隠蔽された供述意図 : 「暴行被害者」が真実を語って偽証罪に問われたと思われる事案

The purpose of this study was to investigate value of combining Real Experimentation (RE) with Virtual Experimentation (VE) with respect to changes in students' conceptual understanding of electric circuits. To achieve this, a pre–post comparison study design was used that involved 88 undergraduate students. The participants were randomly assigned to an experimental (45 students) and a control group (43 students). Each group attended a one semester course in physics for preservice elementary school teachers. Both groups used the same inquiry‐based curriculum materials. Participants in the control group used RE to conduct the study's experiments, whereas, participants in the experimental group used RE in the first part of the curriculum and VE in another part. Conceptual tests were administered to assess students' understanding of electric circuits before, during and after the teaching intervention. Results indicated that the combination of RE and VE enhanced students' conceptual understanding more than the use of RE alone. A further analysis showed that differences between groups on that part of the curriculum in which the experimental group used VE and the control group RE, in favour of VE.

Innovative technologies such as autonomous and connected vehicles can create a better transit mall, a street where only public transit vehicles, bicycles, and pedestrians are allowed. However, successful introduction of such technologies depends on user acceptance. To assess the potential acceptance of these technologies in the context of a new transit mall environment, it is crucial to provide an opportunity to experience them before they roll out. This study explores how real and video-based experiences of new technologies can affect public acceptance of new transit mall options in Hiroshima City, Japan, where trams and buses are significant modes of public transportation. We conducted a survey on the stated acceptance of new transit mall options with three groups of respondents: real experience, video-based experience, and no experience groups. The real-experience group self-selected themselves for the experiment, which potentially caused bias. Thus, we used a hybrid choice model with attitudinal variables (ethical, legal, and social concerns regarding emerging technologies, as well as risk-related factors) introduced to control for this bias. We found that both real and video-based experiences improved overall acceptance of new transit mall options, but there were differences in preferences between those who had only video-based experiences and those who had real experiences. We also found that prior knowledge of new transport services and infrastructure had a considerable influence on stated acceptance.

There seems to be two shortcomings in the recently published papers on the so called “integrated models” of intra-urban retailing structures in Japan. Firstly, the division and typology of retailing areas, which is largely inspired by the hierarchical division of central places, hardly gives any proper image which fits for our real experience. Secondly, since the division of distribution types of retailings is not enough logical, the interpretation on the factors of retailing types scarcely gives so well-founded understanding. Owing to these, areal characteristics of retailings which should be premise for the objective interpretation of factors are not so clear, and explanation on the urban retailing areas, which should be based on one's real experience, is inclined to mechanistic. In this paper, the authors reconsider these problems, and propose an improved method and attempt to make more realistic interpretation on intra-urban retailing stracture, using the data collected from the urbanized area of Hamamatsu City (Fig. 2) in the central Japan.The process of analysis is as follows. (1) 200m×200m quadratatic meshes are created over the urbanized area and the number of outlets of each cell by each retailing types is counted. (2) These numbers are adjusted by the shifting average method (Fig. 1), and 302 cells with ten and over outlets are taken for the following analysis. (3) The cells are aggregated into five equidistance concentric zones, and the specialization indices for each zone and for each retailing are worked out. (4) The logically exlusive category of the distribution pattern of intra-urban retailings are established (shown below):(5) Using these categories and the specialized patterns, the distribution types of each retailing are judged.The geographical matrix of the outlet numbers with 302 quadrats×41 retailings obtained from (2) are subjected for the factor analysis, and four factors with clear meanings—urban center oriented, peripheral oriented, urban arterial oriented, and unusually specialized retailings—are extracted. Then, using the factor scores of these four factors, the cluster analysis is carried out. Through the interpretation based on the real practical experience, each clusters can be explained as following seven retaling areas (Fig. 4): urban center oriented type (K, L), specialized type on high-class restaurants and lodging facilities adjacent to CBD and terminal (M), neighborhood type in densely inhabitated old inner town (N), old arterial type on the outskirts of inner area (O), new suburban arterial type (P), suburban arterial type specialized in the automobile shops and big shopping centers (Q), suburban neighborhood type (R).

