With the wide usage of multispectral images, a fast efficient multidimensional clustering method becomes not only meaningful but also necessary. In general, to speed up the multidimensional images' analysis, a multidimensional feature vector should be transformed into a lower dimensional space. The Hilbert curve is a continuous one-to-one mapping from N-dimensional space to one-dimensional space, and can preserves neighborhood as much as possible. However, because the Hilbert curve is generated by a recurve division process, 'Boundary Effects' will happen, which means data that are close in N-dimensional space may not be close in one-dimensional Hilbert order. In this paper, a new efficient approach based on the space-filling curves is proposed for classifying multispectral satellite images. In order to remove 'Boundary Effects' of the Hilbert curve, multiple Hilbert curves, z curves, and the Pseudo-Hilbert curve are used jointly. The proposed method extracts category clusters from one-dimensional data without computing any distance in N-dimensional space. Furthermore, multispectral images can be analyzed hierarchically from coarse data distribution to fine data distribution in accordance with different application. The experimental results performed on LANDSAT data have demonstrated that the proposed method is efficient to manage the multispectral images and can be applied easily.

In this paper, we introduce an approach of service adaptation for behavior mismatching services using pushdown model checking. This approach uses pushdown systems as model of adaptors so that capturing non-regular behavior in service interactions is possible. Also, the use of pushdown model checking integrates adaptation and verification. This guarantees that an adaptor generated by our approach not only solves behavior mismatches but also satisfies usual verification properties if specified. Unlike conventional approaches, we do not count on specifications of adaptor contracts but take only information from behavior interfaces of services and perform fully automated adaptor generation. Three requirements relating to behavior mismatches, unbounded messages, and branchings are retrieved from behavior interfaces and used to build LTL properties for pushdown model checking. Properties for unbounded messages, i.e., messages sent and received arbitrary multiple times, are especially addressed since it characterizes non-regular behavior in service composition. This paper also shows some experimental results from a prototype tool and provides directions for building BPEL adaptors from behavior interface of generated adaptor. The results show that our approach does solve behavior mismatches and successfully capture non-regular behavior in service composition under the scale of real service applications.

Cubic TCP, one of transport protocols designed for high bandwidth-delay product (BDP) networks, has successfully been deployed in the Internet. Multi-homed computers with multiple interfaces to access the Internet via high speed links will become more popular. In this work, we introduce an extended version of Cubic TCP for multiple paths, called MPCubic. The extension process is approached from an analysis model of Cubic by using coordinated congestion control between paths. MPCubic can spread its traffic across paths in load-balancing manner, while preserving fair sharing with regular TCP, Cubic, and MPTCP at common bottlenecks. Moreover, to improve resilience to link failure, we propose a multipath fast recovery algorithm. The algorithm can significantly reduce the recovery time of data rate after restoration of failed links. These techniques can be useful for resilient high-bandwidth applications (for example, tele-health conference) in disaster-affected areas. Our simulation results show that MPCubic can achieve stability, throughput improvement, fairness, load-balancing, and quick data rate recovery from link failure under a variety of network conditions.

Nowadays portable devices with multiple wireless interfaces and using multimedia services are becoming more popular on the Internet. This paper describes a family of multipath binomial congestion control algorithms for audio/video streaming, where a low variant of transmission rate is important. We extend the fluid model of binomial algorithms for single-path transmission to support the concurrent transmission of packets across multiple paths. We focus on the extension of two particular algorithms, SQRT and IIAD, for multiple paths, called MPSQRT and MPIIAD, respectively. Additionally, we apply the design technique (using the multipath fluid model) for multipath TCP (MPTCP) into the extension of SQRT and IIAD, called fbMPSQRT and fbMPIIAD, respectively. Both two approaches ensure that multipath binomial congestion control algorithms achieve load-balancing, throughput improvement, and fairness to single-path binomial algorithms at shared bottlenecks. Through the simulations and comparison with the uncoordinated protocols MPSQRT/MPIIAD, fbMPSQRT/fbMPIIAD and MPTCP, we find that our extended multipath transport protocols can preserve lower latency and transmission rate variance than MPTCP, fairly share with single-path SQRT/IIAD, MPTCP and TCP, and also can achieve throughput improvements and load-balancing equivalent to those of MPTCP under various scenarios and network conditions.

A transmission control protocol (TCP) using an additive increase multiplicative decrease (AIMD) algorithm for congestion control plays a leading role in advanced Internet services. However, the AIMD method shows only low link utilization in lossy networks with long delay such as satellite networks. This is because the cwnd dynamics of TCP are reduced by long propagation delay, and TCP uses an inadequate congestion control algorithm, which does not distinguish packet loss from wireless errors from that due to congestion of the wireless networks. To overcome these problems, we propose an exponential recovery (ER) TCP that uses the exponential recovery function for rapidly occupying available bandwidth during a congestion avoidance period, and an adaptive congestion window decrease scheme using timestamp base available bandwidth estimation (TABE) to cope with wireless channel errors. We simulate the proposed ER-TCP under various test scenarios using the ns-2 network simulator to verify its performance enhancement. Simulation results show that the proposal is a more suitable TCP than the several TCP variants under long delay and heavy loss probability environments of satellite networks.

