Hasil untuk "Competition"

Thitaporn Chaisilprungraung, Prapasiri Sawetsuttipan, John T. Serences et al.

Selective attention can momentarily alter visual appearance, but can such effects be learned? We tested whether training attention under sensory competition produces lasting changes in perceived contrast. Across seven days, participants trained on an orientation task with a fixed target location, with or without a salient distractor. Before and after training, we measured the point of subjective equality (PSE). Training under competition produced a reliable push-pull shift. Stimuli at the trained location appeared higher in contrast, whereas stimuli at the untrained location appeared lower. Conversely, training without distractors improved performance but did not alter appearance. Crucially, these opponent shifts were robust to task variations, persisting even in equality judgments designed to minimize response bias. Furthermore, the effect generalized to stimuli with novel orientation and contrast levels. These findings demonstrate that resolving sensory competition does not merely improve discrimination, but durably recalibrates the subjective appearance of the visual world.

Congzhe Yan Zhijun Jiang Jinyang Ni, Guoqing Chang

The magnons in altermagnets exhibit chiral splitting even in the absence of spin-orbit coupling and external magnetic fields. Typically, this chiral splitting behavior can be well described by alternating isotropic spin exchanges (ISE) near the zero temperature. However, its finite-temperature dynamics, particularly when incorporating spin-orbit coupling effects, remains elusive. In this study, we reveal that, when including magnon-magnon interactions, long-range anisotropic spin exchange (ASE) can also induce chiral splitting of magnons at a finite temperature. Crucially, the chiral splitting induced by ASE competes with that arising from ISE, leading to a pronounced temperature-dependent modulation of the altermagnetic chiral splitting. Moreover, this competition is intimately connected to spin fluctuations, and can reverse the spin current driven by the band splitting as temperature increases. Our work uncovers the intrinsic competition governing collective spin excitations in altermagnets, providing new insights into their finite-temperature dynamical behavior.

Muhamad Adnan Royandi, Enung Hasanah, Suyatno Suyatno

The ever-growing era of globalization places demands on having 21st century skills which include Critical Thinking, Creativity, Communication, and Collaboration. Technological advances require us to have communication and English language skills, and as Muslims, we are also required to have Arabic language skills to understand the holy book. In its implementation, Student Management has the function of improving these abilities and skills. This research aims to determine the planning, organization, implementation and control, and supervision of boarding school student management in improving Arabic and English language skills. This research uses a qualitative type of research, with a field observation approach, and data collection techniques using interviews, observation, and documentation. The results of this research explain that boarding school student management in improving Arabic and English language skills is by: 1) Planning which begins with a Work Meeting which plans one semester's work program, committee design, budget, and activity calendar; 2) Organizing by dividing tasks, committee obligations, and coordinating with PLC, LA, and SOS; 3) Implementation of daily language programs using Arabic and English which change every 2 weeks, weekly programs with vocabulary learning, public speaking, and muhadatsah, as well as semester programs in the form of language competitions such as the LHI Language Competition and Public Speaking Contest; 4) Control and supervision carried out by all teachers and also dormitory supervisors as well as evaluations held every week.

P A Robinson, Alexander McInnes, Najmeh Sajedianfard et al.

A model of time-dependent trade of goods between spatial locations is formulated via an electric circuit analogy, in which goods are analogous to charge and price to voltage, while producers and consumers are represented by sources and sinks of goods flow, which is represented by current, located at the nodes of a trade network. The core ansatz is that the flow of goods along each network link is driven by the voltage difference across that link, opposed by resistance that represents trade friction. Market prices are then determined indirectly by internal balances of flows, subject to external constraints on supply and demand. The model yields multiple outcomes that support its validity and applicability, including price setting via emergent balance of supply and demand, price fluctuations, traditional and generalized elasticities, network structure-flow relations, competition between producers, and substitution between suppliers, between consumers, and/or between trade links. All these results prove to be consistent with observed features of trade dynamics, thereby supporting the validity of the model. The new model is then used to derive the widely used gravity model of international trade from a mechanistic basis, yielding exponents consistent with published data and leading naturally to core-periphery structure, as observed in real trade networks. The analysis also implies that trade flows self-organize to minimize trade friction in the system as a whole, an emergent global outcome from the purely local dynamics of the populations of producers, consumers, and traders. Possible generalizations and further applications are outlined, including incorporation of asymmetry and capacity limits of trade links, constraints on supply and demand, behavioral responses, and coupling to models of investment strategies.

