Personal communication service (PCS) networks support the delivery of communication services as the mobile user moves from one region to another. When a mobile user receives a call, the network has to quickly determine its current location. The existing approach suffers from high delay in locating the mobile since the mobile's current location has to be always consulted on the location databases. Caching the location of the remote mobile is useful to reduce this delay. However, the longer the useless record caused by the movement of the mobile remains in a cache, the higher the degradation of cache memory utilization is imposed on a system. In this paper, we propose an efficient caching scheme that a cached record is not allowed to remain over the predefined time, called a time-threshold, in a cache. A long time-threshold may cause to increase the obsoleteness of the cached record. In contrast, a short time-threshold may cause to degrade memory utilization. This paper finds the optimal time-threshold to enlarge cache memory utilization. Also, we provide a unique solution for determining the optimal time-threshold, and study the effects of changing the important parameters of mobility, calling patterns, and network conditions on the optimal time-threshold. Furthermore, we compare the performance of the proposed caching call delivery scheme and the existing call delivery schemes.

CDN (Content Delivery Networks) improves end-user performance by replicating web contents on a group of geographically distributed servers. However, repeatedly keeping the entire replica of the original objects into many content servers consumes too much server resource. This problem becomes more serious for the large-sized objects such as streaming media, e.g. high quality video. In this paper, we therefore propose an efficient replication method for layered video streams in CDN, which can reduce user response delays and storage costs simultaneously. Based on an analytical formulation of the cooperative replication of layers and segments of each video stream, we derive a replication algorithm which solves next three problems quantitatively. (1) How many servers should be selected to replicate a given video stream? (2) For a single video stream, how many layers and segments should be stored in a given server? (3) After selecting a group of servers for each video stream, how do we allocate the replication priority (i.e. order) to each server? Simulation results verify that the proposed algorithm efficiently resolves the above problems and provides much better performance than conventional methods.

In this paper, we have proposed to apply a combinatorial approach to investigate the Schottky diode based on electrochemically polymerized conjugated polymer. The concept of combinatorial approach was emerged in the biochemical field and lately used in the materials science to screen a number of experimental conditions efficiently. Some tips for designing the polymerization bath suitable for our purpose, such as the way to suppress the interference of polymerization currents, have been described. In the case of Schottky diodes based on poly (3-methylthiophene), the system chosen to test our idea, the effects of polymer thickness and the supporting salt on the device characteristics have been surveyed clearly and rapidly. The map or library of the relationship between the polymerization condition and device characteristic may be useful to tune the device characteristics as desired. Our preliminary result has shown that the combinatorial approach proposed here can be a powerful tool to investigate the conjugated polymer devices by electrochemical polymerization such as electrochromic devices.

The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, the Web Robot Agent or WebBot, which integrates with the web and acts as a personal recommendation system that cooperates with the user in order to identify interesting pages. The Apriori algorithm extracts the characteristics of the web pages in the form of association words that are semantically related and mines a bag of association words. Using hybrid components from collaborative filtering and content-based filtering, this hybrid recommendation system can overcome the shortcomings associated with traditional recommendation systems. In this paper, we present an improved recommendation system, which uses the user preference mining through hybrid 2-way filtering. The proposed method was tested on a database, and its effectiveness compared with existent methods was proven in on-line experiments.

The choice of kernel is an important issue in the support vector machine algorithm, and the performance of it largely depends on the kernel. Up to now, no general rule is available as to which kernel should be used. In this paper we investigate two kernels: Gaussian RBF kernel and polynomial kernel. So far Gaussian RBF kernel is the best choice for practical applications. This paper shows that the polynomial kernel in the normalized feature space behaves better or as good as Gaussian RBF kernel. The polynomial kernel in the normalized feature space is the best alternative to Gaussian RBF kernel.

The volume of mass unsolicited electronic mail, often known as spam, has recently increased enormously and has become a serious threat not only to the Internet but also to society. This paper proposes a new spam detection method which uses document space density information. Although the proposed method requires extensive e-mail traffic to acquire the necessary information, it can achieve perfect detection (i.e., both recall and precision is 100%) under practical conditions. A direct-mapped cache method contributes to the handling of over 13,000 e-mail messages per second. Experimental results, which were conducted using over 50 million actual e-mail messages, are also reported in this paper.

This paper proposes a Real-Time Compression Architecture (RTCA), which maximizes the efficiency of web services, while reducing the response time at the same time. The developed architecture not only guarantees the freshness of compressed contents but also minimizes the time needed to compress the message, especially when the traffic is heavy.

