Optical Code Division Multiplexing (OCDM) is a multiplexing technology for constructing future all-optical networks. Compared with other multiplexing technologies, it can be easily controlled and can establish lightpaths of smaller granularity. However, previous research has revealed that OCDM networks are vulnerable to cycle attacks. Cycle attacks are caused by multi-access interference (MAI), which is crosstalk noise on the same wavelength in OCDM networks. If cycle attacks occur, they disrupt all network services immediately. Previous research has proposed a logical topology design that is free of cycle attacks. However, this design assumes that path assignment is centrally controlled. It also does not consider the delay between each node and the centralized controller. In this paper, we propose novel logical topology designs that are free of cycle attacks and methods of establishing paths. The basic concepts underlying our methods are to autonomously construct a cycle-attack-free logical topology and to establish lightpaths by using a distributed controller. Our methods can construct a logical network and establish lightpaths more easily than the previous method can. In addition, they have network scalability because of their distributed control. Simulation results show that our methods have lower loss probabilities than the previous method and better mean hop counts than the centralized control approach.

Recently, the compound element pseudo transient analysis, CEPTA, method is regarded as an efficient practical method to find DC operating points of nonlinear circuits when the Newton-Raphson method fails. In the previous CEPTA method, an effective SPICE3 implementation algorithm was proposed without expanding the Jacobian matrix. However the limitation of step size was not well considered. Thus, the non-convergence problem occurs and the simulation efficiency is still a big challenge for current LSI nonlinear cicuits, especially for some practical large-scale circuits. Therefore, in this paper, we propose a new SPICE3 implementation algorithm and an embedding algorithm, which is where to insert the pseudo capacitors, for the CEPTA method. The proposed implementation algorithm has no limitation for step size and can significantly improve simulation efficiency. Considering the existence of various types of circuits, we extend some possible embedding positions. Numerical examples demonstrate the improvement of simulation efficiency and convergence performance.

This paper derives the average symbol and bit weight distributions for the irregular non-binary cluster low-density parity-check (LDPC) code ensembles. Moreover, we give the exponential growth rates of the average weight distributions in the limit of large code length. We show the condition that the typical minimum distances linearly grow with the code length.

The use of computing resources on network is becoming active in the Internet and private networks. OpenFlow/Software-Defined Networking (SDN) is drawing attention as a method to control network virtualization for the cloud computing services and other carrier services. This paper introduces examples of OpenFlow/SDN technologies applied to commercial cloud services. Various activities to expand coverage over commercial carrier networks are also mentioned.

The equivalent circuit of aperture-coupled cavities filled with a lossy dielectric is considered by means of an eigenmode expansion technique founded on the segmentation concept. It is different from a series LCR resonant circuit, and the resistor which symbolizes the dielectric loss is connected to the capacitor in parallel. If the cavities are formed by a short-circuited oversize waveguide, then the input admittance can be represented by the product of a coupling factor to the connected waveguide port and the equivalent admittance of the short-circuited waveguide. The transmission line model is effective even if lossy wall effect and dielectric partially-loading effect are considered. As a result, three-dimensional eigenmode parameters, such as the resonant frequency and the Q-factor, become dispensable and the computational complexity for the cavity simulation in the field of microwave heating is dramatically reduced.

In this study, the influence of Gd composition on current-induced domain wall motion in a Gd-Co ferrimagnetic nanowire was theoretically investigated with taking into account of composition dependence of magnetic properties. As a result, the intrinsic critical density to move domain wall significantly reduces near the compensation composition, which is achieved to be less than 105A/cm2. Moreover, the intrinsic critical current density also significantly reduces near a certain Gd composition where the domain wall energies of Bloch and Néel walls are almost the same.

This paper presents a real-time and memory-efficient arrhythmia detection system with binary classification that uses antidictionary coding for the analysis and classification of electrocardiograms (ECGs). The measured ECG signals are encoded using a lossless antidictionary encoder, and the system subsequently uses the compression rate to distinguish between normal beats and arrhythmia. An automated training data procedure is used to construct the automatons, which are probabilistic models used to compress the ECG signals, and to determine the threshold value for detecting the arrhythmia. Real-time computer simulations with samples from the MIT-BIH arrhythmia database show that the averages of sensitivity and specificity of the proposed system are 97.8% and 96.4% for premature ventricular contraction detection, respectively. The automatons are constructed using training data and comprise only 11 kilobytes on average. The low complexity and low memory requirements make the system particularly suitable for implementation in portable ECG monitors.

