Fast proliferation of mobile Internet and high-demand mobile applications necessitates the introduction of different priority classes in next-generation cellular networks. This is especially crucial for efficient use of radio resources in the heterogeneous and virtualized network environments. Despite the fact that many analytical tools have been proposed for capacity and radio resource modelling in cellular networks, only a few of them explicitly incorporate priorities among services. We propose a novel analytical model to analyse the performance of a priority-based cellular CDMA system with finite source population. When the cell load is above a certain level, low-priority calls may be blocked to preserve the quality of service of high-priority calls. The proposed model leads to an efficient closed-form solution that enables fast and very accurate calculation of resource occupancy of the CDMA system and call blocking probabilities, for different services and many priority classes. To achieve them, the system is modelled as a continuous-time Markov chain. We evaluate the accuracy of the proposed analytical model by means of computer simulations and find that the introduced approximation errors are negligible.

In the future Internet of Things/M2M network, enormous amounts of data generated from sensors must be processed and utilized by cloud applications. In recent years, sensor data stream delivery, which collects and sends sensor data periodically, has been attracting great attention. As for sensor data stream delivery, the receivers have different delivery cycle requirements depending on the applications or situations. In this paper, we propose a sensor data stream delivery method to accommodate heterogeneous cycles on the cloud. The proposed method uses distributed hashing to determine relay nodes on the cloud and construct delivery paths autonomously. We evaluate the effectiveness of the proposed method in simulations. The simulation results show that the proposed method halves the maximum load of nodes compared to the baseline methods and achieves high load balancing.

This paper analyzes three passive noise shaping techniques in a SAR ADC. These passive noise shaping techniques can realize 1st and 2nd order noise shaping. These proposed opamp-less noise shaping techniques are realized by charge-redistribution. This means that the proposals maintain the basic architecture and operation principle of a charge-redistribution SAR ADC. Since the proposed techniques work in a passive mode, the proposals have high power efficiency. Meanwhile, the proposed noise shaping SAR ADCs are robust to feature size scaling and power supply reduction. Flicker noise is not introduced into the ADC by passive noise shaping techniques. Therefore, no additional calibration techniques for flicker noise are required. The noise shaping effects of the 1st and 2nd order noise shaping are verified by behavioral simulation results. The relationship between resolution improvement and oversampling rate is also explored in this paper.

This paper proposes the proportional static-phase-error reduction (SPER) for the frequency-multiplier-based delay-locked-loop (DLL) architecture. The frequency multiplier (FM) can synthesize a combined clock to solve the high operational frequency of DLL. However, FM is sensitive to the static phase error of DLL. A SPER loop adopts a timing amplifier and a coarse-fine tuning technique to enhance the deterministic jitter of FM. The SPER loop proportionally reduces the static phase error and can extend the operating range of FM.

A single-flux-quantum (SFQ) arithmetic logic unit (ALU) was designed and tested to evaluate the effectiveness of introducing dynamically reconfigurable logic gates in the design of a superconducting logic circuit. We designed and tested a bit-serial SFQ ALU that can perform six arithmetic/logic functions by using a dynamically reconfigurable AND/OR gate. To ensure stable operation of the ALU, we improved the operating margin of the SFQ AND/OR gate by employing a partially shielded structure where the circuit is partially surrounded by under- and over-ground layers to reduce parasitic inductances. Owing to the introduction of the partially shielded structure, the operating margin of the dynamically reconfigurable AND/OR gate can be improved without increasing the circuit area. This ALU can be designed with a smaller circuit area compared with the conventional ALU by using the dynamically reconfigurable AND/OR gate. We implemented the SFQ ALU using the AIST 2.5kA/cm2 Nb standard process 2. We confirmed high-speed operation and correct reconfiguration of the SFQ ALU by a high-speed test. The measured maximum operation frequency was 30GHz.

We present a hierarchical replicated state machine (H-RSM) and its corresponding consensus protocol D-Paxos for replication across multiple data centers in the cloud. Our H-RSM is based on the idea of parallel processing and aims to improve resource utilization. We detail D-Paxos and theoretically prove that D-Paxos implements an H-RSM. With batching and logical pipelining, D-Paxos efficiently utilizes the idle time caused by high-latency message transmission in a wide-area network and available bandwidth in a local-area network. Experiments show that D-Paxos provides higher throughput and better scalability than other Paxos variants for replication across multiple data centers. To predict the optimal batch sizes when D-Paxos reaches its maximum throughput, an analytical model is developed theoretically and validated experimentally.

