Sign Language Recognition System

We witness many people who face disabilities like being deaf, dumb, blind etc. They face a lot of challenges and difficulties trying to interact and communicate with others. This paper presents a new technique by providing a virtual solution without making use of any sensors. Histogram Oriented Gradient (HOG) along with Artificial Neural Network (ANN) have been implemented. The user makes use of web camera, which takes input from the user and processes the image of different gestures. The algorithm recognizes the image and identifies the pending voice input. This paper explains two way means of communication between impaired and normal people which implies that the proposed ideology can convert sign language to text and voice.

Sign Language Recognition System

We witness many people who face disabilities like being deaf, dumb, blind etc. They face a lot of challenges and difficulties trying to interact and communicate with others. This paper presents a new technique by providing a virtual solution without making use of any sensors. Histogram Oriented Gradient (HOG) along with Artificial Neural Network (ANN) have been implemented. The user makes use of web camera, which takes input from the user and processes the image of different gestures. The algorithm recognizes the image and identifies the pending voice input. This paper explains two way means of communication between impaired and normal people which implies that the proposed ideology can convert sign language to text and voice.

Home Automation and Security System Using Internet of Things

The internet of things (IoT) is viewed as something that connects everyday objects like smart TV and smart phones. Automation is the future of human civilization. It's like operating various devices and machinery with minimum or no human intervention. In this chapter, home appliances and other electronic devices are proposed to be controlled over internet with the help of website or smartphone. Speech recognition technology has been implemented in this chapter which will help complete or partially visually impaired people or persons with physical disability. Smart CCTV concept has been developed in this chapter which will allow to operate the web camera whenever it detects motion and sleep at other times which will save energy as well as storage unlike current CCTV scenario. Also, smart CCTV captures images and video footage and provides the real-time status of the place via a registered email address, website, and mobile app. If you are outside, you can check the status of your home and be in line with it, and you will activate the home appliances from the web site and through speech.

Personal Assistant Robot

Since the boom in science and technology, humans have been trying to invent machines that could reduce their efforts in day to day activities. In this paper, we develop a personal assistant robot that could pick up objects and return it to the user. The robot is controlled using an android application in mobile phones. The robot can listen to user’s command and then respond in the best way possible. The user can command the robot to move to given location, capture images and pick objects. The robot is equipped with ultrasonic sensor and web camera that helps it to move to different location effectively. It is also equipped with sleds that play important role in object picking process. The robot uses a tiny YOLOv3 model which is rigorously trained on several images of the object. There are some possible improvements that can be achieved which could help this robot to be used in several other fields as well.

A novel hybrid face recognition framework based on a low-resolution camera for biometric applications

In research work, human face recognition is an essential biometric symbol persistently continued so far due to its different levels of applications in society. Since the appearance of the human faces can have many variations due to issues like the effect of illumination, expression and face pose. These differences are correlated with one another, which results in a helpless ability to recognize a particular person's face. The motivation behind our work in this paper is to give a new framework for face recognition based on frequency analysis that contributes to solving the distinguishing proof issues with enormous varieties of boundaries like the effect of illumination, expression, and face pose. Here three algorithms combined for provable results: i) Difference of Gaussian filtered discrete wavelet transform (DDWT) for feature extraction; ii) Log Gabor (LG) filter for feature extraction; and iv) Multiclass support vector machine classifier, where feature coefficients of DDWT and LG filter are fused for classification and parameters evaluation. The evaluation of our experiment is carried out on a large database consisting of 15 persons of each 200-face image which are captured using a 5-megapixel low-resolution web camera and yielding satisfactory results on various parameters compared to existing methods.

Refractor telescope design using web camera

The purpose of this study was to develop a refractor telescope using a web camera as learning media. It was the Research and Development (R&D) study which referred to the model modified by Sugiyono. The product was evaluated by a media expert and undergraduate students of Sub-Department of Physics Education, Tadulako University using questionnaires with a 4-point Likert scale. The product quality data obtained were analyzed using descriptive analysis. The quality of the product based on the analysis of the media expert’s assessment was good with the average score of 2.92. Meanwhile, the results of student responses to the limited trial obtained a score of 3.20 which indicated the agreement of usability. The test results and questionnaire analysis showed that the refractor telescope using the developed Web Camera (WebCam) is feasible to be used as learning media.

