Artículos de revistas: "Event-based evaluation"

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Yılmaz, Özgün, Camille Simon-Chane y Aymeric Histace. "Evaluation of Event-Based Corner Detectors". Journal of Imaging 7, n.º 2 (3 de febrero de 2021): 25. http://dx.doi.org/10.3390/jimaging7020025.

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Bio-inspired Event-Based (EB) cameras are a promising new technology that outperforms standard frame-based cameras in extreme lighted and fast moving scenes. Already, a number of EB corner detection techniques have been developed; however, the performance of these EB corner detectors has only been evaluated based on a few author-selected criteria rather than on a unified common basis, as proposed here. Moreover, their experimental conditions are mainly limited to less interesting operational regions of the EB camera (on which frame-based cameras can also operate), and some of the criteria, by definition, could not distinguish if the detector had any systematic bias. In this paper, we evaluate five of the seven existing EB corner detectors on a public dataset including extreme illumination conditions that have not been investigated before. Moreover, this evaluation is the first of its kind in terms of analysing not only such a high number of detectors, but also applying a unified procedure for all. Contrary to previous assessments, we employed both the intensity and trajectory information within the public dataset rather than only one of them. We show that a rigorous comparison among EB detectors can be performed without tedious manual labelling and even with challenging acquisition conditions. This study thus proposes the first standard unified EB corner evaluation procedure, which will enable better understanding of the underlying mechanisms of EB cameras and can therefore lead to more efficient EB corner detection techniques.

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Vogler, Arne y Florian Ziel. "Event-Based Evaluation of Electricity Price Ensemble Forecasts". Forecasting 4, n.º 1 (29 de diciembre de 2021): 51–71. http://dx.doi.org/10.3390/forecast4010004.

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The present paper considers the problem of choosing among a collection of competing electricity price forecasting models to address a stochastic decision-making problem. We propose an event-based evaluation framework applicable to any optimization problem, where uncertainty is captured through ensembles. The task of forecast evaluation is simplified from assessing a multivariate distribution over prices to assessing a univariate distribution over a binary outcome directly linked to the underlying decision-making problem. The applicability of our framework is demonstrated for two exemplary profit-maximization problems of a risk-neutral energy trader, (i) the optimal operation of a pumped-hydro storage plant and (ii) the optimal trading of subsidized renewable energy in Germany. We compare and contrast the approach with the full probabilistic and profit–loss-based evaluation frameworks. It is concluded that the event-based evaluation framework more reliably identifies economically equivalent forecasting models, and in addition, the results suggest that an event-based evaluation specifically tailored to the rare event is crucial for decision-making problems linked to rare events.

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Lu, Jing y Vincent Ng. "Span-Based Event Coreference Resolution". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 15 (18 de mayo de 2021): 13489–97. http://dx.doi.org/10.1609/aaai.v35i15.17591.

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Motivated by the recent successful application of span-based models to entity-based information extraction tasks, we investigate span-based models for event coreference resolution, focusing on determining (1) whether the successes of span-based models of entity coreference can be extended to event coreference; (2) whether exploiting the dependency between event coreference and the related subtask of trigger detection; and (3) whether automatically computed entity coreference information can benefit span-based event coreference resolution. Empirical results on the standard evaluation dataset provide affirmative answers to all three questions.

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Beebeejaun, Kazim, James Elston, Isabel Oliver, Adachioma Ihueze, Chika Ukenedo, Olusola Aruna, Favour Makava et al. "Evaluation of National Event-Based Surveillance, Nigeria, 2016–2018". Emerging Infectious Diseases 27, n.º 3 (marzo de 2021): 694–702. http://dx.doi.org/10.3201/eid2703.200141.

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Jolley, Andrew, Greg Cohen, Damien Joubert y Andrew Lambert. "Evaluation of Event-Based Sensors for Satellite Material Characterization". Journal of Spacecraft and Rockets 59, n.º 2 (marzo de 2022): 627–36. http://dx.doi.org/10.2514/1.a35015.

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Hwang, Soo-Hee, Sukhyang Lee, Hyun-Kyung Koo y Yoon Kim. "Evaluation of a computer-based adverse-drug-event monitor". American Journal of Health-System Pharmacy 65, n.º 23 (1 de diciembre de 2008): 2265–72. http://dx.doi.org/10.2146/ajhp080122.

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Bowers, Clint, Florian Jentsch, David Baker, Carolyn Prince y Eduardo Salas. "Rapidly Reconfigurable Event-Set Based Line Operational Evaluation Scenarios". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 41, n.º 2 (octubre de 1997): 912–15. http://dx.doi.org/10.1177/107118139704100243.

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An important cornerstone of the Advanced Qualification Program is the use of realistic flight simulations to train flight crews and evaluate their proficiency. This is achieved through the use of Line Operational Simulations (LOSs) which contain a number of realistic event sets that require flight crews to use the knowledge, skills, and abilities they gained in training in both technical and crew resource management areas. In the past, the development of LOS scenarios was complex, expensive, and time-consuming. As a result, the number of LOS scenarios used by any particular training organization was limited. This may have led, in some cases, to the LOS scenarios being compromised among flight crews, thus reducing the validity and reliability of the assessment process. In response to this problem, it has been suggested to create a methodology for quickly reconfiguring the content of flight simulator LOS scenarios. This paper provides a background for this new development and describes a research project that was begun in response to this need. A number of specific research questions are discussed which need to be answered before the methodology can be adopted by participants in the AQP program.