This article proposes a versatile model of a multiservice queueing system with elastic traffic. The model can provide a basis for an analysis of telecommunications and computer network systems, internet network systems in particular. The advantage of the proposed approach is a possibility of a determination of delays in network nodes for a number of selected classes of calls offered in modern telecommunications networks.

One of the fundamental problems in many-pixel detectors implemented in cryogenics environments is the number of bias and read-out wires. If one targets a megapixel range detector, number of wires should be significantly reduced. One possibility is that the detectors are serially connected and biased by using only one line and read-out is accomplished by on-chip circuitry. In addition to the number of pixels, the detectors should have fast response times, low dead times, high sensitivities, low inter-pixel crosstalk and ability to respond to simultaneous irradiations to individual pixels for practical purposes. We have developed an equivalent circuit model for a serially connected superconducting strip line detector (SSLD) array together with the read-out electronics. In the model we take into account the capacitive effects due to the ground plane under the detector, effects of the shunt resistors fabricated under the SSLD layer, low pass filters placed between the individual pixels that enable individual operation of each pixel and series resistors that prevents the DC bias current flowing to the read-out electronics as well as adjust the time constants of the inductive SSLD loop. We explain the results of investigation of the following parameters: Crosstalk between the neighbor pixels, response to simultaneous irradiation, dead times, L/R time constants, low pass filters, and integration with the SFQ front-end circuit. Based on the simulation results, we show that SSLDs are promising devices for detecting a wide range of incident radiation such as neurons, X-rays and THz waves in many-pixel configurations.

Radio frequency over fiber (RoF) advanced technology is already integrated into current 3G and 4G radio access networks in which the digital unit and remote radio head equipped with nonlinear high power amplifiers (HPAs) are connected through the RoF-based fronthaul links. In this study, we investigated the degradation in the adjacent channel leakage ratio (ACLR) of equipment with the adaptive linearizer RF HPA when both the direct and feedback paths of the transmitting system include RoF links. We show that an ACLR exceeding -57dBc @ 5-MHz offset, which completely satisfies the requirements of the 3GPP technical specifications, can be achieved for a 20-W-class Doherty power amplifier linearized through commercial RoF links. Experiments showed that the achieved ACLR strongly depends on the RoF-link noise figure and that most of the nonlinear distortions caused by RoF can be completely suppressed with the proposed joint linearization approach for simultaneous linearization of RoF and HPA nonlinearities with a single common “joint” linearizer. Experimental results confirm significant ACLR performance enhancements as a result of RoF noise floor reduction, which is achieved under RoF driving conditions optimized together with joint RoF and HPA linearization. Our joint linearization approach via RoF links is confirmed to be applicable for next-generation mobile fronthaul architectures.

Sentence similarity computation is an increasingly important task in applications of natural language processing such as information retrieval, machine translation, text summarization and so on. From the viewpoint of information theory, the essential attribute of natural language is that the carrier of information and the capacity of information can be measured by information content which is already successfully used for word similarity computation in simple ways. Existing sentence similarity methods don't emphasize the information contained by the sentence, and the complicated models they employ often need using empirical parameters or training parameters. This paper presents a fully unsupervised computational model of sentence semantic similarity. It is also a simply and straightforward model that neither needs any empirical parameter nor rely on other NLP tools. The method can obtain state-of-the-art experimental results which show that sentence similarity evaluated by the model is closer to human judgment than multiple competing baselines. The paper also tests the proposed model on the influence of external corpus, the performance of various sizes of the semantic net, and the relationship between efficiency and accuracy.

Recovery of low-rank matrices has seen significant activity in many areas of science and engineering, motivated by theoretical results for exact reconstruction guarantees and interesting practical applications. Recently, numerous methods incorporated the nuclear norm to pursue the convexity of the optimization. However, this greatly restricts its capability and flexibility in dealing with many practical problems, where the singular values have clear physical meanings. This paper studies a generalized non-convex low-rank approximation, where the singular values are in lp-heuristic. Then specific results are derived for image restoration, including denoising and deblurring. Extensive experimental results on natural images demonstrate the improvement of the proposed method over the recent image restoration methods.

