This paper deals with an LC-ladder power divider operating at two frequency bands, and also shows the design equations for the power divider operating as unequal power divider. By bringing these two frequencies close to each other, the LC-ladder power dividers can achieve broadband characteristics equal to or better than those of conventional Wilkinson power divider based on the distributed circuit theory. We show unequal power dividers with several power split ratios of 2 to 4. The circuit parameters are determined by even/odd mode analysis techniques. Finally, we have confirmed the effectiveness of those power dividers by electromagnetic simulations and trial experiments.

A wireless communication system using spatial waveform modulation is proposed. The electromagnetic waves, which the transceivers of this system provide, transfer an information signal by using a spatially modulated electromagnetic waveform to achieve a better communication quality in an environment where electromagnetic scatters surround them. When the wireless system transfers an information signal on an electromagnetic wave at much higher frequency than that of this signal, the system modifies the propagating waveform consisting of plural electromagnetic waves to transfer the same signal because these waves become the wave varying its envelope at a different frequency from the propagation frequency. The modified waveform is able to increase an intensity of the information signal at the frequency which is much higher than that of the varying envelope. This system drastically improves either a data transfer range or a signal quality by using the rotating polarization of the transmitting waves with the same signal at different frequencies, in comparison with the conventional wireless system which uses the fixed polarization wave.

Because low-loss transmission lines are desired to construct higher-performance circuits, a DTM line which consists of metal rod inserted into a dielectric tube and sandwiched by parallel metal plates has been proposed as a new transmission line. In the THz bands, the dimensions are so small that undesired air gaps between the parallel metal plates and the dielectric tube may occur, causing structural irregularities. The effect was analyzed for the air gap by calculating the normalized phase constant compared with that of the NRD guide which featured a low loss dielectric waveguide.

In wireless systems, such as fifth-generation mobile communication (5G) and distributed antenna systems, wireless environments are assumed to be line of sight (LOS) environments. This study proposes a frequency selective Nakagami-Rice fading model by introducing the time difference between the direct wave and first delayed wave to a typical Rayleigh fading model with an exponential decay delay profile. Thus, the proposed model includes the conventional models. We derived the frequency correlation for the proposed model and demonstrated its effectiveness through a numerical evaluation of the impact of various parameters on the derived expression.

In this study, the optimization problem is solved considering the time and cost performance obtained by users of electric kickboards as evaluation criteria. Based on data from Shibuya-ku, Tokyo, where electric kickboard installations have already progressed, we make predictions regarding port candidate at Setagaya-ku using the optimization problem. The problem is solved by considering the demand and supply of electric kickboards as constraints to determine port candidate. The proposed problem is a bi-objective optimization problem, with two objective functions exhibiting a trade-off relationship. This study adopts a linear weighted sum minimization method, which is a type of scalarization. After optimizing time and cost performance in the first stage, the optimization problem is solved again in the second stage using the optimal solution obtained in the first stage. As a result, we verified the optimal placement method for electric kickboards that balances both cost and time performance.

While the spread of COVID-19 is coming to an end, Overtourism, which has been apparent in various tourist destinations since the 2010s, is once again becoming an important issue. In order to relieve congestion, some areas have introduced applications that allow visitors to check the congestion status of tourist attractions with their smartphones. On the other hand, not much research has been conducted on what kind of congestion information is effective for decentralizing the congestion at tourist attractions from the viewpoint of eliminating overtourism. In this study, we analyze how the waiting time and the degree of congestion at tourist spots change when agents are given several measures with different tourist information by reproducing tourist spots using Multi-Agent Simulation (MAS).