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Stöcker, Christian, Daniel Vey y Jan Lunze. "Decentralized event-based control: Stability analysis and experimental evaluation". Nonlinear Analysis: Hybrid Systems 10 (noviembre de 2013): 141–55. http://dx.doi.org/10.1016/j.nahs.2013.05.001.

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Billinton, R. y W. Wangdee. "Approximate Methods for Event-Based Customer Interruption Cost Evaluation". IEEE Transactions on Power Systems 20, n.º 2 (mayo de 2005): 1103–10. http://dx.doi.org/10.1109/tpwrs.2005.846098.

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Birawo, Birtukan y Pawel Kasprowski. "Review and Evaluation of Eye Movement Event Detection Algorithms". Sensors 22, n.º 22 (15 de noviembre de 2022): 8810. http://dx.doi.org/10.3390/s22228810.

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Eye tracking is a technology aimed at understanding the direction of the human gaze. Event detection is a process of detecting and classifying eye movements that are divided into several types. Nowadays, event detection is almost exclusively done by applying a detection algorithm to the raw recorded eye-tracking data. However, due to the lack of a standard procedure for how to perform evaluations, evaluating and comparing various detection algorithms in eye-tracking signals is very challenging. In this paper, we used data from a high-speed eye-tracker SMI HiSpeed 1250 system and compared event detection performance. The evaluation focused on fixations, saccades and post-saccadic oscillation classification. It used sample-by-sample comparisons to compare the algorithms and inter-agreement between algorithms and human coders. The impact of varying threshold values on threshold-based algorithms was examined and the optimum threshold values were determined. This evaluation differed from previous evaluations by using the same dataset to evaluate the event detection algorithms and human coders. We evaluated and compared the different algorithms from threshold-based, machine learning-based and deep learning event detection algorithms. The evaluation results show that all methods perform well for fixation and saccade detection; however, there are substantial differences in classification results. Generally, CNN (Convolutional Neural Network) and RF (Random Forest) algorithms outperform threshold-based methods.

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Schulz, Axel, Frederik Janssen, Petar Ristoski y Johannes Fürnkranz. "Event-Based Clustering for Reducing Labeling Costs of Event-related Microposts". Proceedings of the International AAAI Conference on Web and Social Media 9, n.º 1 (3 de agosto de 2021): 686–89. http://dx.doi.org/10.1609/icwsm.v9i1.14658.

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Automatically identifying the event type of event-related information in the sheer amount of social media data makes machine learning inevitable. However, this is highly dependent on (1) the number of correctly labeled instances and (2) labeling costs. Active learning has been proposed to reduce the number of instances to label. Albeit the thematic dimension is already used, other metadata such as spatial and temporal information that is helpful for achieving a more fine-grained clustering is currently not taken into account. In this paper, we present a novel event-based clustering strategy that makes use of temporal, spatial, and thematic metadata to determine instances to label. An evaluation on incident-related tweets shows that our selection strategy for active learning outperforms current state-of-the-art approaches even with few labeled instances.

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Miao, Y. P. "Workflow Simulation Modeling Based on Discrete Event Approach". Advanced Materials Research 69-70 (mayo de 2009): 700–704. http://dx.doi.org/10.4028/www.scientific.net/amr.69-70.700.

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In order to apply simulation to analysis, evaluation and optimization of the workflow performances, workflow process model for simulation is firstly formalized. Then workflow simulation model is bulit based on discrete event approach. Finally the supporting software tool system has been developed which shows feasibility of the proposed method.

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GLAVAŠ, GORAN y JAN ŠNAJDER. "Construction and evaluation of event graphs". Natural Language Engineering 21, n.º 4 (1 de mayo de 2014): 607–52. http://dx.doi.org/10.1017/s1351324914000060.

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AbstractEvents play an important role in natural language processing and information retrieval due to numerous event-oriented texts and information needs. Many natural language processing and information retrieval applications could benefit from a structured event-oriented document representation. In this paper, we proposeevent graphsas a novel way of structuring event-based information from text. Nodes in event graphs represent the individual mentions of events, whereas edges represent the temporal and coreference relations between mentions. Contrary to previous natural language processing research, which has mainly focused on individual event extraction tasks, we describe a complete end-to-end system for event graph extraction from text. Our system is a three-stage pipeline that performs anchor extraction, argument extraction, and relation extraction (temporal relation extraction and event coreference resolution), each at a performance level comparable with the state of the art. We presentEvExtra, a large newspaper corpus annotated with event mentions and event graphs, on which we train and evaluate our models. To measure the overall quality of the constructed event graphs, we propose two metrics based on the tensor product between automatically and manually constructed graphs. Finally, we evaluate the overall quality of event graphs with the proposed evaluation metrics and perform a headroom analysis of the system.

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Amorim, G. A., L. A. S. Lopes y O. S. Silva Junior. "Discrete Event-Based Railway Simulation Model for Eco-Efficiency Evaluation". International Journal of Simulation Modelling 19, n.º 3 (15 de septiembre de 2020): 375–86. http://dx.doi.org/10.2507/ijsimm19-3-517.

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ÇELİK, Fatih, Ahmet ZENGİN y Bülent ÇOBANOĞLU. "Discrete event simulation-based performance evaluation of Internet routing protocols". TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 21 (2013): 1720–36. http://dx.doi.org/10.3906/elk-1112-68.

