： Zhou, Hao Qiao, Lifeng Jiang, Yi Sun, Hejiang Chen, Qingyan Tianjin Univ Sch Environm Sci & Engn Tianjin Key Lab Indoor Air Environm Qual Control Tianjin 300072 Peoples R China Intelligent Green Solut Ltd Beijing 100084 Peoples R China Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA

The variety of occupant behaviors in buildings have led to a significant mismatch between simulated building energy performance and measured one. It is crucial to collect real occupant behaviors in buildings to achieve accurate simulation purpose, although there exists a great challenge due to the cost of monitoring devices and privacy concerns. This study proposed an inexpensive and minimally intrusive method, to recognize behavior information from environment parameters by data mining approach. To validate this method, experiments were conducted in three bedrooms. Two types of classification algorithms were developed to recognize AC operations from the experiment data of indoor air temperature and relative humidity. Two types of recognition rules were generated from algorithm training in one dataset, and tested in the other datasets. Based on the testing results, the performance of the two algorithms were evaluated and compared. The results indicated that the C4.5 decision tree algorithm was not suitable for mining AC operations, while the curve description algorithm had good performance in processing the time-series curves of air temperature and relative humidity. Through this experiment, it is confirmed that AC operations can be recognized from indoor air temperature and relative humidity by data mining approach. The main contribution of this study is that a promising approach was developed, which is inexpensive and minimally intrusive on gathering and interpreting information about occupants' daily behaviors. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Occupant behavior Air-conditioner operation Data mining classification algorithm C4.5 decision tree Curve description Time-series curve

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Load level forwarding work element analysis based on automatic follow-up data

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SILVA FENNICA 2016年第3期50卷

作者： Manner, Jussi Palmroth, Lauri Nordfjell, Tomas Lindroos, Ola Forestry Res Inst Sweden Skogforsk Uppsala Sci Pk SE-75183 Uppsala Sweden John Deere Forestry POB 472 FI-33101 Tampere Finland Swedish Univ Agr Sci Dept Forest Biomat & Technol SE-90183 Umea Sweden

Recent developments in on-board technology have enabled automatic collection of follow-up data on forwarder work. The objective of this study was to exploit this possibility to obtain highly representative information on time consumption of specific work elements (including overlapping crane work and driving), with one load as unit of observation, for large forwarders in final felling operations. The data used were collected by the John Deere TimberLink system as nine operators forwarded 8868 loads, in total, at sites in mid-Sweden. Load-sizes were not available. For the average and median extraction distances (219 and 174 m, respectively), Loading, Unloading, Driving empty, Driving loaded and Other time effective work (PM) accounted for ca. 45, 19, 8.5, 7.5 and 14% of total forwarding time consumption, respectively. The average and median total time consumptions were 45.8 and 42.1 minutes/load, respectively. The developed models explained large proportions of the variation of time consumption for the work elements Driving empty and Driving loaded, but minor proportions for the work elements Loading and Unloading. Based on the means, the crane was used during 74.8% of Loading PM time, the driving speed was nonzero during 31.9% of the Loading PM time, and Simultaneous crane work and driving occurred during 6.7% of the Loading PM time. Time consumption per load was more strongly associated with Loading drive distance than with extraction distance, indicating that the relevance of extraction distance as a main indicator of forwarding productivity should be re-considered.

关键词： haulage cut-to-length logging harvesting data gathering automatic recording classification algorithm Hidden Markov Models

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Research on Node Detection algorithm of Tomato Seedlings Based on Digital Image

Research on Node Detection Algorithm of Tomato Seedlings Bas...

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2017 2nd International Conference on Computer, Mechatronics and Electronic Engineering(CMEE 2017)

作者： Xue-guan ZHAO Xiu WANG Jin-wei ZHANG Kai JIANG Shuai SU Beijing Research Center for Intelligent Equipment Technology in Agricultural National Engineering Research Center Information Technology in Agricultural

According to a large number of studies, the internode length is sensitive to environmental stress. In the quality testing of tomato seedlings, optimization algorithm is proposed to extract tomato seedling stem node, using line scan algorithm to extract the main stem area, improve the accuracy of the main stem region selection, and finally through the bag of words model extract main stem node, this method has good robustness. Through the test, it is found that the accuracy of main stem node detection is lowest at fourth nodes, which is 81%.These results demonstrate that our method has the ability to evaluate the vigor of tomato seedlings quickly and accurately.

