Traditional Event Research Articles

Distributed Two-Channel Dynamic Event-Triggered Adaptive Finite-Time Fault-Tolerant Containment Control for Multi-Leader UAV Formations

This paper addresses the distributed adaptive finite-time containment control problem in multi-leader UAV formations with actuator failures, limited communication, and external disturbances. A two-channel dynamic event-triggered strategy based on adaptive and sliding mode control is proposed as a containment control scheme, which solves the contradiction between the need to include containment error in the continuous term of the sliding mode surface in the adaptive law and the discontinuity of the communication between neighboring subsystems (follower UAVs) by constructing intermediate variables. Unlike the traditional event triggering condition that can only be applied to asymptotically convergent systems, the dynamic triggering condition designed in this paper, based on auxiliary variables, hyperbolic tangent function, and adaptive techniques, realizes finite-time convergence during the adjustment of the system and sets a more reasonable lower limit for the triggering thresholds, thus further reducing the communication frequency and ensuring the finite-time convergence of the system. The stability of the closed-loop system can be proved by the Lyapunov theorem. Zeno behavior can be avoided. The simulation results verify the effectiveness of the developed control algorithm.

PAIReD jet: A multi-pronged resonance tagging strategy across all Lorentz boosts

We propose a new approach of jet-based event reconstruction that aims to optimally exploit correlations between the products of a hadronic multi-pronged decay across all Lorentz boost regimes. The new approach utilizes clustered small-radius jets as seeds to define unconventional jets, referred to as PAIReD jets. The constituents of these jets are subsequently used as inputs to machine learning-based algorithms to identify the flavor content of the jet. We demonstrate that this approach achieves higher efficiencies in the reconstruction of signal events containing heavy-flavor jets compared to other event reconstruction strategies at all Lorentz boost regimes. Classifiers trained on PAIReD jets also have significantly better background rejections compared to those based on traditional event reconstruction approaches using small-radius jets at low Lorentz boost regimes. The combined effect of a higher signal reconstruction efficiency and better classification performance results in a two to four times stronger rejection of light-flavor jets compared to conventional strategies at low Lorentz-boosts, and rejection rates similar to classifiers based on large-radius multi-pronged jets at high Lorentz-boost regimes.

Research on the Collision Risk of Fusion Operation of Manned Aircraft and Unmanned Aircraft at Zigong Airport.

Low-altitude airspace is developing rapidly, but the utilization rate of airspace resources is low. Therefore, in order to solve the problem of the safe operation of the fusion of large UAVs and manned aircraft in the same airspace, this paper analyzes the theoretical calculation of the collision risk of the fusion operation of manned aircraft and UAVs at Feng Ming Airport in Zigong, verifying that while assessing the safety spacing of 10 km in the lateral direction, it further simulates the possibility of calculating the theoretical smaller safety spacing. The study will propose a new theory of error spacing safety margin and improve it according to the traditional Event collision risk model, combining the error spacing safety margin to establish an improved collision model more suitable for the fusion operation of manned and unmanned aircraft and reduce the redundancy of calculation. The error factors affecting manned and unmanned aircraft at Zigong Airport are analyzed, and theoretical calculations are analyzed by combining the actual data of Zigong Airport. Finally, the Monte Carlo simulation method is used to solve the error, substitute the calculation results, and simulate a section of the trajectory of the fusion operation for the reverse argument. The theoretical calculation results show that the collision risk from 10 km to 8 km satisfies the lateral target safety level (TSL) specified by ICAO under both traditional and improved models. The collision risk calculated by the improved model incorporating the error spacing safety margin is smaller, which enhances the safety of the model calculations. The results of the study can provide theoretical references for the fusion operation of manned and unmanned aircraft.

