In this paper, an improved B-picture coding algorithm based on the symmetric bi-directional motion estimation (ME) is proposed. In addition to the block match error between blocks in the forward and backward reference frames, the proposed method exploits the previously-reconstructed template regions in the current and reference frames for bi-directional ME. The side match error between the predicted target block and its template is also employed in order to alleviate block discontinuities. To efficiently perform ME, an initial motion vector (MV) is adaptively derived by exploiting temporal correlations. Experimental results show that the number of generated bits is reduced by up to 9.31% when the proposed algorithm is employed as a new macroblock (MB) coding mode for the H.264/AVC standard.

Discrete-Time fractional Brownian motion (DFBM) and its increment process, called discrete-time fractional Gaussian noise (DFGN), are usually used to describe natural and biomedical phenomena. These two processes are dominated by one parameter, called the Hurst exponent, which needs to be estimated in order to capture the characteristics of physical signals. In the previous work, a variance estimator for estimating the Hurst exponent directly via DFBM was provided, and it didn't consider point selection for linear regression. Since physical signals often appear to be DFGN-type, not DFBM-type, it is imperative to first transform DFGN into DFBM in real applications. In this paper, we show that the variance estimator possesses another form, which can be estimated directly via the autocorrelation functions of DFGN. The above extra procedure of transforming DFGN into DFBM can thus be avoided. On the other hand, the point selection for linear regression is also considered. Experimental results show that 4-point linear regression is almost optimal in most cases. Therefore, our proposed variance estimator is more efficient and accurate than the original one mentioned above. Besides, it is also superior to AR and MA methods in speed and accuracy.

This paper customizes Goal/Question/Metric (GQM) project monitoring models for various projects and organizations to take advantage of the data from the software tool EPM and to allow the tailoring of the interpretation models based upon the context and success criteria for each project and organization. The basic idea is to build less concrete models that do not include explicit baseline values to interpret metrics values. Instead, we add hypothesis and interpretation layers to the models to help people of different projects make decisions in their own context. We applied the models to two industrial projects, and found that our less concrete models could successfully identify typical problems in software projects.

Sensor deployment to achieve better system performance is one of the critical issues in wireless sensor networks (WSN). This letter proposes an effective sensor deployment scheme for large area sensor networks, where the event occurrence rate varies over the sensor-deployed region. Based on local event occurrence rate, the proposed scheme determines the number of sensors that should be deployed in each local region to maximize the overall detection probability. Simulation results show that the sensor deployment by the proposed scheme improves detection capability by 21% in comparison to the Incidence algorithm.

Performance of CSMA/CA wireless communication is severely affected by hidden terminal (HT) problem that results in failure of carrier sense and causes packet error due to collision. However, no mathematical analysis method for the HT problem has been available that takes into account actual radio environments including both fading and capture effect. This paper presents an analysis method that enables to well predict the probability of successful communication (PSC) and communication efficiency for CSMA/CA unicast communication including the interaction of data and ACK packets. Analysis of the PSC with two-dimensional HT distribution makes it easy to understand the influence of HT location and carrier sense level. Also it is shown that there is considerable difference on the PSC between fading and fading-free environments. The obtained results as well as the proposed analysis method are quite useful in CSMA/CA network design for WLAN and sensor network applications.

This letter presents a novel opportunistic cooperative positioning approach for orthogonal frequency-division multiple access (OFDMA) systems. The basic idea is to allow idle mobile terminals (MTs) opportunistically estimating the arrival timing of the training sequences for uplink synchronization from active MTs. The major advantage of the proposed approach over state-of-the-arts is that the positioning-related measurements among MTs are performed without the paid of training overhead. Moreover, Cramer-Rao lower bound (CRLB) is utilized to derive the positioning accuracy limit of the proposed approach, and the numerical results show that the proposed approach can improve the accuracy of non-cooperative approaches with the a-priori stochastic knowledge of clock bias among idle MTs.

In this letter a general admission control strategy is proposed and mathematically analyzed. Fractional buffering finely adjusts different QoS metrics allowing them to simultaneously achieve their maximum acceptable values, maximizing system capacity. Fractional buffering also allows the adequate and fair performance comparison among different resource management strategies and/or evaluation scenarios.

