BPCoach: Exploring Hero Drafting in Professional MOBA Tournaments via Visual Analytics

Hero drafting for multiplayer online arena (MOBA) games is crucial because drafting directly affects the outcome of a match. Both sides take turns to "ban"/"pick" a hero from a roster of approximately 100 heroes to assemble their drafting. In professional tournaments, the process becomes more complex as teams are not allowed to pick heroes used in the previous rounds with the "best-of-N" rule. Additionally, human factors including the team's familiarity with drafting and play styles are overlooked by previous studies. Meanwhile, the huge impact of patch iteration on drafting strengths in the professional tournament is of concern. To this end, we propose a visual analytics system, BPCoach, to facilitate hero drafting planning by comparing various drafting through recommendations and predictions and distilling relevant human and in-game factors. Two case studies, expert feedback, and a user study suggest that BPCoach helps determine hero drafting in a rounded and efficient manner.Comment: Accepted by The 2024 ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW) (Proc. CSCW 2024

Dampak Pembangunan Infrastruktur Perdesaan Pada Program PNPM Mandiri Perdesaan Di Kabupaten Toli Toli

The purpose of this study was to determine the Development Impact of Rural Infrastructure in PNPM RuralProgram in Toli-Toli. Research conducted on the implementation of PNPM Rural Program in Toli-Toli forfiscal year 2007 and 2008.Primary data obtained from interviews with relevant parties and direct observation in the field, then the datais processed with Descriptive Analysis.The results showed the impact of rural infrastructure development in poor communities in Toli Toli, namely:increasing revenue, impoving public education, improving health and improving the public midset. Impact onvillage institutions, namely: the function and role of local government to be effective, institutions ofparticipatory development and improvement of the quality of facilities.and social infrastructure andeconomic base of societ

Uniform Approximation Is More Appropriate for Wilcoxon Rank-Sum Test in Gene Set Analysis

Gene set analysis is widely used to facilitate biological interpretations in the analyses of differential expression from high throughput profiling data. Wilcoxon Rank-Sum (WRS) test is one of the commonly used methods in gene set enrichment analysis. It compares the ranks of genes in a gene set against those of genes outside the gene set. This method is easy to implement and it eliminates the dichotomization of genes into significant and non-significant in a competitive hypothesis testing. Due to the large number of genes being examined, it is impractical to calculate the exact null distribution for the WRS test. Therefore, the normal distribution is commonly used as an approximation. However, as we demonstrate in this paper, the normal approximation is problematic when a gene set with relative small number of genes is tested against the large number of genes in the complementary set. In this situation, a uniform approximation is substantially more powerful, more accurate, and less intensive in computation. We demonstrate the advantage of the uniform approximations in Gene Ontology (GO) term analysis using simulations and real data sets

Research on the Influence of Information Diffusion on the Transmission of the Novel Coronavirus (COVID-19)

With the rapid development of the Mobile Internet in China, epidemic information is real-time and holographic, and the role of information diffusion in epidemic control is increasingly prominent. At the same time, the publicity of all kinds of big data also provides the possibility to explore the impact of media information diffusion on disease transmission. We explored the mechanism of the influence of information diffusion on the transmission of COVID-19, developed a model of the interaction between information diffusion and disease transmission based on the Susceptible–Infected–Recovered (SIR) model, and conducted an empirical test by using econometric methods. The benchmark result showed that there was a significant negative correlation between the information diffusion and the transmission of COVID-19. The result of robust test showed that the diffusion of both epidemic information and protection information hindered the further transmission of the epidemic. Heterogeneity test results showed that the effect of epidemic information on the suppression of COVID-19 is more significant in cities with weak epidemic control capabilities and higher Internet development levels

RAIH-Det: An End-to-End Rotated Aircraft and Aircraft Head Detector Based on ConvNeXt and Cyclical Focal Loss in Optical Remote Sensing Images

In airport ground-traffic surveillance systems, the detection of an aircraft and its head (AIH) is an important task in aircraft trajectory judgment. However, accurately detecting an AIH in high-resolution optical remote sensing images is a challenging task due to the difficulty in effectively modeling the features of aircraft objects, such as changes in appearance, large-scale differences, complex compositions, and cluttered background. In this paper, we propose an end-to-end rotated aircraft and aircraft head detector (RAIH-Det) based on ConvNeXt-T (Tiny) and cyclical local loss. Firstly, a new U-shaped network based on ConvNeXt-T with the same performance as the Local Vision Transformer (e.g., Swin Transformer) is presented to assess the relationships among aircraft in the spatial domain. Then, in order to enhance the sharing of more mutual information, the extended BBAVectors with six vectors captures the oriented bounding box (OBB) of the aircraft in any direction, which can assist in head keypoint detection by exploiting the relationship between the local and overall structural information of aircraft. Simultaneously, variant cyclical focal loss is adopted to regress the heatmap location of keypoints on the aircraft head to focus on more reliable samples. Furthermore, to perform a study on AIH detection and simplify aircraft head detection, the OBBs of the “plane” category in the DOTA-v1.5 dataset and the corresponding head keypoints annotated by our volunteers were integrated into a new dataset called DOTA-Plane. Compared with other state-of-the-art rotated object and keypoint detectors, RAIH-Det, as evaluated on DOTA-Plane, offered superior performance

Nitrogen-Containing Functional Groups-Facilitated Acetone Adsorption by ZIF-8-Derived Porous Carbon

