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Clients segmentation according to their domestic energy consumption by the use of self-organizing maps

Clients segmentation according to their domestic energy cons...

引用

international conference on European Electricity Market, EEM

作者： Ignacio Benitez Sanchez Ignacio Delgado Espinos Laura Moreno Sarrion Alfredo Quijano Lopez Isabel Navalon Burgos Institute of Electric Technology (ITE) Parque Tecnológico Valencia Spain Iberdrola Distribución S.A. Spain

the CENIT research project GAD (Demand Active Management), partly supported by the Spanish government, has as its objective the demand side management (DSM) of domestic end-users, smoothing the peaks of energy demand, therefore enhancing the conditions of transport and distribution networks and the quality of energy delivery and service. One of the objectives in the development of the project is the classification of users according to their patterns of daily energy load profiles. Based on daily hour measures from a sample of residential users, a self-organizing map (SOM) has been trained to classify users according to a specific number of resulting patterns of daily load profiles, attached to a number of indices that define the users' energy consumption. the so-trained SOM classifier allows the characterization of future users based on their load profiles, thus estimating their energy consumption habits and potentially manageable energy.

关键词： Energy consumption Self organizing feature maps Energy management Project management Quality management Energy measurement Data mining Smoothing methods Knowledge management pattern recognition

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An elastic graph dynamic link model for tropical cyclone pattern recognition

An elastic graph dynamic link model for tropical cyclone pat...

引用

international conference on Neural Information Processing

作者： R.S.T. Lee J.N.K. Liu Department of Computing Hong Kong Polytechnic University Hong Kong China

In this paper, an elastic graph dynamic link model (EGDLM) is proposed to automate the satellite interpretation process (Dvorak technique) and provide an objective analysis for tropical cyclones. the method integrates dynamic link architecture (DLA) for neural dynamics and the active contour model (ACM) for contour extraction of tropical cyclone (TC) patterns. Using satellite pictures provided by National Oceanic and Atmospheric Administration (NOAA), 145 tropical cyclone cases from the period between 1990 to 1998 were extracted for the study. An overall correct rate for TC classification was found to be above 95%. For hurricanes with distinct "eye" formation, the model reported a deviation within 3 km from the "actual eye" location, which was obtained from the aircraft measurement of minimum surface pressure by reconnaissance.

关键词： Tropical cyclones Satellites Atmospheric modeling Active contours Hurricanes Aircraft Sea measurements Pressure measurement Sea surface Reconnaissance

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Experimental analysis of the relationship between neural and muscular recordings during hand control

Experimental analysis of the relationship between neural and...

引用

IEEE/RAS-EMBS international conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Emiliano Noce Loredana Zollo Angelo Davalli Rinaldo Sacchetti Eugenio Guglielmelli Unit of Biomedical Robotics and Biomicrosystems Universita Campus Biomedico di Roma Rome Italy INAIL Centro Protesi Bologna Italy

ISBN: (纸本)9781509032884

In this study, the relationship between the electromyographic (EMG) and neural signals (ENG) recorded during hand control is investigated. EMG and ENG signals are both recorded from an amputee during the ENG control of a hand prosthesis. the EMG signal was processed with standard techniques to compute the envelope. For the neural signal, the processing involved the evaluation of the energy of the recordings with a moving average and the best combination of window width and multiplier for the standard deviation was searched for. Hence, a new curve for the neural signal was generated, gathering information about amplitude and occurrence of action potentials during the motion task. Its correlation with the EMG envelope was studied by means of a parameter purposely conceived, which accounts for the ratio between the areas under the two curves. the proposed approach has been applied to little finger flexion and open hand tasks. Ten movements for each task have been processed for the aim of this study and a comparative analysis with the Pearson coefficient has been carried out.

关键词： Electromyography Standards Electrodes Prosthetics Muscles pattern recognition Robot sensing systems

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Coordinated expansion planning based on a cost benefit analysis

Coordinated expansion planning based on a cost benefit analy...

引用

international conference on European Electricity Market, EEM

作者： Antonis Papaemmanouil Goran Andersson Power Systems Laboratory of Electrical and Computer Engineering Swiss Federal Institute of Technology Zurich Switzerland

Nowadays, the power production and transmission are substantial elements for the society, and will probably play a more important role in the future, but are also associated with various negative effects, which impose additional costs, the so called external costs. As long as these are not included in the electricity prices, market failures most often arise. In order to define expansion projects, right price signals are needed. thus, the internalization of external costs in power production, which typically leads to higher marginal production costs for conventional power plants, can help in the identification of sustainable future transmission and production plans. the aggregated benefit of the internalization of external costs is usually higher than the social welfare deficit, depending on the energy mix, and can be further used in order to reinforce the existing electricity network, financing ldquogreenrdquo investments. the idea in this paper is the coordination of generation, transmission and policy planning, and their interaction, towards a common electricity market. the proposed methodology is based on a cost benefit analysis in order to support the final decision taken. Several scenarios, considering demand changes, power plants installations and investments in transmission are implemented by means of a European ldquocopperplaterdquo model.