Analisis Kinerja Logistic Regression Classifier Berdasarkan Seleksi Fitur Warna, GLCM (Gray Level Co-occurrence Matrix) dan Bentuk (Studi Kasus Jenis Ketupat Khas Bali)

Ketupat is a unique culture and tradition in Bali. Ketupat is often used as a banten offering. This unique procession of the ketupat war is held once a year to coincide with the Purnama Kapat. The ketupat war is a traditional event with participants throwing ketupat at each other. It aims to be grateful for all the gifts that the Creator has given to humans in this world. This tradition has existed since the 1970s with the beginning of its appearance involving two shirtless men. The ketupat war ceremony is part of the yadnya as the basis for the return of the Tri Rna. In today's era of the development of science and technology, people are only focused on meeting material needs, understanding the meaning of rituals and religious events is decreasing, and it is considered an incriminating or even meaningless activity. In this study, a dataset of 90 was used with 18 types of ketupat used, namely: bagia, batu dam-pulan, bracelet, kale, mattress, kedis, kepel, kroso, lepet, pengambean, sai, cow, sari, sirikan, suna, tulud, tumpeng. This study aims to determine the per-formance of Logistic Regression Classifier by using color, HSV, GLCM and shape features. The dataset used is a typical Balinese ketupat type of 90 data. In this test, 4 test scenarios are used: 1) The first test scenario, the dataset input performs the preprocessing process, HSV imagery, and the color feature extraction process where the output results are in the form of hue, saturation and value values in the form of excel files. 2) The second test scenario, the input dataset performs a preprocessing process, grayscale, and performs the GLCM feature extraction process where the output results are in the form of feature values of angle 00, angle 450, angle 900 and angle 1350 in the form of an excel file. 3) The third test scenario, the dataset input performs the preprocessing process, binner, performs the form feature extraction process where the output results are in the form of metric, eccentricity in the form of excel files. 4) The fourth test scenario, from the 3 (three) feature extractions carried out, the new dataset, the next stage is to implement the Logistic Re-gression classifier method to obtain accuracy values. Based on the results of the classification, testing and analysis, the level of accuracy from each of them was obtained with a training accuracy value of 69.84% and a testing accuracy of 22.2%, which means that the classification method was declared ineffective in analyzing the features used in the ketupat classification, so it is necessary to compare it with other methods so that it gets an accuracy result above 90%.

Case Study On the Landmark Ruling On Jallikattu- A Critical Analysis Contemplating the Deviation from Ecocentric Approach

The case "Animal Welfare Board of India vs. A. Nagaraja & Ors," which was determined on May 7, 2014 and Animal Welfare Board of India & Ors vs Union Of India & Anr decided on May 18, 2023, dealt with the practice of Jallikattu. Jallikattu is a traditional event in Tamil Nadu and Maharashtra that involves bulls. This activity, in which individuals attempt to seize money fastened to the horns of a bull, has developed into a pastime that inflicts considerable suffering and injury to the animals. The Supreme Court of India determined that the utilization of bulls in activities such as Jallikattu and bullock cart racing amounted to cruelty, therefore infringing upon the animals' entitlements under Article 21 of the Indian Constitution, which ensures the right to life and freedom. The court's ruling underscored the need of ethical treatment of animals, in accordance with current perspectives on animal welfare. The verdict aimed to prohibit these activities in order to prevent the physical and psychological torment of bulls utilized for human amusement during cultural festivities. This ruling represented a noteworthy advancement in acknowledging and safeguarding animal rights in India, but also considering the need to prevent animal abuse and ensure public safety, while taking into account traditional customs. The case exemplified the convergence of law, culture, and animal ethics, establishing a precedent for the compassionate treatment of animals within the legal framework of the country.

