Search results for: event study

Authors: Tao Zhang

Abstract:

As the competition of all kinds of festival events becomes more and more fierce, more and more event organizers try to design a blended festivalscape by integrating multifaceted environmental cues in order to raise the service quality of festival events and then raise visitors’ satisfaction. As the main type of festival events, food festivals are popular in all over the world. The organizers’ of food festivals also try to mix food with multifaceted environmental cues (e.g., music, stage, light, dance) to design a blended festivalscape. However, until now little studies explore the environmental cues of food festivals and their relationship with visitors’ satisfaction. Therefore, the aim of this study is to ascertain the environmental cues of food festival and their relationship with visitors’ satisfaction by using the blended festivalscape theory. Using convenient sampling method, this study investigated 1,000 food festival visitors in Macau. Factor analysis showed there are mainly six environmental cues (i.e., food, atmosphere, program, staff, facility, and information). All six environmental cues are positively related with visitors’ satisfaction, while the most influential factors are food, atmosphere, and program. This study showed that festival event organizers’ should focus on the topic of their festival event, build festival atmosphere, and create interesting programs in order to design a blended festivalscape and then raise visitors’ satisfaction.

Keywords: environmental cue, event, festival, satisfaction

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Authors: Karen J. Polvado, Betty Bowles, Jansen Lauren, Gibson Martha, Robin Lockhart

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The purpose of this study was to identify motivation to participate in the Hotter ‘n Hell Hundred (HHH) bicycling event, and the participants’ demographics, health risk factors, and preparation to ride in the event. A convenience sample of adults pre-registered for non-competitive cycling events (N = 7,472) were requested to complete a survey. Of these, 2,645 (35%) responded. Questions identified the participants’ demographics, preparation, previous experience with HHH, and motives for riding. The HHH attracted riders of all ages (18-80), genders, ethnicities, and educational levels. The majority were males, 40-59 years old, married, college graduates, and identified themselves as non-Hispanic whites. The majority (68%) reported no existing medical conditions, and were normal weight (70%), although 52% had been overweight or obese in the past. Preparation to ride in the HHH varied from riding more than five times a week for the last year, to riding 1-2 times per week one month before the event. Most (93%) had ridden in the HHH an average of 5 times. Motivations to ride included: personal challenge (75%); to experience the HHH ride (57%); a chance to ride with family/friends/coworkers (52%); improving health (47%); fun (33%); challenge by others (15%); part of a weight loss plan (11%); training for another event (10%); and raising money for a cause (2%). The motivation to participate appeared to move from extrinsic to intrinsic motivation as age increased. Exploration of the exercise habits and motivations of older adults (70+) is suggested by this study.

Keywords: cycling, motivation, physical activity, training

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Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

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Authors: Zhi Zhu, Boquan Zhang, Tian Jing, Jingjing Li, Tao Wang

Abstract:

Data assimilation is a model and data hybrid-driven method that dynamically fuses new observation data with a numerical model to iteratively approach the real system state. It is widely used in state prediction and parameter inference of continuous systems. Because of the discrete event system’s non-linearity and non-Gaussianity, traditional Kalman Filter based on linear and Gaussian assumptions cannot perform data assimilation for such systems, so particle filter has gradually become a technical approach for discrete event simulation data assimilation. Hence, we proposed a particle filter-based discrete event simulation data assimilation method and took the unmanned aerial vehicle (UAV) maintenance service system as a proof of concept to conduct simulation experiments. The experimental results showed that the filtered state data is closer to the real state of the system, which verifies the effectiveness of the proposed method. This research can provide a reference framework for the data assimilation process of other complex nonlinear systems, such as discrete-time and agent simulation.

