In this paper, we propose a framework to allocate code rates of component codes in a Plotkin-type unequal error protection (UEP) code. We derive an equivalent noise variance for each component code using structure of the Plotkin construction and Gaussian assumption. Comparing the equivalent noise variance and Shannon limit, we can find a combination of the code rates for the component codes. We investigate three types of code rate combinations and analyse their UEP performance. We also estimate a performance crossing signal to noise ratio (SNR) of the Plotkin-type UEP code. It indicates that which code has better performance for a given SNR. We confirm that the proposed framework is appropriate to obtain a desired UEP capability.

This paper investigates open-loop Stackelberg games for a class of stochastic systems with multiple players. First, the necessary conditions for the existence of an open-loop Stackelberg strategy set are established using the stochastic maximum principle. Such conditions can be represented as solvability conditions for cross-coupled forward-backward stochastic differential equations (CFBSDEs). Second, in order to obtain the open-loop strategy set, a computational algorithm based on a four-step scheme is developed. A numerical example is then demonstrated to show the validity of the proposed method.

A high-image-rejection wireless receiver with an N-phase active RC complex filter is proposed and analyzed. Signal analysis shows that the double-conversion receiver with (N+N2) mixers corrects the gain and phase mismatches of the adjacent image. Monte Carlo simulations evaluate the relation between image-rejection performances and the dispersions of device parameters for the double-conversion wireless receiver. The Monte Carlo simulations show that the image rejection ratio of the adjacent image depends almost only on R and C mismatches in the complex filter.

Using a matrix approach based on a Markov process, we investigate the reliability of a circular connected-(1,2)-or-(2,1)-out-of-(m,n):F lattice system for the i.i.d. case. We develop a modified linear lattice system that is equivalent to this circular system, and propose a methodology that allows the systematic calculation of the reliability. It is based on ideas presented by Fu and Hu [6]. A partial transition probability matrix is used to reduce the computational complexity of the calculations, and closed formulas are derived for special cases.

As the development of sensor and machine learning technologies has progressed, it has become increasingly important to detect patterns from probabilistic data streams. In this paper, we focus on complex event processing based on pattern matching. When we apply pattern matching to probabilistic data streams, numerous matches may be detected at the same time interval because of the uncertainty of data. Although existing methods distinguish between such matches, they may derive inappropriate results when some of the matches correspond to the real-world event that has occurred during the time interval. Thus, we propose two grouping methods for matches. Our methods output groups that indicate the occurrence of complex events during the given time intervals. In this paper, first we describe the definition of groups based on temporal overlap, and propose two grouping algorithms, introducing the notions of complete overlap and single overlap. Then, we propose an efficient approach for calculating the occurrence probabilities of groups by using deterministic finite automata that are generated from the query patterns. Finally, we empirically evaluate the effectiveness of our methods by applying them to real and synthetic datasets.

Recently, mobile networks employing high-speed high-capacity communications have been investigated extensively to satisfy the demand for faster and higher-capacity data communications. In one approach, frequencies between 6 and 100GHz are candidates to utilize relatively wide frequency bandwidths. Accordingly, radio propagation loss in these frequency bands must be characterized. Ray-tracing (RT) is the most common modeling approach to predict propagation loss in site-specific scenarios. The accuracy of RT simulations has been investigated in urban street cell environments based on comparison to measurement results and we observed that the difference between RT simulation and measurement results tends to increase as the frequency increases. In this paper, we focus on the shape of building corners at an intersection because it is this shape that is a dominant contributing factor in the region away from the intersection. In order to correct the error in the conventional RT method, we propose an alternative model that considers the detailed shape of the building corner and surface roughness. The performance of the RT simulation using the proposed method is then investigated based on comparison of two different sets of measurement results. Finally, we extract the optimal size and roughness for the proposed modeling method. Consequently, we confirm that using the proposed method with optimized parameters significantly enhances the accuracy compared to the conventional method.

