An Efficient SM9 Aggregate Signature Scheme for IoV Based on FPGA.

With the rapid development of the Internet of Vehicles (IoV), the demand for secure and efficient signature verification is becoming increasingly urgent. To meet this need, we propose an efficient SM9 aggregate signature scheme implemented on Field-Programmable Gate Array (FPGA). The scheme includes both fault-tolerant and non-fault-tolerant aggregate signature modes, which are designed to address challenges in various network environments.

A parallel Canny edge detection algorithm based on OpenCL acceleration.

In the process of Canny edge detection, a large number of high complexity calculations such as Gaussian filtering, gradient calculation, non-maximum suppression, and double threshold judgment need to be performed on the image, which takes up a lot of operation time, which is a great challenge to the real-time requirements of the algorithm. The traditional Canny edge detection technology mainly uses customized equipment such as DSP and FPGA, but it has some problems, such as long development cycle, difficult debugging, resource consumption, and so on. At the same time, the adopted CUDA platform has the problem of poor cross-platform.

LPN: Label-Enhanced Prototypical Network for Legal Judgment Prediction.

As one of the most critical tasks in legal artificial intelligence, legal judgment prediction (LJP) has garnered growing attention, especially in the civil law system. However, current methods often overlook the challenge of imbalanced label distributions, treating each label with equal importance, which can lead the model to be biased toward labels with high frequency. In this paper, we propose a label-enhanced prototypical network (LPN) suitable for LJP, that adopts a strategy of uniform encoding and separate decoding.

Multi-View Clustering via Triplex Information Maximization.

In this paper, we address the problem of multi-view clustering (MVC), integrating the close relationships among views to learn a consistent clustering result, via triplex information maximization (TIM). TIM works by proposing three essential principles, each of which is realized by a formulation of maximization of mutual information. 1) Principle 1: Contained.

CFRV: A Decentralized Control-Flow Attestation Schema Using Mutual Secret Sharing.

Control-flow attestation (CFA) is a mechanism that securely logs software execution paths running on remote devices. It can detect whether a device is being control-flow hijacked by launching a challenge-response process. In the growing landscape of the Internet of Things, more and more peer devices need to communicate to share sensed data and conduct inter-operations without the involvement of a trusted center.

Gender-Based Deep Learning Firefly Optimization Method for Test Data Generation.

Software testing is a widespread validation means of software quality assurance in industry. Intelligent optimization algorithms have been proved to be an effective way of automatic test data generation. Firefly algorithm has received extensive attention and been widely used to solve optimization problems because of less parameters and simple implement.

A Depth Evidence Score Fusion Algorithm for Chinese Medical Intelligence Question Answering System.

Question answering (QA) system is becoming the focus of the research in medical health in terms of providing fleetly accurate answers to users. Numerous traditional QA systems are faced to simple factual questions and do not obtain accurate answers for complex questions. In order to realize the intelligent QA system for disease diagnosis and treatment in medical informationization, in this paper, we propose a depth evidence score fusion algorithm for Chinese Medical Intelligent Question Answering System, which can measure the text information in many algorithmic ways and ensure that the QA system outputs accurately the optimal candidate answer.