In this letter, we propose a set of Space-Time Block Codes (STBC) equipped with 4 transmit antennas to transmit one additional information bit achieving rate-9/8. To maintain full rank property of the coding gain matrix, one new orthogonal STBC code with full rate is proposed in this letter. Simulation results show that this method achieves good bit error rate (BER) performance with a small gap compared to that of the rate-1 case and throughput in the high SNR region.

We present a simple technique for enhancing multi-modal images. The unsharp masking (UM) is at first nonlinearized to prevent halos around large edges. This edge-preserving UM is then extended to cross-sharpening of multi-modal images where a component image is sharpened with the aid of more clear edges in another component image.

This paper proposes Bayesian context clustering using cross validation for hidden Markov model (HMM) based speech recognition. The Bayesian approach is a statistical technique for estimating reliable predictive distributions by treating model parameters as random variables. The variational Bayesian method, which is widely used as an efficient approximation of the Bayesian approach, has been applied to HMM-based speech recognition, and it shows good performance. Moreover, the Bayesian approach can select an appropriate model structure while taking account of the amount of training data. Since prior distributions which represent prior information about model parameters affect estimation of the posterior distributions and selection of model structure (e.g., decision tree based context clustering), the determination of prior distributions is an important problem. However, it has not been thoroughly investigated in speech recognition, and the determination technique of prior distributions has not performed well. The proposed method can determine reliable prior distributions without any tuning parameters and select an appropriate model structure while taking account of the amount of training data. Continuous phoneme recognition experiments show that the proposed method achieved a higher performance than the conventional methods.

A new kind of 3D power divider based on a half-mode substrate integrated circular cavity (HSICC) is proposed. This novel power divider can reduce the size of a power divider based on normal substrate integrated circular cavity (SICC) by nearly a half. To verify the validity of the design method, a two-way X-band HSICC power divider using low temperature co-fired ceramic (LTCC) technology is designed, fabricated and measured.

This paper proposes an efficient combination of state likelihood recycling and batch state likelihood calculation for accelerating acoustic likelihood calculation in an HMM-based speech recognizer. Recycling and batch calculation are each based on different technical approaches, i.e. the former is a purely algorithmic technique while the latter fully exploits computer architecture. To accelerate the recognition process further by combining them efficiently, we introduce conditional fast processing and acoustic backing-off. Conditional fast processing is based on two criteria. The first potential activity criterion is used to control not only the recycling of state likelihoods at the current frame but also the precalculation of state likelihoods for several succeeding frames. The second reliability criterion and acoustic backing-off are used to control the choice of recycled or batch calculated state likelihoods when they are contradictory in the combination and to prevent word accuracies from degrading. Large vocabulary spontaneous speech recognition experiments using four different CPU machines under two environmental conditions showed that, compared with the baseline recognizer, recycling and batch calculation, our combined acceleration technique further reduced both of the acoustic likelihood calculation time and the total recognition time. We also performed detailed analyses to reveal each technique's acceleration and environmental dependency mechanisms by classifying types of state likelihoods and counting each of them. The analysis results comfirmed the effectiveness of the combined acceleration technique.

In this paper, we propose a novel stakeholder mining mechanism for analyzing bias in news articles by comparing descriptions of stakeholders. Our mechanism is based on the presumption that interests often induce bias of news agencies. As we use the term, a "stakeholder" is a participant in an event described in a news article who should have some relationships with other participants in the article. Our approach attempts to elucidate bias of articles from three aspects: stakeholders, interests of stakeholders, and the descriptive polarity of each stakeholder. Mining of stakeholders and their interests is achieved by analysis of sentence structure and the use of RelationshipWordNet, a lexical resource that we developed. For analyzing polarities of stakeholder descriptions, we propose an opinion mining method based on the lexical resource SentiWordNet. As a result of analysis, we construct a relations graph of stakeholders to group stakeholders sharing mutual interests and to represent the interests of stakeholders. We also describe an application system we developed for news comparison based on the mining mechanism. This paper presents some experimental results to validate the proposed methods.

This paper introduces a future and past search engine, ChronoSeeker, which can help users to develop long-term strategies for their organizations. To provide on-demand searches, we tackled two technical issues: (1) organizing efficient event searches and (2) filtering out noises from search results. Our system employed query expansion with typical expressions related to event information such as year expressions, temporal modifiers, and context terms for efficient event searches. We utilized a machine-learning technique of filtering noise to classify candidates into information or non-event information, using heuristic features and lexical patterns derived from a text-mining approach. Our experiment revealed that filtering achieved an 85% F-measure, and that query expansion could collect dozens more events than those without expansion.

