Reviewerly/exHarmony huggingface dataset:
Automatic Map Generation for Action Policy Learning of Mobile Robot from Existing Electronic Map

The paper introduces a method of automatic map generation used for learning of action policy in mobile robot navigation. Road contours and waypoint candidates are extracted as map components by image processing from an image of existing electronic map such as Google Map. Road contours are extracted using topological structural analysis of the binarized electronic map image. Also, waypoint candidates used as respawn or destination points in learning system are randomly selected from pixels of road areas. The generated map can be applied to learning simulator based on deep reinforce learning system. The paper describes an abstract of navigation system based on reinforcement learning, a proposed map generation method.
Real-time Visual Servoing Control of an UAV Having Two-Cameras

Recently, the obstacle avoidance and localization of UAV in places without GPS signal has received widespread attention. This paper presents a visual feedback control of UAV with two monocular cameras. In the system, visual odometry and visual servoing are switched in realtime.
An Elastic Anonymization Framework for Open Data

Open data is a vast resource that is waiting for being utilizing. To publish data to an open environment, the privacy preserving requirement is a must. Different solutions are applied to privacy protection, and data anonymization is one of the prominent ones. This paper proposed a framework flexibly applying different anonymization models to work with an arbitrary open data management platform. An experimental setup was implemented with a heterogeneous service architecture using two datasets vary in the data volume and the number of dimensions. The measured results show that the proposed method produces anonymized data in an acceptable time using different anonymization techniques and settings, giving high quality outputs.
Material Mediations Complicate Communication Privacy Management

Increasingly, school settings are implementing digital technologies to coordinate teachers’ work. The article examines the role of these technologies in teachers’ boundary regulation processes through the lens of communication privacy management theory, and it provides empirical insight into the renegotiation of being a teacher in the presence of rules formalized in software code. The case of Finnish high school teachers exposed to the use of Wilma, a distributed computing system used to store, process, and transmit student data, revealed experiences of a need to renegotiate formalized and trackable work processes, faster and more colloquial communication, and intensified day-to-day work. These influence modes of accountability and the need to negotiate visibility, along with understandings of rules as a central coordination mechanism for interpersonal boundary regulation. The authors suggest in addition that these technologies inure various social stakeholders to constant technical monitoring and regular accounting, thereby advancing the normalization of surveillance practices. This creates good reason to pay closer attention to how rules of engagement may be coordinated.
Improvement of straight running stability of 3-wheeled wheelchair with an active-caster

Recently, simplified electric wheelchairs, that is, wheelchair with a motorized device attached to a manual wheelchair has been gathered attention. Simplified electric wheelchairs are relatively lightweight and can be folded. However, simplified electric wheelchairs have a risk that the wheelchair will fall backward when running over a step. To solve this problem, we developed the 3-wheeled simple electric wheelchair. This wheelchair has two large wheels and an active-caster, a type of powered caster which can move in any directions. With this structure, the active-caster saves as a support, the risk of falling backwards can be reduced when the wheelchair running over steps. However, 3-wheeled simple electric wheelchair have a problem that stability of straight running is poor. In this paper, we will clarify that deflection of 3-wheeled wheelchair traveling direction is caused by human control by experiment. Also, confirm the improvement of running stability by the angular velocity feedback.
Dynamically stable omnidirectional personal vehicle with four driving wheels

This paper proposes a new kind of personal vehicle which is driven by four omnidirectional wheels and whose body is dynamically stabilized. Unlike personal vehicles with two or more wheels, the proposed vehicle can move immediately in all directions and the body is always kept upright on the road surface of variety of slopes. The most distinctive mechanical structure is that the chassis and the vehicle body is connected by a single, free universal joint. Since the body is not directly actuated, the vehicle is an unstable, underactuated system and the body attitude needs to be kept stable by appropriate feedback control. The overall mechanical structure, its kinematic and dynamic models, derivation of the controller are described. Early expermiental results request for further refinement of models or design of the controller. Safety issues and automated driving or driver assistance are under development.
Meningkatkan keterampilan berbicara peserta didik kelas IV sekolah dasar melalui penerapan model inside outside circle (ioc)