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Krijnders, J. D., M. E. Niessen y T. C. Andringa. "Sound event recognition through expectancy-based evaluation ofsignal-driven hypotheses". Pattern Recognition Letters 31, n.º 12 (septiembre de 2010): 1552–59. http://dx.doi.org/10.1016/j.patrec.2009.11.004.

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Shen, Di, Lei Wang y Chengfan Li. "Event energy clustering and evaluation based on shock wave model". Cluster Computing 19, n.º 4 (1 de septiembre de 2016): 1963–74. http://dx.doi.org/10.1007/s10586-016-0627-0.

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Sigurani, M., C. Stöcker, L. Grüne y J. Lunze. "Experimental evaluation of two complementary decentralized event-based control methods". Control Engineering Practice 35 (febrero de 2015): 22–34. http://dx.doi.org/10.1016/j.conengprac.2014.10.002.

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Helmer, Sven y Fabio Persia. "ISEQL, an Interval-based Surveillance Event Query Language". International Journal of Multimedia Data Engineering and Management 7, n.º 4 (octubre de 2016): 1–21. http://dx.doi.org/10.4018/ijmdem.2016100101.

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The authors propose ISEQL, a language based on relational algebra extended by intervals for detecting high-level surveillance events from a video stream. The operators they introduce for describing temporal constraints are based on the well-known Allen's interval relationships and we implemented on top of a PostgreSQL database system. The semantics of ISEQL are clearly defined, and the authors illustrate its usefulness by expressing typical events in it and showing the promising results of an experimental evaluation.

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Lan, Tianming, Lei Guo, Xiaofei Li y Guangfu Chen. "Research on the Prediction System of Event Attendance in an Event-Based Social Network". Wireless Communications and Mobile Computing 2022 (5 de agosto de 2022): 1–14. http://dx.doi.org/10.1155/2022/1701345.

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In recent years, an event-based social network recommendation system has attracted more and more researchers’ attention. Most EBSN recommendation systems mainly focus on recommending events to users. However, in many daily activities, it is necessary to accurately estimate the number of event participants for EBSN event organizers. As an effective means to solve the problem of event attendance prediction, the EBSN event attendance prediction system needs to mine the context information in EBSN fully and use the information to alleviate the problems of data sparsity and cold start. It brings some new challenges to the research of EBSN event attendance prediction systems. According to user characteristics and context factors, the main task of the EBSN event attendance prediction system is to obtain accurate user preferences, adopt efficient prediction algorithms to improve prediction performance, and avoid losses. This paper summarizes the research progress of the EBSN event attendance prediction system in recent years. Firstly, this paper analyzes the recent research on event attendance prediction in EBSN; secondly, we summarize the role, significance, and challenges of EBSN event attendance prediction; third, we summarize the critical technologies of EBSN event attendance prediction; the contents include mining the contextual information that affects the user’s participation in the event, user preference acquisition, the method of event attendance prediction, the data set of event attendance prediction, the evaluation indicators of event attendance prediction, etc.; fourth, we look forward to the future development directions of event attendance prediction from six aspects: the methods of integrating contextual factors, the user preference acquisition methods, the prediction algorithms, the utility evaluation of event attendance prediction, the user information security, and privacy protection, and the cold start issues; finally, we conclude this paper.

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Mastan, Mohammed, Gitesh K. Raikundalia y Christopher Bain. "Usability Evaluation of a Discrete Event-based Visual Hospital Management Simulator". Health Informatics - An International Journal 3, n.º 1 (28 de febrero de 2014): 1–21. http://dx.doi.org/10.5121/hiij.2014.3101.

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Kim, Younggab, Namyoung Hur y Jeongjin Park. "Development of Event-based Safety Culture Weakness Evaluation methodology in NPPs". Journal of Energy Engineering 26, n.º 2 (30 de junio de 2017): 50–63. http://dx.doi.org/10.5855/energy.2017.26.2.044.

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Katkoori, Srinivas, Sheikh Ariful Islam y Sujana Kakarla. "Partial evaluation based triple modular redundancy for single event upset mitigation". Integration 77 (marzo de 2021): 167–79. http://dx.doi.org/10.1016/j.vlsi.2020.11.002.

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Lehmann, D. y J. Lunze. "Extension and experimental evaluation of an event-based state-feedback approach". Control Engineering Practice 19, n.º 2 (febrero de 2011): 101–12. http://dx.doi.org/10.1016/j.conengprac.2010.10.003.

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Jang, Joong Soon y Sang C. Park. "Discrete Event Simulation-Based Reliability Evaluation of a Traffic Signal Controller". Modelling and Simulation in Engineering 2018 (11 de junio de 2018): 1–5. http://dx.doi.org/10.1155/2018/5986826.

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A mission reliability evaluation methodology for a signal traffic controller is presented in this paper. To develop the new evaluation methodology, this paper combines the Discrete Event System Specification (DEVS) formalism which has been popular in manufacturing area for three reasons: (1) its features compatible with the object-oriented modeling; (2) its rigorous formal definition; and (3) its support for the specifications of discrete event models in a hierarchical and modular manner. By using the DEVS formalism, we construct a simulation model which takes into account not only the characteristics of a traffic signal controller but also the operating environment. Once a model is constructed, it is possible to perform simulation experiments. The proposed methodology computes the mission reliability of a traffic signal controller by using a simulation record, and this information plays a vital role in preparing optimized maintenance policies that maximize availability or minimize life cycle costs.

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Mu, Xiao, Jiesen Yin y Luodan Zhang. "Application and Evaluation of Sports Event Management Method Based on Recurrent Neural Network". Mathematical Problems in Engineering 2022 (15 de junio de 2022): 1–9. http://dx.doi.org/10.1155/2022/9283296.