On SNS (Social Networking Services), detecting Sybils is an urgent demand. The most famous approach is called “SybilRank” scheme where each node evenly distributes its trust value starting from honest seeds and detects Sybils based on the trust value. Furthermore, Zhang et al. propose to avoid trust values from being distributed into Sybils by pruning suspicious relationships before performing SybilRank. However, we point out that the above two schemes have shortcomings that must be remedied. In the former scheme, seeds are concentrated on the specific communities because they are selected from nodes that have largest number of friends, and thus the trust value is not evenly distributed. In the latter one, a sophisticated attacker can avoid graph pruning by making relationships between Sybil nodes. In this paper, we propose a robust seed selection and graph pruning scheme to detect Sybil nodes more accurately. To more evenly distribute trust value into honest nodes, we first detect communities in the SNS and select honest seeds from each detected community. And then, by leveraging the fact that Sybils cannot make dense relationships with honest nodes, we also propose a graph pruning scheme based on the density of relationships between trusted nodes. We prune the relationships which have sparse relationships with trusted nodes and this enables robust pruning malicious relationships even if the attackers make a large number of common friends. By the computer simulation with real dataset, we show that our scheme improves the detection accuracy of both Sybil and honest nodes.

The recently proposed distributed adaptive direct position determination (D-ADPD) algorithm provides an efficient way to locating a radio emitter using a sensor network. However, this algorithm may be suboptimal in the situation of colored emitted signals. We propose an enhanced distributed adaptive direct position determination (EDA-DPD) algorithm. Simulations validate that the proposed EDA-DPD outperforms the D-ADPD in colored emitted signals scenarios and has the similar performance with the D-ADPD in white emitted signal scenarios.

Let R=Z4 be the integer ring mod 4 and C be a linear code over R. The code C is called a triple cyclic code of length (r, s, t) over R if the set of its coordinates can be partitioned into three parts so that any cyclic shift of the coordinates of the three parts leaves the code invariant. These codes can be viewed as R[x]-submodules of R[x]/×R[x]/×R[x]/. In this paper, we determine the generator polynomials and the minimum generating sets of this kind of codes.

A negative capacitor is fabricated using poly(vinylidene fluoride-trifluoroethylene) copolymer and connected in series to an a-IZO TFT. It is experimentally demonstrated that the negative capacitance of the negative capacitor can create steep switching in the a-IZO TFT (e.g., a subthreshold slope change from 342mV/decade to 102mV/decade at room-temperature).

To find the optimal design in alleviating the effect of random variations on a SRAM cell, a worst-case sampling method is used. From the quantitative analysis using this method, the optimal designs for a process-variation-tolerant 22-nm FinFET-based 6-T SRAM cell are proposed and implemented through cell layouts and a dual-threshold-voltage designs.

As three dimensional (3D) discrete wavelet transform (DWT) is widely used for high resolution volumetric data compression, and to further improve the performance of lossless coding, the adaptive directional lifting (ADL) structure based on non-separable 3D DWT with a (5,3) filter is proposed in this paper. The proposed 3D DWT has less lifting steps and better prediction performance compared to the existing separable 3D DWT with fixed filter coefficients. It also has compatibility with the conventional DWT defined by the JPEG2000 international standard. The proposed method shows comparable and better results with the non-separable 3D DWT and separable 3D DWT and it is effective for lossless coding of high resolution volumetric data.

Human body segmentation has many applications in a wide variety of image processing tasks, from intelligent vehicles to entertainment. A substantial amount of research has been done in the field of segmentation and it is still one of the active research areas, resulting in introduction of many innovative methods in literature. Still, until today, a method that can overcome the human segmentation problems and adapt itself to different kinds of situations, has not been introduced. Many of methods today try to use the graph-cut framework to solve the segmentation problem. Although powerful, these methods rely on a distance penalty term (intensity difference or RGB color distance). This term does not always lead to a good separation between two regions. For example, if two regions are close in color, even if they belong to two different objects, they will be grouped together, which is not acceptable. Also, if one object has multiple parts with different colors, e.g. humans wear various clothes with different colors and patterns, each part will be segmented separately. Although this can be overcome by multiple inputs from user, the inherent problem would not be solved. In this paper, we have considered solving the problem by making use of a human probability map, super-pixels and Grab-cut framework. Using this map relives us from the need for matching the model to the actual body, thus helps to improve the segmentation accuracy. As a result, not only the accuracy has improved, but also it also became comparable to the state-of-the-art interactive methods.