This paper proposes a hierarchical service management system for MPLS network services. Traditionally, general management systems which have been deployed in some service providers control MPLS LSPs (e.g. RSVP-TE, LDP) and services (e.g. L2VPN, L3VPN and IP) separately. If a fault occurs in an MPLS network, the dedicated management system for MPLS LSPs can detect the fault and recognize the state of MPLS LSPs. However, it cannot detect the extent of the impact due to the fault in each service. Furthermore, its own inability to identify the affected customer means it takes some time to identify the affected customers, cooperating manually with the dedicated management system for services. Therefore, this paper proposes a new automatic correlation between MPLS LSPs and each service. In particular, this paper proposes a new algorithm for a correlation between RSVP-TE LSPs and L3VPN services. Simulations are conducted to evaluate the capacity on a correlation table and the performance searching on a correlation table, and results show this system is very scalable within real MPLS production networks. This system, with the automatic correlation, could be sufficiently deployed in real MPLS production networks.

This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix inequality (LMI) problem. If solutions of a specific system exist, the scheme finds more than one solutions at a time, and these fixed potential solutions and variable PID gains are ready for tracking performance optimization. The effectiveness of the proposed control scheme is demonstrated by the numerical example of a cart-pole system.

This paper presents a Maximum Likelihood Location Estimation (MLLE) algorithm for the home network environments. We propose a deployment of cluster-tree topology in the ZigBee networks and derive the MLE under the log-normal models for the Received Signal Strength (RSS) measurements. Experiments are also conducted to validate the effectiveness of the proposed algorithm.

Several approaches have been studied to cope with the exceptional features of non-segmented languages. When there is no explicit information about the boundary of a word, segmenting an input text is a formidable task in language processing. Not only the contemporary word list, but also usages of the words have to be maintained to cover the use in the current texts. The accuracy and efficiency in higher processing do heavily rely on this word boundary identification task. In this paper, we introduce some statistical based approaches to tackle the problem due to the ambiguity in word segmentation. The word boundary identification problem is then defined as a part of others for performing the unified language processing in total. To exhibit the ability in conducting the unified language processing, we selectively study the tasks of language identification, word extraction, and dictionary-less search engine.

Distributed denial-of-service attacks on public servers have recently become more serious. The most effective way to prevent this type of traffic is to identify the attack nodes and detach (or block) attack nodes at their egress routers. However, existing traceback mechanisms are currently not widely used for several reasons, such as the necessity of replacement of many routers to support traceback capability, or difficulties in distinguishing between attacks and legitimate traffic. In this paper, we propose a new scheme that enables a traceback from a victim to the attack nodes. More specifically, we identify the egress routers that attack nodes are connecting to by estimating the traffic matrix between arbitral source-destination edge pairs. By monitoring the traffic variations obtained by the traffic matrix, we identify the edge routers that are forwarding the attack traffic, which have a sharp traffic increase to the victim. We also evaluate the effectiveness of our proposed scheme through simulation, and show that our method can identify attack sources accurately.

From lessons learned in medical data mining projects we show that integration of advanced computation techniques and human inspection is indispensable in medical data mining. We proposed an integrated approach that merges data mining and text mining methods plus visualization support for expert evaluation. We also appropriately developed temporal abstraction and text mining methods to exploit the collected data. Furthermore, our visual discovery system D2MS allowed to actively and effectively working with physicians. Significant findings in hepatitis study were obtained by the integrated approach.

Employee performance appraisal is an effective way to determine the performance of the employees in an organization. A study conducted on companies in Thailand revealed that majority of the companies do not use computer-based employee appraisal system. In the traditional appraisal system, the paper-based appraisal system causes a lot of manual work, is time-consuming, not secure, not flexible, difficult to analyze the performance and see the trend of performance improvement of the employee. We have developed a web-based performance appraisal system, which provides a secure and easy way to perform the appraisal. In our system, the competencies are flexible and can be customized according to the specific job responsibility. Our system is goal-orientated as it calculates the objective scores. The system is connected to the database which is easily accessible. The first stage of our system is the 'Selection Stage' in which the managers and employees can select the competencies and objectives that they want to evaluate for performance appraisal according to the job positions. The second stage is the 'Appraisal/Evaluation Stage' where managers can rate the employees according to different priority levels of competencies and objectives. Moreover, at this stage, employees can perform self-evaluation and 360-degree evaluation for their colleagues, subordinates and managers. The final stage is the 'Development Planning Stage' where the managers and employees can compare their appraisal results, discuss and plan for future training or further steps for reaching the objectives and improving employee's competencies. From user testing, the system was found to be more efficient compared to the traditional appraisal system in the issues like: help evaluate the true abilities of employees, help employees understand organizational goals, and provide fast and effective feedback. The users found the system easy to understand and use and were more satisfied with the overall effectiveness of the system.

