IEICE Transactions on Information and Systems - recent issues

A Tight Upper Bound on Online Buffer Management for Multi-Queue Switches with Bicodal Buffers

KOBAYASHI, K., MIYAZAKI, S., OKABE, Y. — 2008-12-19

The online buffer management problem formulates the problem of queuing policies of network switches supporting QoS (Quality of Service) guarantee. In this paper, we consider one of the most standard models, called multi-queue switches model. In this model, Albers et al. gave a lower bound e/e–1, and Azar et al. gave an upper bound e/e–1 on the competitive ratio when m, the number of input ports, is large. They are tight, but there still remains a gap for small m. In this paper, we consider the case where m = 2, namely, a switch is equipped with two ports, which is called a bicordal buffer model. We propose an online algorithm called Segmental Greedy Algorithm (SG) and show that its competitive ratio is at most 16/13 (~= 1.231), improving the previous upper bound by 9/7 (~= 1.286). This matches the lower bound given by Schmidt.

On Fault Testing for Reversible Circuits

TAYU, S., ITO, S., UENO, S. — 2008-12-19

It has been known that testing of reversible circuits is relatively easier than conventional irreversible circuits in the sense that few test vectors are needed to cover all stuck-at faults. This paper shows, however, that it is NP-hard to generate a minimum complete test set for stuck-at faults on the wires of a reversible circuit using a polynomial time reduction from 3SAT to the problem. We also show non-trivial lower bounds for the size of a minimum complete test set.

Relating L versus P to Reversal versus Access and Their Combinatorial Structures

UENO, K. — 2008-12-19

Reversal complexity has been studied as a fundamental computational resource along with time and space complexity. We revisit it by contrasting with access complexity which we introduce in this study. First, we study the structure of space bounded reversal and access complexity classes. We characterize the complexity classes L, P and PSPACE in terms of space bounded reversal and access complexity classes. We also show that the difference between polynomial space bounded reversal and access complexity is related with the L versus P problem. Moreover, we introduce a theory of memory access patterns, which is an abstracted structure of the order of memory accesses during a random access computation, and extend the notion of reversal and access complexity for general random access computational models. Then, we give probabilistic analyses of reversal and access complexity for almost all memory access patterns. In particular, we prove that almost all memory access patterns have (log n) reversal complexity while all languages in L are computable within O(log n) reversal complexity.

Platform-Based Design for the Low Complexity and High Performance De-Interlacing System

TSAI, T.-H., LIN, H.-L. — 2008-12-19

With the development of digital TV system, how to display the NTSC signal in digital TV system is a problem. De-interlacing is an algorithm to solve it. In previous papers, using motion compensation (MC) method for de-interlacing needs lots of computation complexity and it is not easy to implement in hardware. In this paper, a content adaptive de-interlacing algorithm is proposed. Our algorithm is based on the motion adaptive (MA) method which combines the advantages of intra-field and inter-field method. We propose a block type decision mechanism to predict the video content instead of a blind processing with MC method throughout the entire frame. Additionally, in intra-field method, we propose the edge-base adaptive weight average (EAWA) method to achieve a better performance and smooth the edge and stripe. In order to demonstrate our algorithm, we implement the de-interlacing system on the DSP platform with thorough complexity analysis. Compared to MC method, we not only achieve higher video quality in objective and subjective view, but also consume lower computation power. From the profiling on CPU run-time analysis, the proposed algorithm is only one-fifth of MC method. At the DSP demonstration board, the saving ratio is about 54% to 96%.

A Preemption Algorithm for a Multitasking Environment on Dynamically Reconfigurable Processors

TUAN, V. M., AMANO, H. — 2008-12-19

Task preemption is a critical mechanism for building an effective multi-tasking environment on dynamically reconfigurable processors. When a task is preempted, its necessary state information must be correctly preserved in order for the task to be resumed later. Not only do coarse-grained Dynamically Reconfigurable Processing Array (DRPAs) devices have different architectures using a variety of development tools, but the great amount of state data of hardware tasks executing on such devices are usually distributed on many different storage elements. To address these difficulties, this paper aims at studying a general method for capturing the state data of hardware tasks targeting coarse-grained DRPAs. Based on resource usage, algorithms for identifying preemption points and inserting preemption states subject to user-specified preemption latency are proposed. Moreover, a modification to automatically incorporate proposed steps into the system design flow is also discussed. The performance degradation caused by additional preemption states is minimized by allowing preemption only at predefined points where demanded resources are small. The evaluation result using a model based on NEC Electronics' DRP-1 shows that the proposed method can produce preemption points satisfying a given preemption latency with reasonable hardware overhead (from 6% to 15%).

Proof Score Approach to Verification of Liveness Properties

OGATA, K., FUTATSUGI, K. — 2008-12-19

Proofs written in algebraic specification languages are called proof scores. The proof score approach to design verification is attractive because it provides a flexible way to prove that designs for systems satisfy properties. Thus far, however, the approach has focused on safety properties. In this paper, we describe a way to verify that designs for systems satisfy liveness properties with the approach. A mutual exclusion protocol using a queue is used as an example. We describe the design verification and explain how it is verified that the protocol satisfies the lockout freedom property.

DAC: A Device-Aware Cache Management Algorithm for Heterogeneous Mobile Storage Systems

KIM, Y.-J., KIM, J. — 2008-12-19

In recent years, heterogeneous devices have been employed frequently in mobile storage systems because a combination of such devices can supply a synergistically useful storage solution by taking advantage of each device. One important design constraint in heterogeneous storage systems is to mitigate I/O performance degradation stemming from the difference between access times of different devices. To this end, there has not been much work to devise proper buffer cache management algorithms. This paper presents a novel buffer cache management algorithm which considers both I/O cost per device and workload patterns in mobile computing systems with a heterogeneous storage pair of a hard disk and a NAND flash memory. In order to minimize the total I/O cost under varying workload patterns, the proposed algorithm employs a dynamic cache partitioning technique over different devices and manages each partition according to request patterns and I/O types along with the temporal locality. Trace-based simulations show that the proposed algorithm reduces the total I/O cost and flash write count significantly over the existing buffer cache algorithms on typical mobile traces.

An RFID-Based Manufacturing Control Framework for Loosely Coupled Distributed Manufacturing System Supporting Mass Customization

CHEN, R.-S., TSAI, Y.-S., TU, A. — 2008-12-19

In this study we propose a manufacturing control framework based on radio-frequency identification (RFID) technology and a distributed information system to construct a mass-customization production process in a loosely coupled shop-floor control environment. On the basis of this framework, we developed RFID middleware and an integrated information system for tracking and controlling the manufacturing process flow. A bicycle manufacturer was used to demonstrate the prototype system. The findings of this study were that the proposed framework can improve the visibility and traceability of the manufacturing process as well as enhance process quality control and real-time production pedigree access. Using this framework, an enterprise can easily integrate an RFID-based system into its manufacturing environment to facilitate mass customization and a just-in-time production model.