Keywords: discrete event simulation, data assimilation, particle filter, model and data-driven

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Authors: Padma Sree Potru

Abstract:

Abstract: A co-relational descriptive study was conducted to assess the impact of cancer event on self, on family, coping strategies of cancer clients and quality of life among them in G.G.H., Guntur, Andhra Pradesh, India. Aim: The aim of the study was to investigate the impact of cancer events on self, on family, coping of clients and quality of life among cancer patients. Methods: 50 cancer patients were selected through random sampling technique. The data were obtained by using impact of events scale, impact on family scale, coping health inventory and WHOQOL-BREF scale. Results: The results revealed that majority (32%) of them were in the age group of 36-45 years, 72% were females, 44% were having the income of Rs. 5001-10000/- per month, 40% were working for daily wage, and 15% were newly diagnosed of cancer. Among 50 cancer patients, 65% had extreme impact of events, 61% shows extreme impact on family, 46% possess minimal coping strategies and 68% had poor quality of life. This study focuses on that there is a strong positive correlation between quality of life and coping behavior r=0.603 and also between impact of event and impact on family r=0.610, but a negative correlation existed between quality of life and impact of events r= -0.201. ANOVA test reveals that there is a significant difference between subscales of impact on family and coping behavior with f values = 3.893, 3.957 respectively. Chi-square highlights that there is a significant association between impact of events with age, occupation and impact on family with duration of illness. Conclusion: Even though cancer is a dreadful disease still there are many emerging treatment modalities and innovative procedures which are focusing on improving the standards of life among cancer clients. But all this can happen only when the clients accepts the reality, increase their willpower and confidence, desire to live, focusing on coping mechanisms and good ongoing support from the family members.

Keywords: impact of event, impact on family, coping, quality of event

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Kwaku Damoah

Abstract:

This study presents a comprehensive data-driven analysis to understand the evolution of adverse events (AEs) in pharmacovigilance. Utilizing data from the FDA Adverse Event Reporting System (FAERS), we employed three analytical methods: rank-based, frequency-based, and percentage change analyses. These methods assessed temporal trends and patterns in AE reporting, focusing on various drug-active ingredients and patient demographics. Our findings reveal significant trends in AE occurrences, with both increasing and decreasing patterns from 2000 to 2023. This research highlights the importance of continuous monitoring and advanced analysis in pharmacovigilance, offering valuable insights for healthcare professionals and policymakers to enhance drug safety.

Keywords: event analysis, FDA adverse event reporting system, pharmacovigilance, temporal trend analysis

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Authors: Jawid Ahmad Baktash, Mursal Dawodi, Tomokazu Nagata

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With the rapid growth of Cloud Computing, Formal Methods became a good choice for the refinement of message specification and verification for Dynamic Routing in Cloud Computing. Cloud-based Dynamic Routing is becoming increasingly popular. We propose feedback in Formal Methods for Dynamic Routing and Cloud Computing; the model and topologies show how to send messages from index zero to all others formally. The responsibility of proper verification becomes crucial with Dynamic Routing in the cloud. Formal Methods can play an essential role in the routing and development of Networks, and the testing of distributed systems. Event-B is a formal technique that consists of describing the problem rigorously and introduces solutions or details in the refinement steps. Event-B is a variant of B, designed for developing distributed systems and message passing of the dynamic routing. In Event-B and formal methods, the events consist of guarded actions occurring spontaneously rather than being invoked.

Keywords: cloud, dynamic routing, formal method, Pro-B, event-B

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Authors: S. L. Tulasi Devi, Shivam Azad

