To reduce the server load and communication costs of machine-to-machine (M2M) systems, sensor data are aggregated in M2M gateways. Aggregation logic is typically programmed in the C language and embedded into the firmware. However, developing aggregation programs is difficult for M2M service providers because it requires gateway-specific knowledge and consideration of resource issues, especially RAM usage. In addition, modification of aggregation logic requires the application of firmware updates, which are risky. We propose a rule-based sensor data aggregation system, called the complex sensor data aggregator (CSDA), for M2M gateways. The functions comprising the data aggregation process are subdivided into the categories of filtering, statistical calculation, and concatenation. The proposed CSDA supports this aggregation process in three steps: the input, periodic data processing, and output steps. The behaviors of these steps are configured by an XML-based rule. The rule is stored in the data area of flash ROM and is updatable through the Internet without the need for a firmware update. In addition, in order to keep within the memory limit specified by the M2M gateway's manufacturer, the number of threads and the size of the working memory are static after startup, and the size of the working memory can be adjusted by configuring the sampling setting of a buffer for sensor data input. The proposed system is evaluated in an M2M gateway experimental environment. Results show that developing CSDA configurations is much easier than using C because the configuration decreases by 10%. In addition, the performance evaluation demonstrates the proposed system's ability to operate on M2M gateways.

In multi-FPGA prototyping systems for circuit verification, serialized time-multiplexed I/O technique is used because of the limited number of I/O pins of an FPGA. The verification time depends on a selection of inter-FPGA signals to be time-multiplexed. In this paper, we propose a method that minimizes the verification time of multi-FPGA systems by finding an optimal selection of inter-FPGA signals to be time-multiplexed. In the experiments, it is shown that the estimated verification time is improved 38.2% on average compared with conventional methods.

Nonvolatile flip-flop enables leakage power reduction in logic circuits and quick return from standby mode. However, it has limited write endurance, and its power consumption for writing is larger than that of conventional D flip-flop (DFF). For this reason, it is important to reduce the number of write operations. The write operations can be reduced by stopping the clock signal to synchronous flip-flops because write operations are executed only when the clock is applied to the flip-flops. In such clock gating, a method using Exclusive OR (XOR) of the current value and the new value as the control signal is well known. The XOR based method is effective, but there are several cases where the write operations can be reduced even if the current value and the new value are different. The paper proposes a method to detect such unnecessary write operations based on state transition analysis, and proposes a write control method to save power consumption of nonvolatile flip-flops. In the method, redundant bits are detected to reduce the number of write operations. If the next state and the outputs do not depend on some current bit, the bit is redundant and not necessary to write. The method is based on Binary Decision Diagram (BDD) calculation. We construct write control circuits to stop the clock signal by converting BDDs representing a set of states where write operations are unnecessary. Proposed method can be combined with the XOR based method and reduce the total write operations. We apply combined method to some benchmark circuits and estimate the power consumption with Synopsys NanoSim. On average, 15.0% power consumption can be reduced compared with only the XOR based method.

Self-paced e-learning provides much more freedom in time and locale than traditional education as well as diversity of learning contents and learning media and tools. However, its limitations must not be ignored. Lack of information on learners' states is a serious issue that can lead to severe problems, such as low learning efficiency, motivation loss, and even dropping out of e-learning. We have designed a novel e-learning support system that can visually observe learners' non-verbal behaviors and estimate their learning states and that can be easily integrated into practical e-learning environments. Three pairs of internal states closely related to learning performance, concentration-distraction, difficulty-ease, and interest-boredom, were selected as targets of recognition. In addition, we investigated the practical problem of estimating the learning states of a new learner whose characteristics are not known in advance. Experimental results show the potential of our system.

This paper presents a verification and analysis tool set for embedded systems. Recently, the development scale of embedded systems has been increasing since they are used for mobile systems, automobile platforms, and various consumer systems with rich functionality. This has increased the amount of time and cost needed to develop them. Consequently, it is very important to develop tools to reduce development time and cost. This paper describes a tool set consisting of three tools to enhance the efficiency of embedded system design. The first tool is an integrated tool platform. The second is a remote debugging system. The third is a clock-accurate verification system based on a field-programmable gate array (FPGA) for custom embedded systems. This tool set promises to significantly reduce the time and cost needed to develop embedded systems.

