Phenomenon Of Overload Research Articles

Fuze vibration reduction design based on high-speed rocket sled vibration effect

Abstract Rocket sled is one of the important methods to realize the performance test in fields such as aerospace and weapon equipment. In response to the extremely high overload phenomenon of the tested fuze system in rocket sled impact tests, this paper proposes a new method of fuze vibration reduction. By optimizing the layout and multi-layer potting of fuze shell and internal components, the influence of vibration effects on electronic components is effectively reduced. Comparative analysis of results is based on epoxy resin sealant potting, silicone rubber potting, or without additional protection, to further improve the safety and service life of internal key components and provide necessary structural reference for vibration reduction treatment in rocket sled tests.

User's Dilemma: A Qualitative Study on the Influence of Netflix Recommender Systems on Choice Overload

AbstractIn the digital era, where choices saturate daily life, the phenomenon of choice overload becomes a significant concern in consumer behavior and psychology. Recommender systems, exemplified by Netflix's sophisticated model, play a transformative role in navigating the vast landscape of digital entertainment. This qualitative study examines the impact of recommender systems on choice overload through 12 semi-structured interviews with Netflix users, revealing the intricate dynamics between personalization algorithms and user decision-making processes. The study is guided by the following research questions: (1) How does the Netflix recommendation system influence users' experiences of choice overload and ease of decision-making? (2) To what extent do users perceive Netflix's recommended content as appealing and diverse, and how reliant are they on these recommendations for content selection? (3) How do user interactions with Netflix's recommendation system, including user feedback, impact variables such as search time, choice effort, and choice satisfaction? The findings reveal a notable absence of explicit user feedback and the presence of choice overload in Netflix users. This is evident in prolonged search times, heightened choice effort, and moderate satisfaction levels, coupled with perceptions of unattractiveness and limited diversity in the recommended content. Negative emotional responses during content selection further underscore the challenges users face on the platform. Paradoxically, this gives rise to a potential “user's dilemma,” as the study exposes a high reliance and trust in recommendation lists. However, this reliance also results in users frequently experiencing frustration and disappointment when recommendations fail to meet expectations. The study provides valuable insights into the nuanced interactions between users and the Netflix platform and offers a foundational framework for ongoing refinement of recommender systems in the ever-evolving landscape of streaming services and emphasizes the need for recommendation lists to strike a delicate balance between effective guidance and user exploration.

A Blocking Method for Overload-Dominant Cascading Failures in Power Grid Based on Source and Load Collaborative Regulation

Adjusting generator output and cutting off load can effectively solve the problem of continuous overload and disconnection of power lines caused by power flow transfer. To suppress large-scale power outages caused by overload-dominant cascading failures, a blocking method for overload-dominant cascading failures in the power grid based on source and load collaborative regulation is proposed. The shortest path algorithm was used to identify loads and generators with shorter electrical distances from overloaded lines. Under the premise of meeting the static safety constraints of the power grid, considering the regulation of generator output and the removal of interruptible loads, a multiobjective cascading failure blocking model is established with the minimum overall control cost of the system and the minimum probability coefficient of line failure. Use the NSGA-II algorithm to solve the model and obtain the optimal plan for adjusting generator output and cutting off load. Through example verification, the proposed method can effectively alleviate the phenomenon of line overload, thereby blocking the continuation of overload-dominant cascading failures.

Revealing the impact of losses on flexible pavement due to vehicle overloading

Pavement overload has become a significant concern in Indonesia due to its damaging effects on the pavement system, where most roads use flexible pavements. Meanwhile, overloading is also typical in other developing countries, causing everything from damage to accidents to the detriment of road users and operators. The current problem is that there is no definite knowledge of handling these overloaded vehicles, which has adverse effects. Therefore, this study aims to reveal the impact of losses caused by overloaded vehicles on flexible pavement. This research uses vehicle traffic load data to examine actual conditions in the field, which are converted to axle load values for each vehicle and used to determine pavement condition using the truck factor approach, mechanistic-empirical design, pavement smoothness level, and the impact of overloading due to fuel consumption by vehicles on flexible pavement. The results show that overloaded vehicles harm the flexible pavement. The increase in truck factor values for all vehicles in overloaded vehicles beyond the maximum allowable load results in more damage to the flexible pavement with an increase in truck factor values up to 83 %. The effect of overloading can be mitigated by increasing the thickness of the asphalt layer and the modulus of asphalt, so it is essential to pay attention to the quality of asphalt in anticipation of this overloading. To anticipate the overload phenomenon, it was found that the thickness of the asphalt overlay in the range of 170–205 mm could mitigate this detrimental effect. In addition, overloading affects the flexible pavement roughness and vehicle fuel consumption. Increased roughness and fuel consumption will increase road maintenance costs and affect driving comfort and safety. In addition, excessive fuel consumption can pollute the surrounding environment

Choice overload interferes with early processing and necessitates late compensation: Evidence from electroencephalogram.