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The primary objective of this study is to analyze the impact of green bond issuance on the stock prices of respective Indian companies. An event study methodology has been employed to study the effect of green bond issuance. For in-depth study and analysis, this paper used different window frames, including 15-15 days, 10-10 days, 7-7days, 6-6 days, and 5-5 days. Further, for better clarity, this paper also used an uneven window period of 7-5 days. The period of study covered all the companies which issued green bonds during the period of 2017-2022; Adani Green Energy, State Bank of India, Power Finance Corporation, Jain Irrigation, and Rural Electrification Corporation, except Indian Renewable Energy Development Agency and Indian Railway Finance Corporation, because of data unavailability. The paper used all three event study methods as discussed in earlier literature; 1) constant return model, 2) market-adjusted model, and 3) capital asset pricing model. For the fruitful comparison between results, the study considered cumulative average return (CAR) and buy and hold average return (BHAR) methodology. For checking the statistical significance, a two-tailed t-statistic has been used. All the statistical calculations have been performed in Microsoft Excel 2016. The study found that all other companies have shown positive returns on the event day except for the State Bank of India. The results demonstrated that constant return model outperformed compared to the market-adjusted model and CAPM. The p-value derived from all the methods has shown an almost insignificant impact of the issuance of green bonds on the stock prices of respective companies. The overall analysis states that there’s not much improvement in the market efficiency of the Indian Stock Markets.

Keywords: green bonds, event study methodology, constant return model, market-adjusted model, CAPM

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Authors: Seokbeen Lim, KyeongSeok Sim, DaKyeong Shin, Gilwon Yoon

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Event-related potential (ERP) is one of the useful tools for investigating cognitive reactions. In this study, the potential of ERP components detected after auditory and visual stimuli was examined. Subjects were asked to respond upon stimuli that were of three categories; Target, Non-Target and Standard stimuli. The ERP after stimulus was measured. In the experiment of visual evoked potentials (VEPs), the subjects were asked to gaze at a center point on the monitor screen where the stimuli were provided by the reversal pattern of the checkerboard. In consequence of the VEP experiments, we observed consistent reactions. Each peak voltage could be measured when the ensemble average was applied. Visual stimuli had smaller amplitude and a longer latency compared to that of auditory stimuli. The amplitude was the highest with Target and the smallest with Standard in both stimuli.

Keywords: auditory stimulus, EEG, event related potential, oddball task, visual stimulus

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Authors: Noriko Hanakawa, Masaki Obana

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A simulation tool has been proposed for big-scale projection mapping events. The tool has four main functions based on Mapbox and Unity utilities. The first function is building a 3D model of real cities by MapBox. The second function is a movie projection to some buildings in real cities by Unity. The third function is a movie sending function from a PC to a virtual projector. The fourth function is mapping movies with fitting buildings. The simulation tool was adapted to a real projection mapping event that was held in 2019. The event has been finished. The event had a serious problem in the movie projection to the target building. The extra tents were set in front of the target building. The tents became the obstacles to the movie projection. The simulation tool can be reappeared the problems of the event. Therefore, if the simulation tool was developed before the 2019 projection mapping event, the problem of the tents’ obstacles could be avoided with the simulation tool. In addition, we confirmed that the simulation tool is useful to make a plan of future projection mapping events in order to avoid obstacles of various extra equipment such as utility poles, planting trees, monument towers.

Keywords: projection mapping, projector position, real 3D map, avoiding obstacles

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Authors: X. Wang

Abstract:

Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Tzu-I Chiang

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A central question for finite-nonfinite distinction in Mandarin Chinese is how does Mandarin encode temporal information without the grammatical contrast between past and present tense. Moreover, how do L2 learners of Mandarin whose native language is English and whose L1 system has tense morphology, acquire the temporal encoding system in L2 Mandarin? The current study reports preliminary findings on the relationship between topic prominence and the temporal encoding in L1 and L2 Chinese. Oral narratives data from 30 natives and learners of Mandarin Chinese were collected via a film-retell task. In terms of coding, predicates collected from the narratives were transcribed and then coded based on four major verb types: n-degree Statives (quality-STA), point-scale Statives (status-STA), n-atom EVENT (ACT), and point EVENT (resultative-ACT). How native speakers and non-native speakers started retelling the story was calculated. Results of the study show that native speakers of Chinese tend to express Topic Time (TT) syntactically at the topic position; whereas L2 learners of Chinese across levels rely mainly on the default time encoded in the event types. Moreover, as the proficiency level of the learner increases, learners’ appropriate use of the event predicates increased, which supports the argument that L2 development of temporal encoding is affected by lexical aspect.

