Heterogeneous networks (HetNet) with different radio access technologies have been deployed to support a range of communication services. To manage these HetNets efficiently, some interworking solutions such as MIH (media independent handover), ANQP (access network query protocol) or ANDSF (access network discovery and selection function) have been studied. Recently, the millimeter-wave (mm-wave) based HetNet has been explored to provide multi-gigabits-per-second data rates over short distances in the 60GHz frequency band for 5G wireless networks. WiGig (Wireless Gigabit Alliance) is one of the available radio access technologies using mm-wave. However, the conventional interworking solutions are not sufficient for the implementation of LTE (Long Term Evolution)/WiGig HetNets. Since the coverage area of WiGig is very small due to the high propagation loss of the mm-wave band signal, it is difficult for UEs to perform cell discovery and handover if using conventional LTE/WLAN (wireless local area networks) interworking solutions, which cannot support specific techniques of WiGig well, such as beamforming and new media access methods. To solve these problems and find solutions for LTE/WiGig interworking, RAN (radio access network)-level tightly coupled interworking architecture will be a promising solution. As a RAN-level tightly coupled interworking solution, this paper proposes to design a LTE/WiGig protocol adaptor above the protocol stacks of WiGig to process and transfer control signaling and user data traffic. The proposed extended control plane can assist UEs to discover and access mm-wave BSs successfully and support LTE macro cells to jointly control the radio resources of both LTE and WiGig, so as to improve spectrum efficiency. The effectiveness of the proposal is evaluated. Simulation results show that LTE/WiGig HetNets with the proposed interworking solution can decrease inter-cell handover and improve user throughput significantly. Moreover, the downlink backhaul throughput and energy efficiency of mm-wave HetNets are evaluated and compared with that of 3.5GHz LTE HetNets. Results indicate that 60GHz mm-wave HetNets have better energy efficiency but with much heavier backhaul overhead.

A highly efficient sky-blue organic light-emitting diode (OLED) based on a thermally-activated delayed fluorescence (TADF) molecule, 1,2-bis(carbazol-9-yl)-4,5-dicyanobenzene (2CzPN), was studied. The sky-blue OLED exhibited a maximum external electroluminescence quantum efficiency (ηEQE) of over 24.0%. In addition, a white OLED using 2CzPN combined with green and orange TADF emitters showed a high ηEQE of 17.3% with a maximum power efficiency of 52.3 lm/W and Commission Internationale de l'Eclairage coordinates of (0.32, 0.43).

An Authenticated Encryption scheme is used to guarantee both privacy and authenticity of digital data. At FSE 2014, an authenticated encryption scheme called CLOC was proposed. CLOC is designed to handle short input data efficiently without needing heavy precomputation nor large memory. This is achieved by making various cases of different treatments in the encryption process depending on the input data. Five tweak functions are used to handle the conditional branches, and they are designed to satisfy 55 differential probability constraints, which are used in the security proof of CLOC. In this paper, we show that all these 55 constraints are necessary. This shows the design optimality of the tweak functions in CLOC in that the constraints cannot be relaxed, and hence the specification of the tweak functions cannot be simplified.

A low loss intelligent power module (IPM) that specifically designed for high performance frequency-alterable air conditioner applications is proposed. This IPM utilizes 600 V trench gate field stop insulated gate bipolar transistors (TFS-IGBTs) as the main switching devices to deliver extremely low conduction and switching losses. In addition, 600 V SiC schottky barrier diodes (SBDs) are employed as the freewheeling diodes. Compared to conventional silicon fast recovery diodes (FRDs) SiC SBDs exhibit practically no reverse recovery loss, hence can further reduce the power loss of the IPM. Experimental results reveal that the power loss of the proposed IPM is between 3.5∼21.7 W at different compressor frequencies from 10 to 70 Hz, which achieving up to 12.5%∼25.5% improvement when compared to the state-of-the-art conventional Si-based IGBT IPM.