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The methods of sports event management are the life cycle management method, which can be divided into four stages: start-up planning, plan preparation, real-time control, and followup evaluation. The administrative measures management law includes administrative orders, instructions, regulations, and systems of administrative organizations at all levels. The system management law has four characteristics: mandatory, authoritative, stable, and preventive. The current management mode of sports events is mainly that the government is deeply involved in the operation of the entire event, and relevant personnel are selected from various government departments to form an organizing committee, and the resources related to the event are controlled and regulated by the government. However, in our country, there is currently no unified sports event management standard. Therefore, this paper proposes the application and evaluation of sports event management method based on recurrent neural network (RNN). The comments of sports events are extracted from the network, classified with an RNN, and finally, an improvement plan is obtained through evaluation. The main work of this paper is as follows: (1) the development status of sports event management at home and abroad and the application of RNN are introduced, and RNN is used in the evaluation and classification of sports event management. (2) We propose a sentiment classification model GCNN-GRU that fuses local feature extraction. Aiming at the defect that the basic model is easy to lose key phrase information, a CNN with a gating mechanism is used to extract and filter local features. The classification experiment results show that the proposed GCNN-GRU has the best classification effect on the Chinese sentiment dataset.

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Jin, X., T. Mulnix, C. M. Sandiego y R. E. Carson. "Evaluation of Frame-Based and Event-by-Event Motion-Correction Methods for Awake Monkey Brain PET Imaging". Journal of Nuclear Medicine 55, n.º 2 (16 de enero de 2014): 287–93. http://dx.doi.org/10.2967/jnumed.113.123299.

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Zhao, Shutong y Jiangang Sun. "Design of Sports Event Evaluation and Classification Method Based on Deep Neural Network". Computational Intelligence and Neuroscience 2022 (18 de abril de 2022): 1–10. http://dx.doi.org/10.1155/2022/6820812.

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Large-scale sports events with high-level competition as the main content will have a great impact on the host city whether from the economic level or from the social level. With the improvement of human civilization, people realize that the holding of large-scale sports events not only has a positive impact on the economy and society but also brings some negative effects, such as waste of resources and environmental pollution, which have attracted the attention of the government and investors. Therefore, how to scientifically, comprehensively, and reasonably evaluate large-scale sports events, especially the accurate evaluation of their economic and social effects, has become the focus of attention. The evaluation of large-scale sports events mainly includes two levels: economic and social. Through the specific analysis of the evaluation content and the weight calculation of the evaluation index, the overall optimization of the evaluation of large-scale sports events is realized, and the reference experience is provided for the holding and evaluation of large-scale sports events in the future. Based on this, this article proposes a sports event evaluation and classification method based on the deep neural network. Firstly, on the basis of literature review and field investigation, the evaluation index system of sports events is established. Deep learning models have strong fitting power and robustness and have been applied to many real-world tasks. Then the deep neural network is used to evaluate the holding effect of sports events. The experimental results show that the model has high evaluation accuracy and is of great significance to the supervision and guidance of sports events.

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Shi, Ruisheng, Yang Zhang, Lina Lan, Fei Li y Junliang Chen. "Summary Instance: Scalable Event Priority Determination Engine for Large-Scale Distributed Event-Based System". International Journal of Distributed Sensor Networks 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/390329.

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Data prioritization problem is paramount for distributed publish/subscribe infrastructure to the timely delivery of real-time events since a large number of low priority events may clog the channel thereby causing high priority events to get delayed. The challenge raised for the event-based middleware in large-scale distributed system such as vehicular ad hoc networks is that event priority determination engine must be efficient and scalable in terms of priority rule size and event throughputs. This paper proposes an innovative approach based on Bloom filter and event discretization. A Bloom filter data structure is used to store the rule instances and their priorities. The complex rule evaluation is reduced to set membership testing as queries on Bloom filters. The time complexity of data prioritization is constant and independent of the number of priority rules. As event discretization signatures can be cached, this approach is cache friendly in nature. The previous computation results can be cached in overlay network nodes and reused to improve the system throughputs and determination time. We have evaluated our proposed approach and the results show a significant performance improvement.

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Chu, Fei, Hongzhuan Chen, Chunqing Yu, Lihua You, Liang Wang y Yun Liu. "Quantitative Research on Generalized Linear Modeling of SEU and Test Programs Based on Small Sample Data". Electronics 11, n.º 14 (18 de julio de 2022): 2242. http://dx.doi.org/10.3390/electronics11142242.

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Complex integrated circuits (ICs) have complex functions and various working modes, which have many factors affecting the performance of a single event effect. The single event effect performance of complex ICs is highly program-dependent and the single event sensitivity of a typical operating mode is generally used to represent the single event performance of the circuits. Traditional evaluation methods fail to consider the cross effects of multiple factors and the comprehensive effects of each factor on the single event soft error cross section. In order to solve this problem, a new quantitative study method of single event error cross section based on a generalized linear model for different test programs is proposed. The laser test data is divided into two groups: a training set and a validation set. The former is used for model construction and parameter estimation based on five methods, such as the generalized linear model and Ensemble, while the latter is used for quantitative evaluation and validation of a single event soft error cross section of the model. In terms of percentage error, the minimum mean estimation error on the validation set is 13.93%. Therefore, it has a high accuracy to evaluate the single event soft error cross section of circuits under different testing programs based on the generalized linear model, which provides a new idea for the evaluation of a single event effect on complex ICs.

