Virtual laboratory-Using a hand movement recognition system to improve the quality of chemical education

2017 ◽  
Vol 50 (1) ◽  
pp. 218-231 ◽  
Author(s):  
Robert Wolski ◽  
Piotr Jagodziński
Keyword(s):  
Hand Movement ◽  
Chemical Education ◽  
Recognition System ◽  
Virtual Laboratory ◽  
Movement Recognition

Delays in Manual Reaching Are Associated with Impaired Functional Abilities in Early Dementia Patients

2015 ◽  
Vol 40 (1-2) ◽  
pp. 63-71 ◽  
Author(s):  
Casper de Boer ◽  
Johan J.M. Pel ◽  
Johannes van der Steen ◽  
Francesco Mattace-Raso
Keyword(s):  
Daily Living ◽  
Hand Movement ◽  
Hand Tracking ◽  
Functional Abilities ◽  
Dementia Patients ◽  
Early Dementia ◽  
Tracking Devices ◽  
The Impact ◽  
Hand Response

Background/Aims: Recent evidence shows that early dementia patients have deficits in manual reaching tasks. It is important to understand the impact of these functional disabilities on their quality of life. The aim of this study was to investigate if there is an association between manual reaching and measures of (instrumental) activities of daily living (IADL) in a group of patients with cognitive complaints. Methods: The manual reaching performance of 27 patients was assessed in detail with eye and hand tracking devices. Patients were divided into three groups based on self-reported loss of IADL function. Parameters describing hand response and movement times were compared between groups. Results: Patients with loss of IADL function in ≥1 domain had delayed hand response and hand movement times towards visible targets compared to patients with no loss of IADL function. Conclusion: Delays in manual reaching movements are related to the degree of loss of IADL function in early dementia patients.

scholarly journals Real-time Triplet Loss Embedding Face Recognition for Authentication Student Attendance Records System Framework

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Hady Pranoto ◽  
Oktaria Kusumawardani
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Success Factors ◽  
Recognition System ◽  
Expression Recognition ◽  
Student Attendance ◽  
Face Recognition System ◽  
Triplet Loss ◽  
Education Process

The number of times students attend lectures has been identified as one of many success factors in the learning process in many studies. We proposed a framework of the student attendance system by using face recognition as authentication. Triplet loss embedding in FaceNet is suitable for face recognition systems because the architecture has high accuracy, quite lightweight, and easy to implement in the real-time face recognition system. In our research, triplet loss embedding shows good performance in terms of the ability to recognize faces. It can also be used for real-time face recognition for the authentication process in the attendance recording system that uses RFID. In our study, the performance for face recognition using k-NN and SVM classification methods achieved results of 96.2 +/- 0.1% and 95.2 +/- 0.1% accordingly. Attendance recording systems using face recognition as an authentication process will increase student attendance in lectures. The system should be difficult to be faked; the system will validate the user or student using RFID cards using facial biometric marks. Finally, students will always be present in lectures, which in turn will improve the quality of the existing education process. The outcome can be changed in the future by using a high-resolution camera. A face recognition system with facial expression recognition can be added to improve the authentication process. For better results, users are required to perform an expression instructed by face recognition using a database and the YOLO process.

scholarly journals Projection of the Electronic Toll Collection System in the Republic of Croatia

2020 ◽  
Vol 59 (1) ◽  
pp. 115-130
Author(s):  
Marko Vidmar ◽  
Marino Žagar ◽  
Mile Perić
Keyword(s):  
Road Traffic ◽  
New Technology ◽  
Recognition System ◽  
The European Union ◽  
Collection System ◽  
Electronic Toll Collection ◽  
Toll Collection ◽  
The Republic ◽  
Technological Improvements

This paper deals with the topic of a modern electronic toll collection system that will be applied in the Republic of Croatia from the year 2022 onwards. The paper primarily analyses the existing toll collection systems in Croatia, as well as in the European Union. Modern electronic toll collection systems were analysed with an emphasis on the ANPR (Automatic Number Plate Recognition) system, because ANPR technology will be used in Croatia after the restructuring of road traffic occurs. ANPR is not a new technology, however in the last twenty years it has found its wider application. This happened mostly thanks to local and global infrastructural development and technological improvements therefore in turn infrastructure required for the operation of this system became cheaper. By applying the ETC and ANPR, Croatia will have a system in line with European directives and practices which are being applied in other European countries. The system will in turn significantly raise the quality of road traffic in Croatia and reduce its costs.

scholarly journals URGENSI PENGEMBANGAN KURIKULUM PROGRAM STUDI PENDIDIKAN KIMIA UIN AR- RANIRY

2014 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Ramli Abdullah
Keyword(s):  
Curriculum Development ◽  
Education Program ◽  
Chemistry Education ◽  
Basic Education ◽  
Chemical Education ◽  
Development Education ◽  
Study Program ◽  
The Times ◽  
Banda Aceh