This paper presents an approach to analyze and model tasks of machines being operated. The executions of the tasks were captured through egocentric vision. Each task was decomposed into a sequence of physical hand-machine interactions, which are described with touch-based hotspots and interaction patterns. Modeling the tasks was achieved by integrating the experiences of multiple experts and using a hidden Markov model (HMM). Here, we present the results of more than 70 recorded egocentric experiences of the operation of a sewing machine. Our methods show good potential for the detection of hand-machine interactions and modeling of machine operation tasks.

This study proposes a mathematical model of a gesture-based pointing interface system for simulating pointing behaviors in various situations. We assume an interaction between a pointing interface and a user as a human-in-the-loop system and describe it using feedback control theory. The model is formulated as a hybrid of a target value follow-up component and a disturbance compensation one. These are induced from the same feedback loop but with different parameter sets to describe human pointing characteristics well. The two optimal parameter sets were determined individually to represent actual pointing behaviors accurately for step input signals and random walk disturbance sequences, respectively. The calibrated model is used to simulate pointing behaviors for arbitrary input signals expected in practical situations. Through experimental evaluations, we quantitatively analyzed the performance of the proposed hybrid model regarding how accurately it can simulate actual pointing behaviors and also discuss the advantage regarding the basic non-hybrid model. Model refinements for further accuracy are also suggested based on the evaluation results.

In deep-submicron technologies, process variations can significantly affect the performance and yield of VLSI chips. As a countermeasure to the variations, post-silicon tuning has been proposed. Deskew, where the clock timing of flip-flops (FFs) is tuned by inserted programmable delay elements (PDEs) into the clock tree, is classified into this method. We propose a novel deskew method that decides the delay values of the elements by measuring a small amount of FFs' clock timing and presuming the rest of FFs' clock timings based on a statistical model. In addition, our proposed method can determine the discrete PDE delay value because the rewriting constraint satisfies the condition of total unimodularity.

This paper describes a new method for the simulation environment for a custom processor. It is generally very hard to develop an accurate simulator for a custom processor rapidly, even if simple instruction-set-level simulator (ISS). The proposed method uses a field-programmable-gate-array emulator with a PCI interface and debugging GUI software on a PC. Since the emulator implements the processor design at the register-transfer or net-list level, the emulation results are almost the same as the results obtained with the actual processor. To support rich debugging functions like those provided by the conventional software simulator, we use a debugging buffer and break-control circuits. Experimental results show that a simulator constructed by the proposed method can be constructed within several hours and that it can break the processor operation at any specified point and observe the internal signals when the emulated system is running at 1-30 MHz. The accuracy of the constructed simulator is the same as that of RTL simulation and much higher than that of software ISS simulation. We show that we can provide a fast, accurate, and useful simulator for any processor design specified at the register-transfer level.

Two problems occur when an authorization server is utilized for a use case where a different security profile needs to be applied to a unique client request for accessing a distinct type of an API, such as open banking. A security profile can be applied to a client request by using the settings of an authorization server and client. However, this method can only apply the same security profile to all client requests. Therefore, multiple authorization servers or isolated environments, such as realms of an authorization server, are needed to apply a different security profile. However, this increases managerial costs for the authorization server administration. Moreover, new settings and logic need to be added to an authorization server if the existing client settings are inadequate for applying a security profile, which requires modification of an authorization server's source code. We aims to propose the policy-based method that resolves these problems. The proposed method does not completely rely on the settings of a client and can determine an applied security profile using a policy and the context of the client's request. Therefore, only one authorization server or isolated environment, such as a realm of an authorization server, is required to support multiple different security profiles. Additionally, the proposed method can implement a security profile as a pluggable software module. Thus, the source code of the authorization server need not be modified. The proposed method and Financial-grade application programming interface (FAPI) security profiles were implemented in Keycloak, which is an open-source identity and access management solution, and evaluation scenarios were executed. The results of the evaluation confirmed that the proposed method resolves these problems. The implementation has been contributed to Keycloak, making the proposed method and FAPI security profiles publicly available.