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Benson, Lauren, Christian Clermont, Ricky Watari, Tessa Exley y Reed Ferber. "Automated Accelerometer-Based Gait Event Detection During Multiple Running Conditions". Sensors 19, n.º 7 (27 de marzo de 2019): 1483. http://dx.doi.org/10.3390/s19071483.

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The identification of the initial contact (IC) and toe off (TO) events are crucial components of running gait analyses. To evaluate running gait in real-world settings, robust gait event detection algorithms that are based on signals from wearable sensors are needed. In this study, algorithms for identifying gait events were developed for accelerometers that were placed on the foot and low back and validated against a gold standard force plate gait event detection method. These algorithms were automated to enable the processing of large quantities of data by accommodating variability in running patterns. An evaluation of the accuracy of the algorithms was done by comparing the magnitude and variability of the difference between the back and foot methods in different running conditions, including different speeds, foot strike patterns, and outdoor running surfaces. The results show the magnitude and variability of the back-foot difference was consistent across running conditions, suggesting that the gait event detection algorithms can be used in a variety of settings. As wearable technology allows for running gait analyses to move outside of the laboratory, the use of automated accelerometer-based gait event detection methods may be helpful in the real-time evaluation of running patterns in real world conditions.

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Ge, Hai-hui, Da Xiao, Tian-ping Chen y Yi-xian Yang. "Quantitative Evaluation Approach for Real-time Risk Based on Attack Event Correlating". Journal of Electronics & Information Technology 35, n.º 11 (21 de febrero de 2014): 2630–36. http://dx.doi.org/10.3724/sp.j.1146.2012.01539.

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Ogawa, Ryo, Kaito Kageyama, Yasushi Nakatani, Yumie Ono y Shingo Murakami. "Event-related Potentials-based Evaluation of Attention Allocation while Watching Virtual Reality". Advanced Biomedical Engineering 11 (2022): 1–9. http://dx.doi.org/10.14326/abe.11.1.

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Zhang, Xiaoxia, Jing Yue, Yue Zhang y Guohe Wang. "Fabric Hand-Feel Evaluation Based on Neurophysiology: An Event-Related Potential Study". Open Electrical & Electronic Engineering Journal 8, n.º 1 (31 de diciembre de 2014): 800–805. http://dx.doi.org/10.2174/1874129001408010800.

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Fabric hand-feel is an important indicator of textile comprehensive evaluation. In the past century, many achievements have been made in characterization and evaluation of fabric hand-feel. With the development of experimental methods, the electrophysiological technique was used in exploring the formation mechanism and cognitive principle of fabric hand-feel. In this paper, event-related potential (ERP) technique was used in revealing the difference of handfeel between polyester and silk. The exogenous component P2 showed that polyester caused more excitability in human brain. However, the endogenous component P3 indicated that silk caused more soft and comfortable feelings. Even more amazingly, touching fabrics caused significant activation of the visual cortex from the Brain Electrical Activity Mapping (BEAM), and it is also shown that the potential distribution evoked by grasping silk is wider than the polyester’s. All the experiment results show that potential variation of the cerebral cortex is closely related to perceptual cognition and process. All the above findings show that event-related potential technique is feasible and effective in detecting the differences of tactile cognition, and it provides objective evidence from neurophysiologic in fabric hand-feel research.

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Singh. "An Event-Based Methodology to Generate Class Diagrams and its Empirical Evaluation". Journal of Computer Science 6, n.º 11 (1 de noviembre de 2010): 1301–25. http://dx.doi.org/10.3844/jcssp.2010.1301.1325.

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Elmazi, Donald, Miralda Cuka, Makoto Ikeda, Keita Matsuo y Leonard Barolli. "A fuzzy-based approach for event evaluation and actor selection in WSANs". Internet of Things 11 (septiembre de 2020): 100252. http://dx.doi.org/10.1016/j.iot.2020.100252.

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Uotsu, Kanta, Kosuke Oiwa, Kent Nagumo y Akio Nozawa. "Evaluation of Cognitive Characteristics of Masticatory Sounds based on Event-related Potentials". IEEJ Transactions on Fundamentals and Materials 144, n.º 2 (1 de febrero de 2024): 51–55. http://dx.doi.org/10.1541/ieejfms.144.51.

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Kim, Nam Kyun, Kwang Myung Jeon y Hong Kook Kim. "Convolutional Recurrent Neural Network-Based Event Detection in Tunnels Using Multiple Microphones". Sensors 19, n.º 12 (14 de junio de 2019): 2695. http://dx.doi.org/10.3390/s19122695.

