Hung-Yi Chang

Hybridization strategies for continuous ant colony optimization and particle swarm optimization applied to data clustering

Ant colony optimization (ACO) and particle swarm optimization (PSO) are two popular algorithms in swarm intelligence. Recently, a continuous ACO named ACOR was developed to solve the continuous optimization problems. This study incorporated ACOR with PSO to improve the search ability, investigating four types of hybridization as follows: (1) sequence approach, (2) parallel approach, (3) sequence approach with an enlarged pheromone-particle table, and (4) global best exchange. These hybrid systems were applied to data clustering. The experimental results utilizing public UCI datasets show that the performances of the proposed hybrid systems are superior compared to those of the K-mean, standalone PSO, and standalone ACOR. Among the four strategies of hybridization, the sequence approach with the enlarged pheromone table is superior to the other approaches because the enlarged pheromone table diversifies the generation of new solutions of ACOR and PSO, which prevents traps into the local optimum.

Embedding cycles in IEH graphs

Abstract We embed cycles into IEH graphs. First, IEH graphs are proved to be Hamiltonian except when they are of size 2n − 1 for all n ⩾ 2. Next, we show that for an IEH graph of size N, an arbitrary cycle of even length Ne where 3

A memory-efficient Huffman decoding algorithm

To reduce the memory size and fasten the process of searching for a symbol in a Huffman tree, we exploit the property of the encoded symbols and propose a memory-efficient data structure to represent the Huffman tree, which uses memory nd bits, where n is the number of source symbols and d is the depth of the Huffman tree. Based on the proposed data structure, we present an O(log n)-time Huffman decoding algorithm. An adaptive version for single-side growing Huffman tree is also addressed. This version could improve the average performance from log n to /spl Sigma//sub i//sup n//spl lceil/i/(h - 1)/spl rceil/ /spl times/ w/sub i/log h//spl Sigma/w/sub i/, where w/sub i/ is the frequency for i/sub th/ symbol and h is a pre-defined value.

Elucidating the role of conformity in innovative smartphones

Adoption of innovative products such as smartphones may be due to a mixture of experienced considerations and psychological perceptions. By synthesising adoption theories through reinforcement of the role of conformity. This study explores user intention to adopt innovative smartphones in the Taiwan telecommunication market. The survey data is analysed using structural equation modelling which is based on the constructs of ease of use, compatibility, and relative advantage, analysis results indicate that informational conformity and normative conformity are positively related to the intention to use smartphones. Additionally, early adopters and early majority users have a higher likelihood of conformity driven by informational influence, while the late majority users display a higher tendency towards normative conformity. The results of this study significantly contribute to efforts of mobile communication operators to anticipate and predict a customers intention to adopt smartphones, thus provides further insight into the development of marketing strategies for smartphones.

A New Service Level Agreement Model for Best-Effort Traffics in IP over WDM

In this paper, we propose a new SLA model for best effort IP traffic over WDM networks. This model jointly considers two QoS metrics, workable traffic volume and availability, as SLA parameters. We devise an algorithm of integer programming to minimize operation cost for the incremental traffic.

A scalable hardware solution for packet classification

One of interesting hardware solutions proposed to solve the packet classification problem is bit-vector algorithm. Different from other hardware solutions such as ternary CAM, it efficiently utilizes the memories to achieve an excellent performance in medium size policy database; however, it cannot scale up with the policy number increases. In this paper, we proposed an improved bit-vector algorithm named bit vector condensation, which can be adapted to large policy databases. Experiments showed that our proposed algorithm drastically improves in the storage requirements and search speed as compared to the original algorithm

Performance improvement of vector quantization by using threshold

Vector quantization (VQ) is an elementary technique for image compression. However, the complexity of searching the nearest codeword in a codebook is time-consuming. In this work, we improve the performance of VQ by adopting the concept of THRESHOLD. Our concept utilizes the positional information to represent the geometric relation within codewords. With the new concept, the lookup procedure only need to calculate Euclidean distance for codewords which are within the threshold, thus sifts candidate codewords easily. Our scheme is simple and suitable for hardware implementation. Moreover, the scheme is a plug-in which can cooperate with existing schemes to further fasten search speed. The effectiveness of the proposed scheme is further demonstrated through experiments. In the experimental results, the proposed scheme can reduce 64% computation with only an extra storage of 512 bytes.

Incrementally extensible folded hypercube graphs

In this paper, we propose the incrementally extensible folded hypercube (IEFH) graph as a new class of interconnection networks for an arbitrary number of nodes. We show that this system is optimal fault tolerant and almost regular (i.e., the difference between the maximum and the minimum degree of nodes is at most one). The diameter of this topology is half of that of the incomplete hypercube (IH), the supercube, or the IEH graph. We also devise a simple routing algorithm for the IEFH graph. Finally, we embed cycles and complete binary trees into this graph optimally.

Hardware accelerator for vector quantization by using pruned look-up table

Vector quantization (VQ) is an elementary technique for image compression. However, searching for the nearest codeword in a codebook is time-consuming. The existing schemes focus on software-based implementation to reduce the computation. However, such schemes also incur extra computation and limit the improvement. In this paper, we propose a hardware-based scheme “Pruned Look-Up Table” (PLUT) which could prune possible codewords. The scheme is based on the observation that the minimum one-dimensional distance between the tested vector and its matched codeword is usually small. The observation inspires us to select likely codewords by the one-dimensional distance, which is represented by bitmaps. With the bitmaps containing the positional information to represent the geometric relation within codewords, the hardware implementation can succinctly reduce the required computation of VQ. Simulation results demonstrate that the proposed scheme can eliminate more than 75% computation with an extra storage of 128 Kbytes.

A hierarchical FLP model for broadband networks

In next generation networks (NGNs), broadband networks include various layer 2 and layer 3 devices, e.g., Ethernet switches and routers. When deploying broadband networks, how the devices are appropriately located is an important issue. The device location problem could be treated as a hierarchical facility location problem (FLP). We present detailed mathematical models for the hierarchical FLP encountered in broadband network planning. Through experiments based on real networks, we demonstrate that the linearity of the model could significantly improve both the computational complexity and the optimality.