A Networked Control System (NCS) can be considered a form of Cyber-Physical System (CPS) with its network architecture and typical features, such as delay, jitter and package loss. So far, less discussion has been carried out for NCS from the view point of CPS. In this letter, the NCS with short delay is analyzed with cyber-physical integration. The sampling rate is depicted as one of the states in the state equations. The simulation results show that the cyber-physical integration not only adjusts the sampling rate to the states of the controlled physical system, but also adapts to the delay of the network. The averaged sampling rate and the stabilization time are smaller compared with the traditional NCS.

For battery based real-time embedded systems, high performance to meet their real-time constraints and energy efficiency to extend battery life are both essential. Real-Time Dynamic Voltage Scaling (RT-DVS) has been a key technique to satisfy both requirements. This paper presents EccEDF (Enhanced ccEDF), an efficient algorithm based on ccEDF. ccEDF is one of the most simple but efficient RT-DVS algorithms. Its simple structure enables it to be easily and intuitively coupled with a real-time operating system without incurring any significant cost. ccEDF, however, overlooks an important factor in calculating the available slacks for reducing the operating frequency. It calculates the saved utilization simply by dividing the slack by the period without considering the time needed to run the task. If the elapsed time is considered, the maximum utilization saved by the slack on completion of the task can be found. The proposed EccEDF can precisely calculate the maximum unused utilization with consideration of the elapsed time while keeping the structural simplicity of ccEDF. Further, we analytically establish the feasibility of EccEDF using the fluid scheduling model. Our simulation results show that the proposed algorithm outperforms ccEDF in all simulations. A simulation shows that EccEDF consumes 27% less energy than ccEDF.

This paper proposes the state observer design for feedforward nonlinear systems with delayed output. It is shown that by using the Lyapunov-Krasovskii functional, the proposed design method ensures the asymptotic stability of estimation error for an arbitrarily large output delay. Finally, an illustrative example is given in order to show the effectiveness of our design method.

In this paper, we propose a new trusted modeling approach based on state graphs. We introduce a novel method of deriving state-layer from a system call sequence in terms of probability and statistics theory, and we identify the state sequence with the help of Hidden Markov Model (HMM). We generate state transition graph according to software executing process and pruning rules. Then, we separate local function graphs according to software specific functions by semantic analysis. The state-layer is a bridge between the basic behaviors and the upper layer functions of software to compensate semantic faults. In addition, a pruning strategy of formulating state graphs is designed to precisely describe each piece of software functions. Finally, a detecting system based on our model is proposed, and a case study of RSS software reveals how our system works. The results demonstrate that our trusted model describes software behaviors successfully and can well detect un-trust behaviors, anomaly behaviors, and illegal input behaviors.

This paper addresses a broadcast control problem of multi-agent systems with quantized measurements, where each agent moves based on the common broadcasted signal and tries to minimize a given quadratic performance index. The problem is solved by introducing dither type random movements to the agents' action which reduce the degradation caused by quantized measurements. A broadcast controller is derived and it is proven that the controller approximately achieves given tasks with probability 1. The effectiveness of the proposed controller is demonstrated by numerical simulation.

Faced with social problems such as rapidly aging society, the solutions have been expected in sports medicine. Humans became widely distributed on the earth from their birth by acquiring abilities to walk in an upright position and to adapt themselves to various natural environments. However, seeking a ‘comfortable environment’ in modern civilization has deteriorated these genetic characteristics of humans, and the consumption of resources and energy to acquire such a ‘comfortable environment’ has induced global warming-associated natural disasters and the destruction of social order. To halt this vicious cycle, we may reactivate the genetic characteristics in humans by doing exercise. To do this, we have developed a health promotion program for middle aged and older people, Jukunen Taiikudaigaku Program, in cooperation with the Japanese government, developed high-intensity interval walking training (IWT), and examined the physical and mental effects on 5,400 people for these 10 years. We found that IWT for 4 months increased physical fitness by 10-20%, decreased the indices of life-style related diseases by 10-20%. Since a prescription of IWT can be conducted by using an IT network system called e-Health Promotion System, the participants in the program were able to receive the prescription even if they lived remote from trainers, enabling them to perform IWT at their favored places and times, and also at low cost. Moreover, we found some single nucleotide polymorphisms closely related to inter-individual differences in the responses to IWT. Further, the system enables us to assess the inactivation/activation of genes for inflammatory responses which has been suggested to be involved in life-style related diseases. Also, the system enables us to search foods to promote health when they are consumed during exercise training. Thus, the system would have strong potential to promote health of middle-aged and older people in advanced aging society.