In recent years, there has been a steady year-on-year increase in the benefits that consumers derive from products and services via e-commerce platforms. Specifically, there are e-commerce companies that operate by assigning customer orders to affiliated stores within their platform. In this sales model, it is still common for operators to manually assign orders to affiliated stores. In this study, we developed a method that automatically and dynamically assigns orders based on store scale while considering the efficient distribution of orders to minimize delivery distances. The scale of the stores was quantified using Huff's model. Numerical experiments were conducted using real data from e-commerce companies. The results indicate that the proposed method showed better performance than that of the operators in terms of delivery distance. Furthermore, the proposed method outperformed previous research in terms of the balance of orders at each store. In conclusion, the proposed method offers a more practical approach compared to previous research.

Kobe Tokiwa University witnessed its 1st university reform in 2015. This resulted in the start of a basic education based first-year course from the year 2017. Kobe Tokiwa University constructed the course based on 19 Tokiwa competencies. In order to evaluate the students, who are evaluated by the 20 teachers based on Tokiwa competencies, we constructed a rubric and an evaluation matrix for the first-year course. Already we performed an explorative factor analysis of the evaluation of students by using an evaluation matrix for the 2018 first-year course. The results showed that our evaluation is not based on the Tokiwa competencies. In this research additionally, we performed confirmatory factor analysis, structural equation modeling, to understand the relationship among factors. Results show that we must address evaluation of portfolio.

To cultivate top-tier project managers, we have created a board game specifically designed for project management training. Hundreds of participants have already benefited from this game, receiving valuable feedback on their practical skills. However, the current evaluation method relies heavily on seasoned facilitators. For more consistent and long-term participant development, we aimed to standardize the skill assessment process.

Initially, we conducted a workshop with three veteran project managers and a psychology expert to identify the evaluation criteria and essential skill sets from a problem-solving perspective. We then used statistical methods to analyze rating inconsistencies attributed to the evaluator’s field of experience.

As a next step, we developed a machine learning model to predict ratings from evaluators. This model uses data from a digital version of our training board game. By examining the decision tree within the model, we were able to identify the specific variables causing variations in the evaluators’ ratings.

An increasing number of studies are using information systems in learning and teaching, and they are introducing the system in actual classes. Many such studies and case studies measure and analyze learners' exercise processes. However, there are few reports of such cases that analyze access to learning systems or evaluate missing data in the analysis. When we experienced performance problems with a learning system we developed and operated, the maximum number of requests per second to access a question page reached 33 requests per second, and some of the data in the user operation logs we were measuring was lost. In that case, the same user accessed the same problem every 0.2 seconds. Since we fixed those problems, no similar performance problems have occurred. We introduced retries to send user operations logs into the database. Subsequently, about 660,000 operation logs were generated during the two-and-a-half years to date, and retries occurred in 0.06% of them. In classes with many retries, missing data also occurred. On the other hand, in the most recent month, 62,000 operation logs were generated, but there were five retries, or 0.008% of them, and 0 missing data. These results will benefit the design and operation of learning and education systems.

This paper presents a 0.7V 12-bit 1.5MS/s SAR ADC incorporates an input amplitude attenuation architecture. To sample large amplitude input signals that exceed the supply voltage (V_in>V_DD), a modified bootstrapped switch architecture is proposed, which enhances the dynamic performance of the analog signal sampling switch. The proposed bootstrapped switch is utilized to construct a novel sample-and-hold (S/H) circuit that serves as the front-end for ADCs operating at low supply voltages while tolerating large amplitude input signals. The SAR ADC, which includes this novel S/H circuit, is in 65nm SOTB CMOS technology. It achieves a simulated SNDR of 65.71dB, a SFDR of 81.33dB and an ENOB of 10.62 bits with a full-scale input amplitude of V_{in_pp}=2.8V (peak-to-peak voltage) at 0.7V supply voltage V_DD.

