In this paper, dependency of transmission loss of shielded-flexible printed circuits (FPC) for differential-signaling on thickness of conductive shield is studied by numerical modeling based on an equivalent circuit model compared with the experimental results. Especially, the transmission loss due to the thin conductive shield is focused. The insufficient shielding performance for near magnetic field decreases the resistance due to the thin conductive shield. It is shown that the resistance due to the thin conductive shield at lower frequencies is smaller than that in the “thick conductive shield” case.

With the expansion of the Internet, the number of available Web services has increased. Web service clustering to identify functionally similar clusters has become a major approach to the efficient discovery of suitable Web services. In this study, we propose a Web service clustering approach that uses novel ontology learning and a similarity calculation method based on the specificity of an ontology in a domain with respect to information theory. Instead of using traditional methods, we generate the ontology using a novel method that considers the specificity and similarity of terms. The specificity of a term describes the amount of domain-specific information contained in that term. Although general terms contain little domain-specific information, specific terms may contain much more domain-related information. The generated ontology is used in the similarity calculations. New logic-based filters are introduced for the similarity-calculation procedure. If similarity calculations using the specified filters fail, then information-retrieval-based methods are applied to the similarity calculations. Finally, an agglomerative clustering algorithm, based on the calculated similarity values, is used for the clustering. We achieved highly efficient and accurate results with this clustering approach, as measured by improved average precision, recall, F-measure, purity and entropy values. According to the results, specificity of terms plays a major role when classifying domain information. Our novel ontology-based clustering approach outperforms comparable existing approaches that do not consider the specificity of terms.

We propose a cooperative cognitive radio network (CCRN) with secondary users (SUs) employing two simultaneous transmit and receive (STAR) antennas. In the proposed framework of full-duplex (FD) multiple-input-multiple-output (MIMO) CCRN, the region of achievable rate is expanded via FD communication among SUs enabled by the STAR antennas adopted for the SUs. The link capacity of the proposed framework is analyzed theoretically. It is shown through numerical analysis that the proposed FD MIMO-CCRN framework can provide a considerable performance gain over the conventional frameworks of CCRN and MIMO-CCRN.

We prove generalization error bounds of classes of low-rank matrices with some norm constraints for collaborative filtering tasks. Our bounds are tighter, compared to known bounds using rank or the related quantity only, by taking the additional L1 and L∞ constraints into account. Also, we show that our bounds on the Rademacher complexity of the classes are optimal.

In this paper, we present an Energy-efficient Mobile Group Clustering (EMGC) protocol that supports group mobility and a group handover scheme. The mobile sensor nodes are divided into three categories, namely cluster heads, group leaders and group members. In our cluster formation and group handover scheme, group leaders and cluster heads do most of the communications to save on energy consumption during which group members are placed in the sleep condition. This scheme will reduce the number of control packets and frequent topology changes in the networks. Simulation results show that the EMGC protocol outperforms MN-LEACH, GMAC, MBC protocols in terms of energy dissipation and the number of data items received at a base station.

We review the recent advances on strain and temperature sensing techniques based on multimodal interference in perfluorinated (PF) graded-index (GI) polymer optical fibers (POFs). First, we investigate their fundamental characteristics at 1300nm. When the core diameter is 62.5µm, we obtain strain and temperature sensitivities of -112pm/µε and +49.8nm/°C, the absolute values of which are, by simple calculation, approximately 13 and over 1800 times as large as those in silica GI multimode fibers, respectively. These ultra-high strain and temperature sensitivities probably originate from the unique PF polymer used as core material. Subsequently, we show that the temperature sensitivity (absolute value) is significantly enhanced with increasing temperature toward ∼70°C, which is close to the glass-transition temperature of the core polymer. When the core diameter is 62.5µm, the sensitivity at 72°C at 1300nm is 202nm/°C, which is approximately 26 times the value obtained at room temperature and >7000 times the highest value previously reported using a silica multimode fiber. Then, we develop a single-end-access configuration of this strain and temperature sensing system, which enhances the degree of freedom in embedding the sensors into structures. The light Fresnel-reflected at the distal open end of the POF is exploited. The obtained strain and temperature sensitivities are shown to be comparable to those in two-end-access configurations. Finally, we discuss the future prospects and give concluding remarks.