Component Reduction for Gaussian Mixture Models

MAEBASHI, K., SUEMATSU, N., HAYASHI, A. — 2008-12-19

The mixture modeling framework is widely used in many applications. In this paper, we propose a component reduction technique, that collapses a Gaussian mixture model into a Gaussian mixture with fewer components. The EM (Expectation-Maximization) algorithm is usually used to fit a mixture model to data. Our algorithm is derived by extending mixture model learning using the EM-algorithm. In this extension, a difficulty arises from the fact that some crucial quantities cannot be evaluated analytically. We overcome this difficulty by introducing an effective approximation. The effectiveness of our algorithm is demonstrated by applying it to a simple synthetic component reduction task and a phoneme clustering problem.

Voice Activity Detection Based on High Order Statistics and Online EM Algorithm

COURNAPEAU, D., KAWAHARA, T. — 2008-12-19

A new online, unsupervised voice activity detection (VAD) method is proposed. The method is based on a feature derived from high-order statistics (HOS), enhanced by a second metric based on normalized autocorrelation peaks to improve its robustness to non-Gaussian noises. This feature is also oriented for discriminating between close-talk and far-field speech, thus providing a VAD method in the context of human-to-human interaction independent of the energy level. The classification is done by an online variation of the Expectation-Maximization (EM) algorithm, to track and adapt to noise variations in the speech signal. Performance of the proposed method is evaluated on an in-house data and on CENSREC-1-C, a publicly available database used for VAD in the context of automatic speech recognition (ASR). On both test sets, the proposed method outperforms a simple energy-based algorithm and is shown to be more robust against the change in speech sparsity, SNR variability and the noise type.

A Distributed Stream Multiplexing Architecture for Multi-Chip Configuration beyond HDTV

ONISHI, T., NAKAMURA, K., YOSHITOME, T., NAGANUMA, J. — 2008-12-19

This paper proposes a distributed stream multiplexing architecture for video codec LSIs with multi-chip configuration. This distributed architecture utilizes a built-in media multiplexing unit with an external stream input and inter-chip communication interfaces. Parallel protocol processing, with an autonomous inter-chip control mechanism to mix and concatenate packets through daisy-chained transfer paths, provides a complete multi-chip stream output at the end of the chain. Dispensing with external post-processing devices contributes to both high throughput and downsizing of high-end video codec systems. It is configurable for parallel encoding of super high-resolution video, multi-view/-angled HDTV vision and multiple HDTV programs. The architecture was successfully implemented in a fabricated single-chip MPEG-2 422P@HL codec LSI and utilized for the development of a super high-resolution video codec system.

Automatic Tortuosity-Based Retinopathy of Prematurity Screening System

SUKKAEW, L., UYYANONVARA, B., MAKHANOV, S. S., BARMAN, S., PANGPUTHIPONG, P. — 2008-12-19

Retinopathy of Prematurity (ROP) is an infant disease characterized by increased dilation and tortuosity of the retinal blood vessels. Automatic tortuosity evaluation from retinal digital images is very useful to facilitate an ophthalmologist in the ROP screening and to prevent childhood blindness. This paper proposes a method to automatically classify the image into tortuous and non-tortuous. The process imitates expert ophthalmologists' screening by searching for clearly tortuous vessel segments. First, a skeleton of the retinal blood vessels is extracted from the original infant retinal image using a series of morphological operators. Next, we propose to partition the blood vessels recursively using an adaptive linear interpolation scheme. Finally, the tortuosity is calculated based on the curvature of the resulting vessel segments. The retinal images are then classified into two classes using segments characterized by the highest tortuosity. For an optimal set of training parameters the prediction is as high as 100%.

Secure Handover Protocol for Mobile WiMAX Networks

LEE, S.-H., PARK, N.-S., CHOI, J.-Y. — 2008-12-19

In this paper, we analyze existing vulnerabilities in hand-over for mobile WiMAX networks. To overcome these vulnerabilities, we propose a secure handover protocol that guarantees mutual authentication and forward/backward secrecy in handover. We present a formal analysis of our protocol using a logic-based formal method.

Dual Two-Dimensional Fuzzy Class Preserving Projections for Facial Expression Recognition

ZHI, R., RUAN, Q., WU, J. — 2008-12-19

This paper proposes a novel algorithm for image feature extraction-the dual two-dimensional fuzzy class preserving projections ((2D)²FCPP). The main advantages of (2D)²FCPP over two-dimensional locality preserving projections (2DLPP) are: (1) utilizing the fuzzy assignation mechanisms to construct the weight matrix, which can improve the classification results; (2) incorporating 2DLPP and alternative 2DLPP to get a more efficient dimensionality reduction method-(2D)²LPP.

Traffic Light Detection Using Rotated Principal Component Analysis for Video-Based Car Navigation System

JOO, S.-K., KIM, Y., CHO, S. I., CHOI, K., LEE, K. — 2008-12-19

This letter presents a novel approach for traffic light detection in a video frame captured by an in-vehicle camera. The algorithm consists of rotated principal component analysis (RPCA), modified amplitude thresholding with respect to the histograms of the PC planes and final filtering with a neural network. The proposed algorithm achieves an average detection rate of 96% and is very robust to variations in the image quality.

Objective Pathological Voice Quality Assessment Based on HOS Features

LEE, J.-Y., JEONG, S., CHOI, H.-S., HAHN, M. — 2008-12-19

This work proposes new features to improve the pathological voice quality classification performance. They are the means, the variances, and the perturbations of the higher-order statistics (HOS) such as the skewness and the kurtosis. The HOS-based features show meaningful differences among normal, grade 1, grade 2, and grade 3 voices classified in the GRBAS scale. The jitter, the shimmer, the harmonic-to-noise ratio (HNR), and the variance of the short-time energy are utilized as the conventional features. The performances are measured by the classification and regression tree (CART) method. Specifically, the CART-based method by utilizing both the conventional features and the HOS-based ones shows its effectiveness in the pathological voice quality measurement, with the classification accuracy of 87.8%.

Realtime Joint Speech Coding and Transmission Algorithm for High Packet Loss Rate Wireless Channels

PENG, T., CUI, H., TANG, K., MIAO, W. — 2008-12-19

In digital speech communication over noisy high packet loss rate wireless channels, improving the overall performance of the realtime speech coding and transmission system is of great importance. A novel joint speech coding and transmission algorithm is proposed by fully exploiting the correlation between speech coding, channel coding and the transmission process. The proposed algorithm requires no algorithm delay and less bandwidth expansion while greatly enhancing the error correcting performance and the reconstructed speech quality compared with conventional algorithms. Simulations show that the residual error rate is reduced by 84.36% and the MOS (Mean Opinion Score) is improved over 38.86%.