The notion of Photon Transport Transistor (PTT) similar to Bipolar Junction Transistor (BJT) was announced by IBM in 1989. The PTT is an optical coupling circuit that consists of Light Emitting Diode (LED) and light receiving diode (Photo Diode, PD), where the carrier of the base layer corresponding to that of BJT is light (Photon) only. Later, in 2014, it was reported that the PTT in a positive feedback circuit shows not only an amplification function but also a switching function like thyristor. In this paper, first, we present the thyristor-like operational behavior of PTT in the emitter common circuit by experimentation. Second, based on the experimental results and each VI characteristics of LED and PD, we show the expression of the thyristor-like switching function of PTT and analyze the reason why the PTT has a thyristor-like VI characteristics, from the viewpoint of electronic circuit. Moreover, we discuss the merits of the PTT application, considering the difference between thyristor-like PTT circuit and ordinary thyristor.

A method of a student experiment for high frequency circuits is developed. This training method is based on a quasi-experiment system and movies for educational materials. The quasi-experiment system provides electromagnetic simulation with three-dimensional models of chip inductors and capacitors. It reduces time for making prototypes and measuring them. Visualized electromagnetic fields can be used to design the high frequency circuits using chip components in the system. A part of the circuits is easily evaluated by the system. The student experiment includes fundamental circuits and an applied circuit for a design contest. The method is suitable to obtain knowledge on practical high frequency circuit design within a limited amount of time.

This research focuses on the development of open-source spoofing signal generation software for GPS and QZSS, tailored to work on universal software-defined radio (SDR) platforms. While GPS-SDR-SIM facilitates GPS signal implementation on software radios, it does not support QZSS signals. Therefore, in this research, we extended GPS-SDR-SIM to add compatibility with QZSS. Utilizing the developed software, we implemented GPS and QZSS signals with a universal SDR, that is USRP, and successfully received them with commercially available receivers. The results demonstrate that the developed software can be generated the GPS and QZSS signals at arbitrary times and locations.

With the aim of realizing remote blood glucose level measurement, we constructed a model for estimating blood glucose level base on facial images measured in the near-infrared band, which is highly transparent to living tissue. However, the generalization performance of the estimation model was not evaluated in previous studies due to the small number of data. The objective of this study is to construct an individual model and a general model for blood glucose estimation based on facial images measured in the near-infrared broadband wavelength range of 760 nm to 1650 nm, and to evaluate their generalization performance. Independent Component Analysis(ICA) was applied to facial images during blood glucose variations to obtain spatial features of independent components and their weights. Using the standardized weights as explanatory variables and reference blood glucose levels as objective variables, an individual model and a general model for blood glucose estimation were constructed through multiple regression analysis. Cross-validation was applied to evaluate the generalization performance of the models. The results showed that the accuracies of blood glucose estimation in the 760nm to 1100 nm and 1050nm to 1650 nm wavelength bands were 32.23 mg/dL and 36.10 mg/dL in RMSE for the individual model, and 43.02 mg/dL and 43.61 mg/dL for the general model, respectively. The independent components selected for the models were found to have spatial characteristics associated with variations in glucose concentrations in the orbital region and in the vessels on both sides of the nose.

To realize mobile robot, the path following control method was proposed. Although this method is simple, the desired lane keeping can be realized. In this method, a controller gain must be tuned so that the tracking error is small. However, the feedback gain must be tuned by specific experiments nor iterations. In control theory field, a new auto-tuning method which is called as Virtual internal model tuning (VIMT) was proposed. VIMT can tune the controller by using one-shot experiment data. If this method can be applied to the vehicle, the feedback gain can be tuned. However, VIMT cannot be applied directly because the path following control is nonlinear control method. This study expands VIMT so as to tune the path following control. The proposed method can use VIMT by linearizing the path following control method. The validity of the proposed method is verified via numerical simulation.

This paper addresses drone controller design with 3D target trajectory and presents a backstepping-based controller taking into consideration the integral of tracking error. Performance evaluation is performed in situational and experimental environments, and the advantage of the proposed scheme is illustrated in the comparison with the conventional backstepping and the Proportional-Integral-Differential control. The experiment results show that the proposed scheme exploiting the integral of tracking error can reduce steady-state error. Furthermore, they show that introducing a reference model experimentally improves the tracking performance for a given target trajectory.