Controlled experiment of underwater vision-based mapping: A preliminary evaluation

Underwater vision-based mapping (VbM) constructs three-dimensional (3D) map and robot position simultaneously out of a quasi-continuous structure from motion (SfM) method. It is the so-called simultaneous localization and mapping (SLAM), which might be beneficial for mapping of shallow seabed features as it is free from unnecessary parasitic returns which is found in sonar survey. This paper presents a discussion resulted from a small-scale testing of 3D underwater positioning task. We analyse the setting and performance of a standard web-camera, used for such a task, while fully submerged underwater. SLAM estimates the robot (i.e. camera) position from the constructed 3D map by reprojecting the detected features (points) to the camera scene. A marker-based camera calibration is used to eliminate refractions effect due to light propagation in water column. To analyse the positioning accuracy, a fiducial marker-based system –with millimetres accuracy of reprojection error– is used as a trajectory’s true value (ground truth). Controlled experiment with a standard web-camera running with 30 fps (frame per-second) shows that such a system is capable to robustly performing underwater navigation task. Sub-metre accuracy is achieved utilizing at least 1 pose (1 Hz) every second.

ENHANCING THE MOTIVATION AND LEARNING PERFORMANCE IN AN ONLINE CLASSROOM WITH THE USE OF NEUROMARKETING

In recent years, the newly emerging discipline of neuromarketing, which employs brain (emotions and behaviour) research in an organisational context, has grown in prominence in academic and practice literature. With the increasing growth of online teaching, COVID-19 left no option for higher education institutions to go online. As a result, students who attend an online course are more prone to lose focus and attention, resulting in poor academic performance. Therefore, the primary purpose of this study is to observe the learner's behaviour while making use of an online learning platform. This study presents neuromarketing to enhance students' learning performance and motivation in an online classroom. Using a web camera, we used facial coding and eye-tracking techniques to study students' attention, motivation, and interest in an online classroom. In collaboration with Oxford Business College's marketing team, the Institute for Neuromarketing distributed video links via email, a student representative from Oxford Business College, the WhatsApp group, and a newsletter developed explicitly for that purpose to 297 students over the course of five days. To ensure the research was both realistic and feasible, the instructors in the videos were different, and students were randomly allocated to one video link lasting 90 seconds (n=142) and a second one lasting 10 minutes (n=155). An online platform for self-service called Tobii Sticky was used to measure facial coding and eye-tracking. During the 90-second online lecture, participants' gaze behaviour was tracked overtime to gather data on their attention distribution, and emotions were evaluated using facial coding. In contrast, the 10-minute film looked at emotional involvement. The findings show that students lose their listening focus when no supporting visual material or virtual board is used, even during a brief presentation. Furthermore, when they are exposed to a single shareable piece of content for longer than 5.24 minutes, their motivation and mood decline; however, when new shareable material or a class activity is introduced, their motivation and mood rise. JEL: I20; I21 <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0805/a.php" alt="Hit counter" /></p>

The new normal of web camera theft on campus during COVID-19 and the impact of anti-theft signage

Objective The opportunity for web camera theft increased globally as institutions of higher education transitioned to remote learning during COVID-19. Given the thousands of cameras currently installed in classrooms, many with little protection, the present study tests the effectiveness of anti-theft signage for preventing camera theft. Methods Examined web camera theft at a southern, public university located in the United States of America by randomly assigning N = 104 classrooms to receive either anti-theft signage or no signage. Camera theft was analyzed using Blaker’s exact test. Results Classrooms not receiving anti-theft signage (control) were 3.42 times more likely to exhibit web camera theft than classrooms receiving anti-theft signage (medium effect size). Conclusions Using classrooms as the unit of analysis presents new opportunities for not only future crime prevention experiments, but also improving campus safety and security. Also, preventing web camera theft on campus is both fiscally and socially responsible, saving money and ensuring inclusivity for remote learners.

Changes in kinesiostabilogram parameters and movement speed of stroke patients while increasing their physical activity due to the use of biofeedback method

Balance disorders are complications of stroke survivors. Aim of this study was the establish effectiveness of the biofeedback approach. In this intervention study 245 patients with early diagnosis of acute disturbance of cerebral circulation (ADCC) were examined. Patients able to move independently were treated by standard conservative ADCC therapy on an outpatient approach, but they continued to have problems with coordination of movement in upright position. Then they were submitted to an increasing physical activity based on five sessions of biofeedback, i.e., a complex rehabilitation of patients with motor pathology "Trust-M" according to TU 9442-001-63704475-2010. Mobility rates were assessed using a web camera. Patients' quality of life was evaluated by SF-36 questionnaire and the Hospital Anxiety and Depression Scale (HADS). All parameters were recorded before and after 5 sessions of biofeedback. After treatment, the stability indicators improved and all patients showed a significant increase in motion rate and quality of life. At the same time, the severity of pain and of depression and anxiety decreased. Negative correlations of average strength between the quadrant and patient HADS scaling rates were obtained. In conclusion, our work shows effectiveness of the biofeedback technique for correcting coordination in stroke survivors.