Having a multitude of choices can be advantageous, yet an abundance of options can be detrimental to the decision-making process. Based on existing research, the present study combined electroencephalogram and self-reported methodologies to investigate the neural mechanisms underlying the phenomenon of choice overload. Behavioural data suggested that an increase in the number of options led to negative evaluations and avoidance of choice tendencies, even in the absence of time pressure. Event-related potential results indicated that the large choice set interfered with the early visual process, as evidenced by the small P1 amplitude, and failed to attract more attentional resources in the early stage, as evidenced by the small amplitude of P2 and N2. However, the LPC amplitude was increased in the late stage, suggesting greater investment of attentional resources and higher emotional arousal. Multivariate pattern analysis revealed that the difference between small and large choice set began at around 120 ms, and the early and late stages were characterised by opposite activation patterns. This suggested that too many options interfered with early processing and necessitate continued processing at a later stage. In summary, both behavioural and event-related potential (ERP) results confirm the choice overload effect, and it was observed that individuals tend to subjectively exaggerate the choice overload effect.

Assessing the relationship between information overload, role stress, and teachers’ job performance: Exploring the moderating effect of self-efficacy

The integrated technologies’ role has increased at educational institutes, and multiple information resources have increased the phenomenon of information overload and role stress among teachers. This study investigated the relationship between information overload, role stress, and teachers’ job performance. Additionally, explored the moderating effect of teachers’ self-efficacy. This study employed a quantitative research design and used a survey approach. Data was collected from 284 teachers working in the public –sector primary, middle and secondary schools. IBM SPSS and SmartPLS 3.0 were used to analyze the data. Findings indicated that information overload has a negative direct effect on teachers’ job performance. Further, information overload has a positive and significant impact on role stress that decreases job performance. Moreover, the mediator ‘role ambiguity’ has significantly mediated the effect of information overload on the job performance. However, the impact of information overload was not passing through the mediator role conflict. Self-efficacy has a moderating effect on the relationship between information overload, role stress, and job performance. Additionally, this study has also discussed theoretical and practical implications.

Proposal of a Visualization System for a Hierarchical Clustering Algorithm: The Visualize Proximity Matrix

Visual data mining is a new and effective strategy for dealing with the growing phenomenon of information overload. There is an urgent need for effective visual data mining because the growth of data sets from different domains and sources has made exploring, managing and analyzing vast volumes of data increasingly difficult. Identifying location-based trends and anomalies in data from a numeric output is challenging. The outputs of data mining procedures are often quite difficult to interpret. There is no human input to data exploration or direct involvement in the data mining process. Thus, it is difficult to analyze, explore, understand and view the data. In data mining, massive data sets are clustered using an iterative process that includes human input but data mining algorithms can miss some knowledge and observations. In addition, many users cannot take the appropriate action to address problems or opportunities because the huge amounts of data prevent them from staying aware of what is happening in and around their environments. Visual data mining can help in dealing with information overload and it is effective in analyzing large complex data sets. Visual data mining assists users in gaining a deep visual understanding of data. In the information age, users need to study and observe vast amounts of data to acquire important knowledge, and thus the need for visual and interactive analytical tools is particularly pressing. Visual cluster analysis has long utilized shaded similarity matrices, and this study investigated how they can be used in clustering visualization. We focused on proposing an agglomerative hierarchical clustering method. Ensemble cluster visualization is also presented for handling large data sets. This study proposes the adoption of a shaded similarity matrix to visually cluster knowledge discovered using data mining. Using the technology acceptance model as the measuring tool, we questioned respondents to evaluate the visualization prototype. The findings demonstrated that the visualization was effective and easy to use, and satisfied users.

