CPCP violation induced by the double resonance for pure annihilation decay process in Perturbative QCD

In Perturbative QCD (PQCD) approach we study the direct $CP$ violation in the pure annihilation decay process of $\bar{B}^0_{s}\rightarrow\pi^+\pi^-\pi^+\pi^-$ induced by the $\rho$ and $\omega$ double resonance effect. Generally, the $CP$ violation is small in the pure annihilation type decay process. However, we find that the $CP$ violation can be enhanced by double $\rho-\omega$ interference when the invariant masses of the $\pi^+\pi^-$ pairs are in the vicinity of the $\omega$ resonance. For the decay process of $\bar{B}^0_{s}\rightarrow\pi^+\pi^-\pi^+\pi^-$, the maximum $CP$ violation can reach 28.64{\%}

Inverse Problem Approach for Non-Perturbative QCD: Foundation

We propose a novel theoretical framework to calculate the non-perturbative QCD quantities. It starts from the dispersion relation of quantum field theory, separating the high-energy and low-energy scales and using the known perturbative theories to solve the unknown non-perturbative quantities by the inverse problem. We prove that the inverse problem of dispersion relation is ill-posed, with unique but unstable solutions. The regularization methods must be used to get the stable approximate solutions. The method is based on the strict mathematics, without any artificial assumptions. We have test some toy models to vividly show the main features of the inverse problem. It can be found that this approach can systematically improve the precision of the solutions.Comment: 23 pages, 8 figure

Computation-Performance Optimization of Convolutional Neural Networks with Redundant Kernel Removal

Deep Convolutional Neural Networks (CNNs) are widely employed in modern computer vision algorithms, where the input image is convolved iteratively by many kernels to extract the knowledge behind it. However, with the depth of convolutional layers getting deeper and deeper in recent years, the enormous computational complexity makes it difficult to be deployed on embedded systems with limited hardware resources. In this paper, we propose two computation-performance optimization methods to reduce the redundant convolution kernels of a CNN with performance and architecture constraints, and apply it to a network for super resolution (SR). Using PSNR drop compared to the original network as the performance criterion, our method can get the optimal PSNR under a certain computation budget constraint. On the other hand, our method is also capable of minimizing the computation required under a given PSNR drop.Comment: This paper was accepted by 2018 The International Symposium on Circuits and Systems (ISCAS

ESTIMATION THE PREFERENCE OF ECOTOURISM FOR GAOMEI WETLAND IN TAIWAN

Gaomei Wetland is not only the biggest grassy coastal wetland, but also a wild‐animal protecting area, located on the west‐central coast of Taiwan.Wetlands are considered as one of the most important natural resource, which offer a lot of benefits for human and other creatures. However, it is believed that over-intensive recreational activities in Gaomei Wetland should be responsible for serious damages on natural environment and ecosystem. This study takes Gaomei wetland as an example, and aims to estimate its landscape and ecological services values through Choice experiment. The results of this research showed that Gaomei landscape’s economic value is $2.06 million (USD) per year, and$1.54 million (USD) for its value of ecological services. These findings can help to bring up the awareness of natural resource preservation, and hopefully to keep Gaomei Wetland substantial. The results also indicated that visitors with undergraduate degree or above were willing to pay $6.43 (USD) per year for entry fee to enjoy sunset scenery in Gaomei wetland

A Comprehensive Survey of 3D Dense Captioning: Localizing and Describing Objects in 3D Scenes

Three-Dimensional (3D) dense captioning is an emerging vision-language bridging task that aims to generate multiple detailed and accurate descriptions for 3D scenes. It presents significant potential and challenges due to its closer representation of the real world compared to 2D visual captioning, as well as complexities in data collection and processing of 3D point cloud sources. Despite the popularity and success of existing methods, there is a lack of comprehensive surveys summarizing the advancements in this field, which hinders its progress. In this paper, we provide a comprehensive review of 3D dense captioning, covering task definition, architecture classification, dataset analysis, evaluation metrics, and in-depth prosperity discussions. Based on a synthesis of previous literature, we refine a standard pipeline that serves as a common paradigm for existing methods. We also introduce a clear taxonomy of existing models, summarize technologies involved in different modules, and conduct detailed experiment analysis. Instead of a chronological order introduction, we categorize the methods into different classes to facilitate exploration and analysis of the differences and connections among existing techniques. We also provide a reading guideline to assist readers with different backgrounds and purposes in reading efficiently. Furthermore, we propose a series of promising future directions for 3D dense captioning by identifying challenges and aligning them with the development of related tasks, offering valuable insights and inspiring future research in this field. Our aim is to provide a comprehensive understanding of 3D dense captioning, foster further investigations, and contribute to the development of novel applications in multimedia and related domains

Design of an insert type induction heating and cooling system for injection moulding processes

