Exam Conduction and Proctoring System Using Face Detection

The Online Examination Portal is a web application for taking an online test productively along with face recognition capabilities to perform live proctoring, and there is no time wasted for checking the paper. This report will incorporate all highlights and procedures which are required to develop this portal. This document incorporates details about the objective of the system, approximately targets of the system, system scope confinement, essential system requirements, group advancement, likely venture risks, schedule of the deployment, and finally observing and reporting mechanisms for the whole system. Online Examination Conducting Portal is exceptionally useful for Instructive Institute's to prepare a complete exam, conduct proctoring to prevent misconduct, secure the time that will take to check the paper, and plan check sheets. Online Examination Portal will help the Institutes to test understudies and develop their abilities. But the impediments for the Online Exam systems, it takes more time when the user prepares the exam at the primary time for utilization. To conduct the exam we require the number of computers with the same number of students. With the successful use of the Examination Portal, the facilitator can utilize this system to create the tests as their requirements and we can get accurate results and save time once deployed.

A musculoskeletal model driven by muscle synergy-derived excitations for hand and wrist movements

Objective. Musculoskeletal model (MM) driven by electromyography (EMG) signals has been identified as a promising approach to predicting human motions in the control of prostheses and robots. However, muscle excitations in MMs are generally derived from the EMG signals of the targeted sensor covering the muscle, inconsistent with the fact that signals of a sensor are from multiple muscles considering signal crosstalk in actual situation. To identify more accurate muscle excitations for MM in the presence of crosstalk, we proposed a novel excitation-extracting method inspired by muscle synergy for simultaneously estimating hand and wrist movements. Approach. Muscle excitations were firstly extracted using a two-step muscle synergy-derived method. Specifically, we calculated subject-specific muscle weighting matrix and corresponding profiles according to contributions of different muscles for movements derived from synergistic motion relation. Then, the improved excitations were used to simultaneously estimate hand and wrist movements through musculoskeletal modeling. Moreover, the offline comparison among the proposed method, traditional MM and regression methods, and an online test of the proposed method were conducted. Main results. The offline experiments demonstrated that the proposed approach outperformed the EMG envelope-driven MM and three regression models with higher R and lower NRMSE. Furthermore, the comparison of excitations of two MMs validated the effectiveness of the proposed approach in extracting muscle excitations in the presence of crosstalk. The online test further indicated the superior performance of the proposed method than the MM driven by EMG envelopes. Significance. The proposed excitation-extracting method identified more accurate neural commands for MMs, providing a promising approach in rehabilitation and robot control to model the transformation from surface EMG to joint kinematics.

Deteksi Kesamaan Teks Jawaban pada Sistem Test Essay Online dengan Pendekatan Neural Network

E-learning is an online learning system that applies information technology in the teaching process. E-learning used to facilitate information delivery, learning materials and online test or assignments. The online test in evaluating students’ abilities can be multiple choice or essay. Online test with essay answers is considered the most appropriate method for assessing the results of complex learning activities. However, there are some challenges in evaluating students essay answers. One of the challenges is how to make sure the answers given by students are not the same as other students answers or 'copy-paste'. This study makes a similarity detection system (Similarity Checking) for students' essay answers that are automatically embedded in the e-learning system to prevent plagiarism between students. In this paper, we use Artificial Neural Network (ANN), Latent Semantic Index (LSI), and Jaccard methods to calculate the percentage of similarity between students’ essays. The essay text is converted into array that represents the frequency of words that have been preprocessed data. In this study, we evaluate the result with mean absolute percentage error (MAPE) approach, where the Jaccard method is the actual value. The experimental results show that the ANN method in detecting text similarity has closer performance to the Jaccard method than the LSI method and this shows that the ANN method has the potential to be developed in further research.

