In this paper, we demonstrate that a formal approach is effective for improving reliability of cooperative robot designs, where the control logics are expressed in concurrent FSMs (Finite State Machines), especially in accordance with the standard FSM4RTC (FSM for Robotic Technology Components), by a case study of cooperative transport robots. In the case study, FSMs are modeled in the formal specification language CSP (Communicating Sequential Processes) and checked by the model-checking tool FDR, where we show techniques for modeling and verification of cooperative robots implemented with the help of the RTM (Robotic Technology Middleware).

To realize an information-centric networking, IPFS (InterPlanetary File System) generates a unique ContentID for each content by applying a cryptographic hash to the content itself. Although it could improve the security against attacks such as falsification, it makes difficult to realize a similarity search in the framework of IPFS, since the similarity of contents is not reflected in the proximity of ContentIDs. To overcome this issue, we propose a method to apply a locality sensitive hash (LSH) to feature vectors extracted from contents as the key of indexes stored in IPFS. By conducting experiments with 10,000 random points corresponding to stored contents, we found that more than half of randomly given queries return a non-empty result for the similarity search, and yield an accurate result which is outside the σ confidence interval of an ordinary flooding-based method. Note that such a collection of random points corresponds to the worst case scenario for the proposed scheme since the performance of similarity search could improve when points and queries follow an uneven distribution.

Heterogeneous networks (HetNets) are emerging as an inevitable method to tackle the capacity crunch of the cellular networks. Due to the complicated network environment and a large number of configured parameters, coverage and capacity optimization (CCO) is a challenging issue in heterogeneous cellular networks. By combining the self-optimizing algorithm for radio frequency (RF) parameters with the power control mechanism of small cells, the CCO problem of self-organizing network is addressed in this paper. First, the optimization of RF parameters is solved based on reinforcement learning (RL), where the base station is modeled as an agent that can learn effective strategies to control the tunable parameters by interacting with the surrounding environment. Second, the small cell can autonomously change the state of wireless transmission by comparing its distance from the user equipment with the virtual cell size. Simulation results show that the proposed algorithm can achieve better performance on user throughput compared to different conventional methods.

This paper proposes relay selection techniques for XOR physical layer network coding with MMSE based non-linear precoding in MIMO bi-directional wireless relaying networks. The proposed selection techniques are derived on the different assumption about characteristics of the MMSE based non-linear precoding in the wireless network. We show that the signal to noise power ratio (SNR) is dependent on the product of all the eigenvalues in the channels from the terminals to relays. This paper shows that the best selection techniques in all the proposed techniques is to select a group of the relays that maximizes the product. Therefore, the selection technique is called “product of all eigenvalues (PAE)” in this paper. The performance of the proposed relay selection techniques is evaluated in a MIMO bi-directional wireless relaying network where two terminals with 2 antennas exchange their information via relays. When the PAE is applied to select a group of the 2 relays out of the 10 relays where an antenna is placed, the PAE attains a gain of more than 13dB at the BER of 10-3.

For improving the fifth-generation mobile communication system, a highly efficient power amplifier must be designed for the base station. An outphasing amplifier is expected to be a solution for achieving high efficiency. We designed a combiner, one of the key components of the outphasing amplifier, using a serial Chireix combiner and fabricated an amplifier with a GaN HEMT, achieving 70% or more high efficiency up to 9 dB back-off power in an 800 MHz band. We also fabricated a 2 GHz-band outphasing amplifier with the same design. We applied digital predistortion (DPD) to control the balance of amplifying units in this amplifier and achieved an average efficiency of 65% under a 20 MHz modulation bandwidth.

