Jeng-Shyang Pan

Bio: Jeng-Shyang Pan is an academic researcher from Shandong University of Science and Technology. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 50, co-authored 789 publications receiving 11645 citations. Previous affiliations of Jeng-Shyang Pan include National Kaohsiung Normal University & Technical University of Ostrava.

Study of PSO Optimized BP Neural Network and Smith Predictor for MOCVD Temperature Control in 7 nm 5G Chip Process

Abstract: The key industries of information technology in the semiconductor integrated circuit industry will have an important role after 2020, In the third generation of advanced semiconductor of 7 nm 5G chips GaN is be used, MOCVD is a key technology for preparing high-quality communication semiconductor crystals. This study proposes PID controller of PSO and BP neural network algorithm to improve the control ability of MOCVD temperature. From the research results, it is found that the method proposed in this study adopts the PSO and BP neural network intelligent PID algorithm controller with Smith predictor, which has better dynamic performance, and the value from 150 to 500 s is stable from 0 to 1 no vibration, any overshoot and short adjustment time, ideal control.

A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application

Abstract: The Fruit Fly Optimization Algorithm is a swarm intelligence algorithm with strong versatility and high computational efficiency. However, when faced with complex multi-peak problems, Fruit Fly Optimization Algorithm tends to converge prematurely. In response to this situation, this article proposes a new optimized structure—Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm. The new algorithm uses the evolution matrix in QUasi-Affine TRansformation Evolution algorithm to update the position coordinates of particles. This strategy makes the movement of particles more scientific and the search space broader. In order to prove its effectiveness, we compare Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm with five other mature intelligent algorithms, and test them on 22 different types of benchmark functions. In order to observe the multi-faceted performance of Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm more intuitively, we also conduct experiments on algorithm convergence analysis, the Friedman test, the Wilcoxon signed-rank test, and running time comparison. Through the above several comparative experiments, Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm has indeed demonstrated its strong competitiveness. Finally, we apply it to Capacitated Vehicle Routing Problem. Through comparing with the contrast algorithms, it is confirmed that Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm can achieve better vehicle routes planning.

Multiple Description Image Coding Based on DSC and Pixel Interleaving

Abstract: This paper presents a novel multiple description image coding (MDC) using the theory of distributed source coding (DSC). The scheme is based on pixel interleaving MD image framework. A so-called Slepian-Wolf set partitioning in hierarchical tree (SW-SPIHT) is presented to efficiently and flexibly insert redundancy in each description and help to estimate the lost description. Experiments demonstrate that it can get better performance than some general MDC methods. Besides, it demonstrates higher robustness in packet-loss channel than pixel interleaving MDC method due to the error-correcting decoding adopted by DSC.

Image coding using SMVQ with two-level block classifier

Abstract: The variable-rate classified side-match vector quantizer (CSMVQ) has been presented as an alternative vector quantizer to the side-match vector quantizer (SMVQ) for low-bit-rate image encoding in recent years. In this paper, a two-level block classifier is used to classify the input vectors, and two different master codebooks are used for generating the state codebooks according to the variance of the input vector. Experimental results prove the effectiveness of the proposed new CSMVQ.

A New 3D Shape Descriptor Based on Rotation

Abstract: Recent developments in techniques for modeling, digitizing and visualizing 3D shapes have led to an explosion in the number of available 3D models on the Internet and in domain-specific databases. However, how to describe 3D shape is a difficult problem. A new 3D shape description method based on rotation is proposed in this paper. The first step is to sample points on the surface and compute normal vectors. Secondly, we do Gauss mapping and rotate model, at the same time, rotate the Gauss sphere. The third step is to count normal distributions on the sphere surface. Finally, the Euclidean distance is computed, thus a statistic histogram is constructed. Experimental results show the effectiveness of this method.

Mean shift: a robust approach toward feature space analysis

Abstract: A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational module of the technique is an old pattern recognition procedure: the mean shift. For discrete data, we prove the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density. The relation of the mean shift procedure to the Nadaraya-Watson estimator from kernel regression and the robust M-estimators; of location is also established. Algorithms for two low-level vision tasks discontinuity-preserving smoothing and image segmentation - are described as applications. In these algorithms, the only user-set parameter is the resolution of the analysis, and either gray-level or color images are accepted as input. Extensive experimental results illustrate their excellent performance.

Digital Watermarking

Abstract: Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

PORs: Proofs of Retrievability for Large Files

Abstract: In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.