The abnormal crowd behavior detection is an important research topic in computer vision to improve the response time of critical events. In this letter, we introduce a novel method to detect and localize the crowd gathering in surveillance videos. The proposed foreground stillness model is based on the foreground object mask and the dense optical flow to measure the instantaneous crowd stillness level. Further, we obtain the long-term crowd stillness level by the leaky bucket model, and the crowd gathering behavior can be detected by the threshold analysis. Experimental results indicate that our proposed approach can detect and locate crowd gathering events, and it is capable of distinguishing between standing and walking crowd. The experiments in realistic scenes with 88.65% accuracy for detection of gathering frames show that our method is effective for crowd gathering behavior detection.

Non-volatile memories are a promising alternative to memory design but data stored in them still may be destructed due to crosstalk and radiation. The data stored in them can be restored by using error-correcting codes but they require extra bits to correct bit errors. One of the largest problems in non-volatile memories is that they consume ten to hundred times more energy than normal memories in bit-writing. It is quite necessary to reduce writing bits. Recently, a REC code (bit-write-reducing and error-correcting code) is proposed for non-volatile memories which can reduce writing bits and has a capability of error correction. The REC code is generated from a linear systematic error-correcting code but it must include the codeword of all 1's, i.e., 11…1. The codeword bit length must be longer in order to satisfy this condition. In this letter, we propose a method to generate a relaxed REC code which is generated from a relaxed error-correcting code, which does not necessarily include the codeword of all 1's and thus its codeword bit length can be shorter. We prove that the maximum flipping bits of the relaxed REC code is still limited theoretically. Experimental results show that the relaxed REC code efficiently reduce the number of writing bits.

In this letter, we study a wireless powered communication network (WPCN) with non-orthogonal multiple access (NOMA), where the user clustering scheme that groups each two users in a cluster is adopted to guarantee the system performance. The two users in a cluster transmit data simultaneously via NOMA, while time division multiple access (TDMA) is used among clusters. We aim to maximize the system throughput by finding the optimal cluster permutation and the optimal time allocation, which can be obtained by solving the optimization problems corresponding to all cluster permutations. The closed-form solution of each optimization problem is obtained by exploiting its constraint structures. However, the complexity of this exhaustive method is quite high, we further propose a sub-optimal clustering scheme with low complexity. The simulation results demonstrate the superiority of the proposed scheme.

By focusing on the recent swing to the centralized approach by the software defined network (SDN), this paper presents a novel network architecture for refactoring the current distributed Internet protocol (IP) by not only utilizing the SDN itself but also implementing its cooperation with the optical transport layer. The first IP refactoring is for flexible network topology reconfiguration: the global routing and explicit routing functions are transferred from the distributed routers to the centralized SDN. The second IP refactoring is for cost-efficient maintenance migration: we introduce a resource portable IP router that can behave as a shared backup router by cooperating with the optical transport path switching. Extensive evaluations show that our architecture makes the current IP network easier to configure and more scalable. We also validate the feasibility of our proposal.

This paper introduces a formation method for 3-dimensional 6 ch.×6 ch. shuffling structures with graded-index (GI) circular core in a multimode polymer optical waveguide for optical printed circuit boards (OPCBs) using a unique photomask-free fabrication technique named the Mosquito method. The interchannel pitch of the fabricated waveguides is 250µm, where all the channels consist of both horizontal and vertical bending structures and the last 6 channels in parallel cross over the first 6 channels. We also report 3-dimensional S-shaped polymer waveguides. In the S-shaped waveguides, the first and last 6 channels with both horizontal and vertical core bending composing the above 3-dimensional shuffling waveguide are separated, in order to evaluate the effect of over-crossing on the loss. It is experimentally confirmed that there is no excess insertion loss due to the shuffling structure in the 3-D shuffling waveguide. The evaluated crosstalk of the 3-D shuffling waveguide is lower than -30dB. The 3-D shuffling waveguide proposed in this paper will be a promising component to achieve high bandwidth density wiring for on-board optical interconnects.