A Data Warehouse Architecture Proposal and ETL Analysis, Case study of an Albanian Banking System

The increasing phenomenon of information overload is a direct result of the ongoing trend to reduce the cost of data distribution while the development of data processing platforms is not fast enough. Therefore, sending packets of data is not a big issue, but processing an increasing amount of data is a big challenge.
 Data Warehouse is a concept born in the late ‘80s and has been improved decade after decade with the growth of technology. Despite many application areas, the data warehouse concept is still new and unknown to Albanian businesses and companies with a large amount of data to store and analyze.
 This paper aims to provide an in-depth analysis of the concept of a data warehouse, the different architectures applied, and the Extract, Transform Load (ETL) process. The ETL process as a concept consists of extracting the data from a source, transforming them into different formats or dimensions, and then loading them somewhere to be checked for analysis or other purposes.
 In this paper, we can find different definitions of the data warehouse, where it can be implemented, the different architectures according to the need of the users, and how the ETL process works. The last chapter implements a data warehouse for the banking system seen from a Management Information Systems perspective followed by an application of a step-by-step ETL procedure.

The Influence of Information Types and Search Intention in Using Branded Or Generic Search Query

This study aims to analyze the effect of each type of information and search intention on the use of branded or generic search queries on search engines. This is done because of the emergence of the phenomenon of information overload or explosion of information. The types of tourism information studied are transportation, accommodation, restaurants, shopping places, and tourist attractions with two types of intention, namely purchase intention and intention to search. This study used a quantitative approach by distributing online questionnaires to users who had searched using a search engine and managed to collect 1,256 respondents. Data were analyzed using binary logistic regression. We found that intention influences the use of branded or generic search queries and several types of information influence the use of search queries. Transportation and shopping information could influence users in choosing to use generic or branded search queries.

Correction of dynamic Brazilian disc tensile strength of rocks under preloading conditions considering the overload phenomenon and invoking the Griffith criterion

Correction of dynamic Brazilian disc tensile strength of rocks under preloading conditions considering the overload phenomenon and invoking the Griffith criterion

Responses to News Overload in a Non-Partisan Environment: News Avoidance in China

Studies conducted in Western democratic countries with privately owned press presenting news from different ideological perspectives have found the phenomenon of news overload causes stress in media users (affective load) and this leads to news avoidance behavior. This study, conducting a structural equation modeling using AMOS 27, investigates the relationships between news overload, affective load, and consequent news avoidance behavior in China. The findings suggest, consistent with studies in Western democratic jurisdictions, that news overload and affective load influence users’ news avoidance behavior. However, in contrast to studies outside of China, this study found demographic variables of age, gender, education, and occupation had no statistically significant influence on avoidance behavior by Chinese social media news consumers. The results suggest that either social attributes and responses by media users in China are significantly different from those in Western countries or ideology plays an important role in avoidance behavior and the impact of ideology is different across different demographic groups in Western jurisdictions.

Low-Computation Adaptive Saturated Self-Triggered Tracking Control of Uncertain Networked Systems

In this paper, a low-computation adaptive self-triggered tracking control scheme is proposed for a class of strict-feedback nonlinear systems with input saturation. By introducing two novel error transformation functions, the designed low-computation adaptive control scheme can overcome the problem of complexity explosion in the absence of any filters, such that the developed control scheme is more applicable. In addition, to save communication resources in networked systems, a self-triggered communication strategy is proposed which can predict the next trigger point based on the current information. Compared with traditional event-triggered mechanisms, the computational burden arising from continuous monitoring of threshold conditions was successfully avoided. Furthermore, the input saturation problem considered in this paper prevents the overload phenomenon caused by signal jumps, and the adverse effects are compensated by introducing an auxiliary system. The effectiveness of the developed control scheme is verified through a simulation example.

Algorithm Improvement of Movie Recommendation System based on Hybrid Recommendation Algorithm

In recent years, the Internet has developed rapidly, and in the face of thousands of data and information, it has become very critical for users to find the information that is of high value to them in the mass of information, and the recommendation system is one of the most effective ways to solve this information overload phenomenon. In this paper, the current movie recommendation algorithm is improved by using an item-based collaborative filtering algorithm for the similarity measure of items in the item-based recommendation process; In the recommendation process, two more applicable recommendation methods are considered: collaborative filtering content-based recommendation and matrix decomposition-based recommendation. It saves users time in searching, viewing and filtering, while discovering information about their potential movie preferences.

Vehicle Load Identification on Orthotropic Steel Box Beam Bridge Based on the Strain Response Area

With the development of the economy and the rapid increase in traffic volume, an overload phenomenon often occurs. This paper studied a vehicle load identification technique based on orthotropic bridge deck stress monitoring data. The strain responses on the lower edge of multiple U-ribs were collected under vehicles crossed the deck. Firstly, an index based on the cross-correlation function of strain response between different measurement points on the same U-rib was used to evaluate vehicle speed. Secondly, a cosine similarity index was proposed to locate the transverse position of the vehicle. Finally, the unknown vehicle load was identified on the basis of a calibrated strain response area matrix. The effectiveness and anti-noise performance of the proposed method were verified using numerical simulation. An experimental model was designed and some strain gauges were installed to measure the strain response, and the test was carried out to further verify the algorithm’s performance. Numerical and experimental results show that the proposed method could effectively identify the vehicle load with good anti-noise performance. Moreover, a calibration space was provided to guide practical engineering applications. The proposed method does not damage bridge decks, does not affect traffic, and is economical.