Language is both a means of constructing collective identity and an expression of collective identity in itself. The implications for postcolonial societies are considerable: as long as a colonial language is privileged over its indigenous counterparts in the public sphere, a country remains under the de facto control of the former coloniser. This article engages with the struggle to decolonise language in postcolonial Guinea under Sékou Touré, from 1958 to 1984. Guinea is a particularly attractive case study for several reasons: first, language was central to the nascent national culture; thus, engagement with the question of language played out consciously and publicly. Second, both the Touré government and grassroots movements were actively involved in this process, often with conflicting goals and mechanisms. Third, national language policy confronted a popular, indigenous, and truly postcolonial alternative in the form of N'ko. Finally, Guinea's struggle yielded mixed results, many of which can be traced to particular policies. Using Touré's Guinea as a cautionary tale, this article considers: What is the role of language in the development of postcolonial identity? Can either a colonial or indigenous language effectively give voice to a nation's experience of reality, or do the peculiarities of a postcolonial society necessitate the creation of something new? Ultimately, overcoming the imperialism of language requires a radically egalitarian and multilingual approach, in which language is understood to reflect the discursive experience of postcolonial reality.

It is generally said that dreams are experienced as real. But the notion of reality is often used, in the philosophical literature, along with that of presence. A big problem, in this respect, is that both these terms may assume different meanings. So understanding the nature of presence and reality in dreams depends on the way we conceive these two notions. This paper contributes to the literature on dreaming by describing the experience of presence and reality in dreams in a very specific sense. I consider the experience of presence as related to the experience of possibility of motoric interaction, and the experience of reality as related to the experience of mind-independence. Then, endorsing that dream experiences are different from perception, and similar to imagery, I suggest that the dreamer can experience reality but not presence, with three lines of argument, concerning visual determinacy, stereopsis and peripersonal localization.

Hemi-ablation of prostate cancer (PCa) requires an accurate prediction of laterality. Recently, multi-parametric magnetic resonance imaging (mpMRI) has recently been increasingly used to enhance clinical staging and characterization of tumor foci. Thus, we tried to investigate the real-life accuracy of combinatory approach of using both transrectal ultrasound (TRUS)-guided prostatic biopsy and mpMRI in predicting the laterality of PCa. We reviewed the records of 335 men who were suspected of having unilateral PCa on multi (≥ 12)-core TRUS-guided biopsy and preoperative mpMRI and subsequently had undergone radical prostatectomy (RP) at our institution. Based on the analysis of pathologic outcomes from RP, the performance of the combinatory approach in predicting the pathological laterality of PCa was evaluated. Pathology was classified to be unfavorable when showing a Gleason pattern of 4/5 or pT3/N1 features. Significant cancer was defined as non-organ-confined disease, having a Gleason pattern of 4/5, or showing a cancer volume of ≥ 0.5 mL. Among the 335 unilateral lobes not suspected to harbor tumor from either the TRUS biopsy or mpMRI, the actual absence rate of malignancy was only 13.7% from a pathologic analysis of RP specimens. Even among the 115 D’Amico low-risk group, the absence rate of malignancy was only 26.1% in unilateral lobes not suspected to harbor tumor. Among the 335 lobes, unfavorable pathology and significant cancer were not observed in 36.1% and 30.7%, respectively. The absence rates of unfavorable pathology and significant cancer among the D’Amico low risk group were 56.5% and 47.8%, respectively. Meanwhile, the absence rate of dominant Gleason pattern 4 or 5 was 74.9% among the 335 total subjects. Our real-life clinical experience showed that the combination of multi-core TRUS-guided biopsy and mpMRI did not provide reliable accuracy in the prediction of true unilaterality of PCa.

