Reviewerly/exHarmony huggingface dataset:
Proposal of maneuverability index for remote control systems focusing on the “sense of unity” and its verification

In this paper, we propose maneuverability index focusing on the “sense of unity” as a new performance evaluation method for remote control systems. We used the Crossmodal Congruency Effect (CCE) for the quantitative evaluation of the “sense of unity”. We verified the validity as a maneuverability index of “sense of unity” evaluated by CCE. We compared the measured CCEs between the systems which are different in terms of operation force of the master device and camera view orientation of the remote environment. As a result, task performance and “sense of unity” results were consistent. It was suggested that “sense of unity” could be used as an appropriate maneuverability index. Finally, we propose a method to compensate for a bias effect of CCE due to the appearance similarity of target objects to human hand.
Sosialisasi Trik Menjawab Soal Reading dalam Ujian Nasional Bahasa Inggris di SMKN 1 Samatiga Aceh Barat

Reading is one of the types of questions asked in National Examination. Senior High School/ MA/ SMK students face difficulties in answering reading questions because they require to analize and compare the passage. Based on the results of a study by the Research Center of the Ministry of Education and Culture (2019), only under 50% of students were able to answer the English National Examination questions. Based on these facts, it is necessary to hold a socialization about understanding English test questions and the types of questions asked in the National Examination. In this community service activity, students of SMKN 1 Samatiga who will face the National Examination are the target of the activity. This activity was carried out by lecturing, discussion and simulation test questions. After being given an understanding of the tricks in answering reading questions, the test results showed that students get scores above 50 for each aspect of the question discussed, namely: main ideas, direct and indirect questions, pronoun references, and vocabulary meaning.
The Challenge of Unifying Semantic and Syntactic Inference Restrictions

While syntactic inference restrictions don't play an important role for SAT, they are an essential reasoning technique for more expressive logics, such as first-order logic, or fragments thereof.In particular, they can result in short proofs or model representations.On the other hand, semantically guided inference systems enjoy important properties, such as the generation of solely non-redundant clauses.I discuss to what extend the two paradigms may be unifiable.
LQI based position control of a quad tilt-rotor UAV

A quad tilt-rotor UAV is a UAV which has capability of independent position and attitude flight by adding actuators to change the thrust direction. However, since the number of actuators increases, the control system becomes complicated. It induces difficulty of gain adjustment for stable flight. In this research, focusing on position control, we aim to develop a control system that does not require trial and error gain adjustment for the quad tilt-rotor UAV, and evaluate its validity with numerical simulation and flight experiment.
Operating a Kitchen Robot with Continuous Values by Nonverbal Voice

This paper proposes methods for operating a robot with nonverbal voice using tongue positions as indices. We defined the voice by Mel Frequency Cepstral Coefficients (MFCC). MFCC are acoustic characters and they show the characteristics of the vocal tract such as the mouth and the tongue. Nonverbal voice used for operating a robot is distinguished with tongue positions in our proposed methods. These tongue positions correspond to the coordinate of the robot’s hand and it enables the operators to operate a robot intuitively. We investigated the feasibility of the methods through experiments of operating a kitchen robot. These methods can realize operating a robot intuitively in continuous values with voice and can be utilized for user-friendly system.
A 360-degree Omnidirectional High-speed Human Tracking System

In this paper, we develop an omnidirectional human tracking system for remote wide-area video surveillance; it can simultaneously track humans and objects moving at distant places in high-resolution video images by controlling a high-speed mirror-drive action vision that has three rotary mirrors omnidirectionally with 500-fps visual feedback, which involves real-time execution of CNN-based recognition for human detection. Its effectiveness is demonstrated by showing several omnidirectional video-shooting results when tracking moving objects and humans at distances of several dozen meters in natural outdoor scenes.
RESEARCH ON CYBER SECURITY COUNTERMEASURE TECHNIQUE OF SAFETY DCS IN NUCLEAR POWER PLANT

Cyber security event is one of the main concerns in instrumentation and control system of nuclear power plant, since the application and popularity of digital technology in industrial control area. To ensure the cyber security of safety DCS control system of nuclear power plant, this paper analyzes the security risks and vulnerabilities of field control systems, and proposes the cyber security plan for safety DCS platform. Combining with the point-to-point data flow model and the R&D of safety DCS platform, we depict the application of cyber security strategy in the product design stage.
A generative-predictive framework used for video conversion