This study aims to identify grammatical relations (GRs) in Korean sentences. The key task is to find the GRs in sentences in terms of such GR categories as subject, object, and adverbial. To overcome this problem, we are faced with the structural ambiguity and the grammatical relational ambiguity. We propose a statistical model, which resolves the grammatical relational ambiguity first, and then resolves structural ambiguity by using the probabilities of the GRs given noun phrases and verb phrases in sentences. The proposed model uses the characteristics of the Korean language such as distance, no-crossing and case property. We showed that consideration of such characteristics produces better results than without consideration by experiments. We attempt to enhance our system by estimating the probabilities of the proposed model with the Maximum Entropy (ME) model, and with Support Vector Machines (SVM) classifiers and we confirm that SVM classifiers improved the performance of our proposed model through experiments. Through an experiment with a tree and GR tagged corpus for training the model, we achieved an overall accuracy of 84.8%, 94.1%, and 84.8% in identifying subject, object, and adverbial relations in sentences, respectively.

Active Reliable Multicast (ARM) is a novel loss recovery scheme for large-scale reliable multicast that employs active routers to protect the sender and network bandwidth from unnecessary feedback and repair traffic. Active routers perform NACKs suppression, cache multicast data for local loss recovery, and use scoped retransmission to avoid exposure. Limited active resources at routers need to be optimized to achieve low loss recovery latency and/or high network throughput. In this paper, we study the cache placement strategies and caching policies for ARM. Several heuristics, namely uniform allocation, proportional allocation, max-min fair share and weighted allocation for cache allocation methods are proposed. To further improve the loss recovery performance, caching policies can be employed in conjunction with the cache allocation strategies. Several caching policies, namely complete caching, random caching and deterministic caching, are proposed. Extensive simulation experiments are conducted to evaluate and compare the performance of the proposed strategies and policies. Numerical results reveal that significant performance gains can be achieved when a proper cache placement strategy and a caching policy are used for a given available cache resource. Another interesting finding is that the contributions of the cache placement scheme and caching policy to the recovery latency performance are roughly independent. The obtained insights in this study will provide some design guidelines for optimal active resource allocation and caching polices for reliable multicast communications.

We introduce an inheritance concept into a specification method of a concurrent system in order to reuse and refine existing specifications. Reusability by inheritance is emphasized in this paper. We take multiple inheritance to enable to reuse several specifications at a time. An upper specification can be skillfully reused by dividing inherited parts and non-inherited ones if the specification contains unnecessary parts for a lower specification. As an application, we specify the FIPA contract net interaction protocol (IP) with the function of an agent authentication. This is accomplished by using multiple inheritance. We also specify the FIPA iterated contract net IP by reusing the FIPA contract net IP. We have been developing a validation support tool for specifications described with the proposed method.

Masqueraders who impersonate other users pose serious threat to computer security. Unfortunately, firewalls or misuse-based intrusion detection systems are generally ineffective in detecting masqueraders. Anomaly detection techniques have been proposed as a complementary approach to overcome such limitations. However, they are not accurate enough in detection, and the rate of false alarm is too high for the technique to be applied in practice. For example, recent empirical studies on masquerade detection using UNIX commands found the accuracy to be below 70%. In this research, we performed a comparative study to investigate the effectiveness of SVM (Support Vector Machine) technique using the same data set and configuration reported in the previous experiments. In order to improve accuracy of masquerade detection, we used command frequencies in sliding windows as feature sets. In addition, we chose to ignore commands commonly used by all the users and introduce the concept of voting engine. Though still imperfect, we were able to improve the accuracy of masquerade detection to 80.1% and 94.8%, whereas previous studies reported accuracy of 69.3% and 62.8% in the same configurations. This study convincingly demonstrates that SVM is useful as an anomaly detection technique and that there are several advantages SVM offers as a tool to detect masqueraders.

In this paper, we propose a formal method for detection of three automation surprises in human-machine interaction; a mode confusion, a refusal state, and a blocking state. The mode confusion arises when a machine is in a different mode from that anticipated by the user, and is the most famous automation surprise. The refusal state is a situation that the machine does not respond to a command the user executes. The blocking state is a situation where an internal event occurs, leading to change of an interface the user does not know. In order to detect these phenomena, we propose a composite model in which a machine and a user model evolve concurrently. We show that the detection of these phenomena in human-machine interaction can be reduced to a reachability problem in the composite model.

The relation between resonant frequency of micromirror with vertical combdrives and applied voltage between the upper and lower comb teeth was analyzed. Resonant frequency of the micromirror was controlled by stiffness of the torsion hinge. Resonant frequency of the mirror was proportional to the applied voltage between the upper and lower comb teeth at the same tilt angle.

