Digitization of analog terrestrial TV broadcasting has recently been accelerated in many countries, and the effective utilization of vacant frequencies has also been investigated for new systems in each country. In Japan, a portion of vacant frequencies in the VHF-high band was allocated to the public broadband mobile communication (PBB) system. To evaluate the current PBB system and develop future broadband communication systems in this band, it is important to analyze the propagation channel more accurately. In this study, we characterize the propagation channel for 200MHz band broadband mobile communication systems, using measured channel impulse responses (CIRs). In the characterization process, the Saleh-Valenzuela (S-V) model is utilized to extract channel model parameters statistically. When evaluating the fluctuation of path power gain, we also propose to model the fluctuation of path power gain using the generalized extreme value distribution instead of the conventional log-normal distribution. The extracted CIR model parameters are validated by cumulative distribution function of root-means-square delay spread and maximum excess delay, comparing simulation result to measurement result. From the extracted CIR model parameters, we clarified the characteristics of 200MHz band broadband mobile communication systems in non-line-of-sight environments based on S-V model with the proposed channel model.

Adaptive noise cancellation using adaptive filters is a known method for removing noise that interferes with signal measurements. The adaptive noise canceller performs filtering based on the current situation through a windowing process. The shape of the window function determines the tracking performance of the adaptive noise canceller with respect to the fluctuation of the property of the unknown system that noise (reference signal) passes. However, the shape of the window function in the field of adaptive filtering has not yet been considered in detail. This study mathematically treats the effect of the window function on the adaptive noise canceller and proposes an optimization method for the window function in situations where offline processing can be performed, such as biomedical signal measurements. We also demonstrate the validity of the optimized window function through numerical experiments.

The number of IT services that use machine learning (ML) algorithms are continuously and rapidly growing, while many of them are used in practice to make some type of predictions from personal data. Not surprisingly, due to this sudden boom in ML, the way personal data are handled in ML systems are starting to raise serious privacy concerns that were previously unconsidered. Recently, Fredrikson et al. [USENIX 2014] [CCS 2015] proposed a novel attack against ML systems called the model inversion attack that aims to infer sensitive attribute values of a target user. In their work, for the model inversion attack to be successful, the adversary is required to obtain two types of information concerning the target user prior to the attack: the output value (i.e., prediction) of the ML system and all of the non-sensitive values used to learn the output. Therefore, although the attack does raise new privacy concerns, since the adversary is required to know all of the non-sensitive values in advance, it is not completely clear how much risk is incurred by the attack. In particular, even though the users may regard these values as non-sensitive, it may be difficult for the adversary to obtain all of the non-sensitive attribute values prior to the attack, hence making the attack invalid. The goal of this paper is to quantify the risk of model inversion attacks in the case when non-sensitive attributes of a target user are not available to the adversary. To this end, we first propose a general model inversion (GMI) framework, which models the amount of auxiliary information available to the adversary. Our framework captures the model inversion attack of Fredrikson et al. as a special case, while also capturing model inversion attacks that infer sensitive attributes without the knowledge of non-sensitive attributes. For the latter attack, we provide a general methodology on how we can infer sensitive attributes of a target user without knowledge of non-sensitive attributes. At a high level, we use the data poisoning paradigm in a conceptually novel way and inject malicious data into the ML system in order to modify the internal ML model being used into a target ML model; a special type of ML model which allows one to perform model inversion attacks without the knowledge of non-sensitive attributes. Finally, following our general methodology, we cast ML systems that internally use linear regression models into our GMI framework and propose a concrete algorithm for model inversion attacks that does not require knowledge of the non-sensitive attributes. We show the effectiveness of our model inversion attack through experimental evaluation using two real data sets.

In this letter, we consider the harvested-energy fairness problem in cognitive multicast systems with simultaneous wireless information and power transfer. In the cognitive multicast system, a cognitive transmitter with multi-antenna sends the same information to cognitive users in the presence of licensed users, and cognitive users can decode information and harvest energy with a power-splitting structure. The harvested-energy fairness problem is formulated and solved by using two proposed algorithms, which are based on semidefinite relaxation with majorization-minimization method, and sequential parametric convex approximation with feasible point pursuit technique, respectively. Finally, the performances of the proposed solutions and baseline schemes are verified by simulation results.

