This paper presents a numerical study of the wireless channel characteristics of liver implants in a frequency range of 4.5-6.5GHz, considering different digital human phantoms by employing two inhomogeneous male and female models. Path loss data for in-body to on-body and in-body to off-body communication scenarios are provided. The influence of respiration-induced organ movement on signal attenuation is demonstrated. A narrower range of attenuation deviation is observed in the female model as compared to the male model. The path loss data in the female body is between 40-80dB which is around 5-10dB lower than the male model. Path loss data for the in-body to off-body scenario in both models suggest that in-body propagation is the main component of total path loss in the channel. The results demonstrate that channel characteristics are subject dependent, and thus indicate the need to take subject dependencies into consideration when investigating in-body communication channels.

Soft error jeopardizes the reliability of semiconductor devices, especially those working at low voltage. In recent years, silicon-on-thin-box (SOTB), which is a FD-SOI device, is drawing attention since it is suitable for ultra-low-voltage operation. This work evaluates the contributions of SRAM, FF and combinational circuit to chip-level soft error rate (SER) based on irradiation test results. For this evaluation, this work performed neutron irradiation test for characterizing single event transient (SET) rate of SOTB and bulk circuits at 0.5 V. Using the SBU and MCU data in SRAMs from previous work, we calculated the MBU rate with/without error correcting code (ECC) and with 1/2/4-col MUX interleaving. Combining FF error rates reported in literature, we estimated chip-level SER and each contribution to chip-level SER for embedded and high-performance processors. For both the processors, without ECC, 95% errors occur at SRAM in both SOTB and bulk chips at 0.5 V and 1.0 V, and the overall chip-level SERs of the assumed SOTB chip at 0.5 V is at least 10 x lower than that of bulk chip. On the other hand, when ECC is applied to SRAM in the SOTB chip, SEUs occurring at FFs are dominant in the high-performance processor while MBUs at SRAMs are not negligible in the bulk embedded chips.

In this paper, new classes of binary generalized cyclotomic sequences of period 2pm+1qn+1 are constructed. These sequences are balanced. We calculate the linear complexity of the constructed sequences with a simple method. The results show that the linear complexity of such sequences attains the maximum.

We present InP-based photodetectors monolithically integrated with a 90° hybrid toward over 400Gb/s coherent transmission systems. To attain a wide 3-dB bandwidth of more than 40GHz for 400Gb/s dual-polarization (DP)-16-ary quadrature amplitude modulation (16QAM) and 600Gb/s DP-64QAM through 64GBaud operation, A p-i-n photodiode structure consisting of a GaInAs thin absorption and low doping n-typed InP buffer layers was introduced to overcome the trade-off between short carrier transit time and low parasitic capacitance. Additionally, this InP buffer layer contributes to the reduction of propagation loss in the 90° hybrid waveguide, that is, this approach allows a high responsivity as well as wide 3-dB bandwidth operation. The coherent receiver module for the C-band (1530nm - 1570nm) operation indicated the wide 3-dB bandwidth of more than 40GHz and the high receiver responsivity of more than 0.070A/W (Chip responsivity within the C-band: 0.130A/W) thanks to photodetectors with this photodiode design. To expand the usable wavelengths in wavelength-division multiplexing toward large-capacity optical transmission, the photodetector integrated with the 90° hybrid optimized for the L-band (1565nm - 1612nm) operation was also fabricated, and exhibited the high responsivity of more than 0.120A/W over the L-band. Finally, the InP-based monolithically integrated photonic device consisting of eight-channel p-i-n photodiodes, two 90° hybrids and a beam splitter was realized for the miniaturization of modules and afforded the reduction of the total footprint by 70% in a module compared to photodetectors with the 90° hybrid and four-channel p-i-n photodiodes.

A spectrum-based fault localization technique (SBFL), which identifies fault location(s) in a buggy program by comparing the execution statistics of the program spectra of passed executions and failed executions, is a popular automatic debugging technique. However, the usefulness of SBFL is mainly affected by the following two factors: accuracy and fault understanding in reality. To solve this issue, we propose a SBFL framework to support fault understanding. In the framework, we firstly localize a suspicious fault module to start debugging and then generate a weighted fault propagation graph (WFPG) for the hypothesis fault module, which weights the suspiciousness for the nodes to further perform block-level fault localization. In order to evaluate the proposed framework, we conduct a controlled experiment to compare two different module-level SBFL approaches and validate the effectiveness of WFPG. According to our preliminary experiments, the results are promising.

The needs for ultra-high speed short- to medium-reach optical fiber links beyond 100-Gbit/s is becoming larger and larger especially for intra and inter-data center applications. In recent intensity-modulated/direct-detection (IM/DD) high-speed optical transceivers with the channel bit rate of 50 and/or 100 Gbit/s, multilevel pulse amplitude modulation (PAM) is finally adopted to lower the signaling speed. To further increase the transmission capacity for the next-generation optical transceivers, various signaling techniques have been studied, especially thanks to advanced digital signal processing (DSP). In this paper, we review various signaling technologies proposed so far for short-to-medium reach applications.