An Iterative Joint Source-Channel (De-)Coding and (De-)Modulation Algorithm for G.729EV in Ultrashort Wave Communication

PENG, T., XU, X., CUI, H., TANG, K., MIAO, W. — 2008-12-19

Improving the overall performance of reliable speech communication in ultrashort wave radios over very noisy channels is of great importance and practical use. An iterative joint source-channel (de-)coding and (de-)modulation (JSCCM) algorithm is proposed for ITU-T Rec.G.729EV by both exploiting the residual redundancy and passing soft information throughout the receiver while introducing a systematic global iteration process. Being fully compatible with existing transmitter structure, the proposed algorithm does not introduce additional bandwidth expansion and transmission delay. Simulations show substantial error correcting performance and synthesized speech quality improvement over conventional separate designed systems in delay and bandwidth constraint channels by using the JSCCM algorithm.

Cache Optimization for H.264/AVC Motion Compensation

YOON, S., CHAE, S.-I. — 2008-12-19

In this letter, we propose a cache organization that substantially reduces the memory bandwidth of motion compensation (MC) in the H.264/AVC decoders. To reduce duplicated memory accesses to P and B pictures, we employ a four-way set-associative cache in which its index bits are composed of horizontal and vertical address bits of the frame buffer and each line stores an 8 x 2 pixel data in the reference frames. Moreover, we alleviate the data fragmentation problem by selecting its line size that equals the minimum access size of the DDR SDRAM. The bandwidth of the optimized cache averaged over five QCIF IBBP image sequences requires only 129% of the essential bandwidth of an H.264/AVC MC.

New Rotation-Invariant Texture Analysis Technique Using Radon Transform and Hidden Markov Models

JALIL, A., MANZAR, A., CHEEMA, T. A., QURESHI, I. M. — 2008-12-19

A rotation invariant texture analysis technique is proposed with a novel combination of Radon Transform (RT) and Hidden Markov Models (HMM). Features of any texture are extracted during RT which due to its inherent property captures all the directional properties of a certain texture. HMMs are used for classification purpose. One HMM is trained for each texture on its feature vector which preserves the rotational invariance of feature vector in a more compact and useful form. Once all the HMMs have been trained, testing is done by picking any of these textures at any arbitrary orientation. The best percentage of correct classification (PCC) is above 98 % carried out on sixty texture of Brodatz album.

Special Section on Knowledge, Information and Creativity Support System

Nakagawa, M., Theeramunkong, T. — 2008-11-10

Monotone Increasing Binary Similarity and Its Application to Automatic Document-Acquisition of a Category

SUZUKI, I., MIKAMI, Y., OHSATO, A. — 2008-11-10

A technique that acquires documents in the same category with a given short text is introduced. Regarding the given text as a training document, the system marks up the most similar document, or sufficiently similar documents, from among the document domain (or entire Web). The system then adds the marked documents to the training set to learn the set, and this process is repeated until no more documents are marked. Setting a monotone increasing property to the similarity as it learns enables the system to 1) detect the correct timing so that no more documents remain to be marked and to 2) decide the threshold value that the classifier uses. In addition, under the condition that the normalization process is limited to what term weights are divided by a p-norm of the weights, the linear classifier in which training documents are indexed in a binary manner is the only instance that satisfies the monotone increasing property. The feasibility of the proposed technique was confirmed through an examination of binary similarity and using English and German documents randomly selected from the Web.

Context-Aware Users' Preference Models by Integrating Real and Supposed Situation Data

2008-11-10

This paper proposes a novel approach of constructing statistical preference models for context-aware personalized applications such as recommender systems. In constructing context-aware statistical preference models, one of the most important but difficult problems is acquiring a large amount of training data in various contexts/situations. In particular, some situations require a heavy workload to set them up or to collect subjects capable of answering the inquiries under those situations. Because of this difficulty, it is usually done to simply collect a small amount of data in a real situation, or to collect a large amount of data in a supposed situation, i.e., a situation that the subject pretends that he is in the specific situation to answer inquiries. However, both approaches have problems. As for the former approach, the performance of the constructed preference model is likely to be poor because the amount of data is small. For the latter approach, the data acquired in the supposed situation may differ from that acquired in the real situation. Nevertheless, the difference has not been taken seriously in existing researches. In this paper we propose methods of obtaining a better preference model by integrating a small amount of real situation data with a large amount of supposed situation data. The methods are evaluated using data regarding food preferences. The experimental results show that the precision of the preference model can be improved significantly.

Analysis of Eye Movements and Linguistic Boundaries in a Text for the Investigation of Japanese Reading Processes

TERA, A., SHIRAI, K., YUIZONO, T., SUGIYAMA, K. — 2008-11-10

In order to investigate reading processes of Japanese language learners, we have conducted an experiment to record eye movements during Japanese text reading using an eye-tracking system. We showed that Japanese native speakers use "forward and backward jumping eye movements" frequently [13],[14]. In this paper, we analyzed further the same eye tracking data. Our goal is to examine whether Japanese learners fix their eye movements at boundaries of linguistic units such as words, phrases or clauses when they start or end "backward jumping". We consider conventional linguistic boundaries as well as boundaries empirically defined based on the entropy of the N-gram model. Another goal is to examine the relation between the entropy of the N-gram model and the depth of syntactic structures of sentences. Our analysis shows that (1) Japanese learners often fix their eyes at linguistic boundaries, (2) the average of the entropy is the greatest at the fifth depth of syntactic structures.

Mining Regular Patterns in Transactional Databases

TANBEER, S. K., AHMED, C. F., JEONG, B.-S., LEE, Y.-K. — 2008-11-10

The frequency of a pattern may not be a sufficient criterion for identifying meaningful patterns in a database. The temporal regularity of a pattern can be another key criterion for assessing the importance of a pattern in several applications. A pattern can be said regular if it appears at a regular user-defined interval in the database. Even though there have been some efforts to discover periodic patterns in time-series and sequential data, none of the existing studies have provided an appropriate method for discovering the patterns that occur regularly in a transactional database. Therefore, in this paper, we introduce a novel concept of mining regular patterns from transactional databases. We also devise an efficient tree-based data structure, called a Regular Pattern tree (RP-tree in short), that captures the database contents in a highly compact manner and enables a pattern growth-based mining technique to generate the complete set of regular patterns in a database for a user-defined regularity threshold. Our performance study shows that mining regular patterns with an RP-tree is time and memory efficient, as well as highly scalable.

Handling Dynamic Weights in Weighted Frequent Pattern Mining

AHMED, C. F., TANBEER, S. K., JEONG, B.-S., LEE, Y.-K. — 2008-11-10

Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

Entity Network Prediction Using Multitype Topic Models

SHIOZAKI, H., EGUCHI, K., OHKAWA, T. — 2008-11-10

Conveying information about who, what, when and where is a primary purpose of some genres of documents, typically news articles. Statistical models that capture dependencies between named entities and topics can play an important role. Although some relationships between who and where should be mentioned in such a document, no statistical topic models explicitly address in handling such information the textual interactions between a who-entity and a where-entity. This paper presents a statistical model that directly captures the dependencies between an arbitrary number of word types, such as who-entities, where-entities and topics, mentioned in each document. We show that this multitype topic model performs better at making predictions on entity networks, in which each vertex represents an entity and each edge weight represents how a pair of entities at the incident vertices is closely related, through our experiments on predictions of who-entities and links between them. We also demonstrate the scale-free property in the weighted networks of entities extracted from written mentions.