Keywords: topic prominence, temporal encoding, lexical aspect, L2 acquisition

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Authors: John Allbutt, Andrew Murray, Jonathan Ling, Thomas M. Heffernan

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Ultra-endurance events place unique physical and psychological pressures on participants. In this study, we examined the psychologically challenging aspects of taking part in a 3000 mile transatlantic rowing race using a qualitative approach. To date, more people have been into space than have rowed an ocean and only one psychological study has been conducted on this experience which had a specific research focus. The current study was a qualitative study using semi-structured interviews. Participants were an opportunity sample of seven competitors from a recent ocean rowing race. Participants were asked about the psychological aspects of the event after it had finished. The data were analysed using thematic analysis. Several themes emerged from the analysis. These related to: 1) preparation; 2) bodily aches/pains, 3) race setbacks; 4) boat conditions; 5) interpersonal factors and communication; 6) strategies for managing stress and interpersonal tensions. While participants were generally very positive about the event, the analysis showed that they experienced significant psychological challenges during their voyage. Competitors paid considerable attention to preparing for the physical challenges of the event. However, not all prospective competitors gave the same time to preparing for psychological factors or were aware how they might play out during their voyage. All Atlantic rowing crews should be aware of the psychological challenges they face, and have strategies in place to help cope with the psychological strain of taking part.

Keywords: confinement experiences, ocean rowing, stress, ultra-endurance sport

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Authors: Wheyming Tina Song, Chi-Hao Hong

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In this study, we investigate the effect of a new boarding policy - short stay, on the overcrowding efficiency in emergency department (ED). The decision variables are no. of short stay beds for least acuity ED patients. The performance measurements used are national emergency department overcrowding score (NEDOCS) and ED retention rate (the percentage that patients stay in ED over than 48 hours in one month). Discrete event simulation (DES) is used as an analysis tool to evaluate the strategy. Also, common random number (CRN) technique is applied to enhance the simulation precision. The DES model was based on a census of 6 months' patients who were treated in the ED of the National Taiwan University Hospital Yunlin Branch. Our results show that the new short-stay boarding significantly impacts both the NEDOCS and ED retention rate when the no. of short stay beds is more than three.

Keywords: emergency department (ED), common random number (CRN), national emergency department overcrowding score (NEDOCS), discrete event simulation (DES)

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Authors: Asaad Y. Shamseldin

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Analytical probabilistic approach is an innovative approach for urban stormwater modeling. It can provide information about the long-term performance of a stormwater management facility without being computationally very demanding. This paper explores the application of the analytical probabilistic approach in New Zealand. The paper presents the results of a case study aimed at development of an objective way of identifying what constitutes a rainfall storm event and the estimation of the corresponding statistical properties of storms using two selected automatic rainfall stations located in the Auckland region in New Zealand. The storm identification and the estimation of the storm statistical properties are regarded as the first step in the development of the analytical probabilistic models. The paper provides a recommendation about the definition of the storm inter-event time to be used in conjunction with the analytical probabilistic approach.

Keywords: hydrology, rainfall storm, storm inter-event time, New Zealand, stormwater management

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Authors: Marie-Eve Joret, Marijn Van Vliet, Flavio Camarrone, Marc M. Van Hulle

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Event-related potentials (ERPs) provide evidence that the human brain can process and understand music at a pre-attentive level. Music-specific ERPs include the Early Right Anterior Negativity (ERAN) and a late Negativity (N5). This study aims to further investigate this issue using two types of syntactic manipulations in music: mild violations, containing no out-of-key tones and strong violations, containing out-of-key tones. We will examine whether both manipulations will elicit the same ERPs.