When synthesizing speech from Japanese text, correct assignment of accent nuclei for input text with arbitrary contents is indispensable in obtaining naturally-sounding synthetic speech. A phenomenon called accent sandhi occurs in utterances of Japanese; when a word is uttered in a sentence, its accent nucleus may change depending on the contexts of preceding/succeeding words. This paper describes a statistical method for automatically predicting the accent nucleus changes due to accent sandhi. First, as the basis of the research, a database of Japanese text was constructed with labels of accent phrase boundaries and accent nucleus positions when uttered in sentences. A single native speaker of Tokyo dialect Japanese annotated all the labels for 6,344 Japanese sentences. Then, using this database, a conditional-random-field-based method was developed using this database to predict accent phrase boundaries and accent nuclei. The proposed method predicted accent nucleus positions for accent phrases with 94.66% accuracy, clearly surpassing the 87.48% accuracy obtained using our rule-based method. A listening experiment was also conducted on synthetic speech obtained using the proposed method and that obtained using the rule-based method. The results show that our method significantly improved the naturalness of synthetic speech.

This paper proposes a walking route recommender system aiming at continuously supporting a user to take a walk as means for health promotion. In recent years, taking a walk becomes popular with not only the elderly, but also those from all ages as one of the easiest ways for health promotion. From the viewpoint of health promotion, it is desirable to take a walk as daily exercise. However, walking is very simple activity, which makes it difficult for people to maintain their motivation. Although using an activity monitor is expected to improve the motivation for taking a walk as daily exercise, it forces users to manage their activities by themselves. The proposed system solves such a problem by recommending a walking route that can consume target calories. When a system is to be used for long period of time for supporting user's daily exercise, it should consider the case when a user will not follow the recommended route. It would cause a gap between consumed and target calories. We think this problem becomes serious when a user gradually gets bored with taking a walk during a long period of time. In order to solve the problem, the proposed method implicitly manages calories on monthly basis and recommends walking routes that could keep a user from getting bored. The effectiveness of the recommendation algorithm is evaluated with agent simulation. As another important factor for walking support, this paper also proposes a navigation interface that presents direction to the next visiting point without using a map. As users do not have to continuously focus on the interface, it is not only useful for their safety, but also gives them room to enjoy the landscape. The interface is evaluated by an experiment with test participants.

Conventional image retargeting methods fail to avoid distortion in the case where visually important regions are distributed all over the image. To reduce distortions, this paper proposes a novel image retargeting method that incorporates letterboxing into an image warping framework. Letterboxing has the advantage of producing results without distortion or content loss although being unable to use the entire display area. Therefore, it is preferable to combine a retargeting method with a letterboxing operator when displaying images in full screen. Experimental results show that the proposed method is superior to conventional methods in terms of visual quality measured by an objective metric.

Precise estimation of coronary arteries from computed tomography angiography (CTA) data is one of the challenging problems. This study focuses on automatic delineation of coronary arteries from 3D CTA data that may assess the clinicians in identifying the coronary pathologies. In this work, we present a technique that effectively segments the complete coronary arterial tree under the guidance of initial vesselness response without relying on heavily manual operations. The proposed method isolates the coronary arteries with accuracy by using localized statistical energy model in two directions provided with an automated seed which ensures an optimal segmentation of the coronaries. The detection of seed is carried out by analyzing the shape information of the coronary arteries in three successive cross-sections. To demonstrate the efficiency of the proposed algorithm, the obtained results are compared with the reference data provided by Rotterdam framework for lumen segmentation and the level-set active contour based method proposed by Lankton et al. Results reveal that the proposed method performs better in terms of leakages and accuracy in completeness of the coronary arterial tree.