Masaya Nishihata, Suguru Otani

Understanding how competitive pressure affects risk-taking is crucial in sequential decision-making under uncertainty. This study examines these effects using bench press competition data, where individuals make risk-based choices under pressure. We estimate the impact of pressure on weight selection and success probability. Pressure from rivals increases attempted weights on average, but responses vary by gender, experience, and rivalry history. Counterfactual simulations show that removing pressure leads many lifters to select lower weights and achieve lower success rates, though some benefit. The results reveal substantial heterogeneity in how competition shapes both risk-taking and performance.

Martin Bichler, Julius Durmann, Matthias Oberlechner

This paper examines whether widely used online learning algorithms in pricing can independently reach competitive outcomes or instead foster tacit collusion. This issue has drawn considerable attention from competition regulators as algorithmic pricing becomes more common in digital markets. Understanding when such algorithms lead to equilibrium prices or to supra-competitive prices is critical for buyers, sellers, and policymakers. We study the behavior of multi-armed bandit algorithms in repeated price competition. These algorithms only observe profits from the chosen prices, making them realistic models of automated pricing. Our formal analysis shows that an important class of online learning algorithms, called mean-based algorithms, reliably converges to Nash equilibrium in Bertrand competition. This finding is notable because, generally, online learning algorithms do not guarantee convergence. We also run extensive numerical experiments with different bandit algorithms, confirming that most widely used algorithms, including those not mean-based, converge to equilibrium. We observe supra-competitive prices only in specific cases where all sellers implement the same symmetric version of certain algorithms, such as UCB or Q-learning, and this effect diminishes as the number of competitors increases. Our results highlight that the risk of algorithmic collusion in competitive markets is often overstated. For most practical implementations of bandit algorithms, sellers' prices converge to competitive levels. Only under very specific and symmetric setups do prices remain above competitive benchmarks, and this effect diminishes with more competitors. These insights support regulators concerned with consumer welfare and managers considering algorithmic pricing tools. They suggest that while vigilance is warranted, fears of widespread algorithm-driven collusion may be exaggerated.

Junjia Chen, Zhibin Pan

Activation functions introduce nonlinearity into deep neural networks. Most popular activation functions allow positive values to pass through while blocking or suppressing negative values. From the idea that positive values and negative values are equally important, and they must compete for activation, we proposed a new Competition-based Adaptive ReLU (CAReLU). CAReLU scales the input values based on the competition results between positive values and negative values. It defines two parameters to adjust the scaling strategy and can be trained uniformly with other network parameters. We verify the effectiveness of CAReLU on image classification, super-resolution, and natural language processing tasks. In the experiment, our method performs better than other widely used activation functions. In the case of replacing ReLU in ResNet-18 with our proposed activation function, it improves the classification accuracy on the CIFAR-100 dataset. The effectiveness and the new perspective on the utilization of competition results between positive values and negative values make CAReLU a promising activation function.

Johannes Brustle, José Correa, Paul Dütting et al.

We study the classic single-choice prophet inequality problem through a resource augmentation lens. Our goal is to bound the $(1-\varepsilon)$-competition complexity of different types of online algorithms. This metric asks for the smallest $k$ such that the expected value of the online algorithm on $k$ copies of the original instance, is at least a $(1-\varepsilon)$-approximation to the expected offline optimum on a single copy. We show that block threshold algorithms, which set one threshold per copy, are optimal and give a tight bound of $k = Θ(\log \log 1/\varepsilon)$. This shows that block threshold algorithms approach the offline optimum doubly-exponentially fast. For single threshold algorithms, we give a tight bound of $k = Θ(\log 1/\varepsilon)$, establishing an exponential gap between block threshold algorithms and single threshold algorithms. Our model and results pave the way for exploring resource-augmented prophet inequalities in combinatorial settings. In line with this, we present preliminary findings for bipartite matching with one-sided vertex arrivals, as well as in XOS combinatorial auctions. Our results have a natural competition complexity interpretation in mechanism design and pricing applications.