This paper presents our recent work in regard to building Large Vocabulary Continuous Speech Recognition (LVCSR) systems for the Thai, Indonesian, and Chinese languages. For Thai, since there is no word boundary in the written form, we have proposed a new method for automatically creating word-like units from a text corpus, and applied topic and speaking style adaptation to the language model to recognize spoken-style utterances. For Indonesian, we have applied proper noun-specific adaptation to acoustic modeling, and rule-based English-to-Indonesian phoneme mapping to solve the problem of large variation in proper noun and English word pronunciation in a spoken-query information retrieval system. In spoken Chinese, long organization names are frequently abbreviated, and abbreviated utterances cannot be recognized if the abbreviations are not included in the dictionary. We have proposed a new method for automatically generating Chinese abbreviations, and by expanding the vocabulary using the generated abbreviations, we have significantly improved the performance of spoken query-based search.

TCP Reno is not fully utilized in under-buffered links. We propose a new TCP congestion control algorithm that can utilize the link almost up to 100% except the first congestion avoidance cycle. Our scheme estimates the minimum congestion window size for full link utilization in every congestion avoidance cycle and sends extra packets without touching TCP Reno congestion control. It has the same RTT fairness and the same saw-tooth wave as TCP Reno does. Our scheme does not affect competing TCP Reno flows since it uses only unused link capacity. We provide a simple mathematical modeling as well as ns-2 simulation results which show that the link utilization is improved by up to 19.88% for k=1/8 against TCP Reno when the buffer is k times the optimal buffer size. We claim that our scheme is useful for transmitting large amount of data in under-buffered links.

Requirements are elicited step by step during the requirements engineering (RE) process. However, some types of requirements are elicited completely after the scheduled requirements elicitation process is finished. Such a situation is regarded as problematic situation. In our study, the difficulties of eliciting various kinds of requirements is observed by components. We refer to the components as observation targets (OTs) and introduce the word “Requirements maturation.” It means when and how requirements are elicited completely in the project. The requirements maturation is discussed on physical and logical OTs. OTs Viewed from a logical viewpoint are called logical OTs, e.g. quality requirements. The requirements of physical OTs, e.g., modules, components, subsystems, etc., includes functional and non-functional requirements. They are influenced by their requesters' environmental changes, as well as developers' technical changes. In order to infer the requirements maturation period of each OT, we need to know how much these factors influence the OTs' requirements maturation. According to the observation of actual past projects, we defined the PRINCE (Pre Requirements Intelligence Net Consideration and Evaluation) model. It aims to guide developers in their observation of the requirements maturation of OTs. We quantitatively analyzed the actual cases with their requirements elicitation process and extracted essential factors that influence the requirements maturation. The results of interviews of project managers are analyzed by WEKA, a data mining system, from which the decision tree was derived. This paper introduces the PRINCE model and the category of logical OTs to be observed. The decision tree that helps developers infer the maturation type of an OT is also described. We evaluate the tree through real projects and discuss its ability to infer the requirements maturation types.

Large-scale adoption of electronic healthcare applications requires semantic interoperability. The new proposals propose an advanced (multi-level) DBMS architecture for repository services for health records of patients. These also require query interfaces at multiple levels and at the level of semi-skilled users. In this regard, a high-level user interface for querying the new form of standardized Electronic Health Records system has been examined in this study. It proposes a step-by-step graphical query interface to allow semi-skilled users to write queries. Its aim is to decrease user effort and communication ambiguities, and increase user friendliness.

To reconstruct low-resolution facial photographs which are in focus and without motion blur, a novel algorithm based on local similarity preserving is proposed. It is based on the theories of local manifold learning. The innovations of the new method include mixing point-based entropy and Euclidian distance to search for the nearest points, adding point-to-patch degradation model to restrict the linear weights and compensating the fusing patch to keep energy coherence. The compensation reduces the algorithm dependence on training sets and keeps the luminance of reconstruction constant. Experiments show that our method can effectively reconstruct 1612 images with the magnification of 88 and the 3224 facial photographs in focus and without motion blur.

This letter investigates the problem of distributed channel selection in cognitive radio ad hoc networks (CRAHNs) with heterogeneous spectrum opportunities. Firstly, we formulate this problem as a local congestion game, which is proved to be an exact potential game. Then, we propose a spatial best response dynamic (SBRD) to rapidly achieve Nash equilibrium via local information exchange. Moreover, the potential function of the game reflects the network collision level and can be used to achieve higher throughput.

In this letter, functional duality between distributed source coding (DSC) with correlated messages and broadcast channel coding (BCC) with correlated messages is considered. It is shown that under certain conditions, for a given DSC problem with correlated messages, a functional dual BCC problem with correlated messages can be obtained, and vice versa. That is, the optimal encoder-decoder mappings for one problem become the optimal decoder-encoder mappings for the dual problem. Furthermore, the correlation structure of the messages in the two dual problems and the source distortion and channel cost measure for this duality are specified.

