Spin-torque transfer magnetic random access memory (STT-MRAM) is a promising technology for next generation nonvolatile universal memory because it reduces the high write current required by conventional MRAM and enables write current scaling as technology becomes smaller in size. However, the sensing margin is not improved in STT-MRAM and tends to decrease with technology scaling due to the lowered supply voltage and increased process variation. Moreover, read disturbance, which is an unwanted write in a read operation, can occur in STT-MRAM because its read and write operations use the same path. To overcome these problems, we present a load-line analysis method, which is useful for systematically analyzing the impacts of transistor size and gate voltage of MOSFETs on the sensing margin, and also propose an optimization procedure for the commonly applicable MRAM sensing circuits. This methodology constitutes an effective means to optimize the transistor size and gate voltage of MOSFETs and thus maximizes the sensing margin without causing read disturbance.

In the area of wireless sensor networks, the efficient spatial query processing based on the locations of sensor nodes is required. Especially, spatial queries on two sensor networks need a distributed spatial join processing among the sensor networks. Because the distributed spatial join processing causes lots of wireless transmissions in accessing sensor nodes of two sensor networks, our goal of this paper is to reduce the wireless transmissions for the energy efficiency of sensor nodes. In this paper, we propose an energy-efficient distributed spatial join algorithm on two heterogeneous sensor networks, which performs in-network spatial join processing. To optimize the in-network processing, we also propose a Grid-based Rectangle tree (GR-tree) and a grid-based approximation function. The GR-tree reduces the wireless transmissions by supporting a distributed spatial search for sensor nodes. The grid-based approximation function reduces the wireless transmissions by reducing the volume of spatial query objects which should be pushed down to sensor nodes. Finally, we compare naive and existing approaches through extensive experiments and clarify our approach's distinguished features.

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.

When developing an index for a similarity search in metric spaces, how to divide the space for effective search pruning is a fundamental issue. We present Maximal Metric Margin Partitioning (MMMP), a partitioning scheme for similarity search indexes. MMMP divides the data based on its distribution pattern, especially for the boundaries of clusters. A partitioning boundary created by MMMP is likely to be located in a sparse area between clusters. Moreover, the partitioning boundary is at maximum distances from the two cluster edges. We also present an indexing scheme, named the MMMP-Index, which uses MMMP and pivot filtering. The MMMP-Index can prune many objects that are not relevant to a query, and it reduces the query execution cost. Our experimental results show that MMMP effectively indexes clustered data and reduces the search cost. For clustered data in a vector space, the MMMP-Index reduces the computational cost to less than two thirds that of comparable schemes.

Consider a client who intends to perform a massive computing task comprsing a number of sub-tasks, while both storage and computation are outsourced by a third-party service provider. How could the client ensure the integrity and completeness of the computation result? Meanwhile, how could the assurance mechanism incur no disincentive, e.g., excessive communication cost, for any service provider or client to participate in such a scheme? We detail this problem and present a general model of execution assurance for massive computing tasks. A series of key features distinguish our work from existing ones: a) we consider the context wherein both storage and computation are provided by untrusted third parties, and client has no data possession; b) we propose a simple yet effective assurance model based on a novel integration of the machineries of data authentication and computational private information retrieval (cPIR); c) we conduct an analytical study on the inherent trade-offs among the verification accuracy, and the computation, storage, and communication costs.

This paper reports the effect of corpus size on case frame acquisition for predicate-argument structure analysis in Japanese. For this study, we collect a Japanese corpus consisting of up to 100 billion words, and construct case frames from corpora of six different sizes. Then, we apply these case frames to syntactic and case structure analysis, and zero anaphora resolution, in order to investigate the relationship between the corpus size for case frame acquisition and the performance of predicate-argument structure analysis. We obtained better analyses by using case frames constructed from larger corpora; the performance was not saturated even with a corpus size of 100 billion words.

This letter proposes a low-complexity scheme for estimating the frequency of a complex sinusoid in flat fading channels. The proposed estimator yields an estimation performance that is comparable to the existing autocorrelation-based frequency estimator, while retaining the same frequency range. Its implementation complexity is much lower than the conventional scheme, thus this allows for fast estimation in real time.

In this letter, a new CCM material, adding Ni powder to a conventional CCM, for X-band applications is designed and analyzed to improve the SE. To obtain the SE of the fabricated CCM accurately, material constants of the CCM of the permittivity and permeability were extracted using transmission/reflection measurements. Using the material constants derived from the measurement, the SE was calculated and the results were verified using a commercial full-wave three-dimensional electromagnetic wave simulator. The SE of the proposed the CCM was improved by approximately 4 dB in the X band compared to that of a conventional CCM. The CCM proposed in this paper can be applied as a shielding material as well as for housing of various communication systems and electrical instruments.