This study looks at how an e-Health System can reduce morbidity (poor health) in unreached communities. The e-Health system combines affordable sensors and Body Area Networking technology with mobile health concepts and is called a Portable Health Clinic. The health clinic is portable because all the medical devices fit inside a briefcase and are carried to unreached communities by a healthcare assistants. Patient morbidity is diagnosed using software stratification algorithm and categorized according to triage color-coding scheme within the briefcase. Morbid patients are connected to remote doctor in a telemedicine call center using the mobile network coverage. Electronic Health Records (EHR) are used for the medical consultancy and e-Prescription is generated. The effectiveness of the portable health clinic system to target morbidity was tested on 8690 patients in rural and urban areas of Bangladesh during September 2012 to January 2013. There were two phases to the experiment: the first phase identified the intensity of morbidity and the second phase re-examined the morbid patients, two months later. The experiment results show a decrease in patients to identify as morbid among those who participated in telemedicine process.

In this paper, a new evolutionary approach to recommender systems is presented. The aim of this work is to develop a new recommendation method that effectively adapts and immediately responds to the user's preference. To this end, content-based filtering is judiciously utilized in conjunction with interactive evolutionary computation (IEC). Specifically, a fitness-based truncation selection and a feature-wise crossover are devised to make full use of desirable properties of promising items within the IEC framework. Moreover, to efficiently search for proper items, the content-based filtering is modified in cooperation with data grouping. The experimental results demonstrate the effectiveness of the proposed approach, compared with existing methods.

In this letter, we propose a simple but effective technique that improves statistical model-based voice activity detection (VAD) by both reducing computational complexity and increasing detection accuracy. The improvements are made by applying Taylor series approximations to the exponential and logarithmic functions in the VAD algorithm based on an in-depth analysis of the algorithm. Experiments performed on a smartphone as well as on a desktop computer with various background noises confirm the effectiveness of the proposed technique.

Spectrum sensing is one of the methods to identify available white spaces for secondary usage which was specified by the regulators. However, signal quality to be sensed can plunge to a very low signal-to-noise-ratio due to signal propagation and hence readings from individual sensors will be unreliable. Distributed sensing by the cooperation of multiple sensors is one way to cope with this problem because the diversity gain due to the combining effect of data captured at different position will assist in detecting signals that might otherwise not be detected by a single sensor. In effect, the probability of detection can be improved. We have implemented a distributed sensing system to evaluate the performance of different cooperative sensing algorithms. In this paper we describe our implementation and measurement experience which include the system design, specification of the system, measurement method, the issues and solutions. This paper also confirms the performance enhancement offered by distributed sensing algorithms, and describes several ideas for further enhancement of the sensing quality.

This paper describes an analytical study of performance of a proposed signal detection scheme that will allow coexistence of an additional radio communication system (generally, secondary system) in the service area where the existing communication system (primary system) is operated. Its performance characteristics are derived by an analytical method based on stochastic theory, which is subsequently validated by software simulation. The main purpose of the detection scheme is to protect the primary system from the secondary system. In such a situation, the signals of the primary system and secondary system may be simultaneously received in the signal detector. One application of such a scheme is D-to-D (Device-to-Device) communication, whose system concept including the detection scheme is briefly introduced. For improved secondary signal detection, we propose the signal cancellation method of the primary system and the feature detection method of the secondary system signal. We evaluate the performance characteristics of the detection scheme in terms of “probability of correct detection”. We reveal that an undesired random component is produced in the feature detection procedure when two different signals are simultaneously received, which degrades the detection performance. Such undesired component is included in the analytical equations. We also clarify that the cancellation scheme improves the performance, when the power ratio of the primary signal to secondary signal is higher than 20-22dB.

This paper addresses the discrete abstraction problem for stochastic nonlinear systems with continuous-valued state. The proposed solution is based on a function, called the bisimulation function, which provides a sufficient condition for the existence of a discrete abstraction for a given continuous system. We first introduce the bisimulation function and show how the function solves the problem. Next, a convex optimization based method for constructing a bisimulation function is presented. Finally, the proposed framework is demonstrated by a numerical simulation.

