This paper investigates the closure properties of 1-inkdot nondeterministic Turing machines and 1-inkdot alternating Turing machines with only universal states which have sublogarithmic space. We show for example that the classes of sets accepted by these Turing machines are not closed under length-preserving homomorphism, concatenation with regular set, Kleene closure, and complementation.

An explicit construction of pairing-friendly hyperelliptic curves with ordinary Jacobians was firstly given by D. Freeman for the genus two case. In this paper, we give an explicit construction of pairing-friendly hyperelliptic curves of genus two and four with ordinary Jacobians based on the closed formulae for the order of the Jacobian of special hyperelliptic curves. For the case of genus two, we prove the closed formula for curves of type y2=x5+c. By using the formula, we develop an analogue of the Cocks-Pinch method for curves of type y2=x5+c. For the case of genus four, we also develop an analogue of the Cocks-Pinch method for curves of type y2=x9+cx. In particular, we construct the first examples of pairing-friendly hyperelliptic curves of genus four with ordinary Jacobians.

This letter investigates the space complexity of the sender buffer in a TCP variant, TCP-PR, to deal with packet reordering. Our finding is that with the SACK option used, TCP-PR requires the sender buffer of (β+1) pipesize where β indicates the number of RTTs that must pass before packet loss is detected.

Traditionally, popular synonym acquisition methods are based on the distributional hypothesis, and a metric such as Jaccard coefficients is used to evaluate the similarity between the contexts of words to obtain synonyms for a query. On the other hand, when one tries to compile and clean a thesaurus, one often already has a modest number of synonym relations at hand. Could something be done with a half-built thesaurus alone? We propose the use of spectral methods and discuss their relation to other network-based algorithms in natural language processing (NLP), such as PageRank and Bootstrapping. Since compiling a thesaurus is very laborious, we believe that adding the proposed method to the toolkit of thesaurus constructors would significantly ease the pain in accomplishing this task.

LCD Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because we get different images. This is caused by possible variations in the image acquisition process including optical factors, non-uniform illumination, random noise, and so on. For this reason, conventional area based defect measuring method has some problems in terms of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome these problems. We utilize volume information which is completely ignored in the area based conventional defect measuring method. We choose a bell shape as a defect model for experiment. The results show that our proposed method dramatically improves robustness of defect size measurement. Given proper modeling, the proposed volume based measuring method can be applied to various types of defect for better robustness and consistency.

Reflecting the rapid growth of information technology, the configuration of software applications such as word processors and spreadsheets is both sophisticated and complicated. It is often difficult for users to identify relevant functions in the online manual for a target application. In this paper, we propose a method for question answering that finds functions related to the user's request. To enhance our method, we addressed two "mismatch" problems. The first problem is associated with a mismatch in vocabulary, where the same concept is represented by different words in the manual and in the user's question. The second problem is associated with a mismatch in function. Although the user may have a hypothetical function for a purpose in mind, this purpose can sometimes be accomplished by other functions. To resolve these mismatch problems, we extract terms related to software functions from the Web, so that the user's question can be matched to the relevant function with high accuracy. We demonstrate the effectiveness of our method experimentally.

In this paper, we study multi-layer transmission for wireless multimedia multicast in a cell. Under the assumptions that the users in a cell are uniformly well distributed and that the BS has no channel side information, we find the optimal number of transmission layers and power allocation. This result can be used in highly dynamic dense networks and jamming networks where channel side information at the transmitter is somewhat useless.

A new adaptive algorithm is proposed by introducing some modifications to the recursive least squares (RLS) algorithm. Except for the noise variance, the proposed algorithm does not require any statistics or knowledge of the desired signal, thus, it is suitable for adaptive filtering for channel estimation in code division multiple access (CDMA) systems in cases where the standard RLS approach cannot be used. A theoretical analysis demonstrates the convergence of the proposed algorithm, and simulation results for CDMA channel estimation show that the proposed algorithm outperforms existing channel estimation schemes.