Anchored Map: Graph Drawing Technique to Support Network Mining

MISUE, K. — 2008-11-10

Because network diagrams drawn using the spring embedder are not easy to read, this paper proposes the use of "anchored maps" in which some nodes are fixed as anchors. The readability of network diagrams is discussed, anchored maps are proposed, and a method for drawing anchored maps is explained. The method uses indices to decide the orders of anchors because those orders markedly affect the readability of the network diagrams. Examples showing the effectiveness of the anchored maps are also shown.

An Evaluation System for End-User Computing Capability in a Computing Business Environment

YOON, C. Y. — 2008-11-10

We describe an evaluation system consisting of an evaluation and interpretation model to totally assess and interpret an end-user's computing capability. It includes four evaluation factors and eighteen items, the complex indicators, an evaluation process, and method. We verified the model construct was verified by factor analysis and reliability analysis through a pilot test. We confirmed the application of the developed system by applying the model to evaluating end-users in a computing business environment and presenting the results. This system contributes to developing a practical system for evaluating an end-user's computing capability and hence for improving computing capability of end-users.

combiSQORE: A Combinative-Ontology Retrieval System for Next Generation Semantic Web Applications

UNGRANGSI, R., ANUTARIYA, C., WUWONGSE, V. — 2008-11-10

In order to timely response to a user query at run-time, next generation Semantic Web applications demand a robust mechanism to dynamically select one or more existing ontologies available on the Web and combine them automatically if needed. Although existing ontology retrieval systems return a lengthy list of resultant ontologies, they cannot identify which ones can completely meet the query requirements nor determine a minimum set of resultant ontologies that can jointly satisfy the requirements if no single ontology is available to satisfy them. Therefore, this paper presents an ontology retrieval system, namely combiSQORE, which can return single or combinative ontologies that completely satisfy a submitted query when the available ontology database is adequate to answer such query. In addition, the proposed system ranks the returned results based on their semantic similarities to the given query and their modification (integration) costs. The experimental results show that combiSQORE system yields practical combinative ontologies and useful rankings.

Novel Topic Maps to RDF/RDF Schema Translation Method

SHIN, S., JEONG, D., BAIK, D.-K. — 2008-11-10

We propose an enhanced method for translating Topic Maps to RDF/RDF Schema, to realize the Semantic Web. A critical issue for the Semantic Web is to efficiently and precisely describe Web information resources, i.e., Web metadata. Two representative standards, Topic Maps and RDF have been used for Web metadata. RDF-based standardization and implementation of the Semantic Web have been actively performed. Since the Semantic Web must accept and understand all Web information resources that are represented with the other methods, Topic Maps-to-RDF translation has become an issue. Even though many Topic Maps to RDF translation methods have been devised, they still have several problems (e.g. semantic loss, complex expression, etc.). Our translation method provides an improved solution to these problems. This method shows lower semantic loss than the previous methods due to extract both explicit semantics and implicit semantics. Compared to the previous methods, our method reduces the encoding complexity of resulting RDF. In addition, in terms of reversibility, the proposed method regenerates all Topic Maps constructs in an original source when is reverse translated.

Assisting Pictogram Selection with Categorized Semantics

CHO, H., ISHIDA, T., OYAMA, S., INABA, R., TAKASAKI, T. — 2008-11-10

Since participants at both end of the communication channel must share common pictogram interpretation to communicate, the pictogram selection task must consider both participants' pictogram interpretations. Pictogram interpretation, however, can be ambiguous. To assist the selection of pictograms more likely to be interpreted as intended, we propose a categorical semantic relevance measure which calculates how relevant a pictogram is to a given interpretation in terms of a given category. The proposed measure defines similarity measurement and probability of interpretation words using pictogram interpretations and frequencies gathered from a web survey. Moreover, the proposed measure is applied to categorized pictogram interpretations to enhance pictogram retrieval performance. Five pictogram categories used for categorizing pictogram interpretations are defined based on the five first-level classifications defined in the Concept Dictionary of the EDR Electronic Dictionary. Retrieval performances among not-categorized interpretations, categorized interpretations, and categorized and weighted interpretations using semantic relevance measure were compared, and the categorized semantic relevance approaches showed more stable performances than the not-categorized approach.

Pen-Based Interface Using Hand Motions in the Air

SUZUKI, Y., MISUE, K., TANAKA, J. — 2008-11-10

A system which employs a stylus as an input device is suitable for creative activities like writing and painting. However, such a system does not always provide the user with a GUI that is easy to operate using the stylus. In addition, system usability is diminished because the stylus is not always integrated into the system in a way that takes into consideration the features of a pen. The purpose of our research is to improve the usability of a system which uses a stylus as an input device. We propose shortcut actions, which are interaction techniques for operation with a stylus that are controlled through a user's hand motions made in the air. We developed the Context Sensitive Stylus as a device to implement the shortcut actions. The Context Sensitive Stylus consists of an accelerometer and a conventional stylus. We also developed application programs to which we applied the shortcut actions; e.g., a drawing tool, a scroll supporting tool, and so on. Results from our evaluation of the shortcut actions indicate that users can concentrate better on their work when using the shortcut actions than when using conventional menu operations.

A Retargetable Compiler Based on Graph Representation for Dynamically Reconfigurable Processor Arrays

TUNBUNHENG, V., AMANO, H. — 2008-11-10

For developing design environment of various Dynamically Reconfigurable Processor Arrays (DRPAs), the Graph with Configuration Information (GCI) is proposed to represent configurable resource in the target dynamically reconfigurable architecture. The functional unit, constant unit, register, and routing resource can be represented in the graph as well as the configuration information. The restriction in the hardware is also added in the graph by limiting the possible configuration at a node controlled by the other node. A prototype compiler called Black-Diamond with GCI is now available for three different DRPAs. It translates data-flow graph from C-like front-end description, applies placement and routing by using the GCI, and generates configuration data for each element of the DRPA. Evaluation results of simple applications show that Black-Diamond can generate reasonable designs for all three different architectures. Other target architectures can be easily treated by representing many aspects of architectural property into a GCI.

Non-recursive Discrete Periodized Wavelet Transform Using Segment Accumulation Algorithm and Reversible Round-Off Approach

TSAI, C.-F., WANG, H.-S., HUNG, K.-C., HSIA, S.-C. — 2008-11-10

Wavelet-based features with simplicity and high efficacy have been used in many pattern recognition (PR) applications. These features are usually generated from the wavelet coefficients of coarse levels (i.e., high octaves) in the discrete periodized wavelet transform (DPWT). In this paper, a new 1-D non-recursive DPWT (NRDPWT) is presented for real-time high octave decomposition. The new 1-D NRDPWT referred to as the 1-D RRO-NRDPWT can overcome the word-length-growth (WLG) effect based on two strategies, resisting error propagation and applying a reversible round-off linear transformation (RROLT) theorem. Finite precision performance analysis is also taken to study the word length suppression efficiency and the feature efficacy in breast lesion classification on ultrasonic images. For the realization of high octave decomposition, a segment accumulation algorithm (SAA) is also presented. The SAA is a new folding technique that can reduce multipliers and adders dramatically without the cost of increasing latency.