Pittawat Taveekitworachai, Febri Abdullah, Mury F. Dewantoro et al.

This paper presents the second ChatGPT4PCG competition at the 2024 IEEE Conference on Games. In this edition of the competition, we follow the first edition, but make several improvements and changes. We introduce a new evaluation metric along with allowing a more flexible format for participants' submissions and making several improvements to the evaluation pipeline. Continuing from the first edition, we aim to foster and explore the realm of prompt engineering (PE) for procedural content generation (PCG). While the first competition saw success, it was hindered by various limitations; we aim to mitigate these limitations in this edition. We introduce diversity as a new metric to discourage submissions aimed at producing repetitive structures. Furthermore, we allow submission of a Python program instead of a prompt text file for greater flexibility in implementing advanced PE approaches, which may require control flow, including conditions and iterations. We also make several improvements to the evaluation pipeline with a better classifier for similarity evaluation and better-performing function signatures. We thoroughly evaluate the effectiveness of the new metric and the improved classifier. Additionally, we perform an ablation study to select a function signature to instruct ChatGPT for level generation. Finally, we provide implementation examples of various PE techniques in Python and evaluate their preliminary performance. We hope this competition serves as a resource and platform for learning about PE and PCG in general.

Xudong Kang, Zhaoxin Du, Zhen Wang et al.

In order to reduce the deformation resistance, the rolling process of metastable β titanium alloys is generally carried out in the β single-phase state, which causes the problem of non-uniform grain size during the subsequent annealing process, thus affecting the alloy properties. Here we first solution-treated the as-cast Ti–15Mo–3Al-2.7Nb-0.2Si alloy at 740 °C to obtain α + β phase, then cold rolled it with a reduction of 60 %, and finally annealed it at 710–810 °C for 2–240min. Characterization of the annealed metastable β alloy revealed that α phase was involved in the rolling deformation at the same time and recrystallized on the β matrix during the subsequent annealing process, known as equiaxial dispersion, which impeded the recrystallization of the β grains, and ultimately an ultrafine crystalline microstructure of α + β phases with an average grain size of less than 2 μm was obtained.

ZHANG Wei, LI Qiang

At present, the global wine market is intense, and establishing a strong wine brand has become a key to win the competition. The eastern foothills of Helan Mountain in Ningxia has been rated as a star wine producing area in the world by the International Organization of Grape and Wine. It is the main goal of the local government in Ningxia to make the wine brand in eastern foothills of Helan Mountain famous in the world. The problems and reasons in the process of brand creation were analyzed through field investigation and visited the wine producing region in eastern foothills of Helan Mountain to understand the current situation of the producing areas. The path method of creating the wine brand of the eastern foothills of Helan Mountain in Ningxia was proposed: cultivating the wine consumption market and raising consumer awareness, reducing wine production costs; clarifying the wine products positioning, and choosing suitable brand elements. A strong eastern foothills of Helan Mountain wine brand was created by experiential marketing, relationship marketing, product strategies, channel strategies, public relations strategies, and secondary brand leverage theoretical approach.

Ana Patricia Sandoval-Calderon, Ana Patricia Sandoval-Calderon, Marijke van Kuijk et al.

High-elevation tropical grasslands in South America are vital for sustaining the livelihoods of indigenous communities, particularly in the Central Andes where herding of both wild and domesticated camelids has been a primary socio-economic activity for centuries. However, these grasslands are facing challenges due to changes in land use, economic activities, and climate, posing threats to the sustainability of camelid herding. Here, we determine the intricate relationship between land use management and camelid populations of the highlands of Apolobamba National Park in Bolivia. We identified two critical milestones in land use management across the indigenous communities: the creation of the Tierra Comunitaria de Origen (TCO) in 1999 and the expansion of the National Park in 2000. These initiatives collectively resulted in the diversification of livelihood sources by increasing the number of mining concessions and facilitating the management of wild camelids for their wool and fibers, catering to international markets. We found that this diversification of livelihood sources was negatively related to the densities of domesticated camelids across the studied communities. In contrast, the densities of wild camelids populations increased with an increasing number of mining concessions, likely due to local conservation efforts and reduced competition with livestock. Our results indicate a potential shift in land use management strategies and suggest that mining activities encroach upon pastoralism practices within indigenous communities. Understanding the long-term effects of land use changes is essential for providing comprehensive and sustainable land use strategies that will support both grasslands and animal conservation while providing livelihood security in this ecologically sensitive region.