The purpose of this paper is to propose a flexible load-dependent digital soft-start control method for dc-dc converters in a 380Vdc system. The soft-start operation is needed to prevent negative effects such as large inrush current and output overshoot to a power supply in the start-up process of dc-dc converters. In the conventional soft-start operation, a dc-dc converter has a very slow start-up to deal with the light load condition. Therefore, it always takes a long time in any load condition to start up a power supply and obtain the desired output. In the proposed soft-start control method, the speed of the start-up process is flexibly controlled depending on the load condition. To obtain the optimal speed for any load condition, the speed of the soft-start is determined from a approximated function of load current, which is estimated from experiment results in advance. The proposed soft-start control method is evaluated both in simulations and experiments. From results, it is confirmed that the proposed method has superior soft-start characteristics compared to the conventional one.

Due to the rapid growth of applications that are based on Internet of Things (IoT) and real-time communications, mobile traffic growth is increasing exponentially. In highly populated areas, sudden concentration of numerous mobile user traffic can cause radio resource shortage, where traffic offloading is essential in preventing overload problems. Vertical handover (VHO) technology which supports seamless connectivity across heterogeneous wireless networks is a core technology of traffic offloading. In VHO, minimizing service interruption is a key design factor, since service interruption deteriorates service performance and degrades user experience (UX). Although 3GPP standard VHO procedures are designed to prevent service interruption, severe quality of service (QoS) degradation and severe interruption can occur in real network environments due to unintended disconnections with one's base station (BS) or access point (AP). In this article, the average minimum handover interruption time (HIT) (i.e., the guaranteed HIT influence) between LTE and Wi-Fi VHO is analyzed and measured based on 3GPP VHO access and decision procedures. In addition, the key parameters and procedures which affect HIT performance are analyzed, and a reference probability density function (PDF) for HIT prediction is derived from Kolmogorov-Smirnov test techniques.

In this paper, we investigate a user and antenna joint selection problem in multi-user large-scale MIMO downlink networks, where a BS with N transmit antennas serves K users, and N is much larger than K. The BS activates only S(S≤N) antennas for data transmission to reduce hardware cost and computation complexity, and selects the set of users to which data is to be transmitted by maximizing the sum-rate. The optimal user and antenna joint selection scheme based on exhaustive search causes considerable computation complexity. Thus, we propose a new joint selection algorithm with low complexity and analyze the performance of the proposed scheme in terms of sum-rate and complexity. When S=7, N=10, K=5, and SNR=10dB, the sum-rate of the proposed scheme is 5.1% lower than that of the optimal scheme, while the computation complexity of the proposed scheme is reduced by 99.0% compared to that of the optimal scheme.

In this letter, we focus on the subcarrier allocation problem for device-to-device (D2D) communication in cellular networks to improve the cellular energy efficiency (EE). Our goal is to maximize the weighted cellular EE and its solution is obtained by using a game-theoretic learning approach. Specifically, we propose a lower bound instead of the original optimization objective on the basis of the proven property that the gap goes to zero as the number of transmitting antennas increases. Moreover, we prove that an exact potential game applies to the subcarrier allocation problem and it exists the best Nash equilibrium (NE) which is the optimal solution to optimize the lower bound. To find the best NE point, a distributed learning algorithm is proposed and then is proved that it can converge to the best NE. Finally, numerical results verify the effectiveness of the proposed scheme.

Distributed compressive video sensing (DCVS) is a new paradigm for low-complexity video compression. To achieve the highest possible perceptual coding performance under the measurements budget constraint, we propose a perceptual optimized DCVS codec by jointly exploiting the reweighted sampling and rate-distortion optimized measurements allocation technologies. A visual saliency modulated just-noticeable distortion (VS-JND) profile is first developed based on the side information (SI) at the decoder side. Then the estimated correlation noise (CN) between each non-key frame and its SI is suppressed by the VS-JND. Subsequently, the suppressed CN is utilized to determine the weighting matrix for the reweighted sampling as well as to design a perceptual rate-distortion optimization model to calculate the optimal measurements allocation for each non-key frame. Experimental results indicate that the proposed DCVS codec outperforms the other existing DCVS codecs in term of both the objective and subjective performance.