Keywords: ERAN ERPs, Music, N5, P3, ERPs, Music, N5 component, P3 component

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Authors: Abhijitsinh Gohil, Kaushal Wadhvaniya, Kuldipsinh Jadeja

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Road Safety is a multi-sectoral and multi-dimensional issue. An effective model can assess the risk associated with highway safety. A questionnaire survey is very essential to identify the events or activities which are causing unsafe condition for traffic on an urban highway. A questionnaire of standard questions including vehicular, human and infrastructure characteristics can be made. Responses from the age wise group of road users can be taken on field. Each question or an event holds a specific risk weightage, which contributes in creating an inappropriate and unsafe flow of traffic. The probability of occurrence of an event can be calculated from the data collected from the road users. Finally, the risk score can be calculated by considering the risk factor and the probability of occurrence of individual event and addition of all risk score for the individual event will give the total risk score of a particular road. Standards for risk score can be made and total risk score can be compared with the standards. Thus road can be categorized based on risk associated and traffic safety on it. With this model, one can assess the need for traffic safety improvement on a given road, and qualitative data can be analysed.

Keywords: probability of occurrence, questionnaire, risk factor, risk score

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Authors: Nasir Yusoff, Ahmad Adamu Adamu, Tahamina Begum, Faruque Reza

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The P300 from Event related potential (ERP) explains the psycho-physiological phenomenon in human body. The present study aims to identify the differences of amplitude and latency of P300 component from auditory stimuli, between ambiversion and extraversion types of personality. Ambivert (N=20) and extravert (N=20) undergoing ERP recording at the Hospital Universiti Sains Malaysia (HUSM) laboratory. Electroencephalogram data was recorded with oddball paradigm, counting auditory standard and target tones, from nine electrode sites (Fz, Cz, Pz, T3, T4, T5, T6, P3 and P4) by using the 128 HydroCel Geodesic Sensor Net. The P300 latency of the target tones at all electrodes were insignificant. Similarly, the P300 latency of the standard tones were also insignificant except at Fz and T3 electrode. Likewise, the P300 amplitude of the target and standard tone in all electrode sites were insignificant. Extravert and ambivert indicate similar characteristic in cognition processing from auditory task.

Keywords: amplitude, event related potential, p300 component, latency

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Kyoko Tominaga

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Non-Government Organizations (NGOs), Non-Profit Organizations (NPOs), Social Enterprises and other actors play an important role in political decisions in governments at the international levels. Especially, such organizations’ and activists’ network in civil society is quite important to effect to the global politics. To solve the complex social problems in global era, diverse actors should corporate each other. Moreover, network of protesters is also contributes to diffuse tactics, information and other resources of social movements. Based on the findings from the study of International Trade Fairs (ITFs), the author analyzes the network of activists in anti-globalism movement. This research focuses the transition of 54 activists’ whole network in the “protest event” against 2008 G8 summit in Japan. Their network is examined at the three periods: Before protest event phase, during protest event phase and after event phase. A mixed method is used in this study: the author shows the hypothesis from social network analysis and evaluates that with interview data analysis. This analysis gives the two results. Firstly, the more protesters participate to the various events during the protest event, the more they build the network. After that, active protesters keep their network as well. From interview data, we can understand that the active protesters can build their network and diffuse the information because they communicate with other participants and understand that diverse issues are related. This paper comes to same conclusion with previous researches: protest events activate the network among the political activists. However, some participants succeed to build their network, others do not. “Networked” activists are participated in the various events for short period of time and encourage the diffusion of information and tactics of social movements.

Keywords: social movement, global justice movement, tactics, diffusion

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Authors: Shuyu Zhao

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This study uses the cat-themed "Night at the Museum" event of the Shanghai Museum as a case to examine how museum events are portrayed across various digital news platforms. Grounded in communication and cultural creativity theories and employing a three-tier framing approach, this research provides an in-depth analysis of media strategies in cross-platform museum image building. Through a quantitative content analysis, it is investigated that how digital media employ specific narrative strategies to shape the public perception of museum events. The findings reveal a prevalent use of leadership framing, highlighting the museum's unique role in cultural dissemination. By combining elements of museum culture with a pet-friendly theme, the "catty Night at the Museum" event serves as a distinctive example in exploring museum image construction within digital media. This study sheds light on how museum events, as unique cultural arenas, are positioned in the public mind, offering a fresh perspective for the promotion and image-building of museum activities.