We proposed a model framework which was based on generative adversarial network for video conversion. Our goal is that two different target videos can synchronize the movements (such as the head displacement and facial movements of the person), and the movements was not existed in the original video. Our key observation is that a video prediction model is added to the original framework of the generative adversarial network, so that the generated video can get the time sequence characteristics of the target video to improve the action consistency and time synchronization stability. In the training process, we obtained and aligned the spatial position of the action in video through landmark points detection, to ensure that the generated samples would not appear the phenomenon of spatial dislocation. In the training process, we will generate sample t and obtain t+1 sample through pre-trained time predictor, calculating the generate sample loss feedback pre-trained generative model. Using this framework, we can: (1) obtain more convenient to make available training samples and improve the available range of the model; (2) improve the accuracy of target generate video. We proposed a model framework which was inspired by generative adversarial network for video conversion. Our goal is that two different target videos can synchronize the movements (such as the head displacement and facial movements of the person), and the movements were not existed in the original video. Our key observation is that a video prediction model is added to the original framework of the generative adversarial network, so that the generated video can get the time sequence characteristics of the target video to improve the action consistency and time synchronization stability. In the training process, we obtained and aligned the spatial position of the action in video through landmark points detection, to ensure that the generated samples would not appear the phenomenon of spatial dislocation. In the training process, we will generate sample t and obtain sample t + 1 through pre-trained time predictor, calculating the generate sample loss feedback pre-trained generative model. Using this framework, we can: (1) obtain more convenient to make available training samples and improve the available range of the model; (2) improve the accuracy of target generates video.
Tactical analysis of robot soccer using neural network

With the progress of technology, the realization of a symbiotic society with human beings and robots sharing the same environment has become an important subject. An example of this kind of systems is soccer game. Soccer is a multi-agent game that requires strategies by taking into account each member’s position and actions. The behavior of a player changes depending on the game situation, such as the score gap, the remaining time and the importance of the match. In this paper, a futsal game played by agents is observed and analyzed to find a mapping relationship. The strategy in the team is analyzed based on the state vector parameters using a Self-Organizing Map (SOM) and different behaviors are analyzed and compared to achieve, in the future, the best possible result cooperation in a real game.
Phase Shifting-based Active Visual Servoing

This paper focuses on a problem of positioning a textureless object to a tray for alignment using a robotic manipulator with active visual servo control. In the active visual servo control, a projector projects several patterns to provide artificial visual features to the object and reflected light is captured by a camera. However, the active visual servo control cannot perform positioning the object to the tray whose pose is not fixed. To solve this problem, this paper proposes a novel active visual servo control named Phase Shifting based Active Visual Servoing (PS-AVIS) which uses a phase image instead of the image directly captured by the camera. We also propose a method of computation of a goal phase image corresponding to the changed pose of the tray for PS-AVIS. Experimental results show that the proposed PS-AVIS achieves high position accuracy even if the pose of the tray is changed.
Development of Robot Hand by Imitating Sucker-attached Fingers of Tree Frogs and Grasping Experiment of General Objects

Application of automatic sorting technology in logistics warehouse is considered as one of the development goals with the rapid development of robot technology. However, packaging products with different shapes is usually done by human instead of robots. The reason why robot automation is difficult to implement in operation is that single robot hand could not deal with items with different shapes and sizes. In this study, by imitating the opening and closing of the tree frog's palm to help items stably stand on different surfaces, a four-claw robot hand with vacuum suction cups on their tips is proposed. Robot hand consists of three fingers with sucks and a thumb, and it can adopt different grasping strategies according to objects with different shapes and sizes. A prototype of robot hand was fabricated by a 3D printer. Besides, simple automatic grasping system is established, grasping experiment is accomplished.
A proposal for improving methods the estimation accuracy of localization using image sensors in videos and QR codes

This paper describes the new ideas for improving methods of the estimation accuracy of localization that uses image sensors and QR codes for videos. The ideas the authors describe localization methods which take accounts of continuity of frames in the video and use multiple QR codes filmed in the image sensor ’s view.
Depth Image Generation from monocular RGB image

In recent years, Visual SLAM using only monocular RGB camera has been researched. In this paper, we propose a method to generate depth images from a single RGB image using GAN, which is one of deep learning. As a result of the verification experiments, it is suggested that the depth prediction can be done, although it is large for both indoor and outdoor images. Future tasks include verification experiments using large-scale datasets.
High speed image acquisition system for 3D reconstruction