Educational websites contain rich knowledge components on a web page. Detecting student attention on web pages fulfills the recommendation of adequate knowledge components to students based on students' current interests. Previous studies have shown the application of learner attention in intelligent learning systems. This study proposes a methodology to analyze student on-line mouse movement patterns that indicate student attentions. The methodology can be combined with learning systems that implement pedagogical models such as inquiry-based learning and problem-solving learning activities. The feasibility and effectiveness of the proposed methodology have been evaluated by student mouse movements in problem-solving scenarios.

In the acquisition of projection data of X-ray CT, logarithm operation is indispensable. But noise distribution is nonlinearly projected by the logarithm operation, and this deteriorates the precision of CT number. This influence becomes particularly remarkable when only a few photons are caught with a detector. It generates a strong streak artifact (SA) in a reconstructed image. Previously we have clarified the influence of the nonlinearity by statistical analysis and proposed a correction method for such nonlinearity. However, there is a problem that the compensation for clamp processing cannot be performed and that the suppression of SA is not enough in photon shortage state. In this paper, we propose a new technique for correcting the nonlinearity due to logarithm operation for noisy data by combining the previously presented method and an adaptive filtering method. The technique performs an adaptive filtering only when the number of captured photons is very few. Moreover we quantitatively evaluate the influence of noise on the reconstructed image in the proposed method by the experiment using numerical phantoms. The experimental results show that there is less influence on spatial resolution despite suppressing SA effectively and that CT number are hardly dependent on the number of the incident photons.

In this letter, we propose an enhanced method for inter-layer motion prediction in scalable video coding (SVC). For inter-layer motion prediction, the use of refined motion data in the Fine Granular Scalability (FGS) layer is proposed instead of the conventional use of motion data in the base quality layer to reduce the inter-layer redundancy efficiently. Experimental results show that the proposed method enhances coding efficiency without increasing the computational complexity of the decoder.

A practical optical character reader is required to deal with not only common fonts but also complex designed fonts. However, recognizing various kinds of decorative character images is still a challenging problem in the field of document image analysis. Since appearances of such decorative characters are complicated, most general character recognition systems cannot give good performances on decorative characters. In this paper, an algorithm that recognizes decorative characters by structural analysis using a graph-matching technique is proposed. Character structure is extracted by using topographical features of multi-scale images, and the extracted structure is represented by a graph. A character image is recognized by matching graphs of the input and standard patterns. Experimental results show the effectiveness of the proposed algorithm.

A passive optical network (PON) that provides fiber to the home (FTTH) services is a fundamental access network topology in Japan. An optical fiber line monitoring and testing system is essential if we are to improve service reliability and reduce the maintenance costs of optical access networks. PONs have optical splitters in their optical fiber lines. It is difficult to find a fault in an optical fiber line equipped with an optical splitter by using a conventional optical fiber line testing system, which uses optical time-domain reflectometer (OTDR) in a central office (CO), because Rayleigh backscattering from the branched fibers accumulates in the OTDR trace. This paper describes a newly developed optical fiber line testing method that employs bi-directional OTDRs with two wavelengths at branched fiber regions in a PON to locate a fault precisely. Optical fiber line testing is conducted by two OTDRs that are installed in a CO and on a customer's premises, respectively. The OTDR in the CO has a U-band maintenance wavelength. We present two kinds of maintenance wavelength allocation for OTDRs on a customer's premises, which are in the U-band and C-band respectively. An OTDR whose maintenance wavelength is in the U-band enables us to test in-service PON lines simply by filtering the U-band wavelength. For the maintenance wavelengths in the C-band, we can use a cost-effective conventional OTDR to test the PON from the customer's premises on condition that we clarify the peak pulse power limit and dynamic range. We describe the test procedures for both cases. We also clarify the insertion loss design for an optical filter in the CO when using the U-band to provide the maintenance wavelength and the criteria for in-service line testing when the using C-band to provide the maintenance wavelength. To confirm the feasibility of our approach, we demonstrate a bi-directional OTDR method using the U-band and the C-band, and the test procedure, which successfully detected fault locations in branched fiber regions. We also describe the use of packet loss measurements to investigate the effect of in-service line testing with an OTDR in the C-band on data communication quality.