A practical Doherty amplifier design method has been developed based on an asymmetric configuration scheme. By embedding a load modulation function into matching circuits of a carrier amplifier (CA) and a peaking amplifier (PA) in the Doherty amplifier, an issue of the Doherty amplifier design is boiled down to the CA and PA matching circuit design. The method can be applied to transistors with unknown parasitic elements if optimum termination impedance conditions for the transistor are obtained from a source-/load-pull technique in simulation or measurement. The design method was applied to GaN HEMT Doherty amplifier MMICs. The fabricated 4.5-GHz-band GaN HEMT Doherty amplifier MMIC exhibited a maximum drain efficiency of 66% and a maximum power-added efficiency (PAE) of 62% at 4.1GHz, with a saturation output power of 36dBm. In addition, PAE of 50% was achieved at 4.1GHz on a 7.2-dB output back-off (OBO) condition. The fabricated 8.5-GHz-band GaN HEMT Doherty amplifier MMIC exhibited a maximum drain efficiency of 53% and a maximum PAE of 44% at 8.6GHz, with a saturation output power of 36dBm. In addition, PAE of 35% was achieved at 8.6GHz on a 6.7-dB (OBO). And, the fabricated 12-GHz-band GaN HEMT Doherty amplifier MMIC exhibited a maximum drain efficiency of 57% and a maximum PAE of 52% at 12.4GHz, with a saturation output power of 34dBm. In addition, PAE of 32% was achieved at 12.4GHz on a 9.5-dB (OBO) condition.

With the advent of 5G and external pressure to reduce greenhouse gas emissions, wireless transceivers with low power consumption are strongly desired for future cellular systems. At the same time, increased modulation order due to the evolution of cellular systems will force power amplifiers to operate at much larger output power back-off to prevent EVM degradation. This paper begins with an analysis of load modulation and asymmetrical Doherty amplifiers. Measurement results will show an apparent 60% efficiency plateau for modulated signals with a large peak-to-average power ratio (PAPR). To exceed this efficiency limitation, the second part of this paper focuses on a new amplification topology based on the amalgamation between Doherty and outphasing. Measurement results of the proposed Doherty-outphasing power amplifier (DOPA) will confirm the feasibility of the approach with a modulated efficiency greater than 70% measured at 10 dB output power back-off.

High power amplifier technologies for base transceiver stations (BTSs) for the 5th generation (5G) mobile communication systems and so-called beyond 5G (B5G) systems are reviewed. For sub-6, which is categorized into frequency range 1 (FR1) in 5G, wideband Doherty amplifiers are introduced, and a multi-band load modulation amplifier, an envelope tracking amplifier, and a digital power amplifier for B5G are explained. For millimeter wave 5G, which is categorized into frequency range 2 (FR2), GaAs and GaN MMICs operating at around 28GHz are introduced. Finally, future prospect for THz GaN devices is described.

Research on wireless power transmission technology is being actively conducted, and studies on spatial transmission methods such as SSPS are currently underway for applications such as power transfer to the upper part of steel towers and power transfer to flying objects such as drones. To enable such applications, it is necessary to examine the configuration of the power-transfer and power-receiving antennas and to improve the RF-DC conversion efficiency (hereinafter referred to as conversion efficiency) of the rectifier circuit on the power-receiving antenna. To improve the conversion efficiency, various methods that utilize full-wave rectification rather than half-wave rectification have been proposed. However, these come with problems such as a complicated circuit structure, the need for additional capacitors, the selection of components at high frequencies, and a reduction in mounting yield. In this paper, we propose a method to improve the conversion efficiency by loading a high-impedance microstrip line as a feedback line in part of the rectifier circuit. We analyzed a class-F rectifier circuit using circuit analysis software and found that the conversion efficiency of the conventional configuration was 54.2%, but the proposed configuration was 69.3%. We also analyzed a measuring circuit made with a discrete configuration in the 5.8-GHz band and found that the conversion efficiency was 74.7% at 24dBm input.