Malware-infected hosts have typically been detected using network-based Intrusion Detection Systems on the basis of characteristic patterns of HTTP requests collected with dynamic malware analysis. Since attackers continuously modify malicious HTTP requests to evade detection, novel HTTP requests sent from new malware samples need to be exhaustively collected in order to maintain a high detection rate. However, analyzing all new malware samples for a long period is infeasible in a limited amount of time. Therefore, we propose a system for efficiently collecting HTTP requests with dynamic malware analysis. Specifically, our system analyzes a malware sample for a short period and then determines whether the analysis should be continued or suspended. Our system identifies malware samples whose analyses should be continued on the basis of the network behavior in their short-period analyses. To make an accurate determination, we focus on the fact that malware communications resemble natural language from the viewpoint of data structure. We apply the recursive neural network, which has recently exhibited high classification performance in the field of natural language processing, to our proposed system. In the evaluation with 42,856 malware samples, our proposed system collected 94% of novel HTTP requests and reduced analysis time by 82% in comparison with the system that continues all analyses.

To solve the low accuracy problem of the recommender system for long term users, in this paper, we propose a top-N-balanced sequential recommendation based on recurrent neural network. We postulated and verified that the interactions between users and items is time-dependent in the long term, but in the short term, it is time-independent. We balance the top-N recommendation and sequential recommendation to generate a better recommender list by improving the loss function and generation method. The experimental results demonstrate the effectiveness of our method. Compared with a state-of-the-art recommender algorithm, our method clearly improves the performance of the recommendation on hit rate. Besides the improvement of the basic performance, our method can also handle the cold start problem and supply new users with the same quality of service as the old users.

In this paper, a scramble phase assisting weighted-type fractional Fourier transform (SPA-WFRFT) based system is proposed to guarantee the communication's security. The original transmitting signal is divided into two parts. The first part is modulated by WFRFT and subsequently makes up the constellation beguiling. The other part is used to generate the scramble phase and also to assist in the encryption of the WFRFT modulated signal dynamically. The novel constellation optimal model is built and solved through the genetic algorithm (GA) for the constellation beguiling. And the double pseudo scheme is implemented for the scramble phase generation. Theoretical analyses show that excellent security performances and high spectral efficiency can be attained. Final simulations are carried out to evaluate the performances of the SPA-WFRFT based system, and demonstrate that the proposed system can effectively degrade the unauthorized receivers' bit error rate (BER) performance while maintaining its own communication quality.

A topological quantum circuit is a representation model for topological quantum computation, which attracts much attention recently as a promising fault-tolerant quantum computation model by using 3D cluster states. A topological quantum circuit can be considered as a set of “loops,” and we can transform the topology of loops without changing the functionality of the circuit if the transformation satisfies certain conditions. Thus, there have been proposed many researches to optimize topological quantum circuits by transforming the topology. There are two directions of research to optimize topological quantum circuits. The first group of research considers so-called a placement and wiring problem where we consider how to place “parts” in a 3D space which corresponds to already optimized sub-circuits. The second group of research focuses on how to optimize the structure and locations of loops in a relatively small circuit which is treated as one part in the above-mentioned first group of research. This paper proposes a new idea for the second group of research; our idea is to consider topological transformations as a placement and wiring problem for modules which we derive from the information how loops are crossed. By using such a formulation, we can use the techniques for placement and wiring problems, and successfully obtain an optimized solution. We confirm by our experiment that our method indeed can reduce the cost much more than the method by Paetznick and Fowler.

The IEEE 802.11p Enhanced Distributed Channel Access (EDCA) is a standardization for vehicle-to-vehicle and road-to-vehicle communications. The saturated throughputs of the IEEE 802.11p EDCA obtained from previous analytical expressions differ from those of simulations. The purpose of this paper is to explain the reason why the differences appear in the previous analytical model of the EDCA. It is clarified that there is a special state wherein the Backoff Timer (BT) is decremented in the first time slot of after a frame transmission, which cannot be expressed in the previous Markov model. In addition, this paper proposes modified Markov models, which allow the IEEE 802.11p EDCA to be correctly analyzed. The proposed models describe BT-decrement procedure in the first time slot accurately by adding new states to the previous model. As a result, the proposed models provide accurate transmission probabilities of network nodes. The validity of the proposed models is confirmed by the quantitative agreements between analytical predictions and simulation results.

We report our recent progress in silicon photonics integrated device technology targeting on-chip-level large-capacity optical interconnect applications. To realize high-capacity data transmission, we successfully developed on-package-type silicon photonics integrated transceivers and demonstrated simultaneous 400 Gbps operation. 56 Gbps pulse-amplitude-modulation (PAM) 4 and wavelength-division-multiplexing technologies were also introduced to enhance the transmission capacity.