Application of Internet of Things technology in Human resource recommendation engine

In order to avoid the phenomenon of information overload in the field of human resources, the author proposes a human resource recommendation engine based on Internet of Things technology. Firstly, the application fields of the Internet of Things are introduced, and the human resource recommendation engine is designed, use a mixed referral approach in the HR field. We chose a hybrid recommendation strategy of PLSA and content based on the Internet of Things. The author introduces the human resource recommendation and content-based human resource recommendation of PLSA based on the Internet of Things respectively, on the basis of the above introduction, through the analysis of the existing hybrid recommendation strategy, a weighted hybrid method of PLSA based on the Internet of Things and content-based recommendation algorithm is proposed. In order to verify the feasibility of the proposed IoT-based PLSA and content-based HR recommendation method, we conducted a multi-step experiment. We selected 50 graduating students from A University to participate in this experiment, and the results show that in order to verify the overall effect of the algorithm, with accuracy and recall as evaluation criteria, we conducted experiments on recommendation algorithms of PLSA based on Internet of Things, content-based recommendation algorithms, and recommendation algorithms based on PLSA and content weighting mixture, where, the number of z in PLSA algorithm is 10, the value of β in mixed recommendation is 0.6, the size of N in TopN recommendation is N=5,10,20, and 30. Experiments were carried out on the accuracy and recall of the three recommendation algorithms, the number of z in PLSA algorithm is 10, the value of β is 0.6, and the size of N in TopN recommendation is N=3,5,7,9. The recommendation effect of PLSA based on the Internet of Things is better than that of content-based recommendation algorithm, and the recommendation effect of the combination of the two algorithms is better than either of them.

Responsive and intelligent service recommendation method based on deep learning in cloud service.

The rapid expansion of the cloud service market is inseparable from its widely acclaimed service model. The rapid increase in the number of cloud services has resulted in the phenomenon of service overload. Service recommendations based on services' function attributes are important because they can help users filter services with specific functions, such as the function of guessing hobbies on shopping websites and daily recommendation functions in the listening app. Nowadays, cloud service market has a large number of services, which have similar functions, but the quality of service (QoS) is very different. Although the recommendation based on services' function attributes satisfies users' basic demands, it ignores the impact of the QoS on the user experience. To further improve users' satisfaction with service recommendations, researchers try to recommend services based on services' non-functional attributes. There is sparsity of the QoS matrix in the real world, which brings obstacles to service recommendation; hence, the prediction of the QoS becomes a solution to overcome this obstacle. Scholars have tried to use collaborative filtering (CF) methods and matrix factorization (MF) methods to predict the QoS, but these methods face two challenges. The first challenge is the sparsity of data; the sparsity makes it difficult for CF to accurately determine whether users are similar, and the gap between the hidden matrices obtained by MF decomposition is large; the second challenge is the cold start of recommendation when new users (or services) participate in the recommendation; its historical record is vacant, making accurately predicting the QoS value be more difficult. To solve the aforementioned problems, this study mainly does the following work: 1) we organized the QoS matrix into a service call record, which contains user characteristic information and current QoS. 2) We proposed a QoS prediction method based on GRU-GAN. 3) We used the time series data for quality predictions and compared some QoS prediction methods, such as CF and MF. The results showed that the prediction results based on GRU-GAN are far superior to other prediction methods under the same data density. We aim to help the engineering community promote their findings, shape the technological revolution, improve multidisciplinary collaborations, and collectively create a better future.

The consequences of collaborative overload: A long-term investigation of helping behavior

Given the growing demand for interpersonal helping in contemporary organizations, this study proposes a mechanism and a boundary condition by which helpers incur personal and professional costs over time. Drawing on the conservation of resources theory, we hypothesize that job demands mediate the link between helping escalation and negative outcomes and that the resulting detrimental processes depend on organizational tenure. Our analysis of a four-wave dataset of 898 workers in a U.S. health care organization reveals that helping escalation leads to emotional exhaustion and work-to-family conflict through job demands. Furthermore, the adverse outcomes of collaborative overload are more salient among helpers with a longer tenure. Our claims and findings provide theoretical and practical implications about the rampant phenomenon of collaborative overload and its dynamics from a long-term perspective.