This research aims to determine if the model inside outside circle can enhance the speaking skills in class IV elementary school Negeri Tunggulsari 1 Surakarta school year 2019/2020.This research uses qualitative descriptive research methods. The variables that was subjected to change in this study was speaking skills, while the variable action used in this study was an application of a model Inside Outside Circle (IOC).This form of research is a class action study of 3 cycles. Cycle I consists of 1 meeting, cycle II consists of 2 meetings and a cycle III consists of 1 meeting. Each cycle consists of 4 stages ie planning, implementation, observation and reflection. Students of class IV SD Negeri Tunggulsari 1 Surakarta which numbered 24 students are the subjects of the study . Data collection techniques using interview, observations, test, and documentation. The techniques of data analysis used are interactive analysis models that have 3 components of which data reduction, data presentation and withdrawal of conclusions.The first cycle generates a 0% percentage of the classifications of speaking skills, then continued with the second cycle resulting in a 54% success percentage, and the third cycle resulted in a percentage of 83% of the classifications of speaking skills. Based on research results, it may be inconclusive that  application of the inside outside circle learning model can improve the skills of learners of class IV students of the Negeri Tungulsari 1 Surakarta school year 2019/2020.
A New Framework for Efficient Low-light Image Enhancement using Approximated Gaussian Process

Gaussian Process (GP) is a robust distribution modelingtechnique that is very promising for computer visionsystems. In particular, its multivariate distributionmodeling is especially effective for low-light imageenhancement where localized enhancement is requiredto address the over- and under-enhancement problem,and also retrieval of features which has been lost due tolow illumination. However, GP lacks practicality due toits computation complexity that increases cubicallyfollowing data increment. This paper proposes a sparseGP regression based solution whereby clustering isexploited to reduce the training cost of a GP model.Instead of utilizing all values from an image, clusteringgroups similar training pixels or image patches pairsinto clusters and the cluster centers are used to train anapproximate GP enhancement model. Experimentsconducted showed the proposed framework can achievetraining time reduction of as much as 75% from thebaseline. In line with this, the proposed approach alsoimproved the enhancement performance in both PSNRand features retrieval metric, and is competitive with thecurrent state-of-the-art.
Approach to Social Implementation Project Using Autonomous Mobile Robot TAKAO Series

In the near future, autonomous mobile robots are expected to operate in various locations, such as in living spaces as well as in industrial establishments. Against this background, an autonomous mobile robot TAKAO series has been developed since 2009 as an approach to the social implementation project. For example, one of the robot series, TAKAO 7 consists of two low-end in-wheel motors for the sake of simplicity of the design and assembly of the drive unit. It is also effective for high power and flexible control for various road surface conditions. This paper presents our autonomous mobile robot TAKAO series and its preliminary experiments using the TAKAO 7.
Study on Efficiency of Cleaning by Large and Small Robots Using Path Search Method

Large cleaning robots can clean floor quickly and small cleaning robots can clean narrow floor. This study suggests ways to enable quick, detailed and energy saving cleaning by using multiple large and small cleaning robots. We established a method to generated cleaning paths of each robot combination using A* algorithm. We verified that it is possible to move along generated cleaning paths by experiment. We found that some rooms’ structures can be derived cleaning paths using current algorithms. We derived the cleaning efficiency by calculating from results of derived cleaning paths. We showed the usefulness of multiple large and small cleaning robots in cleaning.
Watermarking of Electronic Patient Record in Parkinson Disease Affected Speech: A Robust and Secure Audio Hiding Technique for Smart e-healthcare Application

A cloud-based framework for security of electronic patient record, in telediagnosis of Parkinson's disease (PD) speech signal has been proposed in this paper. The security and authenticity of patient's personal information is achieved using proposed Discrete Cosine Transform-Singular Value Decomposition (DCT-SVD) based audio watermarking technique. The automatic classification of PD affected speech signal from healthy person's speech signal requires high computational accuracy and in this work, it is addressed by extracting various time frequency features for the Support Vector Machine (SVM) classifier. In the proposed framework the speech signal of PD suspected person is recorded by a mobile application. The personal information is securely embedded in this speech signal using proposed DCT-SVD based audio watermarking technique, before transmitting to cloud for automatic classification. To ensure the security of electronic patient record (EPR), proposed watermarking technique is tested against various signal processing attacks and the performance of classifier has been evaluated by computing classification sensitivity, specificity, accuracy and area under the curve of receiver operating characteristics (ROC). The theoretical proofs and experimental results, show that proposed framework provides telediagnosis of PD affect patients without compromising the security and privacy of patient's records. The classification accuracy of $89\%$ with high data payload of $6kbps$ is proposed leading to a smart and secure e-healthcare application.
AN ANALYSIS OF VIOLATION MAXIM IN THE HOME ALONE 5 MOVIE (A Content Analysis of Movie “Home Alone 5”)