With the diffusion of web services caused by the appearance of a new architecture known as cloud computing, a large number of websites have been used by attackers as hopping sites to attack other websites and user terminals because many vulnerable websites are constructed and managed by unskilled users. To construct hopping sites, many attackers force victims to download malware by using vulnerabilities in web applications. To protect websites from these malware infection attacks, conventional methods, such as using anti-virus software, filter files from attackers using pattern files generated by analyzing conventional malware files collected by security vendors. In addition, certain anti-virus software uses a behavior blocking approach, which monitors malicious file activities and modifications. These methods can detect malware files that are already known. However, it is difficult to detect malware that is different from known malware. It is also difficult to define malware since legitimate software files can become malicious depending on the situation. We previously proposed an access filtering method based on communication opponents, which are other servers or terminals that connect with our web honeypots, of attacks collected by web honeypots, which collect malware infection attacks to websites by using actual vulnerable web applications. In this blacklist-based method, URLs or IP addresses, which are used in malware infection attacks collected by web honeypots, are listed in a blacklist, and accesses to and from websites are filtered based on the blacklist. To reveal the effects in an actual attack situation on the Internet, we evaluated the detection ratio of anti-virus software, our method, and a composite of both methods. Our evaluation revealed that anti-virus software detected approximately 50% of malware files, our method detected approximately 98% of attacks, and the composite of the two methods could detect approximately 99% of attacks.

Nowadays, with spreads of inexpensive small communication devices, a number of wireless local area networks (WLANs) have been deployed even in the same building for the Internet access services. Their wireless access-points (APs) are often independently installed and managed by different groups such as departments or laboratories in a university or a company. Then, a user host can access to multiple WLANs by detecting signals from their APs, which increases the energy consumption and the operational cost. It may also degrade the communication performance by increasing interferences. In this paper, we present an AP aggregation approach to solve these problems in multiple WLAN environments by aggregating deployed APs of different groups into limited ones using virtual APs. First, we formulate the AP aggregation problem as a combinatorial optimization problem and prove the NP-completeness of its decision problem. Then, we propose its heuristic algorithm composed of five phases. We verify the effectiveness through extensive simulations using the WIMNET simulator.

Text sentiment classification aims to automatically classify subjective documents into different sentiment-oriented categories (e.g. positive/negative). Given the high dimensionality of features describing documents, how to effectively select the most useful ones, referred to as sentiment-bearing features, with a lack of sentiment class labels is crucial for improving the classification performance. This paper proposes an unsupervised sentiment-bearing feature selection method (USFS), which incorporates sentiment discriminant analysis (SDA) into sentiment strength calculation (SSC). SDA applies traditional linear discriminant analysis (LDA) in an unsupervised manner without losing local sentiment information between documents. We use SSC to calculate the overall sentiment strength for each single feature based on its affinities with some sentiment priors. Experiments, performed using benchmark movie reviews, demonstrated the superior performance of USFS.

In this paper, we propose a novel voice activity detection (VAD) algorithm based on the generalized normal-Laplace (GNL) distribution to provide enhanced performance in adverse noise environments. Specifically, the probability density function (PDF) of a noisy speech signal is represented by the GNL distribution; the variance of the speech and noise of the GNL distribution are estimated using higher-order moments. After in-depth analysis of estimated variances, a feature that is useful for discrimination between speech and noise at low SNRs is derived and compared to a threshold to detect speech activity. To consider the inter-frame correlation of speech activity, the result from the previous frame is employed in the decision rule of the proposed VAD algorithm. The performance of our proposed VAD algorithm is evaluated in terms of receiver operating characteristics (ROC) and detection accuracy. Results show that the proposed method yields better results than conventional VAD algorithms.

As a consequence of recent developments in communications, the parameters of communication signals, such as the modulation parameter values, are becoming unstable because of time-varying SNR under electromagnetic conditions. In general, it is difficult to classify target signals that have time-varying parameters using traditional signal recognition methods. To overcome this problem, this study proposes a novel recognition method that works well even for such time-dependent communication signals. This method is mainly composed of feature extraction and classification processes. In the feature extraction stage, we adopt Shannon entropy and index entropy to obtain the stable features of modulated signals. In the classification stage, the interval gray relation theory is employed as suitable for signals with time-varying parameter spaces. The advantage of our method is that it can deal with time-varying SNR situations, which cannot be handled by existing methods. The results from numerical simulation show that the proposed feature extraction algorithm, based on entropy characteristics in time-varying SNR situations,offers accurate clustering performance, and the classifier, based on interval gray relation theory, can achieve a recognition rate of up to 82.9%, even when the SNR varies from -10 to -6 dB.