In wireless networking R&D we typically depend on experimentation to further evaluate a solution, as simulation is inherently a simplification of the real-world. However, experimentation is limited in aspects where simulation excels, such as repeatability and reproducibility. Real wireless experiments are hardly repeatable. Given the same input they can produce very different output results, since wireless communications are influenced by external random phenomena such as noise, interference, and multipath. Real experiments are also difficult to reproduce due to testbed operational constraints and availability.We have previously proposed the Trace-based Simulation (TS) approach, which uses the TraceBasedPropagationLossModel to successfully reproduce past experiments. Yet, in its current version, the TraceBasedPropagationLossModel only supports point-to-point scenarios. In this paper, we introduce a new version of the model that supports Multiple Access wireless scenarios. To validate the new version of the model, the network throughput was measured in a laboratory testbed. The experimental results were then compared to the network throughput achieved using the ns-3 trace-based simulation and a pure ns-3 simulation, confirming the TS approach is valid for multiple access scenarios too.

This study investigates how middle school students coordinate multiple representations while learning about reflection and refraction of light in a hybrid laboratory environment that combines real and virtual settings. Conducted as a qualitative case study, the research involved a group of 48 students enrolled in a public school. The dataset comprised video and screen recordings from real and virtual experiment sessions, student worksheets, drawings, semi-structured interviews, and findings from a concept test administered prior to the implementation. The data were coded with respect to representation use, patterns of transitions and correspondences among representations, and levels of abstraction (concrete–intermediate–general). After establishing inter-coder reliability, the data were analyzed through descriptive and content analysis methods. The findings indicate that students transitioned between real experiments, simulations, schematic drawings, and mathematical expressions using specific strategies, such as verification, re-representation, and elaboration of explanations. However, these representations were not always fully integrated. Levels of abstraction were found to be predominantly concrete during the exploration phase, while shifting toward more general principles during the modeling and discussion phases. The results from this two-session implementation suggest that hybrid laboratories may not fully realize their pedagogical potential for supporting multiple representations unless representational transitions are intentionally structured and guided by the teacher.

Dripping water from a faucet is a typical example exhibiting rich nonlinear phenomena. For such a system, the time stamps at which water drops separate from the faucet can be directly observed in real experiments, and the time series of intervals τn between drop separations becomes a subject of analysis. Even if the mass mn of a drop at the onset of the nth separation, which is difficult to observe experimentally, exhibits perfectly deterministic dynamics, it may be difficult to obtain the same information about the underlying dynamics from the time series τn. This is because the return plot τn-1 vs. τn may become a multivalued relation (i.e., it doesn't represent a function describing deterministic dynamics). In this paper, we propose a method to construct a nonlinear coordinate which provides a "surrogate" of the internal state mn from the time series of τn. Here, a key of the proposed approach is to use isomap, which is a well-known method of manifold learning. We first apply it to the time series of τn generated from the numerical simulation of a phenomenological mass-spring model for the dripping faucet system. It is shown that a clear one-dimensional map is obtained by the proposed approach, whose characteristic quantities such as the Lyapunov exponent, the topological entropy, and the time correlation function coincide with the original dripping faucet system. Furthermore, we also analyze data obtained from real dripping faucet experiments, which also provide promising results.

With the rapid development of unmanned aerial vehicles (UAVs), UAV-based intelligent airborne surveillance systems represented by real-time ground vehicle speed estimation have attracted wide attention from researchers. However, there are still many challenges in extracting speed information from UAV videos, including the dynamic moving background, small target size, complicated environment, and diverse scenes. In this paper, we propose a novel adaptive framework for multi-vehicle ground speed estimation in airborne videos. Firstly, we build a traffic dataset based on UAV. Then, we use the deep learning detection algorithm to detect the vehicle in the UAV field of view and obtain the trajectory in the image through the tracking-by-detection algorithm. Thereafter, we present a motion compensation method based on homography. This method obtains matching feature points by an optical flow method and eliminates the influence of the detected target to accurately calculate the homography matrix to determine the real motion trajectory in the current frame. Finally, vehicle speed is estimated based on the mapping relationship between the pixel distance and the actual distance. The method regards the actual size of the car as prior information and adaptively recovers the pixel scale by estimating the vehicle size in the image; it then calculates the vehicle speed. In order to evaluate the performance of the proposed system, we carry out a large number of experiments on the AirSim Simulation platform as well as real UAV aerial surveillance experiments. Through quantitative and qualitative analysis of the simulation results and real experiments, we verify that the proposed system has a unique ability to detect, track, and estimate the speed of ground vehicles simultaneously even with a single downward-looking camera. Additionally, the system can obtain effective and accurate speed estimation results, even in various complex scenes.