This research is conducted on the research question: 1.) What are the types of violation maxims used by the characters in The Home Alone 5 movie? 2.) How do the characters violated the maxims in The Home Alone 5 movie?. The aims of this research are: 1) To analyze the types of violation maxims used by the characters and 2) To know the characters violated the maxims. The method of this research is summative content analysis. The way of the writer analyzes this movie through many steps: 1) Selecting, watching and observing the Home Alone 5 movie, 2) Investigate how do the characters violated the maxim is used based on the gricean maxim theory. 3) Taking note and mark anything that is related to violating maxim. 4) Describing the maxim violation data and give the reason why utterance happened and the last is classifying the data which contains maxim violation. The research conducted in The Home Alone 5 movie. The result of the research shows that in The Home Alone 5 movie, a few characters have violated all of the Gricean Maxim also it found as many 10 violation maxim in the conversation of movie. From the result, it can be concluded that Home Alone 5 movie could be as learning process to gain more knowledge in pragmatics field.
Proposal of an Optical Flow Driven Particle Filter Considering Luminance Change

In recent years, in object tracking of expecting the children’s monitoring and the automotive applications, modeling the motion of a tracked object is an important task for determining the performance of the tracking algorithm. If there is no prior knowledge about the motion of a target, it often tracks it with a particle filter under the assumption of “ smooth motion. ”Note however that, this doesn’t work well for sudden movement changes and unexpected movements, and fails to track them. Thus, a system has been already developed to model the motion of a tracked object by optical flow and track it with a particle filter. The Lucas and Kanade (LK) method is known as a typical algorithm that acquires the optical flow. In this method, the brightness is assumed to be preserved such that the brightness value in the same pixel doesn’t change between frames. However, the brightness preservation is not held in reality due to noises caused by the change of the photography environment and the change of amount of solar radiation. In this paper, an algorithm for estimating the optical flow, which is robust against luminance changes, is developed by calculating the amount of luminance changes with the difference average and by correcting the temporal luminance gradient. In addition, some experiments on object tracking are conducted using an optical flow–based particle filter that is robust to luminance changes, so that its effectiveness is verified through such experiments.
Research on Cloud Architecture of Enterprise Distributed Business Information System Based on SOA

Abstract The current SOA-based Enterprise Distributed Business Information System has poor scalability and low utilization, in order to solve this problem, this article analyzes the possibility of integration between Cloud Computing and SOA after telling the similarities between the two. We proposed a SOA-based Cloud architecture model, and applied it to Enterprise Distributed Information Systems, and proposed SOA-based Enterprise Distributed Business Information System Cloud Architecture Conceptual Model and Operating Model. This scheme can well solve the problems of the current system, and can greatly improve the quality and efficiency of system development, and has guiding significance for the development direction of enterprise information systems.
Penerapan Sistem Absensi Finger Print Terhadap Kinerja Pegawai Melalui Displin Kerja Di Dinas Kependudukan Dan Pencatatan Sipil Kabupaten Sumenep

Work discipline is the beginning of the process of improving employee performance, therefore employee discipline needs to be maximized to employees either through rules or the use of tools that can bind and reduce fraud from the employees themselves, in this case in every organization, agency, company has used a lot. a tool in the form of a fingerprint attendance system. Increasing discipline by using the fingerprint attendance system is inseparable from the obstacles that occurred previously in the form of the number of employees who are still not maximal in terms of their attendance levels and carrying out their duties. Therefore, researchers want to know how the effect of applying the fingerprint attendance system on work discipline on employee performance in Dispendukcapil of Sumenep Regency. The purpose of this study was to determine and analyze the effect of fingerprint application on employee performance through work discipline at the Dispendukcapil of Sumenep Regency. The analysis in this study uses path analysis. The results of the study indicate that the fingerprint has a significant relationship to the performance of both employees through employee work discipline at the Dispendukcapil of Sumenep Regency. This is very good for improving employee performance.
Motion Analysis with Scope of Human Manipulability Sharing Using VR System

This paper explains the motion analysis using a new scope of human manipulability sharing (SoHMS). The new SoHMS is composed of a depth sensor and a head-mount-type VR system, which can provide a human manipulability ellipsoid evaluated at the hand/foot to a user in real time. The user can select one of digital human models, and can measure EMG signals (maximum 4 ch) as needed. A set of basic experiments was carried out for the motion task of the spear throwing and shot put by the right arm in order to validate the developed SoHMS.
Application of Master-slave Control and Visual Display in Air Hockey Robot System

In this paper, we propose a high-speed and accurate operation system for an air hockey robot by master-slave control. In this system, the position of the operator’s hand is predicted using a Kalman filter, and the robot is controlled based on the prediction. In addition, several visual presentation techniques using AR can help the operator.
Examination of posture evaluation method using machine learning for lower limb muscle strength training