An important step for improving software analyzability is applying refactorings during the maintenance phase to remove bad smells, especially the long method bad smell. Long method bad smell occurs most frequently and is a root cause of other bad smells. However, no research has proposed an approach to repeating refactoring identification, suggestion, and application until all long method bad smells have been removed completely without reducing software analyzability. This paper proposes an effective approach to identifying refactoring opportunities and suggesting an effective refactoring set for complete removal of long method bad smell without reducing code analyzability. This approach, called the long method remover or LMR, uses refactoring enabling conditions based on program analysis and code metrics to identify four refactoring techniques and uses a technique embedded in JDeodorant to identify extract method. For effective refactoring set suggestion, LMR uses two criteria: code analyzability level and the number of statements impacted by the refactorings. LMR also uses side effect analysis to ensure behavior preservation. To evaluate LMR, we apply it to the core package of a real world java application. Our evaluation criteria are 1) the preservation of code functionality, 2) the removal rate of long method characteristics, and 3) the improvement on analyzability. The result showed that the methods that apply suggested refactoring sets can completely remove long method bad smell, still have behavior preservation, and have not decreased analyzability. It is concluded that LMR meets the objectives in almost all classes. We also discussed the issues we found during evaluation as lesson learned.

This paper proposes MRO-PUF, a new architecture for ring-oscillator-based physically unclonable functions (PUFs) with enhanced resistance against machine learning attacks. In the proposed PUF, an instantaneous output value of a ring oscillator is used as a response, whereas the most existing PUFs directly use propagation delays to determine the response. Since the response of the MRO-PUF is non-linear and discontinuous as the delay of the ring oscillator increases, the prediction of the response by machine learning attacks is difficult. Through the performance evaluation of the MRO-PUF with simulations, it achieves 15 times stronger resistance against machine learning attacks using a support vector machine compared to the existing ones such as an arbiter PUF and a bistable ring PUF. The MRO-PUF also achieves a sufficient level of the basic performance of PUFs in terms of uniqueness and robustness.

Most conventional research on target motion analysis (TMA) based on least squares (LS) has focused on performing asymptotically unbiased estimation with inaccurate measurements. However, such research may often yield inaccurate estimation results when only a small set of measurement data is used. In this paper, we propose an accurate TMA method even with a small set of bearing measurements. First, a subset of measurements is selected by a random sample consensus (RANSAC) algorithm. Then, LS is applied to the selected subset to estimate target motion. Finally, to increase accuracy, the target motion estimation is refined through a bias compensation algorithm. Simulated results verify the effectiveness of the proposed method.

Formal series are a natural extension of formal languages by associating each word with a value called a coefficient or a weight. Among them, recognizable series and algebraic series can be regarded as extensions of regular languages and context-free languages, respectively. The coefficient of a word w can represent quantities such as the cost taken by an operation on w, the probability that w is emitted. One of the possible applications of formal series is the string counting in quantitative analysis of software. In this paper, we define the counting problems for formal series and propose algorithms for the problems. The membership problem for an automaton or a grammar corresponds to the problem of computing the coefficient of a given word in a given series. Accordingly, we define the counting problem for formal series in the following two ways. For a formal series S and a natural number d, we define CC(S,d) to be the sum of the coefficients of all the words of length d in S and SC(S,d) to be the number of words of length d that have non-zero coefficients in S. We show that for a given recognizable series S and a natural number d, CC(S,d) can be computed in O(η log d) time where η is an upper-bound of time needed for a single state-transition matrix operation, and if the state-transition matrices of S are commutative for multiplication, SC(S,d) can be computed in polynomial time of d. We extend the notions to tree series and discuss how to compute them efficiently. Also, we propose an algorithm that computes CC(S,d) in square time of d for an algebraic series S. We show the CPU time of the proposed algorithm for computing CC(S,d) for some context-free grammars as S, one of which represents the syntax of C language. To examine the applicability of the proposed algorithms to string counting for the vulnerability analysis, we also present results on string counting for Kaluza Benchmark.