Spectral graph theory, based on the adjacency matrix or the Laplacian matrix that represents the network topology and link weights, provides a useful approach for analyzing network structure. However, in large scale and complex social networks, since it is difficult to completely know the network topology and link weights, we cannot determine the components of these matrices directly. To solve this problem, we propose a method for indirectly determining the Laplacian matrix by estimating its eigenvalues and eigenvectors using the resonance of oscillation dynamics on networks.

All digital phased arrays generate multiple beams concurrently through the digital beam forming technique, which features digital processing with multiple identical receiving/transmitting channels in RF or microwave frequencies. However, the performance of this process strongly depends on accurately matching the amplitude and phase of the channels, as mismatching is likely to degrade radar performance. In this paper, we present a method to calibrate receiving array by using NCO phase increasing algorithm, which simplifies array system by removing the external far-field calibration signals often needed in array systems. Both analysis and simulation results suggest that the proposed method attains better calibration performance than existing approaches, even with a low SNR input signal. Experiments also varify that the proposed calibration method is effective and achieves a desired radiation pattern. We can further boost calibration accuracy and reduce calibration time by programming NCO phase width and NCO phase resolution.

This paper surveys advances in biomedical processor SoC technology for healthcare application and reviews state-of-the-art architecture and circuits used in SoC integration. Particularly, this paper categorizes and describes techniques for improving power efficiency in communication, computation, and sensing. Additionally, it surveys accuracy enhancement techniques for bio-signal measurement and recognition. Finally, we have discussed the potential new directions for development as well as research.

To address the bandwidth bottleneck that exists between LSI chips, we have proposed a novel, high-sensitivity receiver circuit for differential optical transmission on a silicon optical interposer. Both anodes and cathodes of the differential photodiodes (PDs) were designed to be connected to a transimpedance amplifier (TIA) through coupling capacitors. Reverse bias voltage was applied to each of the differential PDs through load resistance. The proposed receiver circuit achieved double the current signal amplitude of conventional differential receiver circuits. The frequency response of the receiver circuit was analyzed using its equivalent circuit, wherein the temperature dependence of the PD was implemented. The optimal load resistances of the PDs were determined to be 5kΩ by considering the tradeoff between the frequency response and bias voltage drop. A small dark current of the PD was important to reduce the voltage drop, but the bandwidth degradation was negligible if the dark current at room temperature was below 1µA. The proposed circuit achieved 3-dB bandwidths of 18.9 GHz at 25°C and 13.7 GHz at 85°C. Clear eye openings in the TIA output waveforms for 25-Gbps 27-1 pseudorandom binary sequence signals were obtained at both temperatures.

This study presents a joint dictionary learning approach for speech emotion recognition named locality preserved joint nonnegative matrix factorization (LP-JNMF). The learned representations are shared between the learned dictionaries and annotation matrix. Moreover, a locality penalty term is incorporated into the objective function. Thus, the system's discriminability is further improved.

The recent widespread use of high-performance terminals has resulted in a rapid increase in mobile data traffic. Therefore, public wireless local area networks (WLANs) are being used often to supplement the cellular networks. Capacity improvement through the dense deployment of access points (APs) is being considered. However, the effective throughput degrades significantly when many users connect to a single AP. In this paper, users are classified into guaranteed bit rate (GBR) users and best effort (BE) users, and we propose a network model to provide those services. In the proposed model, physical APs and the bandwidths are assigned to each service class dynamically using a virtual AP configuration and a virtualized backhaul network, for reducing the call-blocking probability of GBR users and improving the satisfaction degree of BE users. Finally, we evaluate the performance of the proposed model through simulation experiments and discuss its feasibility.

To recognize transportation modes without any additional sensor devices, we demonstrate that the transportation modes can be recognized from communication quality factors. In the demonstration, instead of using global positioning system (GPS) and accelerometer sensors, we collect mobile TCP throughputs, received-signal strength indicators (RSSIs), and cellular base-station IDs (Cell IDs) through in-line network measurement when the user enjoys mobile services, such as video streaming. In accuracy evaluations, we conduct two different field experiments to collect the data in six typical transportation modes (static, walking, riding a bicycle, riding a bus, riding a train and riding a subway), and then construct the classifiers by applying a support-vector machine (SVM), k-nearest neighbor (k-NN), random forest (RF), and convolutional neural network (CNN). Our results show that these transportation modes can be recognized with high accuracy by using communication quality factors as well as the use of accelerometer sensors.

In this paper, a parallel flow monitoring technique that achieves accurate measurement of end-to-end delay of networks is proposed. In network monitoring tasks, network researchers and practitioners usually monitor multiple probe flows to measure delays on multiple paths in parallel. However, when they measure an end-to-end delay on a path, information of flows except for the flow along the path is not utilized in the conventional method. Generally, paths of flows share common parts in parallel monitoring. In the proposed method, information of flows on paths that share common parts, utilizes to measure delay on a path by partially converting the observation results of a flow to those of another flow. We perform simulations to confirm that the observation results of 72 parallel flows of active measurement are appropriately converted between each other. When the 99th-percentile of the end-to-end delay for each flow are measured, the accuracy of the proposed method is doubled compared with the conventional method.