Citrus Greening disease (CG) is the most destructive disease of citrus, leading to branch dieback and plant death. Currently, there is no cure for CG, the early detection and removal of infected trees is important to prevent the spread of the disease. In recent years, there have been growing expectations for CG detection with digital images, especially deep learning techniques applied to digitized herbarium specimen image data. However, this approach faces challenges in practical applicability and detection efficiency. In this paper, we proposed a simple diagnostic method for CG using transfer learning with the Faster RCNN architecture. We collected in-field images from a citrus orchard in Thailand where CG has caused significant damage. We compared the performance of two annotation methods with the in-field leaf dataset and discussed their effects on pre-trained VGG and Resnet models. 5-fold cross-validation was utilized for model training and evaluation, with Average Precision (AP) used as the performance metric. The results showed that the Resnet models performed better than the VGG models, with the Resnet152 model scoring the highest in this task. The annotation method which including annotations of healthy and other diseases leaves achieved an AP of 84.13% lower than another one but indicated better performance in practical applications with more robustness. Additionally, we developed a web application that performs real-time diagnosis using our trained models and verified the effectiveness of our system.

In the urban railways of the metropolitan area, train delays during morning rush hours have become a significant issue. This problem isn't merely caused by large, sudden delays, but also by an accumulation of minor delays, which can escalate into substantial setbacks. This presents a disadvantage not only for the operators managing the train services but also for the users. Recent years have seen active reporting of studies predicting delay times. However, these studies do not take into account the accumulative nature of delays because the data input to the learning machine is only for stations behind the target station. Therefore, this paper aims to predict the delay time that occurs when each train departs from a station. To do so, we constructed a network that takes into account the propagation of delays by using data from stations in front of the target station as input. We will provide an overview of the network we constructed and report on its predictive accuracy.

Chasm or crack in the diffusion process of a new product is a long-term decline in sales. If the occurrence of chasm or crack is predicted and the chasm factor is understood by analyzing consumers’ evaluation information on the product, the product can penetrate the market more effectively. In this study, we developed an agent-based diffusion model that incorporates the concepts of cluster connectivity, which represents word-of-mouth effect, product recognition range, which represents promotion effect, and purchase probability of individual consumers, which are not considered in conventional models, to reproduce the diffusion process of new products. Furthermore, the amount of sales decline that can occur in the diffusion process of a new product is calculated by using the Chasm at Risk (CaR), and detect chasm or crack in the product. For validation, we reproduced the diffusion process of a new product and the occurrence of chasm or crack using data from an O2O site, which gathers users who go back and forth between online on Web and offline in real stores. In addition, we also examined the method of chasm suppression when the effects of consumer word-of-mouth and company promotion were varied.

In public wireless LAN services such as free WiFi, the dangers of eavesdropping and tampering with communications have been pointed out. Evil Twin attack which is one of the problems utilizes a fake access point (AP) which has the same configuration as a genuine AP. This study develops a platform for evaluating Evil Twin attacks and investigates information leakage scenarios and thier countermeasures. The information leakage scenarios in the evaluation experiment are the theft of IDs and passwords when logging in via Web authentication and the list attack that attempts to log in to other services using the stolen ID and password pairs.

In this letter, the summary of design method for a kind of tunable matching circuit composed of tunable capacitors, short stubs and a uniform transmission line is described. The best feature of the proposal circuit is that two target matching frequencies can be varied at the same time within operating frequency range.

Visualizing imperceptible wireless communications has the potential to spark interest among individuals in the field of wireless communications. In this letter, we propose a system that visualizes BLE advertising packets using an LED panel. Our proposed system consists of a Raspberry Pi and an LED panel, and the panel blinks in color depending on the type of BLE advertising packet sent from the nearest device. As a result of using our proposed system at an open campus, we found that our system can be used to raise awareness to get people interested in wireless communications.