We propose the cube-based perceptual encryption (C-PE), which consists of cube scrambling, cube rotation, cube negative/positive transformation, and cube color component shuffling, and describe its application to the encryption-then-compression (ETC) system of Motion JPEG (MJPEG). Especially, cube rotation replaces the blocks in the original frames with ones in not only the other frames but also the depth-wise cube sides (spatiotemporal sides) unlike conventional block-based perceptual encryption (B-PE). Since it makes intra-block observation more difficult and prevents unauthorized decryption from only a single frame, it is more robust than B-PE against attack methods without any decryption key. However, because the encrypted frames including the blocks from the spatiotemporal sides affect the MJPEG compression performance slightly, we also devise a version of C-PE with no spatiotemporal sides (NSS-C-PE) that hardly affects compression performance. C-PE makes the encrypted video sequence robust against the only single frame-based algorithmic brute force (ABF) attack with only 21 cubes. The experimental results show the compression efficiency and encryption robustness of the C-PE/NSS-C-PE-based ETC system. C-PE-based ETC system shows mixed results depending on videos, whereas NSS-C-PE-based ETC system shows that the BD-PSNR can be suppressed to about -0.03dB not depending on videos.

In this paper, we consider coded multi-input multi-output (MIMO) systems with low-density parity-check (LDPC) codes and space-time block code (STBC) in MIMO channels. The LDPC code takes the role of a channel code while the STBC provides spatial-temporal diversity. The performance of such coded MIMO system has been shown to be excellent in the past. In this paper, we present a performance analysis for an upper bound on probability of error for coded MIMO schemes. Compared to previous works, the proposed approach for the upper bound can avoid any explicit weight enumeration of codewords and provide a significant step for the upper bound by using a multinomial theorem. In addition, we propose a log domain convolution that enables us to handle huge numbers, e.g., 10500. Comparison of system simulations and numerical evaluations shows that the proposed upper bound is applicable for various coded MIMO systems.

This paper presents a high step-up DC-DC converter for low voltage sources such as solar cells, fuel cells and battery banks. A novel non isolated Zero-Voltage Switching (ZVS) interleaved DC-DC boost converter condition is introduced. In this converter, by using coupled inductor and active clamp circuit, the stored energy in leakage inductor is recycled. Furthermore, ZVS turn on condition for both main and clamp switches are provided. The active clamp circuit suppresses voltage spikes across the main switch and the voltage of clamp capacitor leads to higher voltage gain. In the proposed converter, by applying interleaved technique, input current ripple and also conduction losses are decreased. Also, with simple and effective method without applying any additional element, the input ripple due to couple inductors and active clamp circuit is cancelled to achieve a smooth low ripple input current. In addition, the applied technique in this paper leads to increasing the life cycle of circuit components which makes the proposed converter suitable for high power applications. Finally an experimental prototype of the presented converter with 40 V input voltage, 400 V output voltage and 200 W output power is implemented which verifies the theoretical analysis.

As real-time embedded systems are required to accommodate various tasks with different levels of criticality, scheduling algorithms for MC (Mixed-Criticality) systems have been widely studied in the real-time systems community. Most studies have focused on MC uniprocessor systems whereas there have been only a few studies to support MC multiprocessor systems. In particular, although the ZL (Zero-Laxity) policy has been known to an effective technique in improving the schedulability performance of base scheduling algorithms on SC (Single-Criticality) multiprocessor systems, the effectiveness of the ZL policy on MC multiprocessor systems has not been revealed to date. In this paper, we focus on realizing the potential of the ZL policy for MC multiprocessor systems, which is the first attempt. To this end, we design the ZL policy for MC multiprocessor systems, and apply the policy to EDF (Earliest Deadline First), yielding EDZL (Earliest Deadline first until Zero-Laxity) tailored for MC multiprocessor systems. Then, we develop a schedulability analysis for EDZL (as well as its base algorithm EDF) to support its timing guarantee. Our simulation results show a significant schedulability improvement of EDZL over EDF, demonstrating the effectiveness of the ZL policy for MC multiprocessor systems.