Julia Nerantzia Tzortzi

This paper deals with the landscape design strategy that was followed in the proposal that was submitted to the International Architecture Competition of the New Archaeological Museum of Cyprus. The aim of this document is to analyze how landscape and architecture interact. In the author’s design proposal for the New Archaeological Museum of Cyprus, the various “gardens” integrated into the Landscape are analyzed. The concept of landscape design is related to the sacredness of trees to certain gods in Ancient Greece and Greek Mythology. The proposal addresses the symbolic meaning of trees and water. The design triggered the creation of several “gardens”: the “Sacred Garden”, the “Stone Garden”, the “Olive Garden”, the “Sacred Grove”, and the “Public Garden”, combining their soft landscapes with the hard landscape of the “Plaza” and the “Courtyard”. Each figure in the garden has a symbolic meaning that allows for a dialogue between landscape and architectural design. In addition, the findings provide valuable insights into the historical and spiritual value of landscape elements (plants, water) that are also thermal regulators for sustainable urban planning. The research results may be of value to landscape architects, architects, and landscape designers in the Mediterranean region.

Juan Carlos Moreno García

The First Intermediate Period was a time of cultural innovation and social competition. The collapse of the monarchy and the cultural productions it sponsored paved the way for the emergence of new artistic and cultural expressions, better adapted to a context of fragile authorities and competing local powers. Warfare between rival regional polities became frequent, so tomb scenes and funerary stelae from Middle and Upper Egypt began depicting military actions and men posing as archers. Moreover, local authorities sought the support of local levies and fellow citizens to strengthen and legitimate their fragile rule. Therefore, many monuments and inscriptions celebrate successful command, effective leadership, and caring about one’s city and its inhabitants. These conditions favoured the emergence of cultural innovations and social values aiming to express new identities. Depicting weapons, mainly bows, was crucial in this respect in some areas of Southern Egypt and echoed comparable phenomena occurring in neighbour regions like Nubia and the Levant.

Khushboo Rani, Hansika Weerasena, Stephen A. Butler et al.

Network-on-Chip (NoC) enables energy-efficient communication between numerous components in System-on-Chip architectures. The optical NoC is widely considered a key technology to overcome the bandwidth and energy limitations of traditional electrical on-chip interconnects. While optical NoC can offer high performance, they come with inherent security vulnerabilities due to the nature of optical interconnects. In this paper, we investigate the gain competition attack in optical NoCs, which can be initiated by an attacker injecting a high-power signal to the optical waveguide, robbing the legitimate signals of amplification. To the best of our knowledge, our proposed approach is the first attempt to investigate gain competition attacks as a security threat in optical NoCs. We model the attack and analyze its effects on optical NoC performance. We also propose potential attack detection techniques and countermeasures to mitigate the attack. Our experimental evaluation using different NoC topologies and diverse traffic patterns demonstrates the effectiveness of our modeling and exploration of gain competition attacks in optical NoC architectures.

Yongfeng Zhang, Chenchen Xiong, Wenbo Wang et al.

Abstract Buckybowl structures as non‐uniform electrostatic potential distributions of polycyclic aromatic materials show a unique photoelectric performance. In this work, OTC was utilized for dynamic modulation of triplet exciton transition processes. Five host molecules with different functional units were selected, thus providing different intermolecular interactions in the host/guest systems. Therefore, the delayed emissions were regulated from 536 to 624 nm via the tuning of the triplet exciton transition processes of OTC in different hosts. Experimental data and theoretical calculations revealed that the varied triplet transition behaviors resulted from the competition between the intersystem crossing (ISC) process of OTC‐monomer and the reverse intersystem crossing (RISC) process of OTC‐aggregates. This work proves the superior structure of buckybowl‐based luminophore for controlling triplet exciton transition processes and supplies a new perspective for persistent afterglow luminophore design.

