Computer Assistance Research Articles

Prognostic Value of Transthoracic Echocardiography in Children With Pulmonary Arterial Hypertension.

Background Transthoracic echocardiography is part of the regular follow-up protocol at most pediatric pulmonary arterial hypertension (PAH) centers. We aimed to develop a comprehensive and simple echocardiographic risk stratification for children with PAH. Methods and Results We included 63 children with PAH and a biventricular cardiac anatomy without relevant shunt lesions (60% female patients; mean age, 9.0years; 42 idiopathic PAH and 21 associated PAH) undergoing a standardized transthoracic echocardiographic assessment. The prognostic value of echocardiographic parameters was assessed using Cox proportional hazards survival analysis and recursive partitioning for classification tree methods. Over a median follow-up period of 4.0years, 17 patients died and 4 underwent lung transplantation. Various echocardiographic parameters were associated with the combined endpoint of death and transplantation on univariate analysis. On further analysis, right atrial area (z score) and left ventricular diastolic eccentricity index (LVEId) emerged as robust and independent predictors of transplant-free survival. Considering mortality alone as an end point, a combination of right atrial area, left ventricular diastolic eccentricity index, and tricuspid annular plane systolic excursion were identified as independent predictors of outcome. Based on these parameters, we propose simple risk scores that can be applied at the bedside without computer assistance. CONCLUSIONS Echocardiographic parameters predict prognosis in children with pulmonary hypertension. A combination of widely available parameters including right atrial area, left ventricular eccentricity index, and tricuspid annular plane systolic excursion emerged as risk stratifiers that await external validation but may assist clinicians determining the prognosis of children with PAH.

Mentoring Teachers during Covid-19: A Collaborative Organizational Approach

Mentoring is an essential part of teacher development. It is generally acknowledged that a master talent in mentoring is the ability to make resources available to a novice protégé to help them educate successfully. This study illustrates how mentorship technique aided in boosting teacher motivation for online instruction during COVID-19. According to the research, learning is successful when there are close relationships between mentors and mentees, opportunities for growth, and a supportive atmosphere. The investigation took place in a Nepalese school in Kathmandu. Ten English Language (EL) instructors from Nursery - 10 participated in the study. They were mentored by the head of the English Department and a computer assistant for two months. The Technological Pedagogical and Content Knowledge (TPACK) model of mentoring was used, which stood on connectivism philosophy. The study employed a narrative methodology. Semi-structured interview and thematic analysis techniques were used to produce and analyse data. Standing on their stories, the teachers were familiarized with the concept of Web-Enhanced Language Learning (WELL), Mobile-Assisted Language Learning (MALL), and Computer-Assisted Language Learning (CALL). Finally, teachers produced technology enhanced lesson plans fusing the content with technology for the new pedagogy. To assess the results of mentoring during the pre-phase, while-phase, and post-phase, in-depth interviews were carried out. The findings highlight the difficulties mentees faced: a lack of confidence or a sense of inferiority in online teaching environment, as well as how self-sufficiency was restored after mentoring. According to the study, effective mentorship can still take place in challenging educational circumstances.

Classification and Segmentation of Diabetic Retinopathy: A Systemic Review

Diabetic retinopathy (DR) is a major reason of blindness around the world. The ophthalmologist manually analyzes the morphological alterations in veins of retina, and lesions in fundus images that is a time-taking, costly, and challenging procedure. It can be made easier with the assistance of computer aided diagnostic system (CADs) that are utilized for the diagnosis of DR lesions. Artificial intelligence (AI) based machine/deep learning methods performs vital role to increase the performance of the detection process, especially in the context of analyzing medical fundus images. In this paper, several current approaches of preprocessing, segmentation, feature extraction/selection, and classification are discussed for the detection of DR lesions. This survey paper also includes a detailed description of DR datasets that are accessible by the researcher for the identification of DR lesions. The existing methods limitations and challenges are also addressed, which will assist invoice researchers to start their work in this domain.

Ability 50 Meters Sprint In Terms Of The Performance Of Leg Length And Weight Of SDS Bakau Estate Students

This study aims to determine the performance of leg length and body weight in the ability to sprint 50 meters of SDS Bakau Estate students. This research is a quantitative descriptive study with two independent variables, namely leg length and body weight with one dependent variable sprint of 50 meters. The number of samples in this study is limited to 30 students from SDS Bakau Estate. The technique for determining the sample was by using purposive sampling, taking based on certain objectives as many as 30 students from SDS Mangrove Estate. Data analysis techniques were processed using computer assistance through the SPSS 22.0 program. Based on the data analysis, the results obtained: (1) There is a leg length performance with a 50-meter sprint ability of SDS Bakau Estate students, as evidenced by the value of r arithmetic ( ro ) = 0.382 (0.037 <0.05), (2) There is a weight performance with a 50 sprint ability meters at SDS Bakau Estate students, as evidenced by the value of r arithmetic ( ro ) = 0.409 (0.025<0.05), and (3) there is a performance of leg length and body weight on the 50-meter sprint ability of SDS Bakau Estate, as evidenced by the calculated R-value obtained R = 0.533, R2 value = 0.285 or 36.6% and calculated F value = 5.368 (0.011<0.05).

Communication Technology and Teacher-Student Relationship in the Tertiary ESL Classroom During the Pandemic: A Case Study.