The optimal way to build speech understanding modules depends on the amount of training data available. When only a small amount of training data is available, effective allocation of the data is crucial to preventing overfitting of statistical methods. We have developed a method for allocating a limited amount of training data in accordance with the amount available. Our method exploits rule-based methods for when the amount of data is small, which are included in our speech understanding framework based on multiple model combinations, i.e., multiple automatic speech recognition (ASR) modules and multiple language understanding (LU) modules, and then allocates training data preferentially to the modules that dominate the overall performance of speech understanding. Experimental evaluation showed that our allocation method consistently outperforms baseline methods that use a single ASR module and a single LU module while the amount of training data increases.

We investigate the impact of traffic on the performance of large-scale NAT (LSN), since it has been attracting attention as a means of better utilizing the limited number of global IPv4 addresses. We focus on the number of active flows because they drive up the LSN memory requirements in two ways; more flows must be held in LSN memory, and more global IPv4 addresses must be prepared. Through traffic measurement data analysis, we found that more than 1% of hosts generated more than 100 TCP flows or 486 UDP flows at the same time, and on average, there were 1.43-3.99 active TCP flows per host, when the inactive timer used to clear the flow state from a flow table was set to 15 s. When the timer is changed from 15 s to 10 min, the number of active flows increases more than tenfold. We also investigate how to reduce the above impact on LSN in terms of saving memory space and accommodating more users for each global IPv4 address. We show that to save memory space, regulating network anomalies can reduce the number of active TCP flows on an LSN by a maximum of 48.3% and by 29.6% on average. We also discuss the applicability of a batch flow-arrival model for estimating the variation in the number of active flows, when taking into account that the variation is needed to prepare an appropriate memory space. One way to allow each global IPv4 address to accommodate more users is to better utilize destination IP address information when mapping a source IP address from a private address to a global IPv4 address. This can effectively reduce the required number of global IPv4 addresses by 85.9% for TCP traffic and 91.9% for UDP traffic on average.

In this paper, we discuss the stochastic modeling for operational software reliability measurement, assuming that the testing environment is originally different from the user operation one. In particular, we introduce the concept of systemability which is defined as the reliability characteristic subject to the uncertainty of the field operational environment into the model. First we introduce the environmental factor to consistently bridge the gap between the software failure-occurrence characteristics during the testing and the operation phases. Then we consider the randomness of the environmental factor, i.e., the environmental factor is treated as a random-distributed variable. We use the Markovian imperfect debugging model to describe the software reliability growth phenomena in the testing and the operation phases. We derive the analytical solutions of the several operational software reliability assessment measures which are given as the functions of time and the number of debuggings. Finally, we show several numerical illustrations to investigate the impacts of the consideration of systemability on the field software reliability evaluation.

The impact and benefits of infrastructure support are shown by introducing an achievable throughput scaling law of a ultra-wide band (UWB) ad hoc network in which m base stations (BSs) are regularly located. The existing multi-hop scheme consisting of two variants, with and without BS help, is utilized with a slight modification. Our result indicates that the derived throughput scaling depends on the path-loss exponent due to the power-limited characteristics for all operating regimes examined. Furthermore, it is shown that the total throughput scales linearly with parameter m as m is larger than a certain level. It thus turns out the use of infrastructure is also helpful in improving the throughput scaling of UWB networks in some conditions.

In this letter, we propose a packet loss probability (PLP) assessment method that uses active measurements. Considering the statistical nature of measurement data in a network, we adopt the confidence interval to assess whether the performance of a network complies with a target PLP or not. Using both analysis and simulations, we show that the proposed method can guarantee that the probabilities of erroneous assessments are not more than a given significance level. In addition, we provide a systematic method to determine the number of probing packets needed for statistical assurance by presenting a clear relation between the assessment accuracy and the measurement overhead.

In this paper, the correspondence between the weighted line graph and the Mason signal flow graph (MSFG) has been established, which gives an interpretation of a convolutional network code (CNC) over a cyclic network from a different perspective. Furthermore, by virtue of Mason theorem, we present two new equivalent conditions to evaluate whether the global encoding kernels (GEKs) can be uniquely determined by the given complete set of local encoding kernels (LEKs) in a CNC over a cyclic network. These two new equivalent conditions turn out to be more intuitive. Moreover, we give an alternative simple proof of an existing result.