In this paper, we propose a secure near-field communication (NFC) for smartphones by combining acoustic and vibrational communication. In our hybrid system, a transmitter transmits an encrypted message and encryption key from a loudspeaker and vibration motor, respectively. While the sound emitted from the loudspeaker propagates through the air, the vibration emitted by the vibration motor propagates through the body of smartphones. Hence, only receivers touching the transmitter can receive both the encrypted message and the key, resulting in secure communication. We designed a software modulator and demodulator suitable for the vibrational communication by using return-to-zero (RZ) code. Then we established a hybrid communication system by combining acoustic and vibrational communication modems, and evaluated its performance in experiments. The results indicate that our hybrid system achieved a secure (among physically contacted devices) and fast (800kbps) NFC for smartphones.

Security facilities such as firewall system and IDS/IPS (Intrusion Detection System/Intrusion Prevention System) have become fundamental solutions against cyber threats. With the rapid change of cyber attack tactics, detail investigations like DPI (Deep Packet Inspection) and SPI (Stateful Packet Inspection) for incoming traffic become necessary while they also cause the decrease of network throughput. In this paper, we propose an SDN (Software Defined Network) - based proactive firewall system in collaboration with domain name resolution to solve the problem. The system consists of two firewall units (lightweight and normal) and a proper one will be assigned for checking the client of incoming traffic by the collaboration of SDN controller and internal authoritative DNS server. The internal authoritative DNS server obtains the client IP address using EDNS (Extension Mechanisms for DNS) Client Subnet Option from the external DNS full resolver during the name resolution stage and notifies the client IP address to the SDN controller. By checking the client IP address on the whitelist and blacklist, the SDN controller assigns a proper firewall unit for investigating the incoming traffic from the client. Consequently, the incoming traffic from a trusted client will be directed to the lightweight firewall unit while from others to the normal firewall unit. As a result, the incoming traffic can be distributed properly to the firewall units and the congestion can be mitigated. We implemented a prototype system and evaluated its performance in a local experimental network. Based on the results, we confirmed that the prototype system presented expected features and acceptable performance when there was no flooding attack. We also confirmed that the prototype system showed better performance than conventional firewall system under ICMP flooding attack.

Zero-difference balanced (ZDB) functions, which have many applications in coding theory and sequence design, have received a lot of attention in recent years. In this letter, based on two known classes of ZDB functions, a new class of ZDB functions, which is defined on the group (Z2e-1×Zn,+) is presented, where e is a prime and n=p1m1p2m2…pkmk, pi is odd prime satisfying that e|(pi-1) for any 1≤i≤k . In the case of gcd(2e-1,n)=1, the new constructed ZDB functions are cyclic.

In this letter, a new semi-blind approach incorporating the bounded nature of communication sources with the distance between the equalizer outputs and the training sequence is proposed. By utilizing the sparsity property of l1-norm cost function, the proposed algorithm can outperform the semi-blind method based on higher-order statistics (HOS) criterion especially for transmitting sources with non-constant modulus. Experimental results demonstrate that the proposed method shows superior performance over the HOS based semi-blind method and the classical training-based method for QPSK and 16QAM sources equalization. While for 64QAM signal inputs, the proposed algorithm exhibits its superiority in low signal-to-noise-ratio (SNR) conditions compared with the training-based method.

Both spatial diversity and multihop relaying are considered to be effective methods for mitigating the impact of atmospheric turbulence-induced fading on the performance of free-space optical (FSO) systems. Multihop relaying can significantly reduce the impact of fading by relaying the information over a number of shorter hops. However, it is not feasible or economical to deploy relays in many practical scenarios. Spatial diversity could substantially reduce the fading variance by introducing additional degrees of freedom in the spatial domain. Nevertheless, its superiority is diminished when the fading sub-channels are correlated. In this paper, our aim is to study the fundamental performance limits of spatial diversity suffering from correlated Gamma-Gamma (G-G) fading channels in multihop coherent FSO systems. For the performance analysis, we propose to approximate the sum of correlated G-G random variables (RVs) as a G-G RV, which is then verified by the Kolmogorov-Smirnov (KS) goodness-of-fit statistical test. Performance metrics, including the outage probability and the ergodic capacity, are newly derived in closed-form expressions and thoroughly investigated. Monte-Carlo (M-C) simulations are also performed to validate the analytical results.