A new scheme for reducing optical beat interference noise in a reflective semiconductor optical amplifier based wavelength division multiplexed/subcarrier multiplexing -- passive optical network is proposed. This method uses an Fabry Perot laser locked by modulated lights from optical network units in a central office. As an experimental verification, it is reported that carrier to noise ratio is enhanced by 10 dB and power penalty is improved by 16 dB.

A comparison among the possible nonlinear photonic interactions for scalable nanometer networks and quantum gates as well as for coherence retention in solids is made theoretically, and then numerical plottings are given, on the basis of the dipole length estimated from our µ-PL (microphotoluminescence) spectra of GaAs/AlGaAs coupled quantum dots (QDs) having a pair of 0.3 meV splittings. Furthermore, prospective device concepts based on these nonlinear multipolar interactions are given.

In order to support decision making, text classification is an important tool. Recently, in addition to term frequency and inverse document frequency, term distributions have been shown to be useful to improve classification accuracy in multi-class classification. This paper investigates the performance of these term distributions on binary classification using a centroid-based approach. In such one-against-the-rest, there are only two classes, the positive (focused) class and the negative class. To improve the performance, a so-called hierarchical EM method is applied to cluster the negative class, which is usually much larger and more diverse than the positive one, into several homogeneous groups. The experimental results on two collections of web pages, namely Drug Information (DI) and WebKB, show the merits of term distributions and clustering on binary classification. The performance of the proposed method is also investigated using the Thai Herbal collection where the texts are written in Thai language.

Note taking is a fundamental activity for learning, and many software tools which enable students to take digitized notes have been proposed. Digitized notes are advantageous because they can be easily edited, rearranged, and shared. Although many note-taking tools have been proposed, there has been little research to examine the effect of note annotation and rearrangement with a digitized tool in terms of knowledge acquisition. Therefore, we have investigated the effect of note annotation and rearrangement on how well lecture content is remembered by learners. By annotation, we mean adding both handwritten and typed text, and rearrangement includes moving and deleting handwritten notes. We developed a simple note-taking application specialized for explanation, and evaluated it through a laboratory experiment with eight participants. The results show that note annotation and rearrangement significantly improved how well the participants remembered lecture content. Thus, the effect of annotation and rearrangement on remembrance was confirmed with respect to digitized notes.

In this paper, we have systematically investigated parasitic effects due to the gate and source-drain engineering in multi-gate transistors. The potential impact of high-K dielectrics on multi-gate MOSFETs (MuGFETs), such as FinFET, is evaluated through 2D and 3D device simulations over a wide range of proposed dielectric values. It is observed that introduction of high-K dielectrics will significantly degrade the short channel effects (SCEs), however a combination of oxide and high-K stack can effectively control this degradation. The degradation is mainly due to the increase in the internal fringe capacitance coupled with the decrease in gate-channel capacitance. From the circuit perspective, an optimum K value has been identified through mixed mode simulations. Further, as a part of this work, the importance of optimization of the shape of the spacer region is highlighted through full 3D simulations.

Recently we proposed a new waveband MUX/DEMUX that uses two concatenated cyclic AWGs. We analyse and formulate connection arrangements of the waveguides connecting the two AWGs. The port utilization of the device is shown to be 100% with bi-directional input fibers.

We propose in this paper a SOM-like algorithm that accepts online, as inputs, starts and ends of viewing of a multimedia content by many users; a one-dimensional map is then self-organized, providing an approximation of density distribution showing how many users see a part of a multimedia content. In this way "viewing behavior of crowds" information is accumulated as experience accumulates, summarized into one SOM-like network as knowledge is extracted, and is presented to new users as the knowledge is transmitted. Accumulation of multimedia contents on the Internet increases the need for time-efficient viewing of the contents and the possibility of compiling information on many users' viewing experiences. In the circumstances, a system has been proposed that presents, in the Internet environment, a kind of summary of viewing records of many viewers of a multimedia content. The summary is expected to show that some part is seen by many users but some part is rarely seen. The function is similar to websites utilizing "wisdom of crowds" and is facilitated by our proposed algorithm.

In this paper, a computationally efficient stack-based iterative detection algorithm is proposed for V-BLAST systems. To minimize the receiver's efforts as much as possible, the proposed scheme employs iterative tree search for complexity reduction and storage saving. After an M-ary tree structure by QR decomposition of channel matrix is constructed, the full tree depth is divided into the first depth and the remaining ones. At tree depth of one, the proposed algorithm finds M candidate symbols. Based on these symbols, it iteratively searches the remaining symbols at second-to-last depth, until finding an optimal symbol sequence. Simulation results demonstrate that the proposed algorithm yields the performance close to that of sphere detection (SD) with significant saving in complexity and storage.