In this paper, synchronization for uncertain fractional order chaotic systems is investigated. By using the fractional order extension of the Lyapunov stability criterion, a linear feedback controller and an adaptive controller are designed for synchronizing uncertain fractional order chaotic systems without and with unknown external disturbance, respectively. Quadratic Lyapunov functions are used in the stability analysis of fractional-order systems, and fractional order adaptation law is constructed to update design parameter. The proposed methods can guarantee that the synchronization error converges to zero asymptotically. Finally, illustrative examples are given to confirm the theoretical results.

In this letter, a new subband adaptive filter (SAF) which is robust against impulsive noise in system identification is presented. To address the vulnerability of adaptive filters based on the L2-norm optimization criterion to impulsive noise, the robust SAF (R-SAF) comes from the L1-norm optimization criterion with a constraint on the energy of the weight update. Minimizing L1-norm of the a posteriori error in each subband with a constraint on minimum disturbance gives rise to robustness against impulsive noise and the capable convergence performance. Simulation results clearly demonstrate that the proposal, R-SAF, outperforms the classical adaptive filtering algorithms when impulsive noise as well as background noise exist.

In this paper, we introduce a distributed power allocation strategy for random access, that has the capabilities of multipacket reception (MPR) and successive interference cancellation (SIC). The proposed random access scheme is suitable for machine-to-machine (M2M) communication application in fifth-generation (5G) cellular networks. A previous study optimized the probability distribution for discrete transmission power levels, with implicit limitations on the successful decoding of at most two packets from a single collision. We formulate the optimization problem for the general case, where a base station can decode multiple packets from a single collision, and this depends only on the signal-to-interference-plus-noise ratio (SINR). We also propose a feasible suboptimal iterative per-level optimization process; we do this by introducing relationships among the different discrete power levels. Compared with the conventional power allocation scheme with MPR and SIC, our method significantly improves the system throughput; this is confirmed by computer simulations.

In our previous work [12], [13], we introduced generalized feed-forward shift registers (GF2SR, for short) to apply them to secure and testable scan design, where we considered the security problem from the viewpoint of the complexity of identifying the structure of GF2SRs. Although the proposed scan design is secure in the sense that the structure of a GF2SR cannot be identified only from the primary input/output relation, it may not be secure if part of the contents of the circuit leak out. In this paper, we introduce a more secure concept called strong security such that no internal state of strongly secure circuits leaks out, and present how to design such strongly secure GF2SRs.

Collective activity recognition plays an important role in high-level video analysis. Most current feature representations look at contextual information extracted from the behaviour of nearby people. Every person needs to be detected and his pose should be estimated. After extracting the feature, hierarchical graphical models are always employed to model the spatio-temporal patterns of individuals and their interactions, and so can not avoid complex preprocessing and inference operations. To overcome these drawbacks, we present a new feature representation method, called attribute-based spatio-temporal (AST) descriptor. First, two types of information, spatio-temporal (ST) features and attribute features, are exploited. Attribute-based features are manually specified. An attribute classifier is trained to model the relationship between the ST features and attribute-based features, according to which the attribute features are refreshed. Then, the ST features, attribute features and the relationship between the attributes are combined to form the AST descriptor. An objective classifier can be specified on the AST descriptor and the weight parameters of the classifier are used for recognition. Experiments on standard collective activity benchmark sets show the effectiveness of the proposed descriptor.

In this paper, a new single soft switched forward converter with a self driven synchronous rectification (SDSR) is introduced. In the proposed converter, a soft switching condition (ZCS turn on and ZVS turn off) is provided for the switch, by an auxiliary circuit without any extra switch. In additional, this auxiliary circuit does not impose high voltage or current stresses on the converter. Since the proposed converter uses SDSR to reduce conductive loss of output rectifier, the rectifier switches are switched under soft switching condition. So, the conductive and switching losses on the converter reduce considerably. Also, implementing control circuit of this converter is very simple, due to the self-driven method employed in driving synchronous rectification and the converter is controlled by pulse width modulation (PWM). The experimental results of the proposed converter are presented to confirm the theoretical analysis.