Automated bug localization is an important issue in software engineering. In the last few decades, various proactive and reactive localization approaches have been proposed to predict the fault-prone software modules. However, most proactive or reactive approaches need source code information or software complexity metrics to perform localization. In this paper, we propose a reactive approach which considers only bug report information and historical revision logs. In our approach, the co-location relationships among bug reports are explored to improve the prediction accuracy of a state-of-the-art learning method. Studies on three open source projects reveal that the proposed scheme can consistently improve the prediction accuracy in all three software projects by nearly 11.6% on average.

In this paper, we propose a file replication method to achieve load balancing in terms of write access to storage device ("write storage access load balancing" for short) in unstructured peer-to-peer (P2P) file-sharing networks in which the popularity trend of queried files varies dynamically. The proposed method uses a write storage access ratio as a load balance index value in order to stabilize dynamic P2P file-sharing environments adaptively. In the proposed method, each peer autonomously controls the file replication ratio, which is defined as a probability to create the replica of the file in order to uniform write storage access loads in the similar way to thermal diffusion phenomena. Theoretical analysis results show that the behavior of the proposed method actually has an analogy to a thermal diffusion equation. In addition, simulation results reveal that the proposed method has an ability to realize write storage access load balancing in the dynamic P2P file-sharing environments.

In this paper, we propose a robust room inverse filtering algorithm for speech dereverberation based on a kurtosis maximization. The proposed algorithm utilizes a new normalized kurtosis function that nonlinearly maps the input kurtosis onto a finite range from zero to one, which results in a kurtosis warping. Due to the kurtosis warping, the proposed algorithm provides more stable convergence and, in turn, better performance than the conventional algorithm. Experimental results are presented to confirm the robustness of the proposed algorithm.

The proportionate normalized least mean square algorithm (PNLMS) greatly improves the convergence of the sparse impulse response. It exploits the shape of the impulse response to decide the proportionate step gain for each coefficient. This is not always suitable. Actually, the proportionate step gain should be determined according to the difference between the current estimate of the coefficient and its optimal value. Based on this idea, an approach is proposed to determine the proportionate step gain. The proposed approach can improve the convergence of proportionate adaptive algorithms after a fast initial period. It even behaves well for the non-sparse impulse response. Simulations verify the effectiveness of the proposed approach.

This paper presents a novel cross-layer approach to explore selection diversity for distributed clustering based wireless sensor networks (WSNs) by selecting a proper cluster-head. We develop and analyze an instantaneous channel state information (CSI) based cluster-head selection algorithm for a distributed, dynamic and randomized clustering based WSN. The proposed cluster-head selection scheme is also random and capable to distribute the energy uses among the nodes in the network. We present an analytical approach to evaluate the energy efficiency and system lifetime of our proposal. Analysis shows that the proposed scheme outperforms the performance of additive white Gaussian noise (AWGN) channel under Rayleigh fading environment. This proposal also outperforms the existing cooperative diversity protocols in terms of system lifetime and implementation complexity.

We propose a high-speed protection scheme for multiple-priority-class traffic transmission in WDM ring networks. This scheme achieves high-speed protection by quickly suspending transmission of low-priority traffic when a failure is detected. Each node suspends transmission of the low-priority traffic being sent over the backup path corresponding to the impaired primary path after receiving a failure notification and checking a table that includes the primary paths passing through the node, the backup paths corresponding to the primary paths, and low-priority traffic transmitted by the node. If a node detects a failure, it sends a single failure notification for each ring to the source node of the primary path, and the nodes on the route sequentially suspend low-priority traffic. Simulation shows that the proposed scheme reduces the failure-recovery time by up to 60% compared with the conventional scheme.

Multipath routing and the ability to simultaneously use multiple network paths has long been proposed as a means for meeting the reliability and performance improvement goals of a next generation Internet. However, its use causes out-of-order packet delivery, which is well known to hinder TCP performance. While next-generation transport protocols will no doubt better cope with this phenomenon, a complete switch to these new protocols cannot be made on all devices "overnight"; the reality is that we will be forced to continue using TCP on such multipath networks well after deployment of a future Internet is complete. In this paper, we investigate the use of best-effort packet reordering -- an optional network layer service for improving the performance of any TCP session in the presence of out-of-order packet delivery. Such a service holds the promise of allowing unmodified TCP to take advantage of the reliability and performance gains offered by a future multipath-enabled Internet without suffering the adverse performance effects commonly associated with out-of-order packet delivery. Our experiments test the performance of two common TCP variants under packet dispersion with differing numbers of paths and amounts of inter-path latency variance. They were conducted using multipath network and packet reorderer implementations implemented within the Emulab testbed. Our results demonstrate that a simple best-effort reordering service can insulate TCP from the type of reordering that might be expected from use of packet dispersion over disjoint paths in a wide-area network, and is capable of providing significant performance benefits with few ill side-effects.