The need for real-time use of human dynamics data is increasing. The technical requirements for this include improved databases for handling a large amount of data as well as highly accurate sensing of people's movements. A bitmap index format has been proposed for high-speed processing of data that spreads in a two-dimensional space. Using the same format is expected to provide a service that searches queries, reads out desired data, visualizes it, and analyzes it. In this study, we propose a coding format that enables human dynamics data to compress it in the target data size, in order to save data storage for successive increase of real-time human dynamics data. In the proposed method, the spatial population distribution, which is expressed by a probability distribution, is approximated and compressed using the one-pixel one-byte data format normally used for image coding. We utilize two kinds of approximation, which are accuracy of probability and precision of spatial location, in order to control the data size and the amount of information. For accuracy of probability, we propose a non-linear mapping method for the spatial distribution, and for precision of spatial location, we propose spatial scalable layered coding to refine the mesh level of the spatial distribution. Also, in order to enable additional detailed analysis, we propose another scalable layered coding that improves the accuracy of the distribution. We demonstrate through experiments that the proposed data approximation and coding format achieve sufficient approximation of spatial population distribution in the given condition of target data size.

In an amusement park, an attraction-visiting route considering the waiting time and traveling time improves visitors' satisfaction and experience. We focus on Ising machines to solve the problem, which are recently expected to solve combinatorial optimization problems at high speed by mapping the problems to Ising models or quadratic unconstrained binary optimization (QUBO) models. We propose a mapping of the visiting-route recommendation problem in amusement parks to a QUBO model for solving it using Ising machines. By using an actual Ising machine, we could obtain feasible solutions one order of magnitude faster with almost the same accuracy as the simulated annealing method for the visiting-route recommendation problem.

Code smells can be detected using tools such as a static analyzer that detects code smells based on source code metrics. Developers perform refactoring activities based on the result of such detection tools to improve source code quality. However, such an approach can be considered as reactive refactoring, i.e., developers react to code smells after they occur. This means that developers first suffer the effects of low-quality source code before they start solving code smells. In this study, we focus on proactive refactoring, i.e., refactoring source code before it becomes smelly. This approach would allow developers to maintain source code quality without having to suffer the impact of code smells. To support the proactive refactoring process, we propose a technique to detect decaying modules, which are non-smelly modules that are about to become smelly. We present empirical studies on open source projects with the aim of studying the characteristics of decaying modules. Additionally, to facilitate developers in the refactoring planning process, we perform a study on using a machine learning technique to predict decaying modules and report a factor that contributes most to the performance of the model under consideration.

Effective emergency resource allocation is essential to guarantee a successful emergency disposal, and it has become a research focus in the area of emergency management. Emergency event logs are accumulated in modern emergency management systems and can be analyzed to support effective resource allocation. This paper proposes a novel approach for efficient emergency resource allocation by mining emergency event logs. More specifically, an emergency event log with various attributes, e.g., emergency task name, emergency resource type (reusable and consumable ones), required resource amount, and timestamps, is first formalized. Then, a novel algorithm is presented to discover emergency response process models, represented as an extension of Petri net with resource and time elements, from emergency event logs. Next, based on the discovered emergency response process models, the minimum resource requirements for both reusable and consumable resources are obtained, and two resource allocation strategies, i.e., the Shortest Execution Time (SET) strategy and the Least Resource Consumption (LRC) strategy, are proposed to support efficient emergency resource allocation decision-making. Finally, a chlorine tank explosion emergency case study is used to demonstrate the applicability and effectiveness of the proposed resource allocation approach.

Contamination of water resources with pathogenic microorganisms excreted in human feces is a worldwide public health concern. Surveillance of fecal contamination is commonly performed by routine monitoring for a single type or a few types of microorganism(s). To design a feasible routine for periodic monitoring and to control risks of exposure to pathogens, reliable statistical algorithms for inferring correlations between concentrations of microorganisms in water need to be established. Moreover, because pathogens are often present in low concentrations, some contaminations are likely to be under a detection limit. This yields a pairwise left-censored dataset and complicates computation of correlation coefficients. Errors of correlation estimation can be smaller if undetected values are imputed better. To obtain better imputations, we utilize side information and develop a new technique, the asymmetric Tobit model which is an extension of the Tobit model so that domain knowledge can be exploited effectively when fitting the model to a censored dataset. The empirical results demonstrate that imputation with domain knowledge is effective for this task.