Etnoscience of Traditional Alcoholic Beverages (Moke Putih) of Ngada East Nusa Tenggara

Ngada district has a traditional drink called moke putih. Moke putih is a traditional alcoholic beverage made from the Aren’s water (Arenga pinnata Merr.) that is found in Flores. For the people of Ngada, moke putih is a symbol of being kind and harmony, and the consumption of moke has become a lifestyle for most people in there. This drink has a lot of potential because it has strong historical elements and cultural values. The purpose of this research is to know the history, processing, and the connection between moke putih and the culture of Ngada. The research method is a qualitative approach to ethnoscience through purposive sampling techniques and snowball samplings from villages with 10 respondents and data collection through interviews, observations, and documentation. Moke Putih is a traditional drink that has been passed down from generation to generation and is closely related to the culture, customs, and characteristics of the Ngada people. White moke is made from slicing the fruit stalks of the sap tree, and this drink is used at every traditional event and in daily activities as a substitute for drinking water.

An extended event study methodology and its application in the HNA group's overseas market contraction

This paper introduces a novel framework for analyzing the performance of cross-border merger and acquisition (M&A) activities in international business. It investigates whether the contraction of overseas market activities can mitigate financial crises, using the case study of a Chinese multinational enterprise (MNE). Traditional event study methodology, commonly used for assessing business performance changes, relies on assumptions of normality and homoscedasticity in data. However, real financial data often exhibits high volatility and non-normal distribution, rendering traditional methods inadequate for estimation. To address this limitation, we propose an enhanced analytical framework integrating the Shapiro–Wilk test, event studies, quantile regression, and nonparametric rank tests. This approach provides more robust estimates, facilitating a more accurate and comprehensive analysis of business performance changes under specific events. Applying this methodology to assess the short-term performance of HNA Group, a cross-border airline in China, during its financial crisis, we find that while overseas market contraction events generate overall positive short-term value for enterprises, the impact varies depending on the assets sold. However, given HNA Group's substantial debt burden, the positive effect is minimal, indicating that overseas market contraction alone is insufficient as a "self-help" strategy in addressing corporate financial crises.

Real-time data analytics in distributed systems

Real-time data analytics involves the processing and analysis of data as it arrives, delivering immediate insights that are crucial for time-sensitive applications. This research explores the platforms and techniques necessary for supporting real-time analytics, extending beyond traditional Event Processing Systems (EPS) to include broader big data contexts that integrate both 'data at rest' and 'data in motion' solutions. A detailed case study is presented, showcasing the application of the Event Swarm complex event processing engine in addressing financial analytics challenges. The study identifies key research challenges in the field, emphasizing the need for innovative approaches and algorithms to enhance real-time data filtering, exploration, statistical analysis, and machine learning.

Multimodal Shot Prediction Based on Spatial-Temporal Interaction between Players in Soccer Videos

Sports data analysis has significantly advanced and become an indispensable technology for planning strategy and enhancing competitiveness. In soccer, shot prediction has been realized on the basis of historical match situations, and its results contribute to the evaluation of plays and team tactics. However, traditional event prediction methods required tracking data acquired with expensive instrumentation and event stream data annotated by experts, and the benefits were limited to only some professional athletes. To tackle this problem, we propose a novel shot prediction method using soccer videos. Our method constructs a graph considering player relationships with audio and visual features as graph nodes. Specifically, by introducing players’ importance into the graph edge based on their field positions and team information, our method enables the utilization of knowledge that reflects the detailed match situation. Next, we extract latent features considering spatial–temporal interactions from the graph and predict event occurrences with uncertainty based on the probabilistic deep learning method. In comparison with several baseline methods and ablation studies using professional soccer match data, our method was confirmed to be effective as it demonstrated the highest average precision of 0.948, surpassing other methods.

Searching for gluon quartic gauge couplings at muon colliders using the autoencoder

One of the difficulties one has to face in the future phenomenological studies of new physics (NP), is the need to deal with increasing amounts of data. It is therefore increasingly important to improve the efficiency in the phenomenological study of NP. Whether it is the use of the Standard Model effective field theory (SMEFT), the use of machine learning (ML) algorithms, or the use of quantum computing, all are means of improving the efficiency. In this paper, we use a ML algorithm, the autoencoder (AE), to study the dimension-8 operators in the SMEFT which contribute to the gluon quartic gauge couplings (gQGCs) at muon colliders. The AE is one of the ML algorithms that has the potential to be accelerated by the quantum computing. It is found that the AE-based anomaly detection algorithm can be used as event selection strategy to study the gQGCs at the muon colliders, and is effective compared with traditional event selection strategies. Published by the American Physical Society 2024