Despite the recent advances in personal communication devices and access network technology, users still face problems such as high device maintenance costs, complication of inter-device cooperation, illegal access to devices, and leakage of personal information. Consequently, it is difficult for users to construct a secure network with local as well as remote personal devices. We propose a User-driven Service Creation Platform (USCP), which enables users to construct a secure private network using a simple and intuitive approach that leverages the authentication mechanism in mobile phone networks. USCP separates signaling and data paths in a flat, virtual network topology. In this paper, we describe the basic design of USCP, the current implementation, and system evaluations.

This paper presents a syntax-based framework for gap resolution in analytic languages. CCG, reputable for dealing with deletion under coordination, is extended with a memory mechanism similar to the slot-and-filler mechanism, resulting in a wider coverage of syntactic gaps patterns. Though our grammar formalism is more expressive than the canonical CCG, its generative power is bounded by Partially Linear Indexed Grammar. Despite the spurious ambiguity originated from the memory mechanism, we also show that its probabilistic parsing is feasible by using the dual decomposition algorithm.

This paper proposes a new semantics that characterizes the time and/or situation dependencies of properties, together with the ontological notion of existential rigidity. For this purpose, we present order-sorted tempo-situational logic (OSTSL) with rigid/anti-rigid sorts and an existential predicate. In this logic, rigid/anti-rigid sorted terms enable the expressions for sortal properties, and temporal and situational operators suitably represent the ontological axioms of existential rigidity and time and/or situation dependencies. A specific semantics of OSTSL adheres to the temporal and situational behaviors of properties based on existential rigidity. As a result, the semantics guarantees that the ontological axioms of properties expressed by sorted tempo-situational formulas are logically valid.

Due to the limitations of language-processing tools for the Thai language, pattern-based information extraction from Thai documents requires supplementary techniques. Based on sliding-window rule application and extraction filtering, we present a framework for extracting semantic information from medical-symptom phrases with unknown boundaries in Thai unstructured-text information entries. A supervised rule learning algorithm is employed for automatic construction of information extraction rules from hand-tagged training symptom phrases. Two filtering components are introduced: one uses a classification model to predict rule application across a symptom-phrase boundary based on instantiation features of rule internal wildcards, the other uses weighted classification confidence to resolve conflicts arising from overlapping extractions. In our experimental study, we focus our attention on two basic types of symptom phrasal descriptions: one is concerned with abnormal characteristics of some observable entities and the other with human-body locations at which primitive symptoms appear. The experimental results show that the filtering components improve precision while preserving recall satisfactorily.

XQuery has become the standard for querying XML. Just like SQL, XQuery allows nested expressions. To optimize XQuery processing, a lot of research has been done on normalization, i.e., transforming nested expressions to equivalent unnested ones. Previous normalization rules are classified into two categories—source-level/ and algebra-level/—depending on whether a construct is specified in the XQuery syntax or as equivalent algebraic expressions. From an implementation point of view, the former is preferable to the latter since it can be implemented in a variety of XQuery engines with different algebras. However, existing source-level rules have several problems: They do not handle quantified expressions, incur duplicated query results, and use many temporary files. In this paper, we propose new source-level normalization rules that solve these problems. Through analysis and experiments, we show that our normalization rules can reduce query execution time from hours to a few seconds and can be adapted to a variety of XQuery engines.

In this paper, accuracy or error in permeability measurement using a combined microstrip line-coaxial conductor method was investigated. The measurement circuit used in this study is composed of a microstrip line (MSL) circuit and a grounded metal pipe with a center conductor passing through it coaxially. A sample is placed between the metal pipe and the center conductor. We evaluated the measurement accuracy for this measurement arrangement with electromagnetic simulation for the case where there are gaps between the sample and the holder. As a result, it has been shown that the normalized errors for this method have similar gap size dependence to the conventional coaxial method, but are about 10 to 20 percent greater than the coaxial method. With a view to improving the measurement accuracy, a correction method for the error is also discussed.

In this paper, we introduce a new sequential pattern, the Interactive User Sequence Pattern (IUSP). This pattern is useful for grouping highly interrelated users in one-way communications such as e-mail, SMS, etc., especially when the communications include many spam users. Also, we propose an efficient algorithm for discovering IUSPs from massive one-way communication logs containing only the following information: senders, receivers, and dates and times. Even though there is a difficulty in that our new sequential pattern violates the Apriori property, the proposed algorithm shows excellent processing performance and low storage cost in experiments on a real dataset.

Due to the increased preservation efforts, large amounts of past Web data have been stored in Web archives and other archival repositories. Utilizing this data can offer certain benefits to users, for example, it can facilitate page understanding. In this paper, we propose a system for interactive exploration of page histories. We demonstrate an application called Page History Explorer (PHE) for summarizing and visualizing histories of Web pages. PHE portrays the overview of page evolution, characterizes its typical content over time and lets users observe page histories from different viewpoints. In addition, it enables flexible comparison of histories of different pages.

