Chin-Shiuh Shieh

Genetic watermarking based on transform-domain techniques

Abstract An innovative watermarking scheme based on genetic algorithms (GA) in the transform domain is proposed. It is robust against watermarking attacks, which are commonly employed in the literature. In addition, the watermarked image quality is also considered. In this paper, we employ GA for optimizing both the fundamentally conflicting requirements. Watermarking with GA is easy for implementation. We also examine the effectiveness of our scheme by checking the fitness function in GA, which includes both factors related to robustness and invisibility. Simulation results also show both the robustness under attacks, and the improvement in watermarked image quality with GA.

Progressive watermarking techniques with genetic algorithms

An innovative watermarking scheme based on progressive transmission with genetic algorithms (GA) is proposed. We implement the watermarking embedding and extraction system in the discrete cosine transform (DCT) domain, and apply the JPEG spectral selection mode for progressive transmission. By employing GA with a proper fitness function into the watermarking system, both the watermark imperceptibility and watermark robustness requirements are considered and optimized. In addition, the embedded watermark can be partly extracted in the receiver side even when the watermarked image is being transmitted. Simulation results show both the robustness and the effectiveness of progressive transmission under different attacking schemes and different bandwidth variations.

Fault Diagnosis of Power Transformers Using SVM/ANN with Clonal Selection Algorithm for Features and Kernel Parameters Selection

For the purpose of fault diagnosis of power transformers, a novel approach based on artificial neural network (ANN) and multi-layer support vector machine (SVM) is presented in the paper. The proposed approach is distinguished by features and kernel parameters selection using clonal selection algorithms (CSA). It is capable of filtering out irrelevant input features, leading to improve prediction accuracy. As revealed in the experimental results, the proposed approach outperforms previous ones in both classification accuracy and computational efficiency

Compact Bat Algorithm

Addressing to the computational requirements of the hardware devices with limited resources such as memory size or low price is critical issues. This paper, a novel algorithm, namely compact Bat Algorithm (cBA), for solving the numerical optimization problems is proposed based on the framework of the original Bat algorithm (oBA). A probabilistic representation random of the Bat’s behavior is inspired to employ for this proposed algorithm, in which the replaced population with the probability vector updated based on single competition. These lead to the entire algorithm functioning applying a modest memory usage. The simulations compare both algorithms in terms of solution quality, speed and saving memory. The results show that cBA can solve the optimization despite a modest memory usage as good performance as oBA displays with its complex population-based algorithm. It is used the same as what is needed for storing space with six solutions.

Improving handover performance by switching between unicast and multicast addressing

With increased popularity and pervasiveness, mobile networking has become a definite trend for future networks. Users strongly demand that the connectivity of ongoing services be retained while roaming across different points of attachment. Efficient handover schemes are essential to the aforementioned vision. However, there are time-consuming procedures in the process. Various research has been devoted to the acceleration of movement detection and registration. However, a time-consuming operation, i.e., duplicate-address detection (DAD), was overlooked by most studies. One novel scheme that features anycast technique is developed and presented in this paper. The proposed approach switches to anycast addressing during handover and switches back to normal unicast addressing after all required operations are completed. By switching to anycast addressing, a mobile node can continue the reception of packets from its corresponding node before its new care-of address is actually validated. Thus, transmission disruption can effectively be minimized. In addition, a simple but effective buffer-control scheme is designed to reduce possible packet loss and prevent the out-of-order problem. Analytical study reveals that improved performance can be guaranteed, as reflected in the simulation results.

An Information Hiding Scheme for OFDM Wireless Networks

The traditional information hiding schemes embed the information into the image, audio and video etc, for the purposes of copyright protection, authentication, and authorized access control etc. In this paper, we propose to embed the data into the physical layer of the baseband Orthogonal Frequency Division Multiplexing (OFDM) wireless networks. We test the information hiding scheme in an additive white Gaussian noise (AWGN) channel. The experimental results indicate that when the number of carriers is limited and the channel SNR is high enough, the proposed information hiding scheme can work effectively, while the OFDM system can also work well as it used to be.