关键词： Image processing Seedling detection classification algorithm Machine vision

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Computerized Adaptive Test vs. decision trees: Development of a support decision system to identify suicidal behavior

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JOURNAL OF AFFECTIVE DISORDERS 2016年第0期206卷 204-209页

作者： Delgado-Gomez, D. Baca-Garcia, E. Aguado, D. Courtet, P. Lopez-Castroman, J. Carlos III Univ Dept Stat Madrid Spain IIS Jimenez Diaz Fdn CIBERSAM Dept Psychiat Madrid Spain Columbia Univ Dept Psychiat New York State Psychiat Inst New York NY USA Univ Autonoma Madrid Inst Ingn Conocimiento Madrid Spain CHRU Montpellier Montpellier France Univ Montpellier Montpellier France INSERM Unit 1061 Montpellier France CHU Nimes Nimes France

Background: Several Computerized Adaptive Tests (CATs) have been proposed to facilitate assessments in mental health. These tests are built in a standard way, disregarding useful and usually available information not included in the assessment scales that could increase the precision and utility of CATs, such as the history of suicide attempts. Methods: Using the items of a previously developed scale for suicidal risk, we compared the performance of a standard CAT and a decision tree in a support decision system to identify suicidal behavior. We included the history of past suicide attempts as a class for the separation of patients in the decision tree. Results: The decision tree needed an average of four items to achieve a similar accuracy than a standard CAT with nine items. The accuracy of the decision tree, obtained after 25 cross-validations, was 81.4%. A shortened test adapted for the separation of suicidal and non-suicidal patients was developed. Conclusion: CATs can be very useful tools for the assessment of suicidal risk. However, standard CATs do not use all the information that is available. A decision tree can improve the precision of the assessment since they are constructed using a priori information. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Suicide attempt classification algorithm Evaluation Screening Performance

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A classification algorithm for Ground Moving Targets Based on Magnetic Sensors

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Defence Technology（防务技术） 2011年第1期7卷 52-58页

作者：崔逊学刘綦刘坤 Military Network Engineering Department Artillery Academy of PLA Intelligence Information Department Artillery Command Academy of PLA

A novel classification algorithm based on abnormal magnetic signals is proposed for ground moving targets which are made of ferromagnetic material. According to the effect of diverse targets on earth's magnetism,the moving targets are detected by a magnetic sensor and classified with a simple computation method. The detection sensor is used for collecting a disturbance signal of earth magnetic field from an undetermined target. An optimum category match pattern of target signature is tested by training some statistical samples and designing a classification machine. Three ordinary targets are researched in the paper. The experimental results show that the algorithm has a low computation cost and a better sorting accuracy. This classification method can be applied to ground reconnaissance and target intrusion detection.

关键词： information processing magnetic sensor abnormal magnetic signal target detection target classification classification algorithm

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Intelligent System for Learning of Comfort Preferences to Help People with Mobility Limitations 4th

Intelligent System for Learning of Comfort Preferences to He...

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4th KES International Conference on Innovation in Medicine and Healthcare (InMed)

作者： Lopez, Sandra Baltazar, Rosario Lemus Zuniga, Lenin Angel Casillas, Miguel Alanis, Arnulfo Mateo Pla, Miguel A. Zamudio, Victor Mendez, Guillermo Inst Tecnol Leon Guanajuato Mexico Univ Politecn Valencia Valencia Spain Inst Tecnol Tijuana Tijuana Baja California Mexico

ISBN: (纸本)9783319396873;9783319396866

It is essential to provide better living conditions for vulnerable sectors of society using technology and it is important to consider that the technology must be friendly with users, and even adapt to their needs and desires. We can see in current systems the user has to learn to use the devices or services, but with an intelligence system, the technology is a very effective way to determine the needs of users. In this research, we present the physical implementation of a system to assist users and patients in daily activities or duties. The system include a architecture of agents where a Deliberative agent learns from the interaction with the user, in this way the system detects thermal comfort preferences for give an automatic assistance. We propose an algorithm with a proactive stage and learning stage adapting a classification algorithm. We select the classification algorithm with the best performance using cross validation. The algorithms of pattern recognition was Back Propagation neural network, Naive Bayes, Minimum Distance and KNN (k near neighbor). Our motivation of this work was to help people with motor difficulties or people who use wheelchairs, for this reason it was essential to use a wireless controller and use a friendly interface. The system was implemented in a testbed at the Leon Institute of Technology in Guanajuato, Mexico, and include sensors of humidity and temperature, windows actuators, wireless agents and other devices. Experimental tests were performed with data collected during a time period and using use cases. The results were satisfactory because it was not only possible remote assistance by the user but it was possible to obtain user information to learn comfort preferences using vector features proposed and selecting the classification algorithm with better performance.