A method based on covariance differencing for a uniform linear array is proposed to counter the problem of direction finding of narrowband signals under a colored noise environment. By assuming a Hermitian symmetric Toeplitz matrix for the unknown noise, the array covariance matrix is transformed into a centrohermitian matrix in an appropriate way allowing the noise component to be eliminated. The modified covariance differencing algorithm provides accurate direction of arrival (DOA) estimation when the incident signals are uncorrelated or just two of the signals are coherent. If there are more than two coherent signals, the presented method combined with spatial smoothing (SS) scheme can be used. Unlike the original method, the new approach dispenses the need to determine the true angles and the phantom angles. Simulation results demonstrate the effectiveness of presented algorithm.

With the emergence of Web 2.0, social tagging systems become highly popular in recent years and thus form the so-called folksonomies. Personalized tag recommendation in social tagging systems is to provide a user with a ranked list of tags for a specific resource that best serves the user's needs. Many existing tag recommendation approaches assume that users are independent and identically distributed. This assumption ignores the social relations between users, which are increasingly popular nowadays. In this paper, we investigate the role of social relations in the task of tag recommendation and propose a personalized collaborative filtering algorithm. In addition to the social annotations made by collaborative users, we inject the social relations between users and the content similarities between resources into a graph representation of folksonomies. To fully explore the structure of this graph, instead of computing similarities between objects using feature vectors, we exploit the method of random-walk computation of similarities, which furthermore enable us to model a user's tag preferences with the similarities between the user and all the tags. We combine both the collaborative information and the tag preferences to recommend personalized tags to users. We conduct experiments on a dataset collected from a real-world system. The results of comparative experiments show that the proposed algorithm outperforms state-of-the-art tag recommendation algorithms in terms of prediction quality measured by precision, recall and NDCG.

This paper focuses on the coalescing operator applied to the processing of continuous queries with temporal functions and predicates over windowed data streams. Coalescing is a key operation enabling the evaluation of interval predicates and functions on temporal tuples. Applying this operation for temporal query processing on windowed streams brings the challenge of coalescing tuples in a window extent each time the window slides over the data stream. This coalescing becomes even more involving when some tuples arrive out of order. This paper distinguishes between eager coalescing and lazy coalescing, the two known coalescing schemes. The former coalesces tuples during window extent update and the latter does it during window extent scan. With these two schemes, the paper first presents algorithms for updating a window extent for both tuple-based and time-based windows. Then, the problem of optimally selecting between eager and lazy coalescing for concurrent queries is formulated as a 0-1 integer programming problem. Through extensive performance study, the two schemes are compared and the optimal selection is demonstrated.

This paper presents a novel dynamic subchannel allocation scheme that can improve the cell capacity by coordinating the intercell interference (ICI) in a cellular orthogonal frequency division multiple access (OFDMA) system. The proposed scheme mitigates the ICI by adopting the virtual cell concept and improves the frequency reuse factor through subchannel reuse among different virtual cells. In particular, each virtual cell is assigned a primary and a secondary subchannel group, and each sector base station (BSs) allocates the subchannel resulting in the least ICI in probability out of the candidate subchannels to the mobile stations, dynamically searching from its primary group and then secondary group. In addition, an optional use of pico-cell overlay at the intersection of the virtual cells is also proposed to enhance the fairness of the proposed scheme with the BS-MS distance. Through computer simulation, it is shown that the proposed scheme has the advantages of improved cell capacity and fairness compared to the conventional schemes.

A novel design technique for two-dimensional (2-D) waveguide slot arrays is proposed in this paper that combines a full-wave method of moments (MoM) analysis and an equivalent circuit with the explicit restraint of input matching. The admittance and slot spacing are determined first in an equivalent circuit to realize the desired distribution of power dissipation and phase, with the explicit restraint of input matching. Secondly by applying a full-wave MoM analysis to the finite 2-D array, slot parameters are iteratively determined to realize the active admittance designed above where slot mutual coupling and wall thickness are fully taken into account. The admittance, treated as the key parameter in the equivalent circuit corresponds to the power dissipation of the slots but not to the slot voltage, which is directly synthesized from the radiation pattern. The initial value of the power dissipation is assumed to be proportional to the square of the amplitude of the desired slot voltage. This assumption leads to a feedback procedure, because the resultant slot voltage distribution generally differs from the desired ones due to the effect of non-uniformity in the characteristic impedance on slot apertures. This slot voltage error is used to renew the initial distribution of power dissipation in the equivalent circuit. Generally, only one feedback cycle is needed. Two 2427-element arrays with uniform and Taylor distributions were designed and fabricated at 25.3 GHz. The measured overall reflections for both antennas were suppressed below -18 dB over the 24.3-26.3 GHz frequency range. High aperture efficiencies of 86.8% and 55.1% were realized for the antennas with uniform and Taylor distributions, the latter of which has very low sidelobes below -33 dB in both the E- and H-planes.