This article introduces our investigation on learning state estimation in e-learning on the condition that visual observation and recording of a learner's behaviors is possible. In this research, we examined methods of adaptation for a new learner for whom a small number of ground truth data can be obtained.

In this paper, we propose a novel migration method. In this method, the resultant placement retains the structure of the original placement, called model placement, as much as possible. For this purpose, we minimize the sum of the difference in area between the model placement and the relocated one and the total amount of displacement between them. Moreover, to achieve a short runtime, we limit the solution space and change the packing origin in the optimization process. We construct the system on Sequence-Pair. Experimental results show that our approach preserves the chip area and the overall circuit structure with 98% less runtime than that realized by naive simulated annealing.

This paper introduces a novel skin-stretcher device for gently urging head rotation. The device pulls and/or pushes the skin on the user's neck by using servo motors. The user is induced to rotate his/her head based on the sensation caused by the local stretching of skin. This mechanism informs the user when and how much the head rotation is requested; however it does not force head rotation, i.e., it allows the user to ignore the stimuli and to maintain voluntary movements. We implemented a prototype device and analyzed the performance of the skin stretcher as a human-in-the-loop system. Experimental results define its fundamental characteristics, such as input-output gain, settling time, and other dynamic behaviors. Features are analyzed, for example, input-output gain is stable within the same installation condition, but various between users.

Similarity search is an important and fundamental problem, and thus widely used in various fields of computer science including multimedia, computer vision, database, information retrieval, etc. Recently, since loitering behavior often leads to abnormal situations, such as pickpocketing and terrorist attacks, its analysis attracts increasing attention from research communities. In this paper, we present AntiLoiter, a loitering discovery system adopting efficient similarity search on surveillance videos. As we know, most of existing systems for loitering analysis, mainly focus on how to detect or identify loiterers by behavior tracking techniques. However, the difficulties of tracking-based methods are known as that their analysis results are heavily influenced by occlusions, overlaps, and shadows. Moreover, tracking-based methods need to track the human appearance continuously. Therefore, existing methods are not readily applied to real-world surveillance cameras due to the appearance discontinuity of criminal loiterers. To solve this problem, we abandon the tracking method, instead, propose AntiLoiter to efficiently discover loiterers based on their frequent appearance patterns in longtime multiple surveillance videos. In AntiLoiter, we propose a novel data structure Luigi that indexes data using only similarity value returned by a corresponding function (e.g., face matching). Luigi is adopted to perform efficient similarity search to realize loitering discovery. We conducted extensive experiments on both synthetic and real surveillance videos to evaluate the efficiency and efficacy of our approach. The experimental results show that our system can find out loitering candidates correctly and outperforms existing method by 100 times in terms of runtime.

FPGA-based hardware emulators are often used for the verification of LSI functions. They generally have dedicated external memories, such as SDRAMs, to compensate for the lack of memory capacity in FPGAs. In such a case, access between the FPGAs and the dedicated external memory may represent a major bottleneck with respect to emulation speed since the dedicated external memory may have to emulate a large number of memory blocks. In this paper, we propose three methods, "Dynamic Clock Control (DCC)," "Memory Mapping Optimization (MMO)," and "Efficient Access Scheduling (EAS)," to avoid this bottleneck. DCC controls an emulation clock dynamically in accord with the number of memory accesses within one emulation clock cycle. EAS optimizes the ordering of memory access to the dedicated external memory, and MMO optimizes the arrangement of the dedicated external memory addresses to which respective memories will be emulated. With them, emulation speed can be made 29.0 times faster, as evaluated in actual LSI emulations.