We consider online linear optimization over symmetric positive semi-definite matrices, which has various applications including the online collaborative filtering. The problem is formulated as a repeated game between the algorithm and the adversary, where in each round t the algorithm and the adversary choose matrices Xt and Lt, respectively, and then the algorithm suffers a loss given by the Frobenius inner product of Xt and Lt. The goal of the algorithm is to minimize the cumulative loss. We can employ a standard framework called Follow the Regularized Leader (FTRL) for designing algorithms, where we need to choose an appropriate regularization function to obtain a good performance guarantee. We show that the log-determinant regularization works better than other popular regularization functions in the case where the loss matrices Lt are all sparse. Using this property, we show that our algorithm achieves an optimal performance guarantee for the online collaborative filtering. The technical contribution of the paper is to develop a new technique of deriving performance bounds by exploiting the property of strong convexity of the log-determinant with respect to the loss matrices, while in the previous analysis the strong convexity is defined with respect to a norm. Intuitively, skipping the norm analysis results in the improved bound. Moreover, we apply our method to online linear optimization over vectors and show that the FTRL with the Burg entropy regularizer, which is the analogue of the log-determinant regularizer in the vector case, works well.

In this study, the effect of atomically flat Si(100) surface on Hf-based Metal-Oxide-Nitride-Oxide-Silicon (MONOS) structure was investigated. After the atomically flat Si(100) surface formation by annealing at 1050/60min in Ar/4%H2 ambient, HfO2(O)/HfN1.0(N)/HfO2(O) structure with thickness of 10/3/2nm, respectively, was in-situ deposited by electron cyclotron resonance (ECR) plasma sputtering. The memory window (MW) of Al/HfO2/HfN1.0/HfO2/p-Si(100) diodes was increased from 1.0V to 2.5V by flattening of Si(100) surface. The program and erase (P/E) voltage/time were set as 10V/5s and -8V/5s, respectively. Furthermore, it was found that the gate current density after the 103P/E cycles was decreased one order of magnitude by flattening of Si(100) surface in Ar/4.0%H2 ambient.

In this paper, we have investigated the PdEr-silicide formation utilizing a developed PdEr-alloy target for sputtering, and evaluated the contact resistivity of PdEr-silicide layer formed on n-Si(100) by dopant segregation process for the first time. Pd2Si and ErSi2 have same hexagonal structure, while the Schottky barrier height for electron (Φbn) is different as 0.75 eV and 0.28 eV, respectively. A 20 nm-thick PdEr-alloy layer was deposited on the n-Si(100) substrates utilizing a developed PdEr-alloy target by the RF magnetron sputtering at room temperature. Then, 10 nm-thick TiN encapsulating layer was in-situ deposited at room temperature. Next, silicidation was carried out by the RTA at 500 for 5 min in N2/4.9%H2 followed by the selective etching. From the J-V characteristics of fabricated Schottky diode, qΦbn was reduced from 0.75 eV of Pd2Si to 0.43 eV of PdEr-silicide. Furthermore, 4.0x10-8Ωcm2 was extracted for the PdEr-silicide to n-Si(100) by the dopant segregation process.

Video surveillance from airborne platforms can suffer from many sources of blur, like vibration, low-end optics, uneven lighting conditions, etc. Many different algorithms have been developed in the past that aim to recover the deblurred image but often incur substantial CPU-time, which is not always available on-board. This paper shows how a “strap-on” quasi-Newton method can accelerate the convergence of existing iterative methods with little extra overhead while keeping the performance of the original algorithm, thus paving the way for (near) real-time applications using on-board processing.

Focusing on the defects of famous defogging algorithms for fog images based on the atmosphere scattering model, we find that it is necessary to obtain accurate transmission map that can reflect the real depths both in large depth and close range. And it is hard to tackle this with just one prior because of the differences between the large depth and close range in foggy images. Hence, we propose a novel prior that simplifies the solution of transmission map by transferring coefficient, called saturation prior. Then, under the Random Walk model, we constrain the transferring coefficient with the color attenuation prior that can obtain good transmission map in large depth regions. More importantly, we design a regularization weight to balance the influences of saturation prior and color attenuation prior to the transferring coefficient. Experimental results demonstrate that the proposed defogging method outperforms the state-of-art image defogging methods based on single prior in terms of details restoring and color preserving.