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This paper proposes a sound event detection (SED) method in tunnels to prevent further uncontrollable accidents. Tunnel accidents are accompanied by crashes and tire skids, which usually produce abnormal sounds. Since the tunnel environment always has a severe level of noise, the detection accuracy can be greatly reduced in the existing methods. To deal with the noise issue in the tunnel environment, the proposed method involves the preprocessing of tunnel acoustic signals and a classifier for detecting acoustic events in tunnels. For preprocessing, a non-negative tensor factorization (NTF) technique is used to separate the acoustic event signal from the noisy signal in the tunnel. In particular, the NTF technique developed in this paper consists of source separation and online noise learning. In other words, the noise basis is adapted by an online noise learning technique for enhancement in adverse noise conditions. Next, a convolutional recurrent neural network (CRNN) is extended to accommodate the contributions of the separated event signal and noise to the event detection; thus, the proposed CRNN is composed of event convolution layers and noise convolution layers in parallel followed by recurrent layers and the output layer. Here, a set of mel-filterbank feature parameters is used as the input features. Evaluations of the proposed method are conducted on two datasets: a publicly available road audio events dataset and a tunnel audio dataset recorded in a real traffic tunnel for six months. In the first evaluation where the background noise is low, the proposed CRNN-based SED method with online noise learning reduces the relative recognition error rate by 56.25% when compared to the conventional CRNN-based method with noise. In the second evaluation, where the tunnel background noise is more severe than in the first evaluation, the proposed CRNN-based SED method yields superior performance when compared to the conventional methods. In particular, it is shown that among all of the compared methods, the proposed method with the online noise learning provides the best recognition rate of 91.07% and reduces the recognition error rates by 47.40% and 28.56% when compared to the Gaussian mixture model (GMM)–hidden Markov model (HMM)-based and conventional CRNN-based SED methods, respectively. The computational complexity measurements also show that the proposed CRNN-based SED method requires a processing time of 599 ms for both the NTF-based source separation with online noise learning and CRNN classification when the tunnel noisy signal is one second long, which implies that the proposed method detects events in real-time.

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Nachamkin, Jason E. y Yi Jin. "An Eulerian Framework for Event-Based Pattern Verification". Weather and Forecasting 32, n.º 6 (31 de octubre de 2017): 2027–43. http://dx.doi.org/10.1175/waf-d-17-0065.1.

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Abstract When consulting a forecast, users often ask some variant of the following questions: Will an event of interest occur? If so, when will it occur? How long will it last? How intense will it be? Standard verification measures often do not directly communicate the ability of a forecast to answer these questions. Instead, quantitative scores typically address them indirectly or in some combined form. A more direct performance measure grew from what started as a project for a high-school intern. The challenge was to evaluate aspects of forecast quality from a set of convection-allowing (1.67 km) precipitation forecasts over Florida. Although the output was highly detailed, evaluation became manageable by simply adding a series of static landmarks with range rings and radials. Using the “targets” as a guide, the student and the two authors successfully obtained quantitative estimates of model tendencies that had heretofore only been reported anecdotally. What follows is a description of the method as well as the results from the analysis. It is hoped that this work will stimulate a broader discussion about how to extract performance information from very complex forecasts and present that information in terms that humans can readily perceive.

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Padilla-Cuevas, Josué, José A. Reyes-Ortiz y Maricela Bravo. "Ontology-Based Context Event Representation, Reasoning, and Enhancing in Academic Environments". Future Internet 13, n.º 6 (10 de junio de 2021): 151. http://dx.doi.org/10.3390/fi13060151.

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An Ambient Intelligence responds to user requests based on several contexts. A relevant context is related to what has happened in the ambient; therefore, it focuses a primordial interest on events. These involve information about time, space, or people, which is significant for modeling the context. In this paper, we propose an event-driven approach for context representation based on an ontological model. This approach is extendable and adaptable for academic domains. Moreover, the ontological model to be proposed is used in reasoning and enrichment processes with the context event information. Our event-driven approach considers five contexts as a modular perspective in the model: Person, temporal (time), physical space (location), network (resources to acquire data from the ambient), and academic events. We carried out an evaluation process for the approach based on an ontological model focused on (a) the extensibility and adaptability of use case scenarios for events in an academic environment, (b) the level of reasoning by using competence questions related to events, (c) and the consistency and coherence in the proposed model. The evaluation process shows promising results for our event-driven approach for context representation based on the ontological model.

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Frolyak, Lyubov y Myroslava Froliak. "STRUCTURE AND TYPOLOGY OF ASSESSMENT OF THE "RUSSIAN-UKRAINIAN WAR 2022-2023" MEDIA EVENT IN FRENCH TELEVISION DISCOURSE". Bulletin of Taras Shevchenko National University of Kyiv. Literary Studies. Linguistics. Folklore Studies, n.º 33 (2023): 120–25. http://dx.doi.org/10.17721/1728-2659.2023.33.20.

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The article is devoted to the problems of axiological characterization of a media event as a part of the media picture of the world, which arises in the process of intercultural communication. The axiological characteristics are presented as a necessary constituent element of a media event, which participates in its formation. The structure of evaluation of the media event "Russian-Ukrainian war 2022-2023" in French television discourse is considered, the types of evaluation based on its relationship to the object of the evaluation characteristics and the types of evaluation based on the relationship to the subject of evaluation are identified. It was established that the media event "war in Ukraine" as an object of assessment in the audiovisual text of the analytical and informational telecast is significantly more complex in its structure than the real event, as it also includes elements that arise in the media discourse. As a result of the analysis of the types of subjects of the evaluation characteristics of the war in Ukraine as a media event in the French television discourse, it was found that the main subject of evaluation in the analytical and informative audiovisual text is a professional expert, a political scientist, that is, a person who possesses professional objectivity, authority and professional experience, which affects the formation of the evaluation of the event in the media picture of the world of the addressee of television broadcasting. In order to establish the types of assessment based on its relationship to its subject, which are included in the system of axiological characteristics of the Russian-Ukrainian war of 2022-2023, the assessment statements of heads of state, famous politicians, representatives of world organizations from countries whose interests are affected by the war in Ukraine were also considered. It was found that the introduction to the text of the assessment of a media event, the subject of assessment of which is a well-known political or socio-cultural figure, takes place with the help of the constructions of direct and indirect transmission of someone else's speech with an indication of the subject of the speech and the source of information. It is noted that a separate type of evaluation of a media event is represented by evaluation statements of direct participants of real events that have acquired the status of media events. Prospects for further research into the structure and typology of media event evaluation have been determined.