Changing attitudes toward energy security and energy conservation have led to the introduction of distributed power systems such as photovoltaic, gas-cogeneration, biomass, water, and wind power generators. The mass installation of distributed energy generators often causes instability in the voltage and frequency of the power grid. Moreover, the power quality of distributed power grids can become degraded when system faults or the activation of highly loaded machines cause rapid changes in power load. To avoid such problems and maintain an acceptable power quality, it is important to detect the source of these rapid changes. To address these issues, next-generation power grids that can detect the fault location have been proposed. Fault location demands accurate time synchronization. Conventional techniques use the Global Positioning System (GPS) and/or IEEE 1588v2 for time synchronization. However, both methods have drawbacks — GPS cannot be used in indoor situations, and the installation cost of IEEE 1588v2 devices is high. In this paper, a time synchronization technique using the broadcast function of an Ethernet Passive Optical Network (EPON) system is proposed. Experiments show that the proposed technique is low-cost and useful for smart grid applications that use time synchronization in EPON-based next-generation power grids.

In this study, an anonymization infrastructure for the secondary use of data is proposed. The proposed infrastructure can publish data that includes privacy information while preserving the privacy by using anonymization techniques. The infrastructure considers a situation where ill-motivated users redistribute the data without authorization. Therefore, we propose a watermarking method for anonymized data to solve this problem. The proposed method is implemented, and the proposed method's tolerance against attacks is evaluated.

Multi-FPGA systems, which consist of multiple FPGAs and a printed circuit board connecting them, are useful and important tools for prototyping large scale circuits, including SoCs. In this paper, we propose a method for optimizing inter-FPGA signal transmission to accelerate the system frequency of multi-FPGA prototyping systems and shorten prototyping time. Compared with the number of I/O pins of an FPGA, the number of I/O signals between FPGAs usually becomes very large. Thus, time-multiplexed I/Os are used to resolve the problem. On the other hand, they introduce large delays to inter-FPGA I/O signals, and much lower the system frequency. To reduce the degradation of the system frequency, we have proposed a method for optimally selecting signals to be time-multiplexed and signals not to be time-multiplexed. However, this method assumes that there exist physical connections (i.e., wires on the printed circuit board) between every pair of FPGAs, and cannot handle I/O signals between a pair of FPGAs that have no physical connections between them. Thus, in this paper, we propose a method for obtaining indirect inter-FPGA routes for such I/O signals, and then combine the indirect routing method and the time-multiplexed signal selection method to realize effective time-multiplexing of inter-FPGA I/O signals on systems with various topologies.

This paper presents a novel power estimation method for large and complex LSIs. The proposed method is based on simulation and is used for analyzing the ways in chip-scale gate-level circuits including processors and memory are affected by gated-clock power reduction and the voltage drop due to electrical resistance. The chip-scale power estimation based on simulation patterns generally takes enormous time. In order to reduce the time to obtain accurate estimation results based on simulation patterns, we introduce three approaches: "partitioning of target LSIs and simulation pattern," "memory modeling," and "processor modeling." After placing and routing, the target LSIs are partitioned into hierarchical blocks, memory, and processors. The power consumption of each hierarchical block is calculated by using the partitioned patterns generated from chip-scale simulation patterns. The power consumption of the processor and memory blocks is estimated by a method considering the static power consumption and the rate of LSI activity ratio. Experimental results for a commercial 0.18 µm-technology media processing chip show that the proposed method is 23 times faster than the conventional method without partitioning and that both the results are almost the same.

Pronunciation is a fundamental factor in speaking and listening. However, instructions for important articulation have not been sufficiently provided in conventional computer-assisted language learning (CALL) systems. One typical case is the articulation of rounded vowels. Although lip protrusion is essential for their correct pronunciation, the perception of lip protrusion is often difficult for beginners. To tackle this issue, we propose an innovative method that will provide a comprehensive visual explanation for articulation. Lip movements are three-dimensionally measured, and face images or videos are pseudocoloured on the basis of the movements. The coloured regions represent the lip protrusion of rounded vowels. To verify the learning effect of the proposed method, we conducted experiments with Japanese undergraduates in Chinese classes. The results showed that our method has advantages over conventional video materials.