This article presents an algorithm that solves an on-line version of the longest common subsequence (LCS) problem for two strings over a constant alphabet in O(d+n) time and O(m+d) space, where m is the length of the shorter string, the whole of which is given to the algorithm in advance, n is the length of the longer string, which is given as a data stream, and d is the number of dominant matches between the two strings. A new upper bound, O(p(m-q)), of d is also presented, where p is the length of the LCS of the two strings, and q is the length of the LCS of the shorter string and the m-length prefix of the longer string.

The accurate and fast estimation of link price is the key component of network-based congestion control schemes. A fast estimation method A2DPM is presented. Multiple hashes on IP identifier of packet header are adopted to accelerate the side information transmission, so accurate estimation of maximum price on the flow forwarding path can be realized after the receipt of just a few probe packets, and the sender is capable of reacting to congestion more quickly, making it suitable to meet the demands of dynamic networks.

Previous studies of pattern recognition have shown that classifiers ensemble approaches can lead to better recognition results. In this paper, we apply the voting technique for the CoNLL-2010 shared task on detecting hedge cues and their scope in biomedical texts. Six machine learning-based systems are combined through three different voting schemes. We demonstrate the effectiveness of classifiers ensemble approaches and compare the performance of three different voting schemes for hedge cue and their scope detection. Experiments on the CoNLL-2010 evaluation data show that our best system achieves an F-score of 87.49% on hedge detection task and 60.87% on scope finding task respectively, which are significantly better than those of the previous systems.

This paper concerns cancel minimal linear grammars ([5]) that was introduced to generalize Geffert normal forms for phrase structure grammars. We consider the generative power of restricted cancel minimal linear grammars: the grammars have only one nonterminal symbol C except the start symbol S, and their productions consist of context-free type productions, the left-hand side of which is S and the right-hand side contains at most one occurrence of S, and a unique cancellation production Cm ε that replaces the string Cm by the empty string ε. We show that, for any given positive integer m, the class of languages generated by cancel minimal linear grammars with Cm ε, is properly included in the class of linear languages. Conversely, we show that for any linear language L, there exists some positive integer m such that a cancel minimal linear grammar with Cm ε generates L. We also show how the generative power of cancel minimal linear grammars with a unique cancellation production Cm ε vary according to changes of m and restrictions imposed on occurrences of terminal symbols in the right-hand side of productions.

We propose a system that, using video information, segments the mouth region from a face image and then detects the protrusion of the tongue from inside the oral cavity. Initially, under the assumption that the mouth is closed, we detect both mouth corners. We use a set of specifically oriented Gabor filters for enhancing horizontal features corresponding to the shadow existing between the upper and lower lips. After applying the Hough line detector, the extremes of the line that was found are regarded as the mouth corners. Detection rate for mouth corner localization is 85.33%. These points are then input to a mouth appearance model which fits a mouth contour to the image. By segmenting its bounding box we obtain a mouth template. Next, considering the symmetric nature of the mouth, we divide the template into right and left halves. Thus, our system makes use of three templates. We track the mouth in the following frames using normalized correlation for mouth template matching. Changes happening in the mouth region are directly described by the correlation value, i.e., the appearance of the tongue in the surface of the mouth will cause a decrease in the correlation coefficient through time. These coefficients are used for detecting the tongue protrusion. The right and left tongue protrusion positions will be detected by analyzing similarity changes between the right and left half-mouth templates and the currently tracked ones. Detection rates under the default parameters of our system are 90.20% for the tongue protrusion regardless of the position, and 84.78% for the right and left tongue protrusion positions. Our results demonstrate the feasibility of real-time tongue protrusion detection in vision-based systems and motivates further investigating the usage of this new modality in human-computer communication.

We address the stability property of the FAST TCP congestion control algorithm. Based on a continuous-time dynamic model of the FAST TCP network, we establish that FAST TCP in itself is globally exponentially stable without any specific conditions on the congestion control parameter or the update gain. Simulation results demonstrate the validity of the global exponential stability of FAST TCP.

In this letter, we propose an improved Droptail algorithm that introduces the random packet drop strategy. Our theoretical analysis and experiments prove that the improved Droptail can match the most performance of AQM algorithms in stabilizing the TCP system and solving the global synchronization problem, while significantly reducing the complexity of the router control. This fact shows that our algorithm is superior to the most popular AQM algorithms such as RED, PI, etc.

Let T be a tree in which every edge is associated with a real number. The sum of a path in T is the sum of the numbers associated with the edges of the path and its length is the number of the edges in it. For two positive integers L1 ≤ L2 and two real numbers S1 ≤ S2, a path is feasible if its length is between L1 and L2 and its sum is between S1 and S2. We address the problem: Given a tree T, and four numbers, L1, L2, S1 and S2, find the longest feasible path of T. We provide an optimal O(n log n) time algorithm for the problem, where n =|T|.