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Joshi, Mangesh. "PRIORITIZING PERFORMANCE EVALUATION FACTORS OF EVENT-BASED INFORMATION SYSTEMS USING INTERPRETIVE STRUCTURAL MODELING". Suranaree Journal of Science and Technology 30, n.º 3 (29 de septiembre de 2023): 010236(1–10). http://dx.doi.org/10.55766/sujst-2023-03-e01014.

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This paper is aimed at the application of Interpretive Structural Modeling (ISM) for prioritizing the factors associated with the performance evaluation of event-based information management system (EBIMS). The study identified thirteen such critical factors deciding the performance of Event-Based Information Systems. Literature review along with experts' opinions were collected to arrive at the final thirteen factors. In this paper, the authors have used Interpretive Structural Modeling (ISM) approach to interpret the interdependency among the selected factors. In addition, MICMAC (cross-impact matrix multiplication applied to classification) analysis is also performed to illustrate the relative driving and dependence power among the selected factors. This paper infers that event processing algorithm, data volume and quality, and hardware and software along with query complexity are the most dominating factors which have the highest driving power and the minimum dependence power as they drive other factors and sit at the top of the interpretive structure model.

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Máca, P. y P. Torfs. "The influence of temporal rainfall distribution in the flood runoff modelling". Soil and Water Research 4, Special Issue 2 (19 de marzo de 2010): S102—S110. http://dx.doi.org/10.17221/471-swr.

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The rainfall input is one of the main factors influencing the magnitude of the runoff response during a flood event. Its temporal and spatial distribution significantly contributes to the formation of hydrograph shape, peak discharge and flood volume. A novel approach to the evaluation of the role of the temporal rainfall pattern of hydrograph is presented in this contribution. The methodology shown is based on the coupling of the deterministic event based runoff model with the stochastic rainfall disaggregation model. The rainfall model simulates the hyetograph ensemble, which is the direct input to the calibrated event based runoff model. The event based runoff model calibration is based on the evaluation of real flood events. The rainfall ensemble is simulated according to the preservation of important statistical properties, which are estimated from the real rainfall data inputs. The proposed combination of two simulation techniques enables to generate the hydrograph ensemble upon a single flood event. The evaluation of the temporal rainfall distribution impact on the flood runoff response is performed through the determination of the selected rainfall runoff characteristics of the simulated hydrograph ensemble. The main result confirms the importance of the rainfall volume inputs and its temporal distribution on the flood runoff generation. The methodology shown enables to evaluate the potential of the real flood event to generate the flood event within the conditions of the small catchment scale.

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44

Mehmood, Arfa, Asta Laiho, Mikko S. Venäläinen, Aidan J. McGlinchey, Ning Wang y Laura L. Elo. "Systematic evaluation of differential splicing tools for RNA-seq studies". Briefings in Bioinformatics 21, n.º 6 (5 de diciembre de 2019): 2052–65. http://dx.doi.org/10.1093/bib/bbz126.

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Abstract Differential splicing (DS) is a post-transcriptional biological process with critical, wide-ranging effects on a plethora of cellular activities and disease processes. To date, a number of computational approaches have been developed to identify and quantify differentially spliced genes from RNA-seq data, but a comprehensive intercomparison and appraisal of these approaches is currently lacking. In this study, we systematically evaluated 10 DS analysis tools for consistency and reproducibility, precision, recall and false discovery rate, agreement upon reported differentially spliced genes and functional enrichment. The tools were selected to represent the three different methodological categories: exon-based (DEXSeq, edgeR, JunctionSeq, limma), isoform-based (cuffdiff2, DiffSplice) and event-based methods (dSpliceType, MAJIQ, rMATS, SUPPA). Overall, all the exon-based methods and two event-based methods (MAJIQ and rMATS) scored well on the selected measures. Of the 10 tools tested, the exon-based methods performed generally better than the isoform-based and event-based methods. However, overall, the different data analysis tools performed strikingly differently across different data sets or numbers of samples.

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Dwyer, Larry y Peter Forsyth. "Evaluating Special Events: Merging Two Essential Approaches". Event Management 23, n.º 6 (6 de diciembre de 2019): 897–911. http://dx.doi.org/10.3727/152599519x15506259856417.

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In special event evaluation, given the shift away from standard economic impact analysis based on input–output modeling, increased attention is being paid to the roles that computable general equilibrium modeling (CGE) and cost–benefit analysis (CBA) can play in event evaluation. This article analyzes the strengths and limitations of CGE and CBA in the context of event assessment. A "hybrid" approach is outlined which includes a role for the advantages of both techniques to be included in the evaluation process. The issues addressed are theoretically important for both impact and benefit estimation, while having significant practical implications for event assessment.

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Feng, Yang, Hengyi Lv, Hailong Liu, Yisa Zhang, Yuyao Xiao y Chengshan Han. "Event Density Based Denoising Method for Dynamic Vision Sensor". Applied Sciences 10, n.º 6 (16 de marzo de 2020): 2024. http://dx.doi.org/10.3390/app10062024.