The main purpose of this paper is to propose overtime replacement policies for the system which has a finite life cycle. The newly proposed overtime technique, where the system is replaced preventively at the first completion of some working cycle over a planned time T, is employed into modelings to avoid operational interruptions for successive jobs. We consider two overtime replacement model with finite operating interval which S is given as (i) constant interval, and (ii) random interval. The expected replacement costs per unit of time are obtained and their optimal solutions are discussed analytically. Further, numerical examples are given when the failure time has a Weibull distribution and working cycles are exponentially distributed.

Neural networks are widely used in various fields due to their superior learning abilities. This paper proposes a hardware winner-take-all neural network (WTANN) that employs a new winner-take-all (WTA) circuit with phase-modulated pulse signals and digital phase-locked loops (DPLLs). The system uses DPLL as a computing element, so all input values are expressed by phases of rectangular signals. The proposed WTA circuit employs a simple winner search circuit. The proposed WTANN architecture is described by very high speed integrated circuit (VHSIC) hardware description language (VHDL), and its feasibility was tested and verified through simulations and experiments. Conventional WTA takes a global winner search approach, in which vector distances are collected from all neurons and compared. In contrast, the WTA in the proposed system is carried out locally by a distributed winner search circuit among neurons. Therefore, no global communication channels with a wide bandwidth between the winner search module and each neuron are required. Furthermore, the proposed WTANN can easily extend the system scale, merely by increasing the number of neurons. The circuit size and speed were then evaluated by applying the VHDL description to a logic synthesis tool and experiments using a field programmable gate array (FPGA). Vector classifications with WTANN using two kinds of data sets, Iris and Wine, were carried out in VHDL simulations. The results revealed that the proposed WTANN achieved valid learning.

Sparsity-based methods have been recently applied to abnormal event detection and have achieved impressive results. However, most such methods suffer from the problem of dimensionality curse; furthermore, they also take no consideration of the relationship among coefficient vectors. In this paper, we propose a novel method called consistent sparse representation (CSR) to overcome the drawbacks. We first reconstruct each feature in the space spanned by the clustering centers of training features so as to reduce the dimensionality of features and preserve the neighboring structure. Then, the consistent regularization is added to the sparse representation model, which explicitly considers the relationship of coefficient vectors. Our method is verified on two challenging databases (UCSD Ped1 database and Subway batabase), and the experimental results demonstrate that our method obtains better results than previous methods in abnormal event detection.

With aggressive device scaling, timing failures have become more prevalent due to manufacturing defects and process variations. When timing failure occurs, it is important to take corrective actions immediately. Therefore, an efficient and fast diagnosis method is essential. In this paper, we propose a new diagnostic method using timing information. Our method approximately estimates all the segment delays of measured paths in a design, using inequality-constrained least squares methods. Then, the proposed method ranks the possible locations of delay defects based on the difference between estimated segment delays and the expected values of segment delays. The method works well for multiple delay defects as well as single delay defects. Experiment results show that our method yields good diagnostic resolution. With the proposed method, the average first hit rank (FHR), was within 7 for single delay defect and within 8 for multiple delay defects.

We discuss software reliability assessment considering multiple changes of software fault-detection phenomenon. The testing-time when the characteristic of the software failure-occurrence or fault-detection phenomenon changes notably in the testing-phase of a software development process is called change-point. It is known that the occurrence of the change-point influences the accuracy for the software reliability assessment based on a software reliability growth models, which are mainly divided into software failure-occurrence time and fault counting models. This paper discusses software reliability growth modeling frameworks considering with the effect of the multiple change-point occurrence on the software reliability growth process in software failure-occurrence time and fault counting modeling. And we show numerical illustrations for the software reliability analyses based on our models by using actual data.