Rehabilitation and training must be performed in an appropriate posture, and if performed in an inappropriate posture, the target muscle may not be effectively stimulated. Furthermore, depending on the posture, there is a risk of applying unnecessary load to specific muscles and tendons. Thus, it is known that effective stimulation of the target muscle depends not only on the control of the training support system but also on the posture during training. The purpose of this study is to measure trainees and evaluate their posture so that they can perform effective training with proper posture during lower limb muscle strength training. In addition, it is necessary to evaluate the posture automatically because a skilled person does not always accompany the training.
Reconfigurable Metasurfaces for Rapid Control Over Quantum Interference Using GeTe as Phase-change Material

Tunable quantum interference is enabled by a design incorporating phase-change materials into metasurfaces. Via controlled joule heating, these structures can switch rapidly between phases of constructive and destructive quantum interferences.
IMPLEMENTASI JARINGAN SARAF TIRUAN UNTUK MEMPREDIKSI NILAI MATA PELAJARAN UJIAN NASIONAL SMK NEGERI 2 CIMAHI DENGAN METODE BACKPROPAGATION

Penelitian ini bertujuan untuk mengetahui prediksi nilai Ujian Nasional di SMKN 2 Cimahi dengan menggunakan metode backpropagation. Penggunaan metode backpropagation pada penelitian ini agar metode terbaik untuk mendapatkan hasil yang optimal karena memiliki akurasi tinggi. Untuk mengetahui pengaruh akurasi prediksi terhadap input pembelajaran, maka pelatihan jaringan dilakukan sebanyak dua kali. Semua data diolah menggunakan metode backpropagation. Hasil prediksi 2017-2018 dengan menggunakan data tahun 2011-2016, menggunakan arsitektur jaringan dengan hidden layer 5 dan 10 dengan nilai MSE 0,001 dengan maksimal epoch 1000. Pelatihan terbaik yaitu dengan menggunakan 5 hidden layer karena menghasilkan epoch yang paling kecil dan akurasi yang besar. Pelatihan berhenti di iterasi ke-127 dengan nilai epoch 0,0024058 dengan akurasi sebesar 96,50%. Pada gambar hasil prediksi menunjukkan perbandingan antara target dengan keluaran JST pada data pengujian. Pada gambar tersebut dapat dilihat bahwa sebagian target dan keluaran jaringan sudah berdekatan (hampir menempati posisi yang sama).Prediction of test scores is important to know the level of graduation, therefore we need a system that can predict student test scores so that the school can take action to improve the learning of students that aims to increase the number of students graduating each year. Predictions about the value of the National Examination need to be known early on as a representative step of the ability of students and can be used as a benchmark for the achievement of the value of the National Examination while. Especially at the level of certain subjects that the level of difficulty is relatively higher than other subjects. This study aims to determine the prediction value of the National Examination at SMK 2 Cimahi by using the backpropagation method. The use of the backpropagation method in this study is for the best method to get optimal results because it has high accuracy. To find out the effect of prediction accuracy on learning inputs, network training is carried out twice. All data is processed using the backpropagation method. The 2017-2018 prediction results using 2011-2016 data, using network architecture with hidden layers 5 and 10 with an MSE value of 0.001 with a maximum of epoch 1000. The best training is to use 5 hidden layers because it produces the smallest epoch and great accuracy. The training stopped at 127th iteration with the epoch value of 0.0024058 with an accuracy of 96.50%. Comparison of prediction results with the original 2018 data values resulted in an accuracy of 95.28%
Tempo Estimation by Frequency Analysis for Volume Change of Unaccompanied Singing

We aim at communication between humans and robots where the robot claps hands according to a person who sings without accompaniment. This paper describes acquiring the tempo from unaccompanied singing. This method estimates the tempo of a song by using the Fourier transform to find the frequency component for the rise of the volume intensity in a time series. We also propose a method to calculate the timing of clapping, and show its effectiveness by experiments.
Semi-Device-Independent Quantum Random Number Generator based on heterodyne detection and bounded energy

We show a Semi-Device-Independent QRNG based on energy bound with untrusted source and measurement. Our device exploits heterodyne detection, guaranteeing high generation rates without active phase stabilization. We reach 113 Mbps of generation rate
Gesture Classification Utilizing Reservoir Computing and Spatio-temporal Features Inspired by the Visual Nervous Systems

We developed a gesture classification algorithm that is installable to a small edge device. The algorithm is composed of neuro-inspired spatial and spatio-temporal feature extractors and the echo state network (ESN). The spatial feature extractor is based on the HMAX algorithm, which extracts scale-invariant features of line segments, and the spatio-temporal feature extractor was developed by combining the HMAX algorithm and the motion detection model of the visual cortex. The ESN, which can classify spatio-temporal data in spite of its simple three-layer architecture, was employed to avoid employing deep neural network, which is not suitable for small devices. We evaluated the proposed algorithm by classifying ten kinds of sign language. The results showed that the algorithm was successful in classifying the sign language.