The present paper proposes a new method for constructing polyphase asymmetric zero-correlation zone (A-ZCZ) sequence sets. The proposed method can generate A-ZCZ sequence sets that cannot be obtained from methods proposed by other researchers and is a generalized version of our previously proposed method. An A-ZCZ sequence set can be regarded as a ZCZ sequence set. The newly obtained A-ZCZ sequence sets include quasi-optimal ZCZ sequence sets of which the zero-cross-correlation zone (ZCCZ) length between different sequence subsets is larger than the mathematical upper bound of conventional ZCZ sequence sets. A new method for extending the A-ZCZ sequence sets is also presented in the present paper.

Non-negative matrix factorization (NMF) is widely used for music transcription because of its efficiency. However, the conventional NMF-based music transcription algorithm often causes harmonic confusion errors or time split-up errors, because the NMF decomposes the time-frequency data according to the activated frequency in its time. To solve these problems, we proposed an NMF with temporal continuity and harmonicity constraints. The temporal continuity constraint prevented the time split-up of the continuous time components, and the harmonicity constraint helped to bind the fundamental with harmonic frequencies by reducing the additional octave errors. The transcription performance of the proposed algorithm was compared with that of the conventional algorithms, which showed that the proposed method helped to reduce additional false errors and increased the overall transcription performance.

This paper presents a Microscopic Local Binary Pattern (MLBP) for texture classification. The conventional LBP methods which rely on the uniform patterns discard some texture information by merging the nonuniform patterns. MLBP preserves the information by classifying the nonuniform patterns using the structure similarity at microscopic level. First, the nonuniform patterns are classified into three groups using the macroscopic information. Second, the three groups are individually divided into several subgroups based on the microscopic structure information. The experiments show that MLBP achieves a better result compared with the other LBP related methods.

This paper focuses on the latest research of switching arc both in vacuum and SF6 substitutes in our group. The crucial characteristics of vacuum arc are illustrated, including the motion and distribution of single cathode spot and multiple cathode spots, the influence of axial magnetic field on arc plasma characteristics, the influence of composite magnetic field on cathode jets, and the study of anode activities. Meanwhile, the arc characteristics in SF6 and its substitutes (Ar, CO2 and N2) at different pressures and gap distances are investigated by experiments and simulation.

A novel watermarked MDC system based on the SFQ algorithm and the sub-sampling method is proposed in this paper. Sub-sampling algorithm is applied onto the transformed image to introduce some redundancy between different channels. Secret information is embedded into the preprocessed sub-images. Good performance of the new system to defense the noise and the compression attacks is shown in the experimental results.

Accurate estimation of Software Code Size is important for developing cost-efficient embedded systems. The Code Size affects the amount of system resources needed, like ROM and RAM memory, and processing capacity. In our previous work, we have estimated the Code Size based on CFP (COSMIC Function Points) within 15% accuracy, with the purpose of deciding how much ROM memory to fit into products with high cost pressure. Our manual CFP measurement process would require 2.5 man years to estimate the ROM size required in a typical car. In this paper, we want to investigate how the manual effort involved in estimation of Code Size can be minimized. We define a UML Profile capturing all information needed for estimation of Code Size, and develop a tool for automated estimation of Code Size based on CFP. A case study will show how UML models save manual effort in a realistic case.

This paper develops a methodology of crosstalk analysis/measurement techniques for the design and fabrication of the MEMs (Micro-ElectroMichanical system) probe card. By introducing more ground pins into the connector pins, the crosstalk characteristics can be enhanced and a design guide for the parameters, such as pin's size and pitch is proposed to satisfy the given crosstalk limitation of -30 dB for reliable high speed signal transfer. The paper also presents a novel method to characterize scattering parameters of multiport interconnect circuits with a 4-port VNA (Vector Network Analyzer). By employing the re-normalization of scattering matrices with different reference impedances at other ports, data obtained from 4-port configuration measurements can be synthesized to build a full scattering matrix of the DUT (Device-Under-Test, MEMs probe connector pins). In comparison to the conventional 2-port VNA re-normalization method, proposed technique has two advantages: saving of measuring time, and enhanced accuracy even with open-ended unmeasured ports. A good agreement of the estimated and correct S parameters verifies the validness of the proposed algorithm.