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.

Mean shift: a robust approach toward feature space analysis

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.

Digital Watermarking

/pdf/a-break-in-the-clouds-towards-a-cloud-definition-svovsw1r5a.pdf

A Break in the Clouds: Towards a Cloud Definition

A morphable model for the synthesis of 3D faces

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.

PORs: Proofs of Retrievability for Large Files

Digital watermarking had been well recognized as an effective measure for the copyright protection of multimedia data. Numerous schemes in the domain of vector quantization had been proposed to achieve the desired goal. A new scheme, also in the domain of vector quantization, is developed and presented in this article. The proposed approach use genetic algorithms to reassign the indices of code words. As a result, embedded information will be diffused more evenly across the image to be protected, and therefore possible security leakage can be avoided. Experimental results reveal that the proposed scheme is free from the potential limitations in previous approaches, while maintaining the robustness against various kinds of attacks.

An Improved Digital Watermarking Scheme in the Domain of Vector Quantization

Improving localization performance is one of the critical issues in Wireless Sensor Networks (WSN). As a range-free localization algorithm, Distance Vector-Hop(DV-Hop) is well-known for its simplicity but is hindered by its low accuracy and poor stability. Therefore, it is necessary to improve DV-Hop to achieve a competitive performance. However, the comprehensive performance of WSN is limited by computing and storage capabilities of sensor nodes. In this paper, we propose an algorithm with parallel and compact techniques based on Whale Optimization Algorithm (PCWOA) to improve DV-Hop performance. The compact technique saves memory consumption by reducing the original population. The parallel techniques enhance the ability to jump out of local optimization and improve the solution accuracy. The proposed algorithm is tested on CEC2013 benchmark functions and compared with some popular algorithms and compact algorithms. Experimental results show that the improved algorithm achieves competitive results over compared algorithms. Finally, simulation research is conducted to verify the localization performance of our proposed algorithm. 

https://unisa.alma.exlibrisgroup.com/view/delivery/61USOUTHAUS_INST/12249849860001831

Improved DV-Hop based on parallel and compact whale optimization algorithm for localization in wireless sensor networks

Knowledge graph reasoning is discovering new entity relations by computing and inference from existing relations. However, most reasoning models of translation embedding-based knowledge graphs have not considered the semantic-type constraints of relations in the construction of corrupted triplets. Hence, the constructed corrupted triplets may not conform to the actual semantic information and may, thus, significantly affect the prediction accuracy of the model. Therefore, we propose a constraint-based embedding model in this paper. First, the model establishes the head and tail entity set for each relationship. Then, it ensures that both the replacing head and tail entities in the corrupted triplet belong to the respective entity set so that the corrupted triplets that do not conform to the responding semantic relations are excluded. To evaluate the proposed model, we conduct link prediction and triple classification on WordNet and Freebase databases. The experimental results show that our method remarkably improves the performance compared to several state-of-the-art baselines.

Knowledge Graph Embedding Translation Based on Constraints.

In this paper, we make cryptanalysis on an image encryption scheme based on chaotic Tent map proposed by Li et al. [5]. We find chosen-plaintext attack can break the scheme. And we successfully carry out the chosen-plaintext attack. Last, we make an improvement method for overcome the drawback.

Security Analysis and Improvement of An Image Encryption Scheme Based on Chaotic Tent Map.

The aim of this research is to study the optimal economic dispatch (ED) through Cat Swarm Optimization (CSO) algorithm. Several techniques are applied to determine the proportion of wind generator capacity that can be integrated into an isolated system. The CSO is also extended to coordinate wind and thermal dispatch and to minimize total generation cost. Numerical experiments are included to demonstrate various constraints in production cost analysis and to provide valuable information for both operational and planning problems in the Taiwan power system.

Jeng-Shyang Pan

Papers

An Improved Digital Watermarking Scheme in the Domain of Vector Quantization

Improved DV-Hop based on parallel and compact whale optimization algorithm for localization in wireless sensor networks

Knowledge Graph Embedding Translation Based on Constraints.

Security Analysis and Improvement of An Image Encryption Scheme Based on Chaotic Tent Map.

CSO algorithm for economic dispatch decision of hybrid generation system