Nitrogen-doped porous carbon (ZC) is prepared by modification with ammonia for increasing the specific surface area and surface polarity after carbonization of zeolite imidazole framework-8 (ZIF-8). The structure and properties of these ZCs were characterized by Transmission electron microscopy, X-ray diffraction, N2 sorption, X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy. Through static adsorption tests of these carbons, the sample obtained at 600 °C was selected as an excellent adsorbent, which exhibited an excellent acetone capacity of 417.2 mg g−1 (25 °C) with a very large surface area and high-level nitrogen doping (13.55%). The microporosity, surface area and N-containing groups of the materials, pyrrolic-N, pyridinic-N, and oxidized-N groups in particular, were found to be the determining factors for acetone adsorption by means of molecular simulation with density functional theory. These findings indicate that N-doped microporous carbon materials are potential promising adsorbents for acetone

A Charge-Transfer-Induced Strategy for Enantioselective Discrimination by Potential-Regulated Surface-Enhanced Raman Scattering Spectroscopy

A simple and efficient enantioselective discrimination method, especially the chirality-label-free discrimination method, for the recognition of chiral small molecules with high resolution and wide applicability has been urgently desired. Herein, achiral Au/p-aminothiophenol (PATP) substrates were prepared to link the enantiomers via coupling reactions for constructing the enantioselective discrimination system. The resultant Au/PATP/enantiomer systems displayed charge-transfer (CT)-induced surface-enhanced Raman scattering (SERS) spectra that offered distinguishable information for the systems with different chirality. The differentiated spectral signal can be amplified by regulating the applied electrode potential, leading to great enantioselective discrimination performance. Moreover, the relationship between the discrimination performance and the potential-regulated CT process was revealed by SERS, which enabled an accurate and effective enantiomeric determination for various chiral molecules, including aromatic and aliphatic small molecules. The aliphatic molecule with the shorter chain was discriminated with a higher resolution, since the longer-chain molecule in the discrimination system may cause a change in the molecular electronic structure of the PATP. In addition, the aromatic chiral molecule can be distinguished easier than the aliphatic molecules, which means that the generation of the conjugation of electrons in the aromatic molecule-involved enantiomeric systems facilitates CT-induced SERS discrimination. Our work provides guidance for the design and development of an effective enantioselective discrimination strategy with high discrimination performance in diverse application fields

Bayesian Compressive Sensing Based Optimized Node Selection Scheme in Underwater Sensor Networks

Information acquisition in underwater sensor networks is usually limited by energy and bandwidth. Fortunately, the received signal can be represented sparsely on some basis. Therefore, a compressed sensing method can be used to collect the information by selecting a subset of the total sensor nodes. The conventional compressed sensing scheme is to select some sensor nodes randomly. The network lifetime and the correlation of sensor nodes are not considered. Therefore, it is significant to adjust the sensor node selection scheme according to these factors for the superior performance. In this paper, an optimized sensor node selection scheme is given based on Bayesian estimation theory. The advantage of Bayesian estimation is to give the closed-form expression of posterior density function and error covariance matrix. The proposed optimization problem first aims at minimizing the mean square error (MSE) of Bayesian estimation based on a given error covariance matrix. Then, the non-convex optimization problem is transformed as a convex semidefinite programming problem by relaxing the constraints. Finally, the residual energy of each sensor node is taken into account as a constraint in the optimization problem. Simulation results demonstrate that the proposed scheme has better performance than a conventional compressed sensing scheme.Applied Science, Faculty ofNon UBCElectrical and Computer Engineering, Department ofReviewedFacult

On signal processing scheme based on network coding in relay-assisted D2D systems

Abstract Network coding (NC) can greatly improve a system’s performance on throughput and channel utilization via corresponding signal processing on the relay side. Implementation of NC in relay-assisted device-to-device (RA-D2D) communications is a promising way to further explore the advantages of RA-D2D communications in cellular systems. This paper proposes a signal processing scheme for RA-D2D which jointly takes into account NC and optimal relay selection. First, the optimal relay user equipment (UE) is selected by jointly considering the end-to-end data rate, end-to-end transmission delay, and relay survival time. Then, in the procedure of signal processing, the transmitted useful signal is combined with interference signal for NC operation, and finally, the original useful signal is recovered at the destination node. Simulation results show that the proposed scheme is able to not only eliminate the interference effectively but also has a superior performance on end-to-end transmission delay, reachability, and amount of transmitted information than that without NC. In particular, signal processing via NC is equivalent to encrypting the signal, which further enhances the information security in D2D communications

Measurement of Tunnel Clearance Convergence Using Mobile Laser Detection Technology

Railway and subway tunnels have lengthy runs, long train operation times, high detection pressures, and critical structural safety concerns that affect tunnel service life, train safety, and passenger comfort. The current method of measuring the clearance convergence requires considerable manpower and equipment to identify defects, cannot measure the entire tunnel section, has poor operation efficiency, and provides noncomprehensive results. To address these shortcomings, three-dimensional laser scanning technology has recently been applied to tunnel structure inspection. This study therefore proposes methods for calculating the clearance convergence of a tunnel section, including the calculation of the shield tunnel convergence diameter, shield tunnel and mine tunneling method tunnel chord lengths, track gauge, guide height and offset of overhead lines, and vault clearance height. The tunnel point cloud data were acquired by the Capital Normal University (Beijing) mobile laser tunnel inspection vehicle and were processed using the algorithms developed in this study. The data indicate that the proposed method provides a repeatability and absolute accuracy within ±3 mm. The proposed method improves the efficiency of tunnel clearance convergence measurement by measuring the full section of a tunnel, providing technical support for the safe operation of subway and railway tunnels