EventPro – Application for Events

Abstract: In recent years, the event management landscape has undergone a profound transformation, driven by the emergence of event apps that have played a pivotal role in this evolution. This abstract delves into the concept of event apps, shedding light on their transformative impact and their potential to revolutionize the entire event lifecycle, encompassing planning, execution, and the overall event experience. Event apps are specialized software applications tailored to streamline the comprehensive event management process. Leveraging the widespread adoption of smartphones and the connectivity of the internet, these digital tools provide a seamless, enhanced event experience for attendees, organizers, and stakeholders. A prominent advantage of event apps is their capacity to simplify the event registration and ticketing process. Attendees can swiftly and conveniently register for events, select sessions, and make payments, effectively reducing the administrative workload for event organizers. Furthermore, event apps offer an array of features, including personalized schedules, interactive maps, and real-time notifications, ensuring attendees can effortlessly navigate events and stay informed about the latest updates. Beyond convenience, event apps foster valuable networking interactions among participants. They facilitate connections, meeting scheduling, and the exchange of contact information, opportunities that might have been challenging to achieve in a traditional event setting. They track attendee engagement, preferences, and behaviors, equipping organizers with insights to tailor future events for maximum impact. Additionally, event apps enable real-time communication, simplifying logistics management and responses to unexpected changes or challenges. As technology continues to advance, the potential for event apps to further revolutionize event planning, execution, and overall experiences is virtually limitless.

Using k-means assistant event selection strategy to study anomalous quartic gauge couplings at muon colliders

The search for new physics beyond the Standard Model is one of the central problems of current high energy physics interest. As the luminosities of current and near-future colliders continue to increase, the search for new physics has increased the requirements for processing large amounts of data. Meanwhile, quantum computing which is rapidly evolving, has great potential to become a powerful tool to help search for new physics signals. Since the k-means algorithm is known to be able to be accelerated with the help of quantum computing, we investigate and propose an event selection strategy based on k-means algorithm to search for new physics signals. Taking the case of tri-photon processes at the muon colliders as an example, the event selection strategy is shown to be effective in helping to search for the signals of dimension-8 operators contributing to anomalous quartic gauge couplings. Compared with traditional event selection strategy, the expected constraints are generally tighter.

Multistructure Contrastive Learning for Pretraining Event Representation.

Event representation aims to transform individual events from a narrative event chain into a set of low-dimensional vectors to help support a series of downstream applications, e.g., similarity differentiation and missing event prediction. Traditional event representation models tend to focus on single modeling perspectives and thus are incapable of capturing physically disconnected yet semantically connected event segments. We, therefore, propose a heterogeneous event graph model (HeterEvent) to explicitly represent such event segments. Furthermore, another challenge in traditional event representation models is inherited from the datasets themselves. Data sparsity and insufficient labeled data are commonly encountered in event chains, easily leading to overfitting and undertraining. Therefore, we extend HeterEvent with a multistructure contrastive learning framework (MulCL) to alleviate the training risks from two structural perspectives. From the sequential perspective, a sequential-view contrastive learning component (SeqCL) is designed to facilitate the acquisition of sequential characteristics. From the graph perspective, a graph-view contrastive learning component (GraCL) is proposed to enhance the robustness of graph training by comparing different corrupted graphs. Experimental results confirm that our proposed MulCL [W+E] model outperforms state-of-the-art baselines. Specifically, compared with the previously proposed supervised model HeterEvent [W+E] [Zheng et al. (2020)], MulCL [W+E] shows an average improvement of 5.3% in terms of accuracy for the inference-ability-based tasks. For the representation-ability-based tasks, MulCL [W+E] achieves an average improvement of 2.7% in terms of accuracy for the hard similarity tasks and an improvement of 4.1% in terms of the Spearman's correlation for the transitive sentence similarity task, respectively.