Laser triangulation is often the best solution for the 3D (three-dimensional) image reconstruction of an object. And its features, such as simple structure, fast reconstruction speed and flexible use make it widely used in 3D reconstruction. However, due to its high image frame rate, huge data, and requiring a large amount of computation for image processing algorithm, it is hard to be applied in embedded system. This paper presents a hardware solution for high-speed image acquisition system which is implemented on Xilinx FPGA. The experimental results indicate that this acquisition system works normally and its performance is steady and reliable, under the extreme conditions with an image resolution of 1280*384 and a frame rate of 9,000. It is still a challenging problem to extract the position information of the light bar in real time. In order to solve this problem, a parallel gray center gravity method based on FPGA is proposed to detect the position of light bar in this paper. Test results show that the proposed method can correctly extract the position information of the light bar in real time when the image frame rate reaches 9,000 frames. The power consumption is only about 4 watts.
Verification of Educational Effect of STEM Activities Using Underwater Robot

This paper introduces three educational activities using an underwater robot, conducted by the author. First, the educational underwater robot “Mark3TM” was used for programs for high school students, junior high school students, and technical college students in the underwater robot convention in JAMSTEC '16,'17, and '18. From the questionnaire survey, the conventions were favorable and Mark3TM had learning effects on STEM for the students. Second, elementary school and junior high school students attended an educational program using the robot in "Tokyo Bay Marine Experience Academy". Third, high school students developed the ROV "MOU" to survey the Ryusendo cave. From the above, underwater robots are found to be more effective than expected about STEM education.
Various Cognitive Platforms/Engines

Artificial intelligence (AI) has taken the digital world by storm. AI is increasingly relevant in a varied set of applications and use cases. It is used in a variety of personal digital assistants, including Siri, Cortana, Alexa, and Google Assistant, for solving consumers’ day-to-day use cases. Cognitive computing defines a system that tries to simulate the way a human mind works. These two terms use the same technologies, including machine learning, neural networks, natural language processing, and sentimental analysis. IBM defines cognitive computing as “systems that learn at scale, reason with purpose, and interact with humans naturally.” Cognitive computing focuses on human machine interaction by using self-learning algorithms to enable decision-making and to make life easier for humans.
Spacecraft Stealth Through Orbit-Perturbing Maneuvers Using Reinforcement Learning

Spacecraft maneuvers are planned with operational objectives in mind, ranging from making up for atmospheric drag to collision avoidance. Though these areas have been researched in depth, performing maneuvers to avoid detection by sensors hasn't been explored until recently. Reinforcement learning has been shown to be an effective method for optimizing a maneuver strategy for the purpose of avoiding detection by a sensor with a pre-defined search strategy. This work expands on that further by incorporating the opposed sensor into the learning process as well and results in an optimal strategy for both opponents with respect to one another. It was found that, with an average maneuver magnitude of 19 m/s and an average of 3.12 days between maneuvers, a controlled spacecraft is able to successfully avoid being tracked by a single sensor for 31.2% of the observation windows.
Study on Generation of Virtual Environment Use Motion Data for Machine Learning Motion Identification

Research using machine learning to realize motion identification function is increasing. In order to perform motion identification using machine learning, motion data of motion to be identified in advance is necessary, and it is said that the amount is important for improving the identification rate. However, with the conventional behavior data collection method, it is difficult to collect large quantities. In this research, we generated a large amount of motion data using the virtual environment. As a result of performing an evaluation experiment to confirm whether the generated motion data can be used for motion identification, it was suggested that it is available.
ElGolog: A High-Level Programming Language with Memory of the Execution History

Most programming languages only support tests that refer exclusively to the current state. This applies even to high-level programming languages based on the situation calculus such as Golog. The result is that additional variables/fluents/data structures must be introduced to track conditions that the program uses in tests to make decisions. In this paper, drawing inspiration from McCarthy's Elephant 2000, we propose an extended version of Golog, called ElGolog, that supports rich tests about the execution history, where tests are expressed in a first-order variant of two-way linear dynamic logic that uses ElGolog programs with converse. We show that in spite of rich tests, ElGolog shares key features with Golog, including a sematics based on macroexpansion into situation calculus formulas, upon which regression can still be applied. We also show that like Golog, our extended language can easily be implemented in ElGolog.
Environmental Perception for Mobile Robots Using a Variable Ranging Sensor Array