Urgency curriculum development education courses chemistry Faculty of Tarbiyah and Teaching UIN Ar-Raniry Banda Aceh. Implementation of this research aims to be known: (1) How is the curriculum of Chemical Education Program currently in use, and (2) How is the curriculum of Chemical Education Program that is relevant to the times now. The research was conducted at the Basic Education Program Chemistry Faculty of tarbiyah UIN Ar-Raniry Banda Aceh in April to September 2013. The method used in this research is qualitative descriptive, the population in this study is a faculty, alumni, and students of Chemistry Education Tarbiyah UIN Ar-Raniry Banda Aceh. Retrieving data using instruments interviews with faculty, students, and alumni of Basic Chemical Education Program Faculty of tarbiyah UIN Ar-Raniry Banda Aceh. While the curriculum documentation talaah Basic Chemical Education Program Faculty of tarbiyah UIN Ar-Raniry Banda Aceh and curriculum Document Basic Chemical Education Program FKIP Unsyiah Banda Aceh. The results obtained in this study are: (1) Get a picture of the curriculum of Chemical Education Program currently in use, and (2) Chemistry Education Program curriculum that is relevant to the times now for the Basic Education Program Chemistry Faculty of tarbiyah UIN Ar Raniry Banda Aceh. The conclusion of this study is mengatahui picture of Chemical Education Program curriculum currently in use, and the curriculum of Chemical Education Program are relevant to the development of today for Basic Chemical Education Program Faculty of tarbiyah UIN Ar-Raniry Banda Aceh. Suggestions put forward of this research is to improve the quality of learning in Chemistry Education Program requires continuous curriculum development, improving the quality of teachers and increase motivation and interest in students' growth Study Program Basic Chemistry Faculty of tarbiyah UIN Ar-Raniry Banda Aceh.

scholarly journals The Identification of Non-Driving Activities with Associated Implication on the Take-Over Process

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 42
Author(s):  
Lichao Yang ◽  
Mahdi Babayi Semiromi ◽  
Yang Xing ◽  
Chen Lv ◽  
James Brighton ◽  
...  
Keyword(s):  
Situation Awareness ◽  
Haptic Feedback ◽  
Hand Movement ◽  
Transition Process ◽  
Recognition System ◽  
Steering Wheel ◽  
Automated Driving ◽  
Driver Behaviour ◽  
Active Mode ◽  
The Impact

In conditionally automated driving, the engagement of non-driving activities (NDAs) can be regarded as the main factor that affects the driver’s take-over performance, the investigation of which is of great importance to the design of an intelligent human–machine interface for a safe and smooth control transition. This paper introduces a 3D convolutional neural network-based system to recognize six types of driver behaviour (four types of NDAs and two types of driving activities) through two video feeds based on head and hand movement. Based on the interaction of driver and object, the selected NDAs are divided into active mode and passive mode. The proposed recognition system achieves 85.87% accuracy for the classification of six activities. The impact of NDAs on the perspective of the driver’s situation awareness and take-over quality in terms of both activity type and interaction mode is further investigated. The results show that at a similar level of achieved maximum lateral error, the engagement of NDAs demands more time for drivers to accomplish the control transition, especially for the active mode NDAs engagement, which is more mentally demanding and reduces drivers’ sensitiveness to the driving situation change. Moreover, the haptic feedback torque from the steering wheel could help to reduce the time of the transition process, which can be regarded as a productive assistance system for the take-over process.

A Motion Capture System for Hand Movement Recognition

2021 ◽  
pp. 114-121
Author(s):  
Graciela Rodríguez-Vega ◽  
Dora Aydee Rodríguez-Vega ◽  
Xiomara Penelope Zaldívar-Colado ◽  
Ulises Zaldívar-Colado ◽  
Rafael Castillo-Ortega
Keyword(s):  
Motion Capture ◽  
Hand Movement ◽  
Motion Capture System ◽  
Movement Recognition

scholarly journals SEMG Feature Extraction Based on Stockwell Transform Improves Hand Movement Recognition Accuracy

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4457 ◽  
Author(s):  
She ◽  
Zhu ◽  
Tian ◽  
Wang ◽  
Yokoi ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Frequency Analysis ◽  
Recognition Accuracy ◽  
Hand Movement ◽  
Analysis Method ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Analysis Methods ◽  
Movement Recognition ◽  
S Transform

Feature extraction, as an important method for extracting useful information from surfaceelectromyography (SEMG), can significantly improve pattern recognition accuracy. Time andfrequency analysis methods have been widely used for feature extraction, but these methods analyzeSEMG signals only from the time or frequency domain. Recent studies have shown that featureextraction based on time-frequency analysis methods can extract more useful information fromSEMG signals. This paper proposes a novel time-frequency analysis method based on the Stockwelltransform (S-transform) to improve hand movement recognition accuracy from forearm SEMGsignals. First, the time-frequency analysis method, S-transform, is used for extracting a feature vectorfrom forearm SEMG signals. Second, to reduce the amount of calculations and improve the runningspeed of the classifier, principal component analysis (PCA) is used for dimensionality reduction of thefeature vector. Finally, an artificial neural network (ANN)-based multilayer perceptron (MLP) is usedfor recognizing hand movements. Experimental results show that the proposed feature extractionbased on the S-transform analysis method can improve the class separability and hand movementrecognition accuracy compared with wavelet transform and power spectral density methods.

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