关键词： Assist in daily activities Movement restrictions Architecture of agents Learning of thermal comfort Pattern recognition classification algorithm

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An Extraction Method of Hyponymy based on Multiple Data Sources Fusion 7

An Extraction Method of Hyponymy based on Multiple Data Sour...

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7th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Wang, Shuqi Feng, Xiao Zhang, Shuwu Yin, Chengcheng Commun Univ China Dearpartment Signal & Informat Syst Beijing Peoples R China Chinese Acad Sci Inst Automat Beijing Peoples R China

ISBN: (纸本)9781467399043

Hyponymy is one of the most critical semantic relations, which contributes magnificently to semantic dictionary, information retrieval etc. In this paper, a method of extracting hyponymy is proposed based on multiple data sources fusion, which convert the extraction of hyponymy to the extraction of hypernyms for target words. First, mining candidate hypernyms for the target words based on search engine, encyclopedia resources and core suffix words. Second, fusing the candidates from the above data sources. At last, the classification algorithm is used to filter the noise and extract the hypernyms, which is a quite mature machine learning algorithm. There is hyponymy between the target words and their correctly extracted hypernyms. The experimental results show that the highest accuracy rate of hyponymy extraction reaches 0.832 using the proposed method.

关键词： hyponymy multiple data dources fusion mining candidate hypernyms classification algorithm hypernym extraction

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Predicting IT Employability Using Data Mining Techniques 3

Predicting IT Employability Using Data Mining Techniques

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3rd International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)

作者： Piad, Keno C. Dumlao, Menchita Ballera, Melvin A. Ambat, Shaneth C. Bulacan State Univ Sch Comp Studies Malolos Philippines AMA Univ Sch Grad Studies Quezon City Philippines AMA Univ Sch Comp Studies Quezon City Philippines

ISBN: (纸本)9781467393799

Researchers in higher education are beginning to explore the potential of data mining in analyzing data for the purpose of giving quality service and needs of their graduates. Thus, educational data mining emerges as one tools to study academic data to identify patterns and help for decision making affecting the education. This paper predicts the employability of IT graduates using nine variables. First, different classification algorithms in data mining were tested making logistic regression with accuracy of 78.4 is implemented. Based on logistic regression analysis, three academic variables directly affect;IT_Core, IT_Professional and Gender identified as significant predictors for employability. The data were collected based on the five year profiles of 515 students randomly selected at the placement office tracer study.

关键词： decision tree classification algorithm employability prediction analytics data accuracy

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Improved Method of Character Traits Based on Wechat Dataset 2

Improved Method of Character Traits Based on Wechat Dataset

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2nd IEEE International Conference on Computer and Communications (ICCC)

作者： Li Qinfeng Zhou Xiaofeng Jinling Inst Technol Dept Basic Nanjing Jiangsu Peoples R China Hohai Univ Coll Comp & Informat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781467390262

In recent years the communication tool Wechat is used widely, however few attention to the academic research. Moreover, there are very few studies about identifying character traits from its data. Previously a method based on data features to decide character traits was proposed in our paper. Here an improve method of the feature set is given through refining new features, and building the feature subset employing feature extracting algorithm. Then it compares the contributions of the original feature set with the feature subset through several classification algorithms. Experimental results show that the classification based on data features can efficiently identify character traits.

关键词： feature extracting algorithm feature subset classification algorithm data features

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Head-Mounted Sensory Augmentation Device: Comparing Haptic and Audio Modality 5th

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5th International Conference on Biomimetic and Biohybrid Systems (Living Machines)

作者： Kerdegari, Hamideh Kim, Yeongmi Prescott, Tony J. Univ Sheffield Sheffield Robot Sheffield S Yorkshire England MCI Dept Mech Innsbruck Austria

ISBN: (纸本)9783319424170;9783319424163

This paper investigates and compares the effectiveness of haptic and audio modality for navigation in low visibility environment using a sensory augmentation device. A second generation head-mounted vibrotactile interface as a sensory augmentation prototype was developed to help users to navigate in such environments. In our experiment, a subject navigates along a wall relying on the haptic or audio feedbacks as navigation commands. Haptic/audio feedback is presented to the subjects according to the information measured from the walls to a set of 12 ultrasound sensors placed around a helmet and a classification algorithm by using multilayer perceptron neural network. Results showed the haptic modality leads to significantly lower route deviation in navigation compared to auditory feedback. Furthermore, the NASA TLX questionnaire showed that subjects reported lower cognitive workload with haptic modality although both modalities were able to navigate the users along the wall.

关键词： Sensory augmentation Haptic feedback Audio feedback classification algorithm

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