How do takeovers in the United Kingdom split value gains between domestic deals' parties?

PurposeThis paper aims to address the question: What is the distribution of value (in pounds) created in a sample of domestic takeovers in the United Kingdom from 2013 to 2020 among acquirer and target stockholders?Design/methodology/approachThe author employs a traditional event study methodology to calculate the percentage excess returns of companies on the announcement date. These returns are then converted into pound-denominated excess returns using the companies' market capitalizations. This allows the author to estimate the synergies of the mergers and acquisitions (M&As) and how they are allocated between acquirers and targets. This innovative transformation from percentage to pound excess returns establishes a new ratio methodology for addressing the paper's objective.FindingsThis paper reveals that in UK takeovers, 40 percent of the synergies in pounds are allocated to the stockholders of acquiring companies, while 60 percent go to the stockholders of target companies. In other words, acquirers retain a significant portion—more than half—of the synergies generated in these domestic deals. This original finding is statistically significant at the one percent level and strongly contradicts the hypothesis that acquirers, at best, merely break even.Originality/valueThe evidence that UK takeovers distribute value gains nearly equally between domestic deal parties challenges the enduring conventional insight in the M&A literature. This conventional wisdom suggests that the value created by business combinations is entirely distributed to target company stockholders. Consequently, this reexamination may have broader implications, offering an alternative perspective on the motives behind business combinations. This perspective differs from the “managerial hubris hypothesis,” which aligns with the prevailing conventional insight but receives limited support in the original finding reported here.

PERBANDINGAN SAJIAN MAKANAN DALAM UPACARA BESAR SUKU TENGGER: ANALISIS NILAI BUDAYA

The Tengger tribe is one of the majority Hindus, the sect they profess is mostly Mahayana Hinduism, but not a few are also Muslims. The spread of the Tengger tribe community has expanded not only in the Lumajang argosari area, but also to the Malang area. The Tengger tribe is the tribe best known for the least criminal acts in Indonesia, not only that the Tengger tribe is famous for a tribe that has a very strong tolerance value both in religious life and in community life. This research uses research methods of literature studies or literature reviews, data taken from various references ranging from articles, websites, journals, theses and theses. From the various data that the author has collected, the author can provide conclusions about the differences in presentation in each traditional ceremony. Because the Tengger people beieve that with the dishes they give every time there is a major religious event they do, they always have special dishes as a thanksgiving, the Tengger tribe people believe that by giving symbolic food offerings to the spirits that have left, making them more docile and not disturbing living creatures. The dishes given do not have to be luxurious food but complete according to the provisions of each traditional event. Keywords: tolerance, serving, custom

Behind the Waitress Work Clothes in the House of Raminten Restaurant Indonesia

Traditional cloth is one of the cultural products. Normally, it is worn by people for a certain traditional event. However, it is worn by the waitress in a restaurant, namely the House of Raminten restaurant. Therefore, this research aims to reveal the intent and purpose behind the use of traditional clothes as work clothes for waitresses at the House of Raminten Restaurant. Qualitative approach is employed as a research methodology in this research. The result shows that there is a symbolic meaning of Javanese culture represented by such a use of traditional clothes, namely glorifying guests or consumers. In another word, the use of kemben and jarik is a way for Raminten Restaurant to glorify their consumers. This is then being seen as a strategy for creating profit for the restaurant since it can represent the concern of the restaurant in preserving Javanese culture. The restaurant owner always does such a way to bring in customers since he has a sensitivity to market demand, even though he himself is actually of Chinese descent.