In this paper, a novel approach for central angle estimation of coherently distributed targets that utilizes electric vector sensors in bistatic MIMO radar is proposed. First, the coherently distributed targets signal model in bistatic MIMO radar that equipped with electric vector sensors is reconstructed. The Hadamard product rotation invariance property of the coherently distributed targets' steering vectors is found to get the initial estimation of direction of departure (DOD). 1-D MUSIC is then used to estimate the accurate central angles of direction of arrival (DOA) and DOD. The proposed method can estimate the central angles of DOA and DOD efficiently and accurately without pairing even in the situation where the angular signal distribution functions are unknown. Our method has better performance than Guo's algorithm. Numerical results verify the improvement and performance of the proposed algorithm.

A connected-(r,s)-out-of-(m,n): F system is a kind of the connected-X-out-of-(m,n): F system defined by Boehme et al. [2]. A connected-(r,s)-out-of-(m,n): F system consists of m×n components arranged in (m,n)-matrix. This system fails if and only if there exists a grid of size r×s in which all components are failed. When m=r, this system can be regarded as a consecutive-s-out-of-n: F system, and then the optimal arrangement of this system satisfies theorem which stated by Malon [9] in the case of s=2. In this study, we proposed a new algorithm for obtaining optimal arrangement of the connected-(r,2)-out-of-(m,n): F system based on the above mentioned idea. We performed numerical experiments in order to compare the proposed algorithm with the algorithm of enumeration method, and calculated the order of the computation time of these two algorithms. The numerical experiments showed that the proposed algorithm was more efficiently than the algorithm of enumeration method.

Prediction of seasonal infectious disease spread is traditionally dealt with as a function of time. Typical methods are time series analysis such as ARIMA (autoregressive, integrated, and moving average) or ANN (artificial neural networks). However, if we regard the time series data as the matrix form, e.g., consisting of yearly magnitude in row and weekly trend in column, we may expect to use a different method (matrix approach) to predict the disease spread when seasonality is dominant. The MD (matrix decomposition) method is the one method which is used in recommendation systems. The other is the IRT (item response theory) used in ability evaluation systems. In this paper, we apply these two methods to predict the disease spread in the case of infectious gastroenteritis caused by norovirus in Japan, and compare the results obtained by using two conventional methods in forecasting, ARIMA and ANN. We have found that the matrix approach is simple and useful in prediction for the seasonal infectious disease spread.

This paper considers how to evaluate the resiliency for virtualized system with software rejuvenation. The software rejuvenation is a proactive technique to prevent the failure caused by aging phenomenon such as resource exhaustion. In particular, according to Gohsh et al. (2010), we compute a quantitative criterion to evaluate resiliency of system by using continuous-time Markov chains (CTMC). In addition, in order to convert general state-based models to CTMCs, we employ PH (phase-type) expansion technique. In numerical examples, we investigate the resiliency of virtualized system with software rejuvenation under two different rejuvenation policies.

OSEK/VDX, a standard for an automobile OS, has been widely adopted by many manufacturers to design and develop a vehicle-mounted OS. With the increasing functionalities in vehicles, more and more complex applications are be developed based on the OSEK/VDX OS. However, how to ensure the reliability of developed applications is becoming a challenge for developers. To ensure the reliability of developed applications, model checking as an exhaustive technique can be applied to discover subtle errors in the development process. Many model checkers have been successfully applied to verify sequential software and general multi-threaded software. However, it is hard to directly use existing model checkers to precisely verify OSEK/VDX applications, since the execution characteristics of OSEK/VDX applications are different from the sequential software and general multi-threaded software. In this paper, we describe and develop an approach to translate OSEK/VDX applications into sequential programs in order to employ existing model checkers to precisely verify OSEK/VDX applications. The value of our approach is that it can be considered as a front-end translator for enabling existing model checkers to verify OSEK/VDX applications.