Improved Node Localization for WSN Using Heuristic Optimization Approaches

In Wireless Sensor Network, the localization of sensor nodes is an important problem in many applications. Normally in localization problem, the unknown position nodes will be determined their location through information of three or more anchors. In first part, some popular heuristic optimization methods like Genetic Algorithm (GA), Particle Swarm Optimization (PSO) will be compared with some recent optimization methods like Grey Wolf Optimizer (GWO), Firefly Algorithm (FA), and Brain Storm Optimization (BSO) algorithms in estimating the location of sensor nodes about accuracy. In second part, the improvement in localization algorithm is also proposed to enhance the number of nodes that can be localized. The results of our proposed improvement will be compared with original algorithm in both number of nodes that can be localized and the execute time with different deployment of networks.

Dosimetric advantages of generalised equivalent uniform dose-based optimisation on dose–volume objectives in intensity-modulated radiotherapy planning for bilateral breast cancer

OBJECTIVE We compared and evaluated the differences between two models for treating bilateral breast cancer (BBC): (i) dose-volume-based intensity-modulated radiation treatment (DV plan), and (ii) dose-volume-based intensity-modulated radiotherapy with generalised equivalent uniform dose-based optimisation (DV-gEUD plan). METHODS The quality and performance of the DV plan and DV-gEUD plan using the Pinnacle(3) system (Philips, Fitchburg, WI) were evaluated and compared in 10 patients with stage T2-T4 BBC. The plans were delivered on a Varian 21EX linear accelerator (Varian Medical Systems, Milpitas, CA) equipped with a Millennium 120 leaf multileaf collimator (Varian Medical Systems). The parameters analysed included the conformity index, homogeneity index, tumour control probability of the planning target volume (PTV), the volumes V(20 Gy) and V(30 Gy) of the organs at risk (OAR, including the heart and lungs), mean dose and the normal tissue complication probability. RESULTS Both plans met the requirements for the coverage of PTV with similar conformity and homogeneity indices. However, the DV-gEUD plan had the advantage of dose sparing for OAR: the mean doses of the heart and lungs, lung V(20) (Gy), and heart V(30) (Gy) in the DV-gEUD plan were lower than those in the DV plan (p<0.05). CONCLUSIONS A better result can be obtained by starting with a DV-generated plan and then improving it by adding gEUD-based improvements to reduce the number of iterations and to improve the optimum dose distribution. Advances to knowledge The DV-gEUD plan provided superior dosimetric results for treating BBC in terms of PTV coverage and OAR sparing than the DV plan, without sacrificing the homogeneity of dose distribution in the PTV.

A cluster-based routing protocol for wireless sensor networks with adjustable cluster size

A cluster-based routing scheme for wireless sensor networks featuring adjustable cluster size is proposed in this article. Aimed at the reduction of power consumption, the proposed scheme is designed to adjust cluster sizes on the fly such that communication loads can be evenly shared by individual nodes, and consequently extend the lifetime of an entire sensor network. In the proposed scheme, named ACRP, sensor nodes form clusters automatically. Cluster heads assign time slots to sensor nodes for data transmission. Cluster heads then aggregate received data and forward them to the base station along established routing paths. In particular, based on received cluster information, the base station periodically adjusts the cluster membership of sensor nodes such that each clusters have comparable size, and pick up new head with most residual energy for each cluster. By doing so, the communication load can be shared by participant nodes and the data transmission schedules for each cluster will have similar duration. Both contribute to faster data transmission and extended lifetime for wireless sensor networks. Simulation result reveals that the proposed scheme is effective and outperforms the well-known LEACH in most scenarios.

Particle swarm optimization-based SVM for incipient fault classification of power transformers

A successful adoption and adaptation of the particle swarm optimization (PSO) algorithm is presented in this paper. It improves the performance of Support Vector Machine (SVM) in the classification of incipient faults of power transformers. A PSO-based encoding technique is developed to improve the accuracy of classification. The proposed scheme is capable of removing misleading input features and, optimizing the kernel parameters at the same time. Experiments on real operational data had demonstrated the effectiveness and efficiency of the proposed approach. The power system industry can benefit from our system in both the accelerated operational speed and the improved accuracy in the classification of incipient faults.