ANALISIS PEMBELAJARAN ALGORITMA PEMROGRAMAN BERBASIS APLIKASI WEB

The programming language at this time has become a language that is desirable.In learning programming languages can be done through formal or informaleducation, such as learning online. Online learning has several advantages,including lower costs, more time efficient and can adjust their learning abilities. Ajarin Code was created to assist online students in learning programminglanguages, especially in learning PHP, HMTL, CSS, and MYSQL. In this applicationwill present the discussion material in accordance with the level of understandingof each participant and at the end of the learning is given an online test usingrandomization methods namely Fisher-Yates algorithm. With this algorithm, eachquestion that appears will be different for each participant and when a participantrepeats the test.AbstrakBahasa pemrograman merupakan Bahasa yang paling popular saat ini .Pembelajaran Bahasa pemrograman dapat di lakukan melalui pendidikan formal maupun informalseperti, Lembaga khusus atau pembelajaran secara online. Pembelajaran secara online memeberikan berbagai keunggulan, diantaranya biaya yang lebih murah juga waktu yang fleksible serta setiap peserta dapat menyesuaikan diri dengan kemampuan dan perkembangan pembelajaran yang dibangun oleh para pembelajar online. Dalam memehami Bahasa pemrograman, Khususnya Bahasa pemrograman website yang meliputi PHP, HMTL, CSS Dan MySQL. Aplikasi ini akan memberikan materi yang sesuai dengan level pemahaman peserta dan pada setiap akhir pembelajaran akan di berikan ujian online dengan metode pengacakan soal dengan menggunakan algoritma Fisher-yates .Dengan algoritma ini, maka urutan soal yang dimunculkan akan selalu berbeda dengan setiap peserta dan ketika seorang peserta akan mengulangi ujian. Peserta yang telah menyelesaikan ujian nantinya akan dapat menempuh materi pada level lebih lanjut.

Research on English Online Test Platform Based on Real-Time Web Communication Technology

Due to the multiattribute and multi-related problems of the target English test platform, the efficiency of the platform is low. In order to solve the problem of insufficient control of the difficulty of the test questions in the process of English test paper generation, this paper designs an English test platform based on real-time network communication technology. The English test platform designed in this paper includes three modules: user management module, question bank management module, and test paper management module. Among them, in the test paper management module, we extract English test questions according to the test paper generation strategy, then use real-time web communication technology according to the test paper generation target, and, through effective update of pheromone, solve the problem of high test question repetition rate in automatic test paper generation and design the network. The self-learning platform and English test platform modules have completed the design of the English test platform based on real-time network communication technology. The experimental results show that the designed English test platform has a high success rate, quick test paper generation time, and good application value.

ONLINE TEST ANXIETY AND EXAM PERFORMANCE OF INTERNATIONAL BACCALAUREATE DIPLOMA PROGRAMME STUDENTS UNDER E-PROCTORED EXAMS AMID COVID-19

Outbreak of COVID-19, online examination, and e-proctoring have caused more exam anxiety and affected exam performance among students’ studying in International Baccalaureate (IB) Diploma Programme (DP). Therefore, the present research aimed to find effect of online test anxiety on academic performance of IBDP students in the subjects related to science, technology, engineering, and mathematics (STEM). Study employed quantitative descriptive survey research design and administered survey questionnaire to 200 IB DP students who took online test during COVID-19 through convenient sampling technique. Sample included both first and final year DP students with due representation to boys and girls. Results of the study revealed a moderate negative correlation between online test anxiety and academic performance of IBDP students in STEM subjects. Regression analysis explained 14.1% variation in the STEM subject performance because of online exam anxiety under e-proctored condition. There exists a statistically significant difference between first and final year students’ online exam anxiety and STEM subject average grades. Future research may focus on conducting comfortable online examination methods with no additional exam anxieties. Keywords: International Baccalaureate (IB), Diploma Programme (DP), e-proctored test, virtual examination

Bayesian optimization of peripheral intraneural stimulation protocols to evoke distal limb movements