In this study, a new method for Decode-Distributed Beamforming (D-DB) relaying is proposed. Each relay node decodes the source symbol by maximum likelihood detection. The detected symbol is entered into the stored Quantized Equal-gain (QE) codebook, where the label of the phase region is provided by a feedback link from the destination node. Therefore, the proposed relay network forms a Decode-Distributed QE (D-DQE) relay network. The performances of the D-DQE codebooks are examined by Monte-Carlo simulations, in which the feedback links and channel estimations are assumed to be error-free. The simulation results reveal that the symbol error rates of the D-DQE relay system improve the error performance of the QE codebooks when relay nodes are close to the source node. When error-free feedback bits are provided, the performance of the proposed D-DQE is better than that of Alamouti's Decode-Distributed Space-Time Coding (D-DSTC) relay network. The weakest relays are rejected to improve the performance of the D-DQE codebooks and reduce the number of feedback bits. This relay network is called Decode-Relay Rejection for Distributed Beamforming (D-RRDB) relay networks.

This paper is concerned with exploring an extended approach for the stability analysis and synthesis for Markovian jump nonlinear systems (MJNLSs) via fuzzy control. The Takagi-Sugeno (T-S) fuzzy model is employed to represent the MJNLSs with incomplete transition description. In this paper, not all the elements of the rate transition matrices (RTMs), or probability transition matrices (PTMs) are assumed to be known. By fully considering the properties of the RTMs and PTMs, sufficient criteria of stability and stabilization is obtained in both continuous and discrete-time. Stabilization conditions with a mode-dependent fuzzy controller are derived for Markovian jump fuzzy systems in terms of linear matrix inequalities (LMIs), which can be readily solved by using existing LMI optimization techniques. Finally, illustrative numerical examples are provided to demonstrate the effectiveness of the proposed approach.

Many controllers are implemented on digital platforms as periodic control tasks. But, in embedded systems, an amount of resources are limited and the reduction of resource utilization of the control task is an important issue. Recently, much attention has been paid to a self-triggered controller, which updates control inputs aperiodically. A control task by which the self-triggered controller is implemented skips the release of jobs if the degradation of control performances by the skipping can be allowed. Each job computes not only the updated control inputs but also the next update instant and the control task is in the sleep state until the instant. Thus the resource utilization is reduced. In this paper, we consider self-triggered predictive control (stPC) of mixed logical dynamical (MLD) systems. We introduce a binary variable which determines whether the control inputs are updated or not. Then, we formulate an stPC problem of mixed logical dynamical systems, where activation costs are time-dependent to represent the preference of activations of the control task. Both the control inputs and the next update instant are computed by solving a mixed integer programming problem. The proposed stPC can reduce the number of updates with guaranteeing stability of the controlled system.

This letter deals with a new cell clustering problem subject to signal-to-interference-plus-noise-ratio (SINR) constraints in uplink network MIMO systems, where multiple base stations (BSs) cooperate for joint processing as forming a cluster. We first prove that the SINRs of users in a certain cluster always increase monotonically as the cluster size increases when the receiver filter that maximizes the SINR is used. Using this result, we propose an efficient clustering algorithm to minimize the maximum number of cooperative BSs in a cluster. Simulation results show that the maximum number of cooperative BSs minimized by the proposed method is close to that minimized by the exhaustive search and the proposed scheme outperforms the conventional one in terms of the outage probability.

We propose a fast and resource-efficient agreement protocol on a request set, which is used to realize Byzantine fault tolerant server replication. Although most existing randomized protocols for Byzantine agreement exploit a modular approach, that is, a combination of agreement on a bit value and a reduction of request set values to the bit values, our protocol directly solves the multi-valued agreement problem for request sets. We introduce a novel coin tossing scheme to select a candidate of an agreed request set randomly. This coin toss allows our protocol to reduce resource consumption and to attain faster response time than the existing representative protocols.

This paper presents sufficient conditions for the existence of a common quadratic Lyapunov functions for two classes of switched linear systems which possess negative row strictly diagonally dominant and diagonalizable stable state matrices, respectively. Numerical examples will be given to verify the correctness of the proposed theorems.

A stochastic hybrid system can express complex dynamical systems such as biological systems and communication networks, but computation for analysis and control is frequently difficult. In this paper, for a class of stochastic hybrid systems, a discrete abstraction method in which a given system is transformed into a finite-state system is proposed based on the notion of bounded bisimulation. In the existing discrete abstraction method based on bisimulation, a computational procedure is not in general terminated. In the proposed method, only the behavior for the finite time interval is expressed as a finite-state system, and termination is guaranteed. Furthermore, analysis of genetic toggle switches is also discussed as an application.

We propose a lightweight scheme for fault diagnosis in time-triggered (TT) systems. An existing scheme is preferable in its capability but incurs computation time that can be prohibitively large for some real-time systems, such as automotive control systems. Our proposed scheme, which we call voting sharing, can substantially reduce the computation time by sharing the diagnosis result obtained by each node with all nodes in the system. We clarify the properties of the voting sharing scheme with respect to fault tolerance and show some experimental results.