Configuration Sharing to Reduce Reconfiguration Overhead Using Static Partial Reconfiguration

JUNG, S., KIM, T. G. — 2008-11-10

Reconfigurable architectures are one of the most promising solutions satisfying both performance and flexibility. However, reconfiguration overhead in those architectures makes them inappropriate for repetitive reconfigurations. In this paper, we introduce a configuration sharing technique to reduce reconfiguration overhead between similar applications using static partial reconfiguration. Compared to the traditional resource sharing that configures multiple temporal partitions simultaneously and employs a time-multiplexing technique, the proposed configuration sharing reconfigures a device incrementally as an application changes and requires a backend adaptation to reuse configurations between applications. Adopting a data-flow intermediate representation, our compiler framework extends a min-cut placer and a negotiation-based router to deal with the configuration sharing. The results report that the framework could reduce 20% of configuration time at the expense of 1.9% of computation time on average.

Contract Specification in Java: Classification, Characterization, and a New Marker Method

CHEN, C.-T., CHENG, Y. C., HSIEH, C.-Y. — 2008-11-10

Design by Contract (DBC), originated in the Eiffel programming language, is generally accepted as a practical method for building reliable software. Currently, however, few languages have built-in support for it. In recent years, several methods have been proposed to support DBC in Java. We compare eleven DBC tools for Java by analyzing their impact on the developer's programming activities, which are characterized by seven quality attributes identified in this paper. It is shown that each of the existing tools fails to achieve some of the quality attributes. This motivates us to develop ezContract, an open source DBC tool for Java that achieves all of the seven quality attributes. ezContract achieves streamlined integration with the working environment. Notably, standard Java language is used and advanced IDE features that work for standard Java programs can also work for the contract-enabled programs. Such features include incremental compilation, automatic refactoring, and code assist.

A Fully Consistent Hidden Semi-Markov Model-Based Speech Recognition System

OURA, K., ZEN, H., NANKAKU, Y., LEE, A., TOKUDA, K. — 2008-11-10

In a hidden Markov model (HMM), state duration probabilities decrease exponentially with time, which fails to adequately represent the temporal structure of speech. One of the solutions to this problem is integrating state duration probability distributions explicitly into the HMM. This form is known as a hidden semi-Markov model (HSMM). However, though a number of attempts to use HSMMs in speech recognition systems have been proposed, they are not consistent because various approximations were used in both training and decoding. By avoiding these approximations using a generalized forward-backward algorithm, a context-dependent duration modeling technique and weighted finite-state transducers (WFSTs), we construct a fully consistent HSMM-based speech recognition system. In a speaker-dependent continuous speech recognition experiment, our system achieved about 9.1% relative error reduction over the corresponding HMM-based system.

Fast Image Mosaicing Based on Histograms

MORI, A., UCHIDA, S. — 2008-11-10

This paper introduces a fast image mosaicing technique that does not require costly search on image domain (e.g., pixel-to-pixel correspondence search on the image domain) and the iterative optimization (e.g., gradient-based optimization, iterative optimization, and random optimization) of geometric transformation parameter. The proposed technique is organized in a two-step manner. At both steps, histograms are fully utilized for high computational efficiency. At the first step, a histogram of pixel feature values is utilized to detect pairs of pixels with the same rare feature values as candidates of corresponding pixel pairs. At the second step, a histogram of transformation parameter values is utilized to determine the most reliable transformation parameter value. Experimental results showed that the proposed technique can provide reasonable mosaicing results in most cases with very feasible computations.

A Flexible Video CODEC System for Super High Resolution Video

YOSHITOME, T., NAKAMURA, K., NAGANUMA, J., YASHIMA, Y. — 2008-11-10

We propose a flexible video CODEC system for super-high-resolution videos such as those utilizing 4k x 2k pixel. It uses the spatially parallel encoding approach and has sufficient scalability for the target video resolution to be encoded. A video shift and padding function has been introduced to prevent the image quality from being degraded when different active line systems are connected. The switchable cascade multiplexing function of our system enables various super-high-resolutions to be encoded and super-high-resolution video streams to be recorded and played back using a conventional PC. A two-stage encoding method using the complexity of each divided image has been introduced to equalize encoding quality among multiple divided videos. System Time Clock (STC) sharing has also been implemented in this CODEC system to absorb the disparity in the times streams are received between channels. These functions enable highly-efficient, high-quality encoding for super-high-resolution video.

3D Triangular Mesh Parameterization with Semantic Features Based on Competitive Learning Methods

MATSUI, S., AOKI, K., NAGAHASHI, H. — 2008-11-10

In 3D computer graphics, mesh parameterization is a key technique for digital geometry processings such as morphing, shape blending, texture mapping, re-meshing and so on. Most of the previous approaches made use of an identical primitive domain to parameterize a mesh model. In recent works of mesh parameterization, more flexible and attractive methods that can create direct mappings between two meshes have been reported. These mappings are called "cross-parameterization" and typically preserve semantic feature correspondences between target meshes. This paper proposes a novel approach for parameterizing a mesh into another one directly. The main idea of our method is to combine a competitive learning and a least-square mesh techniques. It is enough to give some semantic feature correspondences between target meshes, even if they are in different shapes or in different poses.

Continuous Range Query Processing over Moving Objects

PARK, Y. H., BOK, K. S., YOO, J. S. — 2008-11-10

In this paper, we propose a continuous range query processing method over moving objects. To efficiently process continuous range queries, we design a main-memory-based query index that uses smaller storage and significantly reduces the query processing time. We show through performance evaluation that the proposed method outperforms the existing methods.

Full-Index-Embedding Patchwork Algorithm for Audio Watermarking

KANG, H., YAMAGUCHI, K., KURKOSKI, B., YAMAGUCHI, K., KOBAYASHI, K. — 2008-11-10

For the digital watermarking patchwork algorithm originally given by Bender et al., this paper proposes two improvements applicable to audio watermarking. First, the watermark embedding strength is psychoacoustically adapted, using the Bark frequency scale. Second, whereas previous approaches leave the samples that do not correspond to the data untouched, in this paper, these are modified to reduce the probability of misdetection, a method called full index embedding. In simulations, the proposed combination of these two proposed methods has higher resistance to a variety of attacks than prior algorithms.

Japanese 45 Single Sounds Recognition Using Intraoral Shape

SAITOH, T., KONISHI, R. — 2008-11-10

This paper describes a recognition method of Japanese single sounds for application to lip reading. Related researches investigated only five or ten sounds. In this paper, experiments were conducted for 45 Japanese single sounds by classifying them into five vowels category, ten consonants category, and 45 sounds category. We obtained recognition rates of 94.7, 30.9 and 30.0% with trajectory feature.