A diversity scheme with Fractional Sampling (FS) in an OFDM receiver has been investigated recently. Through FS, it is possible to separate multipath components and obtain diversity gain in OFDM systems. Enlargement of the bandwidth of the total frequency response between transmit and receive baseband filters allows the FS scheme to achieve path diversity. However, the transmit filter has to be designed according to the spectrum mask of the wireless standards such as IEEE802.11a/g to avoid interference to the other communication systems and the frequency response of the composite channel including the transmit and receive filters has often been set to minimal bandwidth to eliminate adjacent channel signals. In order to achieve the maximum signal-to-noise ratio (SNR), the same filter is commonly used in the transmitter and the receiver. In this paper, the trade-off among the SNR deterioration, adjacent channel interference, and the diversity gain due to the enlargement of the bandwidth of the receive filter is investigated. Numerical results from computer simulations indicate that the BER performance with wider bandwidth in the receiver shows better performance than that with the minimal bandwidth for maximizing the SNR in certain conditions.

The bit-error-rate (BER) performance predicted by the semi-analytical evolution technique proposed by Li Ping et al. becomes inaccurate for parallel concatenated coded interleave-division multiple-access (PCC-IDMA) systems. To solve this problem, we develop a novel evolution technique of such systems. Numerical results show that the predicted performance agrees well with the simulation results, and that this technique is useful for system optimization.

Let V(φ) be a shift invariant subspace of L2(R) with a Riesz or frame generator φ(t). We take φ(t) suitably so that the regular sampling expansion : f(t) = f(n)S(t-n) holds on V(φ). We then find conditions on the generator φ(t) and various bounds of the perturbation {δ n }n∈Z under which an irregular sampling expansion: f(t) = f(n+ δn)Sn(t) holds on V(φ). Some illustrating examples are also provided.

In ubiquitous sensor networks, the estimation accuracy of a node location is limited due to the presence of non-line-of-sight (NLOS) paths. To mitigate the NLOS effects, this letter proposes a simple algorithm where NLOS identification is carried out using angle-of-arrival (AOA). Simulation results show that the use of AOA improves NLOS identification rates and location estimation accuracy.

In digital signal processing, the sampling theorem states that any real valued function f can be reconstructed from a sequence of values of f that are discretely sampled with a frequency at least twice as high as the maximum frequency of the spectrum of f. This theorem can also be applied to functions over finite domain. Then, the range of frequencies of f can be expressed in more detail by using a bounded set instead of the maximum frequency. A function whose range of frequencies is confined to a bounded set is referred to as bandlimited function. And a sampling theorem for bandlimited functions over Boolean domain has been obtained. Here, it is important to obtain a sampling theorem for bandlimited functions not only over Boolean domain (GF(2)n domain) but also over GF(q)n domain, where q is a prime power and GF(q) is Galois field of order q. For example, in experimental designs, although the model can be expressed as a linear combination of the Fourier basis functions and the levels of each factor can be represented by GF(q), the number of levels often take a value greater than two. However, the sampling theorem for bandlimited functions over GF(q)n domain has not been obtained. On the other hand, the sampling points are closely related to the codewords of a linear code. However, the relation between the parity check matrix of a linear code and any distinct error vectors has not been obtained, although it is necessary for understanding the meaning of the sampling theorem for bandlimited functions. In this paper, we generalize the sampling theorem for bandlimited functions over Boolean domain to a sampling theorem for bandlimited functions over GF(q)n domain. We also present a theorem for the relation between the parity check matrix of a linear code and any distinct error vectors. Lastly, we clarify the relation between the sampling theorem for functions over GF(q)n domain and linear codes.

A method of fault diagnosis was proposed for power electronics circuits based on S transforms similarity. At first, the standard module time-frequency matrixes of S transforms for all fault signals were constructed, then the similarity of fault signals' module time-frequency matrixes to standard module time-frequency matrixes were calculated, and according to the principle of maximum similarity, the faults were diagnosed. The simulation result of fault diagnosis of a thyristor in a three-phase full-bridge controlled rectifier shows that the method can accurately diagnose faults and locate the fault element for power electronics circuits, and it has excellent performance for noise robustness and calculation complexity, thus it also has good practical engineering value in the solution to the fault problems for power electronics circuits.

Constriction resistance is calculated by numerical analysis using Laplace's equations for electric potential of steady state in many cases of contact spot dispersion-status. The results show that contact resistance does not increase beyond 1.5 times even if the total real contact area is about 15% of the apparent contact area. When real contact area is at least about 60% of the apparent contact area, the contact resistance is approximately the same as the constriction resistance acquired from the apparent contact area. When the real contact area is about 50% of the apparent contact area, the contact resistance is approximately constant without regard to the contact shape and contact-point dispersion layout. Therefore, it is proved that contact resistance can be practically calculated using apparent contact area instead of real contact area when there are many contact points caused by metal to metal contact.