关键词： Cost benefit analysis Pricing Energy consumption Procurement Data mining Artificial intelligence pattern recognition Computational intelligence Statistical analysis Consumer behavior

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Empowering Deaf Community in Healthcare Communication: 1D-CNN-Based Algerian Sign Language recognition System

Empowering Deaf Community in Healthcare Communication: 1D-CN...

引用

international conference on pattern Analysis and Intelligent Systems (PAIS)

作者： Lyna Bellil Maissoun Ghouzlen Ghiri Abdennour Boulesnane Department of IFA Faculty of NTIC Abdelhamid Mehri University Constantine Algeria BIOSTIM Laboratory Faculty of Medicine Salah Boubnider University Constantine Algeria

ISBN: (数字)9798350350265

ISBN: (纸本)9798350350272

Language is the fundamental means of communication in our daily lives, encompassing various aspects of individual behavior. However, for the deaf community, the absence of participation in the language communication system due to hearing impairment results in a significant disability that leads to isolation. this communication barrier has detrimental effects, particularly in healthcare, where communication between patients and doctors is hindered. In this paper, to support the public health of deaf and hard-of-hearing individuals in Algeria, we created an Algerian medical word recognition system based on one-dimensional Convolutional Neural Networks (1D-CNN) trained on a collected dataset of 100 videos. Our model utilizes body landmark points extracted from video frames, enhanced with novel features capturing the spatial relationships and angles between these points. Notably, our proposed 1D-CNN model achieved an exceptional accuracy of 100% for Algerian word recognition. this result underscores the effectiveness of our proposed model as a powerful tool in breaking down communication barriers for the deaf community in Arabic-speaking countries, with a particular focus on Algeria.

关键词： Sign language Computational modeling Assistive technologies Feature extraction pattern recognition Convolutional neural networks Public healthcare

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A method for automatic detection of traffic incidents using neural networks

A method for automatic detection of traffic incidents using ...

引用

Vehicle Navigation and Information Systems conference

作者： I. Ohe H. Kawashima M. Kojima Y. Kaneko Matsushita Communication Industrial Company Limited Yokohama Japan Faculty of Science and Technology Keio University Yokohama Japan

One of the most important aspects of traffic management systems is their ability to detect traffic incidents such as accidents, disabled vehicles, and obstacles on the road. the incidents affect highway drivers and cause traffic congestion, so an immediate and automatic detection method is desired. We think that the changes in traffic average in case of traffic incidents have certain patterns different from the normal case. Our research tries to detect traffic incidents immediately and automatically by using neural networks, which use one minute average traffic data as input, and decide whether an incident has occurred or not. To train the network we used traffic data from various locations where accidents had occurred and not. the former are generated by a micro simulator and the latter are collected by using ultrasonic vehicle detectors. To reduce the number of false detections so as to improve the process of training of the neural network, we added some data with similar average change patterns as observed when incidents occurred. As a result, we confirmed that adding enough combinations of similar average change patterns was very effective in increasing the recognition rate and to reduce the number of false detections.

关键词： Telecommunication traffic Neural networks Vehicle detection Traffic control Road accidents Road vehicles pattern recognition Technology management Gas detectors Automated highways

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Enhancing Interoperability of Digital Twin in the Maintenance phase of Lifecycle

Enhancing Interoperability of Digital Twin in the Maintenanc...

引用

international conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Dedy Ariansyah Bens Pardamean Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

In today's digitalization era, asset management has evolved following the rapid adoption of information systems and digital technologies. In the maintenance phase of the asset, Digital Twin (DT) emerges as an effective approach to improve failure recognition and structural damage prediction through DT-driven Prognostic and Health Monitoring (PHM). As a result, DT allows asset manager to proactively plan maintenance strategy to improve the availability of the assets. However, to reduce asset downtime in a cost-effective and time efficient manner, DT for maintenance phase needs to be integrated with other software systems that manage the provision of maintenance service and spare part such as computerized maintenance management system (CMMS) or Enterprise Resource Planning (ERP). Nevertheless, many of the developed DT in PHM were not equipped with semantic data model and hence, lacks interoperability with other systems (e.g., other DT or non-DT system) and limits the effective use of the DT. To qualify as an effective DT, it needs a semantical-enabled interface to connect with data and models from various domain to enable DT-driven decision-making. this paper leverages a rule-based ontology reasoning model to enhance DT interoperability with other maintenance software systems. the results depicts that the developed model paves a way for an effective use of DT-driven system in asset maintenance management.