Robust Speaker Clustering Using Affinity Propagation

ZHANG, X., LU, P., SUO, H., ZHAO, Q., YAN, Y. — 2008-11-10

In this letter, a recently proposed clustering algorithm named affinity propagation is introduced for the task of speaker clustering. This novel algorithm exhibits fast execution speed and finds clusters with low error. However, experiments show that the speaker purity of affinity propagation is not satisfying. Thus, we propose a hybrid approach that combines affinity propagation with agglomerative hierarchical clustering to improve the clustering performance. Experiments show that compared with traditional agglomerative hierarchical clustering, the hybrid method achieves better performance on the test corpora.

An OFDM-Based Speech Encryption System without Residual Intelligibility

TSENG, D.-C., CHIU, J.-H. — 2008-11-10

Since an FFT-based speech encryption system retains a considerable residual intelligibility, such as talk spurts and the original intonation in the encrypted speech, this makes it easy for eavesdroppers to deduce the information contents from the encrypted speech. In this letter, we propose a new technique based on the combination of an orthogonal frequency division multiplexing (OFDM) scheme and an appropriate QAM mapping method to remove the residual intelligibility from the encrypted speech by permuting several frequency components. In addition, the proposed OFDM-based speech encryption system needs only two FFT operations instead of the four required by the FFT-based speech encryption system. Simulation results are presented to show the effectiveness of this proposed technique.

Utterance Verification Using Word Voiceprint Models Based on Probabilistic Distributions of Phone-Level Log-Likelihood Ratio and Phone Duration

KWON, S.-B., KIM, H. — 2008-11-10

This paper suggests word voiceprint models to verify the recognition results obtained from a speech recognition system. Word voiceprint models have word-dependent information based on the distributions of phone-level log-likelihood ratio and duration. Thus, we can obtain a more reliable confidence score for a recognized word by using its word voiceprint models that represent the more proper characteristics of utterance verification for the word. Additionally, when obtaining a log-likelihood ratio-based word voiceprint score, this paper proposes a new log-scale normalization function using the distribution of the phone-level log-likelihood ratio, instead of the sigmoid function widely used in obtaining a phone-level log-likelihood ratio. This function plays a role of emphasizing a mis-recognized phone in a word. This individual information of a word is used to help achieve a more discriminative score against out-of-vocabulary words. The proposed method requires additional memory, but it shows that the relative reduction in equal error rate is 16.9% compared to the baseline system using simple phone log-likelihood ratios.

Histogram Equalization-Based Thresholding

KWON, S. H., JEONG, H. C., SEO, S. T., LEE, I. K., SON, C. S. — 2008-11-10

The thresholding results for gray level images depend greatly on the thresholding method applied. However, this letter proposes a histogram equalization-based thresholding algorithm that makes the thresholding results insensitive to the thresholding method applied. Experimental results are presented to demonstrate the effectiveness of the proposed thresholding algorithm.

Scheduling Parallel Tasks with Communication Overhead in an Environment with Multiple Machines

LIN, J.-F. — 2008-10-10

This paper investigates the problem of nonpreemptively scheduling independent parallel tasks in an environment with multiple machines, which is motivated from the recent studies in scheduling tasks in a multi-machine environment. In this scheduling environment, each machine contains a number of identical processors and each parallel task can simultaneously require a number of processors for its processing in any single machine. Whenever tasks are processed in parallel in a parallel machine, message communication among processors is often inevitable. The problem of finding a shortest schedule length on scheduling independent parallel tasks with the consideration of communication overhead in a multi-machine environment is NP-hard. The aim of this paper is to propose a heuristic algorithm for this kind of problem and to analyze the performance bound of this heuristic algorithm.

Memory Allocation for Multi-Resolution Image Processing

KOBAYASHI, Y., HARIYAMA, M., KAMEYAMA, M. — 2008-10-10

Hierarchical approaches using multi-resolution images are well-known techniques to reduce the computational amount without degrading quality. One major issue in designing image processors is to design a memory system that supports parallel access with a simple interconnection network. The complexity of the interconnection network mainly depends on memory allocation; it maps pixels onto memory modules and determines the required number of memory modules. This paper presents a memory allocation method to minimize the number of memory modules for image processing using multi-resolution images. For efficient search, the proposed method exploits the regularity of window-type image processing. A practical example demonstrates that the number of memory modules is reduced to less than 14% that of conventional methods.

kP2PADM: An In-Kernel Architecture of P2P Management Gateway

LIN, Y.-D., LIN, P.-C., TSAI, M.-F., CHANG, T.-J., LAI, Y.-C. — 2008-10-10

Managing increasing traffic from Instant Messengers and P2P applications is becoming more important nowadays. We present an in-kernel architecture of management gateway, namely kP2PADM, built upon open-source packages with several modifications and design techniques. First, the in-kernel design streamlines the data path through the gateway. Second, the dual-queue buffer eliminates head-of-line blocking for multiple connections. Third, a connection cache reduces useless reconnection attempts from the peers. Fourth, a fast-pass mechanism avoids slowing down the TCP transmission. The in-kernel design approximately doubles the throughput of the design in the user space. The internal benchmarks also analyze the impact of each function on performance.

Finding Frequent Closed Itemsets in Sliding Window in Linear Time

CHEN, J., ZHOU, B., CHEN, L., WANG, X., DING, Y. — 2008-10-10

One of the most well-studied problems in data mining is computing the collection of frequent itemsets in large transactional databases. Since the introduction of the famous Apriori algorithm [14], many others have been proposed to find the frequent itemsets. Among such algorithms, the approach of mining closed itemsets has raised much interest in data mining community. The algorithms taking this approach include TITANIC [8], CLOSET+ [6], DCI-Closed [4], FCI-Stream [3], GC-Tree [15], TGC-Tree [16] etc. Among these algorithms, FCI-Stream, GC-Tree and TGC-Tree are online algorithms work under sliding window environments. By the performance evaluation in [16], GC-Tree [15] is the fastest one. In this paper, an improved algorithm based on GC-Tree is proposed, the computational complexity of which is proved to be a linear combination of the average transaction size and the average closed itemset size. The algorithm is based on the essential theorem presented in Sect. 4.2. Empirically, the new algorithm is several orders of magnitude faster than the state of art algorithm, GC-Tree.

An Energy-Aware Multipath Routing Algorithm in Wireless Sensor Networks

KIM, M., JEONG, E., BANG, Y.-C., HWANG, S., SHIN, C., JIN, G.-J., KIM, B. — 2008-10-10

One of the major challenges facing the design of a routing protocol for Wireless Sensor Networks (WSNs) is to find the most reliable path between the source and sink node. Furthermore, a routing protocol for WSN should be well aware of sensor limitations. In this paper, we present an energy efficient, scalable, and distributed node disjoint multipath routing algorithm. The proposed algorithm, the Energy-aware Multipath Routing Algorithm (EMRA), adjusts traffic flows via a novel load balancing scheme. EMRA has a higher average node energy efficiency, lower control overhead, and a shorter average delay than those of well-known previous works. Moreover, since EMRA takes into consideration network reliability, it is useful for delivering data in unreliable environments.