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Dynamic vision sensor (DVS) is a new type of image sensor, which has application prospects in the fields of automobiles and robots. Dynamic vision sensors are very different from traditional image sensors in terms of pixel principle and output data. Background activity (BA) in the data will affect image quality, but there is currently no unified indicator to evaluate the image quality of event streams. This paper proposes a method to eliminate background activity, and proposes a method and performance index for evaluating filter performance: noise in real (NIR) and real in noise (RIN). The lower the value, the better the filter. This evaluation method does not require fixed pattern generation equipment, and can also evaluate filter performance using natural images. Through comparative experiments of the three filters, the comprehensive performance of the method in this paper is optimal. This method reduces the bandwidth required for DVS data transmission, reduces the computational cost of target extraction, and provides the possibility for the application of DVS in more fields.

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47

Kaavya, S. y G. G. Lakshmi Priya. "Static Shot based Keyframe Extraction for Multimedia Event Detection". International Journal of Computer Vision and Image Processing 6, n.º 1 (enero de 2016): 28–40. http://dx.doi.org/10.4018/ijcvip.2016010103.

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Nowadays, processing of Multimedia information leads to high computational cost due its larger size especially for video processing. In order to reduce the size of the video and to save the user's time in spending their attention on whole video, video summarization is adopted. However, it can be performed using keyframe extraction from the video. To perform this task, a new simple keyframe extraction method is proposed using divide and conquer strategy in which, Scale Invariant Feature Transform (SIFT) based feature representation vector is extracted and the whole video is categorized into static and dynamic shots. The dynamic shot is further processed till it becomes static. A representative frame is extracted from every static shot and the redundant keyframes are removed using keyframe similarity matching measure. Experimental evaluation is carried out and the proposed work is compared with related existing work. The authors' method outperforms existing methods in terms of Precision (P), Recall (R), F-Score (F). Also, Fidelity measure is computed for proposed work which gives better result.

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Gluz, João y Patricia A. Jaques. "A Probabilistic Formalization of the Appraisal for the OCC Event-Based Emotions". Journal of Artificial Intelligence Research 58 (28 de marzo de 2017): 627–64. http://dx.doi.org/10.1613/jair.5320.

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This article presents a logical formalization of the emotional appraisal theory, i.e., it formalizes the cognitive process of evaluation that elicits an emotion. This formalization is psychologically grounded on the OCC cognitive model of emotions. More specifically, we are interested in event-based emotions, i.e., emotions that are elicited by the evaluation of the consequences of an event that either happened or will happen. The formal modelling presented here is based on the AfPL Probabilistic Logic, a BDI-like probabilistic modal logic, which allows our model to verify whether the variables that determine the elicitation of emotions achieved the necessary threshold or not. The proposed logical formalization aims at addressing how the emotions are elicited by the agent cognitive mental states (desires, beliefs and intentions), and how to represent the intensity of the emotions. These are important initial points in the investigation of the dynamic interaction among emotions and other mental states.

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Yoon, Young-Joon, Seo-Yeon Kim, Yun-Ku Lee, Namhyuk Ham, Ju-Hyung Kim y Jae-Jun Kim. "GIS-Based Multi-Objective Routing Approach for Street-Based Sporting-Event Routing". Applied Sciences 13, n.º 14 (21 de julio de 2023): 8453. http://dx.doi.org/10.3390/app13148453.

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This study proposes a decision-making framework that integrates a routing model based on the geographic information system (GIS) and a genetic algorithm into a building-information modeling (BIM) environment to overcoming the limitations of the planning process of traditional street-based sporting events. There is a lack of research on improving the manually conducted decision-making processes for street-based sporting events. Moreover, previous routing studies were limited to GIS environments, and proposals for decision-making models integrated with BIM environments are lacking. In this study, the applicability of the framework was verified by presenting the variables of the existing GIS-based routing model as environmental variables to consider the impact of street-based sports events on a city. The evaluation model for the route selection was parameterized independently, such that its priority could be changed according to the user’s needs. Moreover, we integrated the data into BIM to create and analyze models that assess urban effects. This method is a decision-making system for policymakers and event planners to promptly conduct initial venue surveys through the technological integration of GIS–routing–BIM. Additionally, the GIS stipulated in this study can be applied to other cities. The Gwanghwamun area of Seoul, South Korea, was selected as the case study.

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Lei, Yao Long y Zhang Jun Liu. "Probability Density Evolution Method for Seismic Reliability Evaluation of Structural Systems". Advanced Materials Research 255-260 (mayo de 2011): 2606–11. http://dx.doi.org/10.4028/www.scientific.net/amr.255-260.2606.

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A structural system reliability evaluation approach based on the idea of equivalent extreme-value event and the probability density evolution method is presented. Using the idea of equivalent extreme-value event, for a compound random event as combination of a set of random events, an equivalent extreme-value event could be constructed. So, this makes it possible to transform computation of the probability of the compound random event to a one-dimensional integration of the probability density function of the equivalent extreme-value random variable. In conjunction with the probability density evolution method, which is capable of evaluating the extreme-value distribution of a set of random variables or stochastic processes, the structural system reliability could be evaluated through computing the probability of the equivalent extreme-value event. The proposed approach is discussed in detail on how to construct the equivalent extreme-value event and then implement the procedure numerically. On the other hand, based on the orthogonal expansion method, the stochastic process of earthquake ground motion can be represented as a linear combination of deterministic functions modulated by a set of mutually independent random variables. Combining the above methods, the reliability of structures under earthquake excitations could be successfully evaluated. An example, of which deals with a linear frame structure subjected to non-stationary seismic loading, is illustrated to validate the proposed method.

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