Study Of Living Al-Qur’an Analysis: Tale Jei Tradition For Hajj Jama'ah In Koto Petai Kerinci Indonesia

The study of the living Al-Qur’an tradition of Tale Jei in Koto Petai village uses qualitative-descriptive research methods by describing the facts of the reality of the data that is there for the data collection method, namely by interview and documentation methods to analyze the data obtained from various sources and then describe the results of the analysis. Tale Jei in Kerinci is a legacy of the cultural traditions of ninik mamak or previous scholars, especially in the village of Koto Petai, routinely holding this traditional event before releasing the pilgrims, which in the process contains all about the events of Hajj starting from the pillars of Hajj, Hajj obligations, Hajj requirements, Hajj prohibitions made and sung in the form of songs (Tale). With the help of the living Al-Qur’an, the author will analyze Karl Mannheim's Sociology of Knowledge theory, which focuses on three main points: objective, expressive, and documentary. From the results of the analysis, the author found the verses contained in this tradition by using the Living Al-Qur’an Study of the Tale Jei tradition in Koto Petai village, including 1) Surah al-Mujādalah (58: 11), 2) Surah Āli Imrān (3:97), 3) Surah al-Nahl (16:97), 4) Surah Fāṭir (35:29), and then reveal the spirit of the implementation of the tradition.

Instilling Multicultural Values in the Sikep Samin Community in Klopoduwur Village, Blora, Central Java

This research is descriptive and qualitative to examine Sikep Samin multicultural principles. The subjects are the Sikep Samin figure, the Sikep Samin community and the community in Klopoduwur Village. Data is collected through interviews, observation, and documentation. The data analysis process includes reduction, presentation, and verification. This study found: 1) The Sikep Samin community in Klopoduwur Village promotes human values, honesty, politeness, and openness; 2) Habituation of behavior, traditional event meetings, and the Sangkan Paraning Dumadi community instill multicultural values; and 3) Internal constraints constrain multicultural values. External limitations are the stereotypes of ordinary people who are unfamiliar with foreign cultures, producing negative stereotypes in that civilization (The Sikep Samin community).

Kegiatan Komunikasi Dalam Tradisi Nyawer Pada Pesta Pernikahan Adat Sunda

This study aims to describe the communication activities in the Nyawer tradition in Garut during Sundanese traditional weddings. This study discusses the communicative activities seen in communicative situations, events, and communicative behavior.
 This is a qualitative research method for ethnographic research on communication theory and symbolic interaction. The topic of his research is that some people happen when they sign the marriage contract. There are as many as traditional Sundanese, and all the reporters including 5 people. The sampling technique for the purpose of selecting information is used. The data collection techniques are in-depth interviews, non-participant observation, documentation, research, libraries and online data search. Data validity testing technology by increasing endurance, triangulation, discussions with colleagues, friends and members.
 The results showed that when the nyawer ceremony was held outside the building, the families of the bride and groom, the communication sawsman, make-up and the communication of the invited guests were involved. Communication Activities The nyawer ceremony is a special form of celebration, namely a traditional event that lasts 30 minutes and is held after the ceremony, while communication activities are traditional activities. Marriage customs and appear in the form of non-verbal behavior, including rice, turmeric, coins, flowers, candy, and areca nut.

The Dominance of Father's Role in the Film Ngeri-Ngeri Sedap

The purpose of this research is to identify the pattern of family communication in the film "Ngeri-ngeri Sedap". Film Ngeri-ngeri Sedap 2022 directed by Bene Dion tells the story of a family drama, telling the story of Pak Domu and Mak Domu who live with Sarma, their only daughter. The husband-and-wife couple wanted their three sons who had wandered for a long time to come home to attend a traditional event. But their three children refused because their relationship was not harmonious. This research was conducted with a type of qualitative research using the semiotic analysis model developed by John Fiske. The results of this study indicate that the communication in this film is quite problematic. This can be seen in the results of John Fiske's research on three levels of semiotics, namely the level of reality, the level of representation, and the level of ideology. The level of reality shows that the pattern of family communication implemented in this film has a paternalistic, namely a pattern where only one family member controls the family. In the case of this family, it is the father who controls the family.Keywords: Dominance, Fatherhood, Monopoly Communication Patterns, Film Ngeri-ngeri Sedap