关键词： Ontologies Software systems Data models Enterprise resource planning Digital twins Prognostics and health management Interoperability

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Mining closed sequential patterns - A novel approach

Mining closed sequential patterns - A novel approach

引用

international conference on New Trends in Information and Service Science, NISS

作者： Sophia Banu Rahaman M. Shashi Department of Information Technology Manipal University Dubai UAE Department of Computer Science and Systems Engineering Andhra University College of Engineering Visakhapatnam India

ISBN: (纸本)9781467308762

Generation of data with an inherent sequential nature is the order of today's digital society. this kind of data is composed of discrete events that have either a temporal or spatial ordering and is generally obtained by sectors like telecommunication networks, E-Commerce, Internet servers and gene databases, medical domain to name a few. the ability to explore and exploit the sequential nature of the data for prediction leverages strategic decision making and problem solving. Symbolic sequence data consists of long sequence of ordered events with possible relationships among them. Symbolic sequence mining techniques aim at extracting frequent sequential patterns from huge collections of event sequences based on the user defined minimum support threshold. For a given set of symbols / events due to the possible repetition of events an infinite large number of sequences is possible and hence the task of extracting frequent sequences is complex. Whereas in closed sequential patterns, the set of sequential patterns automatically eliminates a lot of redundancy from the set of all frequent sequences and provides a concise set of patterns maintaining completeness. A novel approach is proposed for extracting closed sequential patterns which can be applied to fields that prefer complete and concise number patterns for analysis to aid the process of effective decision making.

关键词： Sequential pattern Mining Closed Sequential patterns Aggregate Tree Condensed AggregateTtree Sequential Sequences Number patterns gene banks decision making spatial ordering SEQUENTIAL pattern recognition

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Revisiting the Benefits of Knowledge Distillation against Adversarial Examples

Revisiting the Benefits of Knowledge Distillation against Ad...

引用

Data Science and Information Technology (DSIT), international conference on

作者： Jiawen Li Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

Deep neural networks (DNNs) have always been a popular base model in many image classification tasks. However, some recent works suggest that there are some man made images will easily lead DNNs give wrong predictions. these images are generated by adding some invisible perturbations into clean images, which are the so-called adversarial examples. Since they are almost similar to original data but can fool DNNs, adversarial examples can bring the insecurity to many life-critical applications. Adversarial knowledge distillation is a positive defense method to attach improved robustness to the target DNNs against adversarial examples. In distillation, student models are trained by soft labels coming from robust pre-trained teacher networks. However, it is hard for researchers to ensure that supervised information comes from a better teacher model. In this paper, We focus on four potential factors of the teacher that may have an effect to the distillation performance of student model, and investigate whether and when they can boost the model robustness against adversarial attacks. Multiple quantitative experiment illustrate that these factors have impact on the distillation process and these results can be considered to choose a better teacher model. Further studies can focus on the combination of adversarial knowledge distillation and other defense schemes. Empirical results in this paper may also help select proper teacher in new complex distillation tasks.

关键词：

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Spatio-temporal pattern Analysis for EEG Classification in Rapid Serial Visual Presentation Task 19

Spatio-temporal Pattern Analysis for EEG Classification in R...

引用

Proceedings of the 6th international conference on bioinformatics Research and Applications

作者： Bowen Li Zhiwen Liu Xiaorong Gao Yanfei Lin School of Information and Electronics Beijing Institute of Technology Beijing China School of Medicine Tsinghua University Beijing China

ISBN: (纸本)9781450372183

this study will explore an algorithm of spatio-temporal pattern analysis for electroencephalographic (EEG) classification in the rapid serial visual presentation (RSVP) task. In this algorithm, the spatial low-rank and temporal-frequency sparse priors are exploited to train the supervised spatial and temporal filters. the discriminant features are extracted by the supervised spatio-temporal filters and classified by support vector machine. the EEG signals were recorded from a total of 12 subjects under RSVP task and were used as training and testing data. the average true positive rate of classification is 79%, and the average false positive rate is only 3.4%. the classification results show that the proposed algorithm has better performance in the target detection than HDCA and SWFP.

关键词： Spatio-temporal pattern Discriminant features EEG Low-rank Sparse prior

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