Bag-of-Visual-Words representation has recently become popular for scene classification. However, learning the visual words in an unsupervised manner suffers from the problem when faced these patches with similar appearances corresponding to distinct semantic concepts. This paper proposes a novel supervised learning framework, which aims at taking full advantage of label information to address the problem. Specifically, the Gaussian Mixture Modeling (GMM) is firstly applied to obtain "semantic interpretation" of patches using scene labels. Each scene induces a probability density on the low-level visual features space, and patches are represented as vectors of posterior scene semantic concepts probabilities. And then the Information Bottleneck (IB) algorithm is introduce to cluster the patches into "visual words" via a supervised manner, from the perspective of semantic interpretations. Such operation can maximize the semantic information of the visual words. Once obtained the visual words, the appearing frequency of the corresponding visual words in a given image forms a histogram, which can be subsequently used in the scene categorization task via the Support Vector Machine (SVM) classifier. Experiments on a challenging dataset show that the proposed visual words better perform scene classification task than most existing methods.

Adaptable workflow participant assignment (WPA) is crucial to the efficiency and quality of workflow execution. This paper proposes an ontology-based approach to adaptable WPA (OWPA). OWPA introduces domain ontology to organize the enterprise data and uses a well-defined OWPA rule to express an authorization constraint. OWPA can represent more complex authorization constraints by flexibly using the enterprise data, the workflow data, the user-input data, and the built-in functions. By a high-usability interactive interface, OWPA allows users to define and modify the OWPA rules easily without any programming work. Moreover, OWPA is bound to the workflow modeling tool and the workflow monitor respectively to adapt to dynamic workflow modification in workflow definitions and workflow instances. OWPA has been applied in three enterprises in China.

With the big success of 802.11 wireless networks, there have been many proposals addressing end-to-end QoS guarantees in 802.11 WLAN. However, we have found that current end-to-end QoS architectures lack of one or more important properties such as cross-layer interaction, end-to-end integration, reconfigurability and modularity. In this work, we present an end-to-end reference QoS architecture for 802.11 WLAN that encapsulates in an unifying fashion software-based QoS components (mechanisms, algorithms, services), proposed in the literature. To show the usefulness and correctness of the reference architecture, we present three case studies of end-to-end QoS architectures addressing different QoS requirements such as bandwidth and delay with different approaches such as differentiated services and integrated services. We will give an architectural comparison and performance evaluation of these architectures. We believe the reference QoS architectures can help QoS designers to understand the importance and the complexity of various QoS components during the design phase and thus choose these QoS components appropriately.

This paper proposes a cross-layer packet scheduling scheme for QoS support in audio-video transmission with IEEE 802.11e HCCA and assesses application-level QoS and QoE of the scheduling scheme under lossy channel conditions. In the proposed scheme, the access point (AP) basically allocates transmission opportunity (TXOP) for each station in a service interval (SI) like the reference scheduler of the IEEE 802.11e standard, which is referred to as the TGe scheme in this paper. In the proposed scheme, however, the AP calculates the number of MAC service data units (MSDUs) arrived in an SI, considering the inter-arrival time of audio samples and that of video frames, which are referred to as media units (MUs), at the application layer. The AP then gives additional TXOP duration in the SI to stations which had audio or video MAC protocol data units (MPDUs) in their source buffers at the end of the previous TXOP. In addition, utilizing video frame information from the application layer, we propose video frame skipping at the MAC-level of a source station. If a station fails to transmit a video MPDU, it drops all the following video MPDUs in the source buffer until the next intra-coded frame comes to the head of the buffer. We compare the reference scheduler (TGe scheme), the proposed packet scheduling scheme with and without the video frame skipping at the source in terms of application-level QoS and QoE. We discuss the effectiveness of the proposed packet scheduling scheme from a viewpoint of QoE as well as QoS. Numerical results reveal that the proposed packet scheduling scheme can achieve higher quality than the TGe scheme under lossy channel conditions. We also show that the proposed scheduling scheme can improve the QoS and QoE by using the video frame skipping at the source. Furthermore, we also examine the effect of SI on the QoS and QoE of the proposed packet scheduling scheme and obtain that the appropriate value of SI is equal to the inter-arrival time of video frame.

Chinese new words and their part-of-speech (POS) are particularly problematic in Chinese natural language processing. With the fast development of internet and information technology, it is impossible to get a complete system dictionary for Chinese natural language processing, as new words out of the basic system dictionary are always being created. A latent semi-CRF model, which combines the strengths of LDCRF (Latent-Dynamic Conditional Random Field) and semi-CRF, is proposed to detect the new words together with their POS synchronously regardless of the types of the new words from the Chinese text without being pre-segmented. Unlike the original semi-CRF, the LDCRF is applied to generate the candidate entities for training and testing the latent semi-CRF, which accelerates the training speed and decreases the computation cost. The complexity of the latent semi-CRF could be further adjusted by tuning the number of hidden variables in LDCRF and the number of the candidate entities from the Nbest outputs of the LDCRF. A new-words-generating framework is proposed for model training and testing, under which the definitions and distributions of the new words conform to the ones existing in real text. Specific features called "Global Fragment Information" for new word detection and POS tagging are adopted in the model training and testing. The experimental results show that the proposed method is capable of detecting even low frequency new words together with their POS tags. The proposed model is found to be performing competitively with the state-of-the-art models presented.