Objective. Motor neuroprostheses require the identification of stimulation protocols that effectively produce desired movements. Manual search for these protocols can be very time-consuming and often leads to suboptimal solutions, as several stimulation parameters must be personalized for each subject for a variety of target movements. Here, we present an algorithm that efficiently tunes peripheral intraneural stimulation protocols to elicit functionally relevant distal limb movements. Approach. We developed the algorithm using Bayesian Optimization and defined multi-objective functions based on the coordinated recruitment of multiple muscles. We implemented different multi-output Gaussian Processes to model our system and compared their functioning by applying the algorithm offline to data acquired in rats for walking control and in monkeys for hand grasping control. We then performed a preliminary online test in a monkey to experimentally validate the functionality of our method. Main results. Offline, optimal intraneural stimulation protocols for various target motor functions were rapidly identified in both experimental scenarios. Using the model that performed best, the algorithm converged to stimuli that evoked functionally consistent movements with an average number of actions equal to 20% (13% unique) and 20% (16% unique) of the search space size in rats and monkeys, respectively. Online, the algorithm quickly guided the observations to stimuli that elicited functional hand gestures, although more selective motor outputs could have been achieved by refining the objective function used. Significance. These results demonstrate that Bayesian Optimization can reliably and efficiently automate the tuning of peripheral neurostimulation protocols, establishing a translational framework to configure peripheral motor neuroprostheses in clinical applications. The proposed method can potentially be applied to optimize motor functions using other stimulation modalities.

Who Volunteers? Results from a Regular Cognitive Monitoring Study

Previous research indicates volunteering promotes well-being of individuals and communities. Volunteering in later-life may buffer some of the negative health effects experienced during retirement, facilitating opportunities for older adults to engage in meaningful activities and stay active. The current study examined characteristics of older adults who volunteered outside of participation in a regular cognitive monitoring study. All 124 members (M= 76.87, SD= 7.47; 80 volunteers, 44 non-volunteers) of a regular cognitive monitoring study, requiring completion of a 15-minute cognitive online test once a month, with complete data on personal characteristics, volunteer activities, as well as study adherence and dropout rates were included. ANCOVA and logistic regression analyses adjusted for sociodemographic characteristics were used to assess differences between volunteers and non-volunteers. Results indicated that volunteers were less educated (p<.05), and slightly more likely to be younger and women compared to non-volunteers. There were no differences in cognitive performance (ps>.05). Volunteers had lower scores for neuroticism (p=.02) and were marginally higher agreeable and extraverted (ps<.09). Volunteers needed more reminders to complete the monthly test (ps<.01) but had lower dropout rates (p=.001). The most frequent type of volunteer activity reported was religious. Volunteers were motivated mainly by altruism, although most reported multiple reasons such as building social relationships and feeling important. Findings provide information about characteristics that can help identify older adults who are likely to volunteer. Results regarding study adherence may have implications for promoting recruitment and retention among older adult volunteers.

Diotic and Dichotic Mechanisms of Discrimination Threshold in Musicians and Non-Musicians

The perception of harmonic complexes provides important information for musical and vocal communication. Numerous studies have shown that musical training and expertise are associated with better processing of harmonic complexes, however, it is unclear whether the perceptual improvement associated with musical training is universal to different pitch models. The current study addresses this issue by measuring discrimination thresholds of musicians (n = 20) and non-musicians (n = 18) to diotic (same sound to both ears) and dichotic (different sounds to each ear) sounds of four stimulus types: (1) pure sinusoidal tones, PT; (2) four-harmonic complex tones, CT; (3) iterated rippled noise, IRN; and (4) interaurally correlated broadband noise, called the “Huggins” or “dichotic” pitch, DP. Frequency difference limens (DLF) for each stimulus type were obtained via a three-alternative-forced-choice adaptive task requiring selection of the interval with the highest pitch, yielding the smallest perceptible fundamental frequency (F0) distance (in Hz) between two sounds. Music skill was measured by an online test of musical pitch, melody and timing maintained by the International Laboratory for Brain Music and Sound Research. Musicianship, length of music experience and self-evaluation of musical skill were assessed by questionnaire. Results showed musicians had smaller DLFs in all four conditions with the largest group difference in the dichotic condition. DLF thresholds were related to both subjective and objective musical ability. In addition, subjective self-report of musical ability was shown to be a significant variable in group classification. Taken together, the results suggest that music-related plasticity benefits multiple mechanisms of pitch encoding and that self-evaluation of musicality can be reliably associated with objective measures of perception.