A free-viewpoint application has been developed that yields an immersive user experience. One of the simple free-viewpoint approaches called “billboard methods” is suitable for displaying a synthesized 3D view in a mobile device, but it suffers from the limitation that a billboard should be positioned in only one position in the world. This fact gives users an unacceptable impression in the case where an object being shot is situated at multiple points. To solve this problem, we propose optimal deformation of the billboard. The deformation is designed as a mapping of grid points in the input billboard silhouette to produce an optimal silhouette from an accurate voxel model of the object. We formulate and solve this procedure as a nonlinear optimization problem based on a grid-point constraint and some a priori information. Our results show that the proposed method generates a synthesized virtual image having a natural appearance and better objective score in terms of the silhouette and structural similarity.

Event-centered information integration is regarded as one of the most pressing issues in improving disaster emergency management. Ontology plays an increasingly important role in emergency information integration, and provides the possibility for emergency reasoning. However, the development of event ontology for disaster emergency is a laborious and difficult task due to the increasingly scale and complexity of emergencies. Ontology pattern is a modeling solution to solve the recurrent ontology design problem, which can improve the efficiency of ontology development by reusing patterns. By study on characteristics of numerous emergencies, this paper proposes a generic ontology pattern for emergency system modeling. Based on the emergency ontology pattern, a set of reasoning rules for emergency-evolution, emergency-solution and emergency-resource utilization reasoning were proposed to conduct emergency knowledge reasoning and q.

We propose a method to derive the loop gain from the open-loop and closed-loop output impedances in a dc-dc buck converter with voltage mode and current mode controls. This enables the loop gain to be measured without injecting a signal into the feedback loop, i.e. without breaking the feedback loop; hence the proposed method can be applied to the control circuits implemented on an IC. Our simulation and experiment show that the loop gain determined by the proposed method closely matches that yielded by the conventional method, which has to break the feedback loop. These results confirm that the proposed method can accurately estimate the phase margin.

In terms of system reliability, data recovery is a crucial capability. The lack of data recovery leads to the permanent loss of valuable data. This paper aims at improving data recovery in flash-based storage devices where extremely poor data recovery is shown. For this, we focus on garbage collection that determines the life span of data which have high possibility of data recovery requests by users. A new garbage collection mechanism with awareness of data recovery is proposed. First, deleted or overwritten data are categorized into shallow invalid data and deep invalid data based on the possibility of data recovery requests. Second, the proposed mechanism selects victim area for reclamation of free space, considering the shallow invalid data that have the high possibility of data recovery requests. Our proposal prohibits more shallow invalid data from being eliminated during garbage collections. The experimental results show that our garbage collection mechanism can improve data recovery with minor performance degradation.

Visual object detection on embedded systems involves a multi-objective optimization problem in the presence of trade-offs between power consumption, processing performance, and detection accuracy. For a new Pareto solution with high processing performance and low power consumption, this paper proposes a hardware architecture for decision tree ensemble using multiple channels of features. For efficient detection, the proposed architecture utilizes the dimensionality of feature channels in addition to parallelism in image space and adopts task scheduling to attain random memory access without conflict. Evaluation results show that an FPGA implementation of the proposed architecture with an aggregated channel features pedestrian detector can process 229 million samples per second at 100MHz operation frequency while it requires a relatively small amount of resources. Consequently, the proposed architecture achieves 350fps processing performance for 1080P Full HD images and outperforms conventional object detection hardware architectures developed for embedded systems.

The output feedback consensus problem of nonlinear multi-agent systems under a directed network with a time varying communication delay is studied. In order to deal with this problem, the dynamic output feedback controller with an additional low gain parameter that compensates for the effect of nonlinearity and a communication delay is proposed. Also, it is shown that under some assumptions, the proposed controller can always solve the output feedback consensus problem even in the presence of an arbitrarily large communication delay.

Along with the sophistication of society, the requirements for infrastructure systems are also becoming more sophisticated. Conventionally, infrastructure systems have been accepted if they were safe and stable, but nowadays they are required for serviceability as a matter of course. For this reason, not only the expansion of the scope of the control system but also the integration with the information service system has been frequently carried out. In this paper, we describe safety technology based on autonomous decentralized technology as one of the measures to secure safety in a control system integrating such information service functions. And we propose its future studies.