Hasil untuk "Competition"

J. Cantwell, E. Helpman, P. Krugman

J. Bangsbo, L. Nørregaard, F. Thorsø

W. Oates, Robert M. Schwab

A. Kyle

J. Kaye, S. Hart

L. Armstrong, D. Casa, M. Millard-Stafford et al.

R. Leeb, C. Brunner

M. Devereux, R. Griffith, Alexander Klemm

H. Cai, Qiao Liu

D. Maio, D. Maltoni, R. Cappelli et al.

Maria‐Eleni K. Agoraki, M. Delis, Fotios Pasiouras

M. C. Urban, J. Tewksbury, Kimberly S. Sheldon

Marius Tacke, Matthias Busch, Kevin Linka et al.

Datasets often incorporate various functional patterns related to different aspects or regimes, which are typically not equally present throughout the dataset. We propose a novel partitioning algorithm that utilizes competition between models to detect and separate these functional patterns. This competition is induced by multiple models iteratively submitting their predictions for the dataset, with the best prediction for each data point being rewarded with training on that data point. This reward mechanism amplifies each model's strengths and encourages specialization in different patterns. The specializations can then be translated into a partitioning scheme. We validate our concept with datasets with clearly distinct functional patterns, such as mechanical stress and strain data in a porous structure. Our partitioning algorithm produces valuable insights into the datasets' structure, which can serve various further applications. As a demonstration of one exemplary usage, we set up modular models consisting of multiple expert models, each learning a single partition, and compare their performance on more than twenty popular regression problems with single models learning all partitions simultaneously. Our results show significant improvements, with up to 56% loss reduction, confirming our algorithm's utility.

Hassan Saad Shallak, Abbas Zaki Abdul Hussein, Ali Sabah Nouri et al.

The aim of the study is to investigate the impact of surgical and non-surgical rehabilitation programs on anterior and posterior cruciate ligament (ACL) injuries in team sports athletes, such as football, basketball, and handball. The methodology used was the descriptive-analytical approach using objective measures. The study included a sample of 60 players aged between 18 and 30 years who had suffered a cruciate ligament injury. The sample was divided into two groups: one group underwent surgical rehabilitation after ACL reconstruction surgery, and another group underwent non-surgical rehabilitation through specialized therapeutic exercises. The researchers concluded that the study showed that surgical rehabilitation for ACL injuries was more effective in improving range of motion, reducing pain, and increasing muscle strength compared to non-surgical treatment. Additionally, the researchers recommended the necessity of designing specialized rehabilitation programs that consider the nature of the injury and the needs of each player to ensure the restoration of movement and safe return to competition

Olga E. Pekelis

This paper investigates the synchronic traits and the microdiachronic evolution of the Russian pronoun nekotoryj. Synchronically, I argue that nekotoryj has four different meanings, with the meaning of an indefinite pronoun being the most frequent and the least distributionally restricted. Diachronically, nekotoryj is shown to have had an article-like function in the Russian language of the 19th century and earlier, which it shared with the numeral odin ‘one,’ while in modern Russian this function is undertaken by odin alone. Within a typological stance on the facts observed, I suggest that nekotoryj displays both expected and unexpected traits. The former includes the outcome of its competition with odin. The latter concerns the distribution of nekotoryj across the contexts that make up the semantic map of indefinite pronouns. Nekotoryj appears to be an instance of an indefinite pronoun that contradicts some predictions put forward by the semantic map.

Stephen M. Garcia, Avishalom Tor, Tyrone M. Schiff

Xizhao Liu, Xiaoshun Li, Yuhang Zhang et al.

In rapidly urbanizing areas, intense human development activities and fierce competition for spatial resources have led to apparent territorial space conflicts. This paper selects Jiangsu Province as the study area to explore the spatiotemporal evolution characteristics and response relationship between the expansion of county-level construction land and territorial space conflicts from 1985 to 2020 to provide a reference for regional territorial space optimization. The results show that the construction land expansion intensity (CEI) at the county level showed a spatial characteristic of greater power in the southeast than in the northwest. The spatial expansion mode (SEI) was mainly characterized by spread type, with construction land experiencing marginal expansion, the emergence of new independent expansion points, and then the expansion process of agglomeration distribution. From 1985 to 2020, there was a significant increase in territorial space conflicts and an increase in spatial aggregation at the county level. The regions with high space conflicts intensity index (SCII) values and high increase in space conflicts intensity changes (SCIIC) were mainly located in Xuzhou, Nanjing, and at the junction of Changzhou, Wuxi, Suzhou, and Zhenjiang. There was a positive correlation between CEI and SCIIC, and the correlation of positive correlation units increased from south to north. There was a positive correlation between SEI and SCIIC, and the units with a strong positive correlation were mainly located in Xuzhou, Nantong, Changzhou, and Wuxi. The changes in population density and GDP also affect SCIIC. This paper strengthens the understanding of the spatiotemporal evolution characteristics and related relationships of construction land expansion and territorial space conflicts at the county level over a long time, which can provide a decision-making basis and reference for the regulation of county construction land expansion, territorial space optimization in Jiangsu Province.

J. Harvey, E. Poelman, Toshiharu Tanaka

Paolo Buccirossi, Lorenzo Ciari, Tomaso Duso et al.

Rong Zheng, Abdelazim G. Hussien, He-Ming Jia et al.

Wild horse optimizer (WHO) is a recently proposed metaheuristic algorithm that simulates the social behavior of wild horses in nature. Although WHO shows competitive performance compared to some algorithms, it suffers from low exploitation capability and stagnation in local optima. This paper presents an improved wild horse optimizer (IWHO), which incorporates three improvements to enhance optimizing capability. The main innovation of this paper is to put forward the random running strategy (RRS) and the competition for waterhole mechanism (CWHM). The random running strategy is employed to balance exploration and exploitation, and the competition for waterhole mechanism is proposed to boost exploitation behavior. Moreover, the dynamic inertia weight strategy (DIWS) is utilized to optimize the global solution. The proposed IWHO is evaluated using twenty-three classical benchmark functions, ten CEC 2021 test functions, and five real-world optimization problems. High-dimensional cases (<i>D</i> = 200, 500, 1000) are also tested. Comparing nine well-known algorithms, the experimental results of test functions demonstrate that the IWHO is very competitive in terms of convergence speed, precision, accuracy, and stability. Further, the practical capability of the proposed method is verified by the results of engineering design problems.