Hadi Givi, Mohammad Dehghani, Stepan Hubalovsky

This paper presents a new bio-inspired metaheuristic algorithm called Red Panda Optimization (RPO) that imitates the natural behaviors of red pandas in nature. The main design idea of RPO is derived from two characteristic natural behaviors of red pandas: (i) foraging strategy, and (ii) climbing trees to rest. The proposed RPO approach is mathematically modeled in two phases of exploration based on the simulation of red pandas’ foraging strategy and exploitation based on the simulation of red pandas’ movement in climbing trees. The main advantage of the proposed approach is that there is no control parameter in its mathematical modeling, and for this reason, it does not need a parameter adjustment process. The performance of RPO is evaluated on fifty-two standard benchmark functions including unimodal, high-dimensional multimodal, and fixed-dimensional multimodal types as well as CEC 2017 test suite. The optimization results obtained by the proposed RPO approach are compared with the performance of twelve well-known metaheuristic algorithms. The simulation results show that RPO, by maintaining the balance between exploration and exploitation, is effective in solving optimization problems and its performance is superior over competitor algorithms. Based on the analysis of the optimization results, RPO has provided more successful performance compared to the competitor algorithms in 100% of unimodal functions, 100% of high-dimensional multimodal functions, 100% of fixed-dimensional multimodal functions, and 86.2% of CEC 2017 test suite benchmark functions. Also, the statistical analysis of the Wilcoxon rank sum test shows that the superiority of RPO in the competition with the compared algorithms is significant from a statistical point of view. In addition, the results of implementing RPO on four engineering design problems confirms the ability of the proposed approach to handle real-world optimization applications.

Xiao Hanyue, Sultan Mohamed Thariq Hameed, Shahar Farah Syazwani et al.

In the face of fierce competition in the automotive market, severe environmental problems, and the consistent enhancement of consumer demands for vehicle performance, research and development for new automotive materials have increased. Fiber metal laminate (FML) is a representative hybrid composite in recent years but the application of FMLs in the automotive industry is still rare. In order to boost the strengths and applications of FMLs, a lot of effort has been put into enhancing their mechanical properties. In this review article, up-to-date information on the mechanical performance of FMLs for automotive components is presented. The mechanical testing methods, materials selection, structure design, fabrication methods, and the application of hybrid FMLs were explored. The objective of this review article is to study different factors that influence the mechanical properties of FMLs and provide some optimization directions from various aspects. From recent research, there will be great opportunities for hybrid FMLs utilizing natural fibers and bio-polymers in the automotive field in the future.

Andrew Lucas

Network effects are the added value derived solely from the popularity of a product in an economic market. Using agent-based models inspired by statistical physics, we propose a minimal theory of a competitive market for (nearly) indistinguishable goods with demand-side network effects, sold by statistically identical sellers. With weak network effects, the model reproduces conventional microeconomics: there is a statistical steady state of (nearly) perfect competition. Increasing network effects, we find a phase transition to a robust non-equilibrium phase driven by the spontaneous formation and collapse of fads in the market. When sellers update prices sufficiently quickly, an emergent monopolist can capture the market and undercut competition, leading to a symmetry- and ergodicity-breaking transition. The non-equilibrium phase simultaneously exhibits three empirically established phenomena not contained in the standard theory of competitive markets: spontaneous price fluctuations, persistent seller profits, and broad distributions of firm market shares.

Shubin Dai

As Transformer-based architectures have recently shown encouraging progresses in computer vision. In this work, we present the solution to the Google Landmark Recognition 2021 Challenge held on Kaggle, which is an improvement on our last year's solution by changing three designs, including (1) Using Swin and CSWin as backbone for feature extraction, (2) Train on full GLDv2, and (3) Using full GLDv2 images as index image set for kNN search. With these modifications, our solution significantly improves last year solution on this year competition. Our full pipeline, after ensembling Swin, CSWin, EfficientNet B7 models, scores 0.4907 on the private leaderboard which help us to get the 2nd place in the competition.