Keywords: cultural communication, digital media, museum, framing theory

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Authors: Jawid Ahmad Baktash, Tadashi Shiroma, Tomokazu Nagata, Yuji Taniguchi, Morikazu Nakamura

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The goal of this paper is to explore the use of formal methods for Dynamic Routing, The purpose of network communication with dynamic routing is sending a massage from one node to others by using pacific protocols. In dynamic routing connections are possible based on protocols of Distance vector (Routing Information Protocol, Border Gateway protocol), Link State (Open Shortest Path First, Intermediate system Intermediate System), Hybrid (Enhanced Interior Gateway Routing Protocol). The responsibility for proper verification becomes crucial with Dynamic Routing. Formal methods can play an essential role in the Routing, development of Networks and testing of distributed systems. Event-B is a formal technique consists of describing rigorously the problem; introduce solutions or details in the refinement steps to obtain more concrete specification, and verifying that proposed solutions are correct. The system is modeled in terms of an abstract state space using variables with set theoretic types and the events that modify state variables. Event-B is a variant of B, was designed for developing distributed systems. In Event-B, the events consist of guarded actions occurring spontaneously rather than being invoked. The invariant state properties must be satisfied by the variables and maintained by the activation of the events.

Keywords: dynamic rout RIP, formal method, event-B, pro-B

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Authors: Assem El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach using the Healthcare Multi-Agent System. The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are: The Behavioral Pattern Analysis (BPA) modeling methodology. The development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases, Healthcare Multi-Agent System

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Authors: Iqbal Felani

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A Coal-Fired Power Plant has some integrated facilities to handle coal from three separated coal yards to eight units power plant’s bunker. But nowadays the facilities are not reliable enough for supporting the system. Management planned to invest some facilities to increase the reliability. They also had a plan to make single spesification of coal used all of the units, called Single Quality Coal (SQC). This simulation would compare before and after improvement with two scenarios i.e First In First Out (FIFO) and Last In First Out (LIFO). Some parameters like stay time, reorder point and safety stock is determined by the simulation. Discrete event simulation based software, Flexsim 5.0, is used to help the simulation. Based on the simulation, Single Quality Coal with FIFO scenario has the shortest staytime with 8.38 days.

Keywords: Coal Yard Management, Discrete event simulation First In First Out, Last In First Out.

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Authors: Assem El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Intelligent Agent Reservation System (IARS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are developing the Behavioral Pattern Analysis (BPA) modeling methodology, and developing an interactive software tool (DECISION) which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, intelligent agent, reservation system, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

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Authors: Ping Xu, Gregory T. Golm, Guanghan (Frank) Liu

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In the presence of competing events, traditional survival analysis may not be appropriate and can result in biased estimates, as it assumes independence between competing events and the event of interest. Instead, competing risk analysis should be considered to correctly estimate the survival probability of the event of interest and the hazard ratio between treatment groups. The COVID-19 pandemic has provided a potential source of competing risks in clinical trials, as participants in trials may experienceCOVID-related competing events before the occurrence of the event of interest, for instance, death due to COVID-19, which can affect the incidence rate of the event of interest. We have performed simulation studies to compare multiple competing risk analysis models, including the cumulative incidence function, the sub-distribution hazard function, and the cause-specific hazard function, to the traditional survival analysis model under various scenarios. We also provide a general recommendation on conducting competing risk analysis in randomized clinical trials during the era of the COVID-19 pandemic based on the extensive simulation results.

Keywords: competing risk, survival analysis, simulations, randomized clinical trial, COVID-19 pandemic

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Authors: Assem I. El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent Railway Control System (MARCS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, multi-agent, railway control, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

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Authors: Jerry Q. Cheng

Abstract:

Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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