A Multi-Code Compression Scheme for Test Time Reduction of System-on-Chip Designs

SHIEH, H.-M., LI, J.-F. — 2008-10-10

With the nano-scale technology, an system-on-chip (SOC) design may consist of many reusable cores from multiple sources. This causes that the complexity of SOC testing is much higher than that of conventional VLSI chip testing. One of the SOC test challenges is the test data reduction. This paper presents a multi-code compression (MCC) technique to reduce the volume of test data and the test application time. A multi-code decompressor for recovering the compressed test data is also proposed. Experimental results show that the MCC scheme can achieve higher compression ratio than single-code compression schemes. The area cost of the proposed multi-code decompressor is small—only about 3498µm² based on TSMC 0.18µm standard cell technology.

Dependability Improvement for PPM Compressed Data by Using Compression Pattern Matching

KITAKAMI, M., OKURA, T. — 2008-10-10

Data compression is popularly applied to computer systems and communication systems in order to reduce storage size and communication time, respectively. Since large data are used frequently, string matching for such data takes a long time. If the data are compressed, the time gets much longer because decompression is necessary. Long string matching time makes computer virus scan time longer and gives serious influence to the security of data. From this, CPM (Compression Pattern Matching) methods for several compression methods have been proposed. This paper proposes CPM method for PPM which achieves fast virus scan and improves dependability of the compressed data, where PPM is based on a Markov model, uses a context information, and achieves a better compression ratio than BW transform and Ziv-Lempel coding. The proposed method encodes the context information, which is generated in the compression process, and appends the encoded data at the beginning of the compressed data as a header. The proposed method uses only the header information. Computer simulation says that augmentation of the compression ratio is less than 5 percent if the order of the PPM is less than 5 and the source file size is more than 1 M bytes, where order is the maximum length of the context used in PPM compression. String matching time is independent of the source file size and is very short, less than 0.3 micro seconds in the PC used for the simulation.

Thermal-Aware Test Access Mechanism and Wrapper Design Optimization for System-on-Chips

YU, T. E., YONEDA, T., CHAKRABARTY, K., FUJIWARA, H. — 2008-10-10

Rapid advances in semiconductor manufacturing technology have led to higher chip power densities, which places greater emphasis on packaging and temperature control during testing. For system-on-chips, peak power-based scheduling algorithms have been used to optimize tests under specified power constraints. However, imposing power constraints does not always solve the problem of overheating due to the non-uniform distribution of power across the chip. This paper presents a TAM/Wrapper co-design methodology for system-on-chips that ensures thermal safety while still optimizing the test schedule. The method combines a simplified thermal-cost model with a traditional bin-packing algorithm to minimize test time while satisfying temperature constraints. Furthermore, for temperature checking, thermal simulation is done using cycle-accurate power profiles for more realistic results. Experiments show that even a minimal sacrifice in test time can yield a considerable decrease in test temperature as well as the possibility of further lowering temperatures beyond those achieved using traditional power-based test scheduling.

Access Control Management for SCADA Systems

HONG, S.-P., AHN, G.-J., XU, W. — 2008-10-10

The information technology revolution has transformed all aspects of our society including critical infrastructures and led a significant shift from their old and disparate business models based on proprietary and legacy environments to more open and consolidated ones. Supervisory Control and Data Acquisition (SCADA) systems have been widely used not only for industrial processes but also for some experimental facilities. Due to the nature of open environments, managing SCADA systems should meet various security requirements since system administrators need to deal with a large number of entities and functions involved in critical infrastructures. In this paper, we identify necessary access control requirements in SCADA systems and articulate access control policies for the simulated SCADA systems. We also attempt to analyze and realize those requirements and policies in the context of role-based access control that is suitable for simplifying administrative tasks in large scale enterprises.

A Method for Recognizing Noisy Romanized Japanese Words in Learner English

NAGATA, R., KAKEGAWA, J.-i., SUGIMOTO, H., YABUTA, Y. — 2008-10-10

This paper describes a method for recognizing romanized Japanese words in learner English. They become noise and problematic in a variety of systems and tools for language learning and teaching including text analysis, spell checking, and grammatical error detection because they are Japanese words and thus mostly unknown to such systems and tools. A problem one encounters when recognizing romanized Japanese words in learner English is that the spelling rules of romanized Japanese words are often violated. To address this problem, the described method uses a clustering algorithm reinforced by a small set of rules. Experiments show that it achieves an F-measure of 0.879 and outperforms other methods. They also show that it only requires the target text and an English word list of reasonable size.

Shape-Direction-Adaptive Lifting-Based Discrete Wavelet Transform for Arbitrarily Shaped Segments in Image Compression

LIN, S.-F., SU, C.-K. — 2008-10-10

In this paper, a new lifting-based shape-direction-adaptive discrete wavelet transform (SDA-DWT) which can be used for arbitrarily shaped segments is proposed. The SDA-DWT contains three major techniques: the lifting-based DWT, the adaptive directional technique, and the concept of object-based compression in MPEG-4. With SDA-DWT, the number of transformed coefficients is equal to the number of pixels in the arbitrarily shaped segment image, and the spatial correlation across subbands is well preserved. SDA-DWT also can locally adapt its filtering directions according to the texture orientations to improve energy compaction for images containing non-horizontal or non-vertical edge textures. SDA-DWT can be applied to any application that is wavelet based and the lifting technique provides much flexibility for hardware implementation. Experimental results show that, for still object images with rich orientation textures, SDA-DWT outperforms SA-DWT up to 5.88 dB in PSNR under 2.15-bpp (bit / object pixel) condition, and reduces the bit-budget up to 28.5% for lossless compression. SDA-DWT also outperforms DA-DWT up to 5.44 dB in PSNR under 3.28-bpp condition, and reduces the bit-budget up to 14.0%.

A Two-Stage Point Pattern Matching Algorithm Using Ellipse Fitting and Dual Hilbert Scans

TIAN, L., KAMATA, S.-i. — 2008-10-10

Point Pattern Matching (PPM) is an essential problem in many image analysis and computer vision tasks. This paper presents a two-stage algorithm for PPM problem using ellipse fitting and dual Hilbert scans. In the first matching stage, transformation parameters are coarsely estimated by using four node points of ellipses which are fitted by Weighted Least Square Fitting (WLSF). Then, Hilbert scans are used in two aspects of the second matching stage: it is applied to the similarity measure and it is also used for search space reduction. The similarity measure named Hilbert Scanning Distance (HSD) can be computed fast by converting the 2-D coordinates of 2-D points into 1-D space information using Hilbert scan. On the other hand, the N-D search space can be converted to a 1-D search space sequence by N-D Hilbert Scan and an efficient search strategy is proposed on the 1-D search space sequence. In the experiments, we use both simulated point set data and real fingerprint images to evaluate the performance of our algorithm, and our algorithm gives satisfying results both in accuracy and efficiency.