This paper describes a C/S model-based network laboratory which combines both real and virtual experiments, the real experiments are based on physical equipments, while the virtual ones on simulation models. There are three experimental modes: the synchronization experimental mode, the asynchronous experimental mode and the virtual simulation mode. Experiments for six courses including circuit theory, analog electronic technique, digital electronic technique, micro-electronics, MCU and DSP have been implemented and they are being used in our school. The netlab enables the experimenters to design their own circuit and get simulation result simultaneously. Teachers may design some new components and add them into the platform.

A quantitative analysis of the evolution of a spherical surface artificially prepared from a potassium alum single-crystal during its regeneration is carried out in real growth experiments. The results are compared with the results of the numerical simulation based on the proposed regeneration process kinematical model. It is demonstrated that for many boundary conditions there is a close quantitative correspondence between the model and real experiments on the regeneration of single-crystal balls. It is shown that the most important parameter that has a quantitative effect on the growing regeneration surface evolution is the geometry of the roughness (protrusions and depressions), initially present on this surface. The rare quantitative discrepancies between the results of real growth and numerical experiments are due to the discrepancies between the geometry of the roughness set in the model and those actually present on the regenerating single-crystal ball. The proximity of the model to real regenerati...

This paper presents a set of novel modifications that can be applied to any grid-based path planning algorithm from the A* family used in mobile robotics. Five modifications are presented regarding the way the robot sees an obstacle and its target to plan the robot’s path. The modifications make it possible for the robot to get to the target faster than traditional algorithms, as well as to avoid obstacles that move as fast as (or even faster than) the robot. Some simulations were made using a crowded and highly dynamic environment with twelve randomly moving obstacles. In these first simulations, a middle sized 5DPO robot was used. Also, real experiments were made with a small-sized version of a 5DPO robot to validate the algorithm’s effectiveness. In all simulations and real robot experiments the objects are considered to be moving at a constant speed. Finally, we present an overall discussion and conclusion of this paper.

This paper presents the development of a novel virtual reality (VR) machine learning (ML) framework that incorporates haptic feedback to improve sports training scenarios. The framework uses You Look Only Once (YoLo) for object detection, and combines it with ensemble learning to analyze the performance of athletes in a simulated environment and provide real-time feedbacks. The system includes haptic feedback devices that are controlled via Grey Wolf Optimization (GWO) to simulate the physical sensation of a real-world sports scenario, allowing athletes to experience the sensation of force, impact, and movements. The proposed system was tested using a group of professional athletes who participated in various sports, including football, basketball, and tennis. The athletes were asked to perform various training scenarios in the virtual environment, and their performance was compared with their real-world performance levels. The results showed that the proposed system improved the athletes' performance significantly, as they were able to receive immediate and accurate feedback on their movements, and the haptic feedback provided a realistic sensory experience that enhanced their trainings. The proposed research has the potential to revolutionize sports training by providing athletes with an efficient and effective way to improve their performance in a set of safe and controlled environments. The system can be customized to suit various sports and training scenarios, and the ML algorithms can be trained on large datasets to improve their accuracy and effectiveness. The incorporation of haptic feedback provides a unique and realistic experience, making the training more engaging and effective under real-time scenarios. The proposed system showcased an accuracy 93.5%, with 3.5% higher precision, and 4.9% higher recall than existing models, which has the potential to enhance athletic performance and revolutionize the way athletes train for different sports.

This paper presents a Japanese emotional database that contains speech and physiological signals that can be used to develop algorithms for emotion recognition using audio, physiological signals, or several combined signals. Research on emotions was underpinned by using this database, and health-care oriented applications were the main reason this database was constructed. All six basic human emotions were elicited by using real emotional experiences, which had different impacts on health conditions. We also describe the experimental setup and protocols. Finally, signals from more than 50 people were included in the database.