Block spin transformation on the dual lattice and monopole action

To find a perfect lattice action in terms of monopole action on the dual lattice, we performed simulations of a monopole effective action obtained numerically from vacuum configurations in SU(2) QCD. Although the Polyakov loop behavior near $T_c$ is well reproduced by the action, a small but repulsive term is needed in addition to get the string tension correctly. It is reported also a monopole effective action in $SU(3)$ QCD which is expressed by one kind of monopole currents.Comment: 4pages (4 figures), Latex, Contribution to Lattice 9

Dengue virus receptor

Dengue virus is an arthropod-borne virus transmitted by Aedes mosquitoes. Dengue virus causes fever and hemorrhagic disorders in humans and non-human primates. Direct interaction of the virus introduced by a mosquito bite with host receptor molecule(s) is crucial for virus propagation and the pathological progression of dengue diseases. Therefore, elucidation of the molecular mechanisms underlying the interaction between dengue virus and its receptor(s) in both humans and mosquitoes is essential for an understanding of dengue pathology. In addition, understanding the molecular mechanism(s) of virus entry is crucial for the development of effective new therapies to treat dengue patients. Binding of dengue virus to its receptor molecules is mediated through a viral envelope glycoprotein, termed E protein. We present a summary and describe the structures, binding properties, and pathological relevance of dengue virus receptor molecules proposed to date. In mammalian cells, there are many candidate molecules that may act as receptors, such as sulfated glycosaminoglycans (GAGs), lectins that recognize carbohydrates, glycosphingolipid (GSL), proteins with chaperone activity, laminin-binding proteins, and other uncharacterized proteins. There are also several lines of evidence for receptor molecules such as GSLs, proteins with chaperone activity, laminin-binding proteins, and other uncharacterized proteins in mosquito cells and organs. This review focuses on several molecules involved in carbohydrate-dependent binding of the virus

Parameter Identification of Water Elevation of Tide by Finite Element Method and Sensitivity Coefficient Method

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Runner re-identification from single-view video in the open-world setting

In many sports, player re-identification is crucial for automatic video processing and analysis. However, most of the current studies on player re-identification in multi- or single-view sports videos focus on re-identification in the closed-world setting using labeled image dataset, and player re-identification in the open-world setting for automatic video analysis is not well developed. In this paper, we propose a runner re-identification system that directly processes single-view video to address the open-world setting. In the open-world setting, we cannot use labeled dataset and have to process video directly. The proposed system automatically processes raw video as input to identify runners, and it can identify runners even when they are framed out multiple times. For the automatic processing, we first detect the runners in the video using the pre-trained YOLOv8 and the fine-tuned EfficientNet. We then track the runners using ByteTrack and detect their shoes with the fine-tuned YOLOv8. Finally, we extract the image features of the runners using an unsupervised method using the gated recurrent unit autoencoder model. To improve the accuracy of runner re-identification, we use dynamic features of running sequence images. We evaluated the system on a running practice video dataset and showed that the proposed method identified runners with higher accuracy than one of the state-of-the-art models in unsupervised re-identification. We also showed that our unsupervised running dynamic feature extractor was effective for runner re-identification. Our runner re-identification system can be useful for the automatic analysis of running videos.Comment: 18 pages, 8 figure

Automatic Edge Error Judgment in Figure Skating Using 3D Pose Estimation from a Monocular Camera and IMUs

Automatic evaluating systems are fundamental issues in sports technologies. In many sports, such as figure skating, automated evaluating methods based on pose estimation have been proposed. However, previous studies have evaluated skaters' skills in 2D analysis. In this paper, we propose an automatic edge error judgment system with a monocular smartphone camera and inertial sensors, which enable us to analyze 3D motions. Edge error is one of the most significant scoring items and is challenging to automatically judge due to its 3D motion. The results show that the model using 3D joint position coordinates estimated from the monocular camera as the input feature had the highest accuracy at 83% for unknown skaters' data. We also analyzed the detailed motion analysis for edge error judgment. These results indicate that the monocular camera can be used to judge edge errors automatically. We will provide the figure skating single Lutz jump dataset, including pre-processed videos and labels, at https://github.com/ryota-takedalab/JudgeAI-LutzEdge

Acoustic characteristics and learner profiles of low, mid and high-level second language fluency

In the context of 90 adult Japanese learners of English with diverse L2 experience and 10 native speakers, this study examined the linguistic characteristics and learner profiles of low, mid and high-level fluency performance. The participants’ spontaneous speech samples were first rated by 10 native listeners for global fluency on a 9-point scale (1 =dysfluent, 9 = very fluent), and then divided into four proficiency groups via cluster analyses: low (n = 29), mid (n = 30), high (n = 31) and native (n = 10). Next, the dataset was analyzed for the number of pauses in mid/final clauses, articulation rate and the frequency of repetitions/self-corrections. According to the results of a series of ANOVAs, the number of final-clause pauses differentiated low and mid-level fluency performance; the number of mid-clause pauses differentiated mid and high-level performance; and articulation rate differentiated high and nativelike performance. The analyses also found that the participants’ L2 fluency was significantly associated with their length of residence profiles (0-18 years), but not with their age of arrival profiles (19-40 years)

Discriminating DRDoS Packets using Time Interval Analysis

Distributed Reflection Denial of Service (DRDoS) attack is one of the critical security threats. As the attack generates unidirectional traffic, it is not easy for the targets of the attack to protect themselves. To mitigate the attack, we need a defense mechanism installed at backbone networks, i.e., detecting and blocking the attack traffic before they reach to the destinations. A conventional approach is to monitor the traffic volume of the attack, i.e., an attack is detected if the observed traffic volume exceeds a certain threshold. However, such a simple approach may not work when an attacker adjusts the traffic volume to evade the detection. This paper proposes a novel method that can detect the DRDoS attacks accurately. The key idea is to leverage the characteristics of time intervals between the packets. We make use of the K-means clustering algorithm to find the best threshold values used to distinguish packets associated with DRDoS attacks. We implement the proposed algorithm into an equipment at a data center and demonstrate that our approach attains high accuracy