A shift of finite type (SFT) is a set of all bi-infinite sequences over some alphabet which is characterized by a finite set of forbidden words. It is a typical example of sofic shifts and has been used in media storage area, such as CD's or DVD's. The study of sofic shifts is based on graph theory, and the irreducibility of shifts is an important property to be considered for the study. In this paper, we will provide some sufficient conditions for an SFT to be irreducible from the perspective of the antidictionary of a word and the number of forbidden words. We also present a necessary and sufficient condition for an SFT to be irreducible when the number of forbidden words is one less than the alphabet size.

Display devices play image files, of which contrast enhancement methods are usually employed to bring out visual details to achieve better visual quality. However, applied to high resolution images, the contrast enhancement method entails high computation costs mostly due to histogram computations. Therefore, this letter proposes a parallel histogram calculation algorithm using the column histograms and difference histograms to reduce histogram computations. Experimental results show that the proposed algorithm is effective for histogram-based image contrast enhancement.

We show teachability of a subclass of simple deterministic languages. The subclass we define is called stack uniform simple deterministic languages. Teachability is derived by showing the query learning algorithm for this language class. Our learning algorithm uses membership, equivalence and superset queries. Then, it terminates in polynomial time. It is already known that simple deterministic languages are polynomial time query learnable by context-free grammars. In contrast, our algorithm guesses a hypothesis by a stack uniform simple deterministic grammar, thus our result is strict teachability of the subclass of simple deterministic languages. In addition, we discuss parameters of the polynomial for teachability. The “thickness” is an important parameter for parsing and it should be one of parameters to evaluate the time complexity.

Weissman introduced a coding problem for channels with action-dependent states. In this coding problem, there are two encoders and a decoder. An encoder outputs an action that affects the state of the channel. Then, the other encoder outputs a codeword of the message into the channel by using the channel state. The decoder receives a noisy observation of the codeword, and reconstructs the message. In this paper, we show an exponential error bound for channels with action-dependent states based on the random coding argument.

To mitigate the impact of the frequency selectivity of the wireless channel on the initial ranging (IR) process in 802.16 based WiMax systems, several well known pre-equalization techniques applied in the IR are first analyzed in detail, and the optimal pre-equalization scheme is further improved for the IR by overcoming its weaknesses. A numerical simulation shows that the proposed pre-equalization scheme significantly improves the performance of multiuser detection and parameter estimation in the IR process.

CoPt and Co3Pt alloy thin films are prepared on MgO(111), SrTiO3(111), and Al2O3(0001) single-crystal substrates by varying the substrate temperature in a range from room temperature to 600°C by using an ultra-high vacuum radio-frequency magnetron sputtering system. The formation of metastable ordered phase and the structural thermal stability are briefly investigated. CoPt and Co3Pt films with the close-packed plane parallel to the substrate surface grow epitaxially on these oxide single-crystal substrates. CoPt epitaxial films are also formed by employing Pt, Pd, Cu, Cr, Ti, and Ru underlayers hetero-epitaxially grown on MgO(111) substrates. The crystal structure is evaluated by considering the order degree and the atomic stacking sequence of close-packed plane. Metastable ordered phases of L11, Bh, and D019 are preferentially formed in the CoPt and the Co3Pt films deposited around 300°C. Metastable ordered phase formation is influenced by the substrate temperature, the film composition, and the underlayer material. With increasing the substrate temperature up to around 300°C, the order degree increases. As the substrate temperature further increases, the order degree decreases. Annealing a disordered film at 300°C does not effectively enhance ordering. The CoPt and the Co3Pt films which include metastable ordered phases have flat surfaces and show strong perpendicular magnetic anisotropies reflecting the magnetocrystalline anisotropies of ordered crystals.

Holographic data storage (HDS) is a next-generation optical storage that uses the principles of holography. The multiplex holographic recording method is an important factor that affects the recording capacity of this storage. Various multiplex recording methods have been proposed so far. In this study, we focus on shift multiplexing with spherical waves and propose a method of shift multiplex recording that combines the in-plane direction and thickness direction of the recording medium. In conventional shift multiplexing with spherical waves, shift multiplexing is usually carried out with respect to the direction parallel to the plane of the recording medium. By focusing on the fact that shift selectivity is also in the thickness direction, we examined the possibility of a multiplex recording method that combines multiple shift directions. Simulation and experimental verification shows that the proposed method is effective in principle.

In this letter, we first introduce a stronger notion of the optimistic achievable coding rate and discuss a coding theorem. Next, we give a necessary and sufficient condition under which the coding rates of all the optimal FF codes asymptotically converge to a constant.