Visual defects, called mura in the field, sometimes occur during the manufacturing of the flat panel liquid crystal displays. In this paper we propose an automatic inspection method that reliably detects and quantifies TFT-LCD region-mura defects. The method consists of two phases. In the first phase we segment candidate region-muras from TFT-LCD panel images using the modified regression diagnostics and Niblack's thresholding. In the second phase, based on the human eye's sensitivity to mura, we quantify mura level for each candidate, which is used to identify real muras by grading them as pass or fail. Performance of the proposed method is evaluated on real TFT-LCD panel samples.

The lithography process on the deep trench pattern above the large cavity is proposed to fabricate the MEMS structure. Generally, bubbles generated on the trench patterns when it was baked after coating resist. The probability of the generation of bubbles was reduced by decreasing the backing rate. The fast scanning micromirror with 50.8 kHz resonant frequency was fabricated by controlling the backing rate.

This paper proposes a learning classifier based on Support Vector Domain Description (SVDD) for two-class problem. First, by the description of the training samples from one class, a sphere boundary containing these samples is obtained; then, this boundary is used to classify the test samples. In addition, instead of the traditional quadratic programming, multiplicative updates is used to solve the Lagrange multiplier in optimizing the solution of the sphere boundary. The experiment on CBCL face database illustrates the effectiveness of this learning algorithm in comparison with Support Vector Machine (SVM) and Sequential Minimal Optimization (SMO).

Shared memory multiprocessors in which each processor has its own TLB must manage consistency among TLBs and a page table. As the large-scale CC-NUMA (cache-coherent non-uniform memory access) shared memory multiprocessors become popular, it is important for TLB consistency management algorithms to be highly scalable. In this paper, we propose a TLB update-hint algorithm as a scalable TLB consistency management solution for CC-NUMA multiprocessors. By using a lazy TLB invalidation approach, we reduced the number of unnecessary processor interruptions and idle-waiting time, and achieved a high level of scalability. Using a shared memory simulator, we evaluated the TLB update-hint algorithm. For performance comparison, we also simulated the TLB shootdown algorithm, one of the most popular TLB consistency algorithms. The simulations demonstrated that the TLB update-hint algorithm scales well in systems with a large number of processors. At 64 node systems, the TLB update-hint algorithm shows 4787% better performance than the TLB shootdown algorithm.

Mobile agent systems are essential in the next generation of electronic commercial applications. However, existing solutions for mobile agents to sign documents without user intervention are problematic because there is no restriction on who can generate the signatures. In this paper, we present a modified version of undetachable signature scheme with which the power to generate digital signatures can be designated to a neutral party. We also give a transaction model to support the scheme. Discussions regarding the security of the signature scheme as well as some attacks on its application in our model are presented too.

In CC-NUMA multiprocessor systems, it is important to reduce the remote memory access time. Based upon the fact that increasing the size of the LRU second-level (L2) cache more than a certain value does not reduce the cache miss rate significantly, in this paper, we propose two split L2 caches to utilize the surplus of the L2 cache. The split L2 caches are composed of a traditional LRU cache and another cache to reduce the remote memory access time. Both work together to reduce total L2 cache miss time by keeping remote (or long-distance) blocks as well as recently used blocks. For another cache, we propose two alternatives: an L2-RVC (Level 2 - Remote Victim Cache) and an L2-DAVC (Level 2 - Distance-Aware Victim Cache). The proposed split L2 caches reduce total execution time by up to 27%. It is also found that the proposed split L2 caches outperform the traditional single LRU cache of double size.

For network computing on desktop machines, fast execution of Java bytecode programs is essential because these machines are expected to run substantial application programs written in Java. We believe higher Java performance can be achieved by exploiting instruction-level parallelism (ILP) in the context of Java JIT compilation. This paper introduces VLaTTe, a Java JIT compiler for VLIW machines that performs efficient scheduling while doing fast register allocation. It is an extended version of our previous JIT compiler for RISC machines called LaTTe whose translation overhead is low (i.e., consistently taking one or two seconds for SPECJVM98 benchmarks) due to its fast register allocation. VLaTTe adds the scheduling capability onto the same framework of register allocation, with a constraint for precise in-order exception handling which guarantees the same Java exception behavior with the original bytecode program. Our experimental results on the SPECJVM98 benchmarks show that VLaTTe achieves a geometric mean of useful IPC 1.7 (2-ALU), 2.1 (4-ALU), and 2.3 (8-ALU), while the scheduling/allocation overhead is 3.6 times longer than LaTTe's on average, which appears to be reasonable.