Recently, large-scale disasters occur frequently, and the demand for disaster robots is increasing. Environmental perception is necessary for mobile robots to act autonomously in complex environments such as disaster sites. Various measurements are necessary for environmental perception in such environments. For example, global measurement for recognizing the entire surrounding environment, local measurement for recognizing an obstacle, and the like are included. Therefore, in this research, we develop a Variable Ranging Sensor Array equipped with multiple Laser Range Finders. In this paper, we propose a control method of the sensor array measurement using the concept of Multi-Objective Behavior Coordination. We showed the effectiveness of the proposed method by experiment that moved the mobile robot autonomously based on the environmental perception result from the sensor array.
Autonomous Gripping and Carrying Method Based on Plane Detection of Polyhedral Shaped Object by a Mobile Robot with Twin Arms

Recently, it is highly expected that robots work instead of human in a dangerous site such as disaster area. Sufficient working ability is required for such robots as well as moving ability. Thus, we have presented a method for autonomous gripping and carrying of a polyhedral shaped object by a mobile robot with twin arms based on plane detection in our earlier study. However, in this method, it is necessary to give the positions to observe the object in advance. Therefore, we aim to present a method for calculating observation positions, and to increase working ability of the robot. We apply the method to a quadruped tracked robot and verify its effectiveness in an experiment for autonomous gripping and carrying of a box shaped object.
Human-Following Mobile Umbrella Robot Capable of Avoiding Obstacles

This paper proposes a human following mobile umbrella robot that is possible to avoid obstacles. In this study, the artificial potential method was used as a movement control method. We propose a method of distinguishing the followee and obstacles by using a laser rangefinder and USB camera. We designed and experimented the developed umbrella robot to confirm the capability of tracking the following human and avoiding obstacles.
KAJIAN PENGELOLAAN JURNAL SENI DI INSTITUT SENI INDONESIA SURAKARTA

This research entitled;The Study of Art Journals Management at the Indonesian Institute of Art in Surakarta. The aim of the research is to find out how the interests, usefulness and what factors which become the obstacles to the sustainability of the publication of journals at the Indonesian Institute of Art in Surakarta. This study uses a qualitative research approach which describes phenomena, digs up data by interviewing, observing and documenting. The problems in qualitative research are still temporary, tentative and will develop or change after the researcher is in the field. Qualitative research requires data sources called informants. This study uses triangulation technique to test the credibility of data by checking the data to the same source with different techniques. For example, data are obtained by doing interview, then checked by observation, documentation, or questionnaire. Interest theory is used in reviewing the management of this journal. The second theory; a research model adapted from Kim (2005) and Nisonger (1997) about the influence factors of a person’s desire to use journal facilities provided by the library. Those variables are; Ease of use, Accessibility, Relevance of information content to the user’s information needs, Quality of information and Intention to use the journal. The results of this study are expected to be an input or recommendation and thoughts for the Indonesian Institute of Arst in Surakarta on how to manage the art journals within the Indonesian Institute of Arts in Surakarta. Keywords: journal, management, interests, usefulness and constraints
Development of rough terrain mobile robot with non-circular wheel

Robot using wheels with special shape have been studied as a kind of robot aiming to search rough terrain. Wheels with the special shapes can leach step by higher than the wheel radius by hooking on steps and irregularities. However, the robot using the wheels with the special shape has a problem that he vehicle body moves up and down while traveling on a flat road. The purpose of this research is to develop a robot that can run on irregular ground and can travel without moving the body up and down during running on flat ground using wheels with special shape. In this paper, we report consideration, construction and operation experiment of turning motion using prototype.
Equipment Fault Case Retrieval Algorithm Based on Mixed Weights

Case-based reasoning (CBR) has been applied to all walks of life as an emerging intelligent fault diagnosis method. For the existing fault situation, the feature weight is mainly given by experts, which has the disadvantages of strong subjectivity and low accuracy of search results. A case retrieval algorithm based on mixed weight (CRAMW) is proposed. Firstly, the entropy weight method is used to obtain the objective weights of the feature attributes of each fault case, and the mixed attribute weight value of the comprehensive attribute is given in combination with the expert experience. Secondly, the similarity between the cases is calculated by using the mixed weight value and the Euclidean distance to find the case base. The most similar case to the case to be tested; finally, the engineering equipment fault diagnosis algorithm simulation of the algorithm is designed. The simulation results show that the algorithm has higher resolution and accuracy than traditional algorithms. Applying the algorithm to equipment fault diagnosis helps the smooth progress of maintenance work and improves equipment support efficiency.
Analysis of the influence that the different format of the compression sound source gives in the brain of the listener

We used a “high resolution sound source” that there was much information for an experiment with high-quality sound this time. When I showed these three kinds of sound sources to a subject by headphones, I measure brain waves using the State Variable Filter which I produced newly every frequency band what kind of influence is given to the brain waves of the person and report it because I analyzed it using wavelet transform.