This paper proposes a novel Particle Swarm Optimization-Aided Reinforcement Learning (PSO-RL) framework for efficient beam and power management in reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) networks. To optimize dynamic beam coordination and resource allocation, we introduce a reinforcement learning (RL)-based approach that integrates value and policy networks, with the policy network enhanced by a target policy network (TPN). By employing PSO, we refine TPN parameters to accelerate convergence and enhance solution exploration. Simulation results validate the effectiveness of the proposed PSO-RL framework, demonstrating significant performance improvements in RISassisted network deployments. The method enhances system capacity by 29.75 % and improves edge user capacity by 36.65 %. These results highlight the potential of PSO-RL for optimizing beam allocation in dynamic urban network environments.

This paper proposes a power rail routing flow for advanced multi-layered printed circuit boards (PCBs) to optimize segment area and via usage while satisfying IR drop requirements. With increasing current/voltage demands in modern PCBs, ultra-wide power rails may consume most routing space and cause significant routing problems. We present an effective overlap-aware rail sizing technique to distribute routing spaces appropriately according to current/voltage demands and a resistance-aware A*-search algorithm to resolve overlapping regions by rail detouring. Experimental results show that our work significantly outperforms the state-of-the-art rail router in the metal area and runtime, achieving respective reductions of 49% and 28%, without any current/voltage violations.

This paper proposes a high-quality 3D placement algorithm to determine the positions of standard cells and inter-die vias to optimize wirelength considering multiple manufacturing technologies for different dies. The algorithm consists of three major novel techniques: (1) a multi-technologies weighted-average (MTWA) wirelength model, (2) a weighted inter-die-connection cost controlling the net-degree distribution of the cut set, and (3) a via-cell co-optimization technique to further improve the quality of placement solutions. Compared with the winners at the 2022 CAD Contest at ICCAD on 3D Placement with D2D Vertical Connections, our placer achieves the best results for all nontrivial cases.

Autonomous driving has become the focus of research and development in recent years. However, the capability of precise positioning and obstacle avoidance for autonomous driving often rely on accurate and dense point cloud images. In particular, the environment in the metropolitan area is relatively complex and there are many viaducts and expressways in modern cities. The spatial features obtained from flat roads are no longer sufficient. If we can obtain the features of higher buildings or higher landforms, a better positioning information and security can be provided when autonomous vehicles are driving on expressways or elevated roads. In addition, the high density of vehicles in the metropolitan area and vision blind spots of vehicles also form a great safety concern for autonomous driving. In order to provide higher density point cloud information so that autonomous driving can ensure the accuracy and safety of navigation and positioning when operating in metropolitan areas, we propose in this paper a data acquisition platform base on multi-LiDAR (VLP-16) as well as a data calibration and fusion algorithm to solve the problems of vision blind spots, low vertical resolution, and sparse high-level point clouds in most of the LiDAR-based system. The proposed system adopts the industrial computer (IPC) of x86 architecture and Robotic Operating System (ROS) for overall operation. In addition, the homogeneous transformation is applied for the calibration and fusion of multi-Lidar point cloud coordinate system. Experimental results have proved that the proposed system can obtain reliable point cloud data, effectively improve the vertical resolution of the point cloud, and increase the point cloud density by more than three times, which can effectively improve the positioning reliability of autonomous driving in metropolitan areas.

The dramatic growth of hardware attacks and the lack of security-concern solutions in design tools lead to severe security problems in modern IC designs. Although many existing countermeasures provide decent protection against security issues, they still lack the global design view with sufficient security consideration in design time. This paper proposes a security-aware framework against Trojan insertion, frontside probing, and fault injection attacks at the design stage. The framework consists of two major techniques: (1) a large-scale shielding method that effectively covers the exposed areas of assets and (2) a cell-movement-based method to eliminate the empty spaces vulnerable to Trojan insertion. Experimental results show that our framework effectively reduces the vulnerability of these attacks and achieves the best overall score compared with the top-3 teams in the 2022 ACM ISPD Security Closure of Physical Layouts Contest.

Formerly computer application development just develops in one computer with one application, if one user wants to use some application in other computer (e.g. a computer or device) then the computer or device must be deployed or reinstalled the application in another computer. As a result, due to improve this problem, many application developer start redesign or translate elder application as Web application, early phases technology we commonly see such as CGI, the near future we commonly see such as Java Server Page (JSP), Active Server Page.Net (ASP.net) and PHP Hypertext Page (PHP). At this research we used Java Server Page (JSP) Servlet Technology to translate an old application called as “Cyber Transformer” (CT), JSP is based on Java Enterprise Technology (J2EE) which can also support Java Commodity Grid (CoG) component, and we also translate CT's speeding download algorithm to speed up File Downloading in Grid Environment. This new web application we called it as a new name MIFAS.