EXPLORING THE RIGHT SPOT: HOW MUCH INFORMATION REALLY TO EXPLORE FOR EFFICIENT CLIMBING?

The purpose of this study was to investigate the optimal amount of information to explore by a climber to effectively anticipate the next actions and therefore ensure efficiency during the climb. Climbers (N=6), with mean age 15.6 years (+/-1.6) were assigned based on their maximal performance to an “expert” group (N=3 who can climb a route with difficulty level 7 or more) and a “beginner” group (N=3 who can climb a route with difficulty level 5c maximum). All those 6 climbers practiced 6 times not identical but similar routes (same difficulty level and technical requirements), but the number of visible holds was decreased trial after trial. In other words, during the first trial the next 6 holds were visible (the holds lights on as far as the climber actually climbs up), the second trial showed only the 5 next holds, the third trial showed only the next 4 holds, etc… Both the performance, efficiency and exploratory activity were measured during the ascent. Results showed that a major drop in performance arose for experts when they went through the condition with 3 visible holds to the condition with only 2 visible holds, showing that expert climbers can ensure fluidity of their climb by anticipating in the next 3 holds. Concerning the beginners, no drop in performance were observed, advocating for a lack of anticipation for the beginners, as they mainly use the next hold to anticipate (or rather “not anticipate”)

ESSAYS ON QUALITY IMPROVEMENT AND SECOND HAND MARKET IN THE VIDEO GAME INDUSTRY

The existence of secondary markets mean that producers of durable goods must compete with previous generations of their own products. Firms can engage in planned obsolescence to limit the scope of this competition. This paper develops a two-period model with a monopolist producer of durable goods, continuously distributed consumers, and a robust secondary market. Firms are shown to deliberately reduce the resale value of previous production by focusing on introducing new generations with large quality improvements. An empirical application to the US video game market confirms that used video game prices experience larger falls when new generation game titles have relatively higher quality levels. The analysis suggests an important role for the secondary market in firm planning. Industries which produce durables, such as video game companies, make contemporaneous production decisions with an eye toward planned obsolescence of previous generations of their own products.Berry (1994) and some later papers provide a way to estimate differentiated product models. When the product of interest is a durable good, consumers do not pay the entire retail price due to the existence of the second hand market. This paper employs data from the US video game market and proposes a new angel to investigate the demand side of a durable good. The results of the empirical investigation suggests that the inclusion of the future resale price makes the model estimation more sensible and reasonable

Chat-PM: A Class of Composite Hybrid Aerial/Terrestrial Precise Manipulator

This paper concentrates on the development of Chat-PM, a class of composite hybrid aerial/terrestrial manipulator, in concern with composite configuration design, dynamics modeling, motion control and force estimation. Compared with existing aerial or terrestrial mobile manipulators, Chat-PM demonstrates advantages in terms of reachability, energy efficiency and manipulation precision. To achieve precise manipulation in terrestrial mode, the dynamics is analyzed with consideration of surface contact, based on which a cascaded controller is designed with compensation for the interference force and torque from the arm. Benefiting from the kinematic constraints caused by the surface contact, the position deviation and the vehicle vibration are effectively decreased, resulting in higher control precision of the end gripper. For manipulation on surfaces with unknown inclination angles, the moving horizon estimation (MHE) is exploited to obtain the precise estimations of force and inclination angle, which are used in the control loop to compensate for the effect of the unknown surface. Real-world experiments are performed to evaluate the superiority of the developed manipulator and the proposed controllers

Visual aesthetic in the restoration of Qin-zither damaged lacquer surface: Taking the restoration of ZhuSe Qin-zither as an example

For Qin-zither with Literati and artistic temperament, there are high requirements for visual aesthetic in the restoration of damaged lacquer surface. In order to avoid the subjectivity and uncertainty of the traditional restoration method, the role of visual aesthetic in Qin-zither lacquer restoration is studied. This article proposes using the figure-ground visual relationship to analyze the figure-ground relationship between the patching surface and the original surface, assisting in restoration decision-making. During the repair process, the main lacquer patching range and shape are determined based on the visual balance of the composition. According to the final aesthetic effect, the grinding and painting repair method is selected to achieve a beautiful patching lacquer surface with different color layers in harmony with the original lacquer part. In the process of Qin-zither restoration, the visual aesthetic is permeated in the processing of figure and ground relationship, the harmony between the patching surface and the original lacquer part and the creation of lacquer layer

Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs

The unique capabilities of Large Language Models (LLMs), such as the natural language text generation ability, position them as strong candidates for providing explanation for recommendations. However, despite the size of the LLM, most existing models struggle to produce zero-shot explanations reliably. To address this issue, we propose a framework called Logic-Scaffolding, that combines the ideas of aspect-based explanation and chain-of-thought prompting to generate explanations through intermediate reasoning steps. In this paper, we share our experience in building the framework and present an interactive demonstration for exploring our results.Comment: The 17th ACM International Conference on Web Search and Data Mining (WSDM 2024

Accelerating-particle-deposition Method for Quickly Evaluating Long-term Performance of Fin-and-tube Heat Exchangers

Fin-and-tube heat exchanger is the most commonly used heat exchanger type in air-conditioning systems. In the actual operation of air-conditioning systems, the dust particles involved in the air may partly deposit and form particulate fouling on fins and tubes when the dusty air flows through the heat exchangers. The deposited particles may gradually block the passageway of air flow and occupy the heat transfer area, which results in the continuous increase of air side thermal resistance and the significant deterioration of the heat transfer capacity of heat exchangers during the long-term operation. In order to quickly evaluate the long-term performance of fin-and-tube heat exchangers, an accelerating-particle-deposition method, which is capable of implementing the particle deposition process on the long-running heat exchangers in a short time, is proposed in this study. The idea of the accelerating-particle-deposition method is to employ high concentration dusty air flow through heat exchangers in the accelerated test, and to quickly form the particulate fouling with the same weight as that on long-running heat exchangers under the actual operating environment with low particle concentration. The accelerating factor, which is defined as the ratio of the actual running time to the accelerated testing time, is calculated based on the deposition weight of dust particles. The deposition weight is calculated by the relationship of the impact frequency and deposition probability of dust particles with the particle concentration of dusty air. An experimental apparatus for accelerating the particle deposition process and testing the heat transfer capacity of fin-and-tube heat exchangers is designed. The predicted long-term performances of heat exchangers based on the proposed accelerating-particle-deposition method are compared with the actual performance data of heat exchangers after 5-8 years’ operation published by China Quality Certification Center. The comparison results show that, the predicted results agree well with the actual operation data, and the mean deviation of the heat transfer capacity is within 10%

Generalizable Whole Slide Image Classification with Fine-Grained Visual-Semantic Interaction

Whole Slide Image (WSI) classification is often formulated as a Multiple Instance Learning (MIL) problem. Recently, Vision-Language Models (VLMs) have demonstrated remarkable performance in WSI classification. However, existing methods leverage coarse-grained pathogenetic descriptions for visual representation supervision, which are insufficient to capture the complex visual appearance of pathogenetic images, hindering the generalizability of models on diverse downstream tasks. Additionally, processing high-resolution WSIs can be computationally expensive. In this paper, we propose a novel "Fine-grained Visual-Semantic Interaction" (FiVE) framework for WSI classification. It is designed to enhance the model's generalizability by leveraging the interaction between localized visual patterns and fine-grained pathological semantics. Specifically, with meticulously designed queries, we start by utilizing a large language model to extract fine-grained pathological descriptions from various non-standardized raw reports. The output descriptions are then reconstructed into fine-grained labels used for training. By introducing a Task-specific Fine-grained Semantics (TFS) module, we enable prompts to capture crucial visual information in WSIs, which enhances representation learning and augments generalization capabilities significantly. Furthermore, given that pathological visual patterns are redundantly distributed across tissue slices, we sample a subset of visual instances during training. Our method demonstrates robust generalizability and strong transferability, dominantly outperforming the counterparts on the TCGA Lung Cancer dataset with at least 9.19% higher accuracy in few-shot experiments. The code is available at: https://github.com/ls1rius/WSI_FiVE.Comment: Accepted by CVPR 202