Home Energy Management Systems (HEMS) contain devices of multiple manufacturers. Also, a large number of groups of devices must be managed according to several clustering situations. Hence, since it is necessary to establish a common secret group key among group members, the group key management scheme of IEEE 802.21 is used. However, no security verification result by formal methods is known. In this paper, we give the first formal verification result of secrecy and authenticity of the group key management scheme of IEEE 802.21 against insider and outsider attacks using ProVerif, which is an automatic verification tool for cryptographic protocols. As a result, we clarify that a spoofing attack by an insider and a replay attack by an outsider are found for the basic scheme, but these attacks can be prevented by using the scheme with the digital signature option.

In general, since the in-band noise of phase-locked loops (PLLs) is mainly caused by charge pumps (CPs), large-size transistors that occupy a large area are used to improve in-band noise of CPs. With the high demand for low phase noise in recent high-performance communication systems, the issue of the trade-off between occupied area and noise in conventional CPs has become significant. A noise-canceling CP circuit is presented in this paper to mitigate the trade-off between occupied area and noise. The proposed CP can achieve lower noise performance than conventional CPs by performing additional noise cancelation. According to the simulation results, the proposed CP can reduce the current noise to 57% with the same occupied area, or can reduce the occupied area to 22% compared with that of the conventional CPs at the same noise performance. We fabricated a prototype of the proposed CP embedded in a 28-GHz LC-PLL using a 16-nm FinFET process, and 1.2-dB improvement in single sideband integrated phase noise is achieved.

Standard neural machine translation (NMT) is on the assumption that the document-level context is independent. Most existing document-level NMT approaches are satisfied with a smattering sense of global document-level information, while this work focuses on exploiting detailed document-level context in terms of a memory network. The capacity of the memory network that detecting the most relevant part of the current sentence from memory renders a natural solution to model the rich document-level context. In this work, the proposed document-aware memory network is implemented to enhance the Transformer NMT baseline. Experiments on several tasks show that the proposed method significantly improves the NMT performance over strong Transformer baselines and other related studies.

Applications of continuous-time (CT) comparator include relaxation oscillators, pulse width modulators, and so on. CT comparator receives a differential input and outputs a strobe ideally when the differential input crosses zero. Unlike the DT comparators with positive feedback circuit, amplifiers consuming static power must be employed in CT comparators to amplify the input signal. Therefore, minimization of comparator delay under the constraint of power consumption often becomes an issue. This paper analyzes transient behavior of a CT comparator. Using “constant delay approximation”, the comparator delay is derived as a function of input slew rate, number of stages of the preamplifier, and device parameters in each block. This paper also discusses optimum design of the CT comparator. The condition for minimum comparator delay is derived with keeping power consumption constant. The results include that the optimum DC gain of the preamplifier is e∼e3 per stage depending on the element which dominates load capacitance of the preamplifier.

Observations of gravity waves based on High Frequency Surface Wave Radar can make contributions to a better understanding of the energy transfer process between the ocean and the ionosphere. In this paper, through processing the observed data of the ionospheric clutter from HFSWR during the period of the Typhoon Rumbia with short-time Fourier transform method, HFSWR was proven to have the capability of gravity wave detection.

We consider an asymptotic stabilization problem for a chain of integrators by using an event-triggered controller. The times required between event-triggered executions and controller updates are uncertain, time-varying, and not necessarily small. We show that the considered system can be asymptotically stabilized by an event-triggered gain-scaling controller. Also, we show that the interexecution times are lower bounded and their lower bounds can be manipulated by a gain-scaling factor. Some future extensions are also discussed. An example is given for illustration.