To evaluate the ability of a programmer in universities or staff agencies, evaluators conduct examination in which applicants solve problems, or they refer to the applicants’ GitHub and review their code. However, th...
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To evaluate the ability of a programmer in universities or staff agencies, evaluators conduct examination in which applicants solve problems, or they refer to the applicants’ GitHub and review their code. However, the collected source code is evaluated by a human under present conditions. This leads to two problems: many source codes cannot be evaluated simultaneously, and it is difficult to maintain consistency in the evaluation criteria among evaluators. We propose methods to estimate the current skill of the programmer, which can be used by the evaluators to understand an applicant’s skill by analyzing the collected source code automatically. In particular, this study visualizes the feature of the students’ source code in term of quarters using a decision tree to estimate the programming skill.
Range verification of therapeutic proton beam is crucial in proton therapy to confirm the irradiation field for ensuring effects and safety of the treatment. The irradiation field reconstruction using prompt gamma-ray...
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ISBN:
(数字)9781728141640
ISBN:
(纸本)9781728141657
Range verification of therapeutic proton beam is crucial in proton therapy to confirm the irradiation field for ensuring effects and safety of the treatment. The irradiation field reconstruction using prompt gamma-rays generated from excited nuclides by proton beam has being studied for the purpose of precision medicine. A simulation tool based on fundamental physics processes employs an important role to understand intermediate relationship between physics interactions and detected observables, and to optimize a detector system with its analysis method. Previously, we reported on the simulation study about an irradiation field reconstruction by using prompt gamma-rays of whole energy range. In this study, we analyzed the energy spectrum and reconstructed the image of irradiation field by using prompt gamma-rays corresponding to a particular energy peak. The simulation was performed for proton beam with a target placed at the isocenter by using Geant4 based particle therapy system simulation framework. A simple tubular detector was placed around the target, in which the kinetic energy and the detected position of each gamma-ray were recorded. The irradiation field was then reconstructed in the ordered subset expectation maximization method. The reconstructed irradiation fields were compared with the dose distribution in the target. The peak positions of these depth distributions were compared each other and discussed about the range verification of therapeutic proton beam.
KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to Apr...
KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to April 21, 2020 (O3GK). This study presents an overview of the input optics systems of the KAGRA detector, which consist of various optical systems, such as a laser source, its intensity and frequency stabilization systems, modulators, a Faraday isolator, mode-matching telescopes, and a high-power beam dump. These optics were successfully delivered to the KAGRA interferometer and operated stably during the observations. The laser frequency noise was observed to limit the detector sensitivity above a few kilohertz, whereas the laser intensity did not significantly limit the detector sensitivity.
Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invas...
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Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.
The non-linear response of dielectrics to intense, ultrashort electric fields has been a sustained topic of interest for decades with one of its most important applications being femtosecond laser micro/nano-machining...
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Emotion is an important part of human interaction. Emotional recognition can greatly promote human-centered interaction techniques. On this basis, multimodal feature fusion can effectively improve the emotion recognit...
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Emotion is an important part of human interaction. Emotional recognition can greatly promote human-centered interaction techniques. On this basis, multimodal feature fusion can effectively improve the emotion recognition rate. However, in the multimodal feature fusion at the feature level, most of the methods do not consider the intrinsic relationship between different modes. Only the fusion of analysis and transformation of the feature matrices of different modes does not make better use of modal differences to improve the recognition rate. This problem led us to propose feature fusion method based on K-Means clustering and kernel canonical correlation analysis (KCCA). Clustering makes the classification of features not classified by mode, but by the degree of influence on emotional labels, thus positively affecting the results of KCCA. The experimental results obtained on the Savee database show that the proposed K-Means based KCCA improves overall classification performance and produces higher recognition rate than that of the state of art methods, such as the Informed Segmentation and Labeling Approach.
The advent of industry 4.0 and the continuous digitalization of production ask for the enhancement of human skills and competences in the field of information and communication technology (ICT). Therefore, higher educ...
The advent of industry 4.0 and the continuous digitalization of production ask for the enhancement of human skills and competences in the field of information and communication technology (ICT). Therefore, higher education has to keep pace with the global market needs for the necessary ICT skills and the overall understanding of the complexity of industries in 21st century. This paper focuses on the development and integration of Virtual Learning Factory (VLF) tools that can be used in production management and engineering education. The digital tools integrated in VLF toolkit can help students to exploit enabling technologies like simulation and virtual reality in their manufacturing studies and practical projects with industrial companies.
Investigated is the problem of estimating the 3 D shape of an object defined by a set of 3 D landmarks with their 2 D correspondences in a single image. To solve this problem, we use a dictionary of the basic shape wi...
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Investigated is the problem of estimating the 3 D shape of an object defined by a set of 3 D landmarks with their 2 D correspondences in a single image. To solve this problem, we use a dictionary of the basic shape with LDD-L1 regularization,which is the construction of the shape space model. Based on the proposed convex optimization method, 3 D human pose reconstruction by shape space model and 3 D variable shape model was carried out on the mocap database. To improve accuracy and reduce the number of iterations, we use PSO algorithm to optimize initial value of the key parameter. The experimental results show that the improved algorithm exhibits less iterations but higher accuracy, which can be much helpful in practical applications.
In this study, the inner position loop addition for plastic deformation control of the error robustness of the model and actual parameters is proposed. The inner position loop is a type of position feedback control ba...
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ISBN:
(数字)9781728167947
ISBN:
(纸本)9781728167954
In this study, the inner position loop addition for plastic deformation control of the error robustness of the model and actual parameters is proposed. The inner position loop is a type of position feedback control based on the estimation of model parameters and dynamics of robots. This position control system with proportional and derivative gains modifies the trajectory of the end effector close to the desired trajectory. The robustness of the proposed control scheme is evaluated by comparing it with plastic deformation control without an inner position loop in both simulation and actual environments. Finally, the stable reaction with the proposed control is demonstrated for the case where a human pushes the robot finger.
This paper investigates the ultimate boundedness control problem for a class of networked systems with redundant channels under uniform quantization effects. Quantized output of concerned NCSs is transmitted to remote...
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This paper investigates the ultimate boundedness control problem for a class of networked systems with redundant channels under uniform quantization effects. Quantized output of concerned NCSs is transmitted to remote controller through a communication channel. For the purpose of improving communication quality, a redundant channel connected with a more precise quantizer is also employed, where the time to accomplish quantizing task is also considered. The transmission delays of such a redundant channel are modelled by a sequence of independent and identically distributed(i.i.d.) stochastic variable. An output feedback controller is developed under which the exponentially ultimate boundedness in mean square could be *** the virtue of stochastic analysis technology and Lyapunov-like method, sufficient conditions are established to ensure the existence of the desired controller, and the desired gain matrices are then obtained by solving a set of linear matrix ***, the effectiveness of designed controller is demonstrated through a simulation example.
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