Kod nekih postupaka kalupljenja uštrcavanjem temperatura alata kod uštrcavanja plastične rastopine mora biti visoka. Uobičajeno se to postiže zagrijavanjem alata toplim uljem ili vodom, ali će zagrijavanje čitavog alata dovesti do nepotrebnog trošenja energije. Ranija istraživanja pokazuju da je primjena vanjske indukcije za zagrijavanje površine alata kod kalupljenja uštrcavanjem i brza i energetski učinkovita. Ipak, iako je vrlo prikladna primjena robota za postavljanje zavojnice za zagrijavanje ispred šupljine alata, alat mora biti otvoren do kraja zagrijavanja, produžujući na taj način vrijeme ciklusa uštrcavanja. Uz to, učestalo izlaganje površine alata veoma visokim i niskim temperaturama može ubrzo dovesti do njegovog oštećenja. Stoga se za zagrijavanje predlaže primjena indukcijske zavojnice tipa umetka. Budući da je masa zagrijana indukcijskim zagrijavanjem umetanjem zavojnice puno veća nego primjenom zavojnice vanjskog indukcijskog zagrijavanja, prvim se načinom postiže sporija brzina zagrijavanja na površini alata i tako produžuje vijek trajanja alata. Kod ovog pristupa zavojnica može grijati alat tijekom otvaranja alata i postupka izbacivanja, a može se također upotrijebiti kanal za hlađenje da se izbjegne interferencija sa zavojnicom unutar alata kao i da se omogući hlađenje na površini šupljine. Stoga se u ovom radu predlaže nova konstrukcija alata te je izrađen alat s dvije šupljine u svrhu provjere koncepta projekta. Rezultati niza eksperimenata pokazuju da se zavojnicom može grijati alat i postići ujednačenost temperature od otprilike 91 %, dok je brzina zagrijavanja bila oko 3 °C/s.For some injection moulding processes, the tool must be kept at high temperature when injecting plastic melt. Conventionally, this is achieved by heating the tool with hot oil or water, but heating the entire tool will cause unnecessary energy consumption. Previous studies show that using external induction in order to heat the surface of injection moulding tools is both rapid and energy efficient. However, while using a robot to put the heating coil in front of a tool cavity is very convenient, the tool must be open until heating is finished, making the injection cycle time longer. In addition, repeatedly making the tool surface exposed to too high and low temperatures may quickly damage it. The use of an insert type induction heating coil has thus been proposed to address this issue. Since the heated mass with insert type induction heating is a lot greater than with coil of external induction heating, the former has a slower heating rate on the tool surface, thus extending the life of the tool. In this approach, a coil can heat the tool during the tool opening and ejection process and a cooling channel can also be used to avoid interference with the coil inside the tool, as well as to enable cooling on the cavity surface. This study thus proposes a new tool structure, and a two-cavity tool was fabricated to verify the design concept. The results of a set of experiments show that the coil could heat the tool and achieve temperature uniformity of about 91 %, while the heating rate was about 3 °C/s

A Museum Exhibits Support System Based on History and Culture Literacy

[[abstract]]Museums need an interactive data collection and visualisation tool for their artefacts. This paper describes a study in which we enable access to Chinese and Japanese cultural heritage information from two history museums, the National Palace Museum in Taiwan and the Tokugawa Art Museum in Japan. Results from these museum databases were used to develop a prototype system to demonstrate advanced cultural learning and historical timeline functionalities for foreigners. This system is based on temporal data from the museums’ databases, and provided the user with powerful data manipulation and graphical visualisation tools. It might become a basis of an interactive digital museum system for Chinese and Japanese heritages especially for foreign users.[[journaltype]]國外[[ispeerreviewed]]Y[[booktype]]電子版[[countrycodes]]GB

Variability of morphology in beat-to-beat photoplethysmographic waveform quantified with unsupervised wave-shape manifold learning for clinical assessment

We investigated the beat-to-beat fluctuation of the photoplethysmography (PPG) waveform. The motivation is that morphology variability extracted from the arterial blood pressure (ABP) has been found to correlate with baseline condition and short-term surgical outcome of the patients undergoing liver transplant surgery. Numerous interactions of physiological mechanisms regulating the cardiovascular system could underlie the variability of morphology. We used the unsupervised manifold learning algorithm, Dynamic Diffusion Map, to quantify the multivariate waveform morphological variation. Due to the physical principle of light absorption, PPG waveform signals are more susceptible to artifact and are nominally used only for visual inspection of data quality in clinical medical environment. But on the other hand, the noninvasive, easy-to-use nature of PPG grants a wider range of biomedical application, which inspired us to investigate the variability of morphology information from PPG waveform signal. We developed data analysis techniques to improve the performance and validated with the real-life clinical database