Effective Acoustic Modeling for Pronunciation Quality Scoring of Strongly Accented Mandarin Speech

GE, F., LIU, C., SHAO, J., PAN, F., DONG, B., YAN, Y. — 2008-10-10

In this paper we present our investigation into improving the performance of our computer-assisted language learning (CALL) system through exploiting the acoustic model and features within the speech recognition framework. First, to alleviate channel distortion, speaker-dependent cepstrum mean normalization (CMN) is adopted and the average correlation coefficient (average CC) between machine and expert scores is improved from 78.00% to 84.14%. Second, heteroscedastic linear discriminant analysis (HLDA) is adopted to enhance the discriminability of the acoustic model, which successfully increases the average CC from 84.14% to 84.62%. Additionally, HLDA causes the scoring accuracy to be more stable at various pronunciation proficiency levels, and thus leads to an increase in the speaker correct-rank rate from 85.59% to 90.99%. Finally, we use maximum a posteriori (MAP) estimation to tune the acoustic model to fit strongly accented test speech. As a result, the average CC is improved from 84.62% to 86.57%. These three novel techniques improve the accuracy of evaluating pronunciation quality.

Skin Color Segmentation Using Coarse-to-Fine Region on Normalized RGB Chromaticity Diagram for Face Detection

SOETEDJO, A., YAMADA, K. — 2008-10-10

This paper describes a new color segmentation based on a normalized RGB chromaticity diagram for face detection. Face skin is extracted from color images using a coarse skin region with fixed boundaries followed by a fine skin region with variable boundaries. Two newly developed histograms that have prominent peaks of skin color and non-skin colors are employed to adjust the boundaries of the skin region. The proposed approach does not need a skin color model, which depends on a specific camera parameter and is usually limited to a particular environment condition, and no sample images are required. The experimental results using color face images of various races under varying lighting conditions and complex backgrounds, obtained from four different resources on the Internet, show a high detection rate of 87%. The results of the detection rate and computation time are comparable to the well known real-time face detection method proposed by Viola-Jones [11],[12].

Enhanced Hand Manipulation Methods for Efficient and Precise Positioning and Release of Virtual Objects

OSAWA, N. — 2008-10-10

Automatic adjustment methods for efficient, precise positioning and release of a virtual 3D object by direct hand manipulation in an immersive virtual reality environment are described and evaluated. The proposed methods are release adjustment, position adjustment, viewpoint adjustment, and virtual hand size adjustment. Combining these methods enables users to manipulate a virtual object efficiently and precisely. An experimental evaluation showed that these methods were effective and useful in terms of the number of task completions and the subjective preference, particularly for a small virtual target.

Some Results on Primitive Words, Square-Free Words, and Disjunctive Languages

MORIYA, T. — 2008-10-10

In this paper, we give some resuts on primitive words, square-free words and disjunctive languages. We show that for a word u ⁺, every element of (cp(u)) is d-primitive iff it is square-free, where cp(u) is the set of all cyclic-permutations of u, and (cp(u)) is the set of all primitive roots of it. Next we show that p^m qⁿ is a primitive word for every n, m ≥ 1 and primitive words p, q, under the condition that |p| = |q| and (m, n) != (1, 1). We also give a condition of disjunctiveness for a language.

Complexity Oscillations in Random Reals

LIU, C., TANAKA, K. — 2008-10-10

The C-oscillation due to Martin-Löf shows that {| n [C( n) ≥ n – O(1)]} = , which also follows {| n [K( n) ≥ n + K(n) – O(1)]} = . By generalizing them, we show that there does not exist a real such that n (K( n) ≥ n + K(n) – O(1)) for any > 0.

Design and Implementation of a Non-pipelined MD5 Hardware Architecture Using a New Functional Description

ALGREDO-BADILLO, I., FEREGRINO-URIBE, C., CUMPLIDO, R., MORALES-SANDOVAL, M. — 2008-10-10

MD5 is a cryptographic algorithm used for authentication. When implemented in hardware, the performance is affected by the data dependency of the iterative compression function. In this paper, a new functional description is proposed with the aim of achieving higher throughput by mean of reducing the critical path and latency. This description can be used in similar structures of other hash algorithms, such as SHA-1, SHA-2 and RIPEMD-160, which have comparable data dependence. The proposed MD5 hardware architecture achieves a high throughput/area ratio, results of implementation in an FPGA are presented and discussed, as well as comparisons against related works.

Delay Analysis of Car-to-Car Reliable Data Delivery Strategies Based on Data Mulling with Network Coding

PARK, J.-S., LEE, U., OH, S. Y., GERLA, M., LUN, D. S., RO, W. W., PARK, J. — 2008-10-10

Vehicular ad hoc networks (VANET) aims to enhance vehicle navigation safety by providing an early warning system: any chance of accidents is informed through the wireless communication between vehicles. For the warning system to work, it is crucial that safety messages be reliably delivered to the target vehicles in a timely manner and thus reliable and timely data dissemination service is the key building block of VANET. Data mulling technique combined with three strategies, network codeing, erasure coding and repetition coding, is proposed for the reliable and timely data dissemination service. Particularly, vehicles in the opposite direction on a highway are exploited as data mules, mobile nodes physically delivering data to destinations, to overcome intermittent network connectivity cause by sparse vehicle traffic. Using analytic models, we show that in such a highway data mulling scenario the network coding based strategy outperforms erasure coding and repetition based strategies.

Masking Property Based Residual Acoustic Echo Cancellation for Hands-Free Communication in Automobile Environment

LEE, Y., JEONG, S., KO, H. — 2008-10-10

A residual acoustic echo cancellation method that employs the masking property is proposed to enhance the speech quality of hands-free communication devices in an automobile environment. The conventional masking property is employed for speech enhancement using the masking threshold of the desired clean speech signal. In this Letter, either the near-end speech or residual noise is selected as the desired signal according to the double-talk detector. Then, the residual echo signal is masked by the desired signal (masker). Experiments confirm the effectiveness of the proposed method by deriving the echo return loss enhancement and by examining speech waveforms and spectrograms.

Switching Search Method for Pulse Assignment in ITU-T G.729D

CHEN, F.-K., TSAI, Y.-R. — 2008-10-10

In this paper, the simplified search designs for the stochastic codebook of algebraic code excited linear prediction (ACELP) for ITU-T G.729D speech coder are proposed. By using two search rounds and limiting the search range, the computational complexity of the proposed approach is only 6.25% of the full search method recommended by G.729D. In addition, the computational complexity of proposed approach is only 59% of the global pulse replacement search method recommended by G.729.1. Simulation results show that the coded speech quality evaluated by using the standard subjective and objective quality measurements is with perceptually negligible degradation.

Text-Independent Speaker Verification Using Artificially Generated GMMs for Cohorts

MUKAI, Y., NODA, H., NIIMI, M., OSANAI, T. — 2008-10-10

This paper presents a text-independent speaker verification method using Gaussian mixture models (GMMs), where only utterances of enrolled speakers are required. Artificial cohorts are used instead of those from speaker databases, and GMMs for artificial cohorts are generated by changing model parameters of the GMM for a claimed speaker. Equal error rates by the proposed method are about 60% less than those by a conventional method which also uses only utterances of enrolled speakers.