To analyze large-scale data efficiently, studies on Hadoop, one of the most popular MapReduce frameworks, have been actively done. Meanwhile, most of the large-scale data analysis applications, e.g., data clustering, are required to do the same map and reduce functions repeatedly. However, Hadoop cannot provide an optimal performance for iterative MapReduce jobs because it derives a result by doing one phase of map and reduce functions. To solve the problems, in this paper, we propose a new efficient resource management framework for iterative MapReduce processing in large-scale data analysis. For this, we first design an iterative job state-machine for managing the iterative MapReduce jobs. Secondly, we propose an invariant data caching mechanism for reducing the I/O costs of data accesses. Thirdly, we propose an iterative resource management technique for efficiently managing the resources of a Hadoop cluster. Fourthly, we devise a stop condition check mechanism for preventing unnecessary computation. Finally, we show the performance superiority of the proposed framework by comparing it with the existing frameworks.

Most existing methods on research collaborator recommendation focus on promoting collaboration within a specific discipline and exploit a network structure derived from co-authorship or co-citation information. To find collaboration opportunities outside researchers' own fields of expertise and beyond their social network, we present an interdisciplinary collaborator recommendation method based on research content similarity. In the proposed method, we calculate textual features that reflect a researcher's interests using a research grant database. To find the most relevant researchers who work in other fields, we compare constructing a pairwise similarity matrix in a feature space and exploiting existing social networks with content-based similarity. We present a case study at the Graduate University for Advanced Studies in Japan in which actual collaborations across departments are used as ground truth. The results indicate that our content-based approach can accurately predict interdisciplinary collaboration compared with the conventional collaboration network-based approaches.

This letter proposes a Non-uniform Cell-based Index (NCI) to enable clients to quickly process window queries in the wireless spatial data broadcast environment. To improve the access time, NCI reduces the probe wait time by equalized spacing between indexes, using non-uniformly partitioned cells of data space. Through the performance evaluation, we show the proposed NCI outperforms the existing index schemes for window queries to spatial data in respect of access time.

Iterative channel estimation and decoding receivers have evolved over the years, most especially with Turbo and LPDC codes. Nevertheless, few works have determined the performance of symbol level Reed-Solomon (RS) codes in iterative receiver structures. The iterative channel estimation and symbol level RS decoding receiver structure found in literature concentrate on M-QAM systems over flat Rayleigh fading channels. In this paper, attention is focused on the performance of RS codes in iterative channel estimation and decoding receiver structures for Orthogonal Frequency Division Multiplexing (OFDM) systems on frequency-selective Rayleigh fading channels. Firstly, the paper extends the Koetter and Vardy (KV) RS iterative receiver structure over flat Rayleigh fading channels to frequency-selective Rayleigh fading channels. In addition, the paper develops a symbol level RS iterative receiver structure for OFDM systems on frequency-selective Rayleigh fading channels based on the Parity-check matrix Transformation Algorithm (PTA). The performance of the RS-KV and RS-PTA iterative receiver structures for OFDM systems are documented through computer simulation. The simulation results verify that both iterative receiver structures are suitable for real time RS OFDM wireless applications. The results also show that the developed RS-PTA iterative receiver structure is a low complexity and high performance alternative to the RS-KV iterative receiver structure.

This paper proposes a new approach for generating pseudo random multi-valued (including binary-valued) sequences. The approach uses a primitive polynomial over an odd characteristic prime field ${p}$, where p is an odd prime number. Then, for the maximum length sequence of vectors generated by the primitive polynomial, the trace function is used for mapping these vectors to scalars as elements in the prime field. Power residue symbol (Legendre symbol in binary case) is applied to translate the scalars to k-value scalars, where k is a prime factor of p-1. Finally, a pseudo random k-value sequence is obtained. Some important properties of the resulting multi-valued sequences are shown, such as their period, autocorrelation, and linear complexity together with their proofs and small examples.