Specifics of Algorithmization in Data Culture

Abstract Information societies effectively transform existing cultures. New cultures are variously defined, but because of the fact that they are dominated by information, the term “data cultures” seems to be the most relevant name for them. Although, it is possible to create a single global data culture in the future and such predictions prevail in academic and non-academic reflections on this subject, so far in addition to global trends there occur local data cultures, what also dynamizes and enriches both individual and collective identities. As Kazimierz Krzysztofek aptly notes, in this situation: "The greatest contradiction of the civilization of the 21st century is drawn. On the one hand, a continuous imperative: be creative and innovative, on the other hand, an increasing pressure on prediction of people’s behaviour, because unpredictability causes chaos, which cannot be managed". In other words, one of the most important social issues today is to create some order in data culture / cultures (often pictured by columnists and researchers as a "magnetic storm"), to reduce its / their infinite complexity, i.e. simply the algorithmization process. With regard to culture, it is not possible to use unequivocally a mathematical algorithm that is the most precise, or a genetic or hormonal algorithm that functions in nature, because accustoming cultural chaos is always strongly ideologized. The algorithm should be treated as a metaphor used to explain cultural phenomena, especially their developmental tendencies. For the researcher of contemporary societies, it is very important to answer the question: what proportions of structure and network are the most beneficial for the survival of data culture / cultures? This answer also directs reflection on the quality of life of individuals and societies, limiting or promoting individualism and collective intelligence in the era of hyper-digitization. These considerations are limited to the initial characterization and evaluation of the information algorithmization of man. The author of the study refers to the concepts of researchers from different countries, highlighting the specificity of today's algorithmization, among others the model of ambient perception, which facilitates participation in the networked information environment, scope and reach of the big data phenomenon, forms of data visualization, personalization of content, Isotype visual language, network custody, data journalism and others. In conclusion, it is pointed out that the information algorithmization of man is constantly growing, which proves that data management strategies weaken the phenomenon of information overload through the logic of numerical civilization, which limits diversity, seeking to count, record and globalize everything.

Differences of Psychopathology of Psychiatric Disorders in Adult Patients with Intellectual Disability

Intellectual disability is a mental disorder which appears during the developmental period in childhood and continues life-long. It is characterized by intellectual deficits on the one side and maladaptive social functioning on the other. The intellectual deficits include problems in abstract and logic thinking, problem solving, reasoning, learning from experience and judging. The deficits in adaptive functioning appear in problems in social communication and participation as well as in mental overload phenomena caused by daily life activities. This overload often results in psychopathological features and psychosocial reactions which are usually observed in Burn-out-Syndromes as e.g. general exhaustion (depletion of primarily reduced mental resources), additional reduced efficacy (accompanied by feelings of insufficiency and poor self-esteem), and most typically feelings alienation (towards intrinsically familiar situations, towards relatives and friends and at least also against oneself ) typically accompanied by irritability and dysphoria. Treatment programs therefore should not only focus on intellectual deficits but should include also the multiple sufferings from psychopathological phenomena and psychosocial effects of such daily life overload syndromes.DisclosureNo significant relationships.

비대면 수업 운영에 따른 한국어 교사의 직무스트레스 및 직무도전성에 관한 연구

The purpose of this study is to empirically identify the job stress and job challenge perceived by Korean teachers in the non-face-to-face classroom environment caused by COVID-19. Today’s evolving technological advances and the variable COVID-19 have had a direct impact on the change in the educational field. The introduction of the non-face-to-face class method changed the educational paradigm and had an effect on the job of the professor. In particular, in the case of Korean classes for foreigners, there was a lot of trouble from designing the class method. In order to achieve the purpose of this study, qualitative data were collected and analyzed from 5 Korean language teachers at metropolitan universities. The research method was a semistructured interview based on a questionnaire, and took three forms: face-to-face, telephone, and video. The results of interview data analysis were able to draw contradictory results in job stress and job challenge. Job stress increased due to non-face-to-face classes, but on the other hand, job challenge also increased. The factors contributing to job stress were the application of the online job environment, the difficulty of interaction between teachers and learners, and the phenomenon of work overload. Nevertheless, the professor had the characteristic of being able to demonstrate job challenge by producing high-quality educational contents. Factors affecting job challenge include competency development and expansion, creative idea creation, and job prospect search. Based on the analysis results, conclusions and implications for improving job stress and job challenge of Korean teachers were presented.