We consider the problem of fast identification of high-rate flows in backbone links with possibly millions of flows. Accurate identification of high-rate flows is important for active queue management, traffic measurement and network security such as detection of distributed denial of service attacks. It is difficult to directly identify high-rate flows in backbone links because tracking the possible millions of flows needs correspondingly large high speed memories. To reduce the measurement overhead, the deterministic 1-out-of-k sampling technique is adopted which is also implemented in Cisco routers (NetFlow). Ideally, a high-rate flow identification method should have short identification time, low memory cost and processing cost. Most importantly, it should be able to specify the identification accuracy. We develop two such methods. The first method is based on fixed sample size test (FSST) which is able to identify high-rate flows with user-specified identification accuracy. However, since FSST has to record every sampled flow during the measurement period, it is not memory efficient. Therefore the second novel method based on truncated sequential probability ratio test (TSPRT) is proposed. Through sequential sampling, TSPRT is able to remove the low-rate flows and identify the high-rate flows at the early stage which can reduce the memory cost and identification time respectively. According to the way to determine the parameters in TSPRT, two versions of TSPRT are proposed: TSPRT-M which is suitable when low memory cost is preferred and TSPRT-T which is suitable when short identification time is preferred. The experimental results show that TSPRT requires less memory and identification time in identifying high-rate flows while satisfying the accuracy requirement as compared to previously proposed methods.

Wireless sensor networks with a star network topology are commonly applied for health monitoring systems. To determine the condition of a patient, sensor nodes are attached to the body to transmit the data to a coordinator. However, this process is inefficient because the coordinator is always communicating with each sensor node resulting in a data processing workload for the coordinator that becomes much greater than that of the sensor nodes. In this paper, a method is proposed to reduce the number of data transmissions from the sensor nodes to the coordinator by establishing a threshold for data from the biological signals to ensure that only relevant information is transmitted. This results in a dramatic reduction in power consumption throughout the entire network.

In this letter, we develop an anycast-based emergency service for healthcare wireless sensor networks. The new service could operate with sensors to detect and activate an alarm system based on predefined conditions that are specific to the patient and the disease. The new service is implemented on 802.15.4 ZigBee which usually has large control overhead and long transmission times. To improve the service performance, our service identifies the closest emergency service provider to alleviate the control overhead and achieve immediate assistance when a patient requests for an emergency service. We also increase the reliability of packet transmission by using a Recovery Point scheme. Our simulations and experiment demonstrate that our scheme is efficient and feasible for healthcare wireless sensor networks.

In this letter, we propose an improved anchor shot detection (ASD) method in order to effectively retrieve anchor shots from news video. The face location and dissimilarity of icon region are used to reduce false alarms in the proposed method. According to the results of the experiment on several types of news video, the proposed method obtained high anchor detection results compared with previous methods.

Wireless mesh networks have been extensively studied as expandable, flexible, and inexpensive access networks to the Internet. This paper focuses on one composed of multiple access points (APs) connected through multihop wireless communications mainly by the wireless distribution system (WDS). For scalability, the proper partition of APs into multiple WDS clusters is essential, because the number of APs in one cluster is limited due to the increasing radio interference and control packets. In this paper, we formulate this WDS clustering problem and prove the NP-completeness of its decision version through reduction from a known NP-complete problem. Then, we propose its heuristic algorithm, using a greedy method and a variable depth search method, to satisfy the complex constraints while optimizing the cost function. We verify the effectiveness of our algorithm through extensive simulations, where the results confirm its superiority to the existing algorithm in terms of throughput.