The study aims to present the potential benefits and challenges of incorporating communication technology (CT), namely synchronous computer-mediated communication (SCMC) (e.g., Zoom Video Communications), computer-mediated communication (CMC) (e.g., WhatsApp), and social networking sites (SNS) (e.g., Instagram) into the tertiary classroom based on the honest account of four English as a Second Language (ESL) teachers during the pandemic. The authors intend to explore the efficacy of SCMC in lowering language anxiety and in fostering closer teacher-student relationship as suggested by the previous literature (Abraham in Comput Assist Lang Learn 21:199-226, 2008; Aristika and Juandi in Emerg Sci J 5:443-456, 2021; Darhower in Synchronous computer-mediated communication in the intermediate foreign language class: a sociocultural case study, University of Pittsburgh, 2000; Hagenauer and Volet in Oxf Rev Educ 40:370-388, 2014). Qualitative data collected from the authors' teaching reflections over a 13-week period were analyzed from a third-person perspective. The above collaborative autoethnography (CAE) approach was adopted in face of the then difficulties in data collection given factors such as social-distancing during the pandemic. The authors selected and agreed on the key observations, feelings, and anecdotes worth-examining in their first-time online teaching experience at informal group interviews facilitated by SCMC. It was identified by the authors that learners' text-based production in the target language increased possibly due to the novelty of online learning platforms, lower affective variables, and a closer teacher-student relationship fostered by teachers' increased self-disclosure and the reduced formality in communication technology. Despite the above potential benefits of CT in ESL, challenges, such as an increasingly blurred teacher-student professional distance, students' increased code-mixed production in their L1 and L2, and the resultant 'teacher burnout' due to the obscured concept of standard office hours, were observed. The incorporation of CT into English Language Teaching (ELT) is desirable for its potential benefits in the affective domain of both teachers and students. However, it is recommended that teachers should establish guidelines in the use of CMC and SNSs both inside and outside class to avoid boundary and privacy issues as well as deviation from the initial lesson objectives.

Augmented Reality Navigation Can Achieve Accurate Coronal Component Alignment During Total Knee Arthroplasty.

Background Computer-navigated knee arthroplasty has been shown to improve accuracy over conventional instruments. The next generation of computer assistance is being developed using augmented reality. The accuracy of augmented reality navigation has not been established. Methods From April 2021 to October 2021, a prospective, consecutive series of 20 patients underwent total knee arthroplasty utilising an augmented reality-assisted navigation system (ARAN). The coronal and sagittal alignment of the femoral and tibial bone cuts was measured using the ARAN and the final position of the components was measured on postoperative CT scans. The absolute difference between the measurements was recorded to determine the accuracy of the ARAN. Results Two cases were excluded due to segmentation errors, leaving 18 cases for analysis. The ARAN produced a mean absolute error of 1.4°, 2.0°, 1.1°and 1.6° for the femoral coronal, femoral sagittal, tibial coronal and tibial sagittal alignments, respectively. No outliers (absolute error of >3°) were identified in femoral coronal or tibial coronal alignment measurements. Three outliers were identified in tibial sagittal alignment, with all cases demonstrating less tibial slope (by 3.1°, 3.3° and 4°). Five outliers were identified in femoral sagittal alignment and in all cases, the component was more extended (3.1°, 3.2°, 3.2°, 3.4° and 3.9°). The mean operative time significantly decreased from the first nine augmented reality cases to the final nine cases by 11 minutes (p<0.05). There was no difference in the accuracy between the early and late ARAN cases. Conclusion Augmented reality navigation can achieve accurate alignment of total knee arthroplasty with a low rate of component malposition in the coronal plane. Acceptable and consistent accuracy can be achieved from the initial adoption of this technique, however, some sagittal outliers were identified and there is a clear learning curve with respect to operating time. The level of evidence was IV.

Classification of Covid-19 Diseases Through Lung CT-Scan Image Using the ResNet-50 Architecture

Covid-19 is a respiratory tract disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The Covid-19 disease was first reported in Wuhan, China, in December 2019. The SARS-CoV-2 virus is primarily transmitted through human contact, and the World Health Organization has proclaimed a global pandemic (WHO). Symptoms of Covid-19 can range from asymptomatic to mild and severe. One way to diagnose Covid-19 disease can be done by examining lung abnormalities on the results of a Computed Tomography Scan (CT-Scan) of the lungs. However, determining the diagnostic results requires high accuracy and a long time. For this reason, an automated system is needed to make it easier for medical personnel to diagnose Covid-19 disease quickly and accurately. One of the automated systems with computer assistance in detecting abnormalities in CT-Scan images of the lungs is to perform pattern recognition

The integration of computer and human assistance for 3D augmented reality robotic surgery

The integration of computer and human assistance for 3D augmented reality robotic surgery

Parent-Child Secure Attachment Relationship with Academic Self-Regulation in Grade 10 Students of Vocational High Schools in Sidoarjo

Adolescence is referred to as the period of self-discovery, where they begin to be sensitive to the environment around them. What happens in his environment and what is done by those around him greatly affects the formation of his personality. Researchers obtained data from BK teachers that there was an Academic Self-Regulation problem in students. The purpose of this study was to find out the relationship between Parent-child Secure Attachment and Academic Self-Regulation in X-grade students at SMK Negeri 1 Jabon. The study used quantitative approaches to correlation methods. The subjects in this study were students of class X smk Negeri 1 Jabon taken with nonprobability sampling techniques. The population of the study was grade X students and sample-setters from the research population used Isaac and Michael's table with a 5% error rate, bringing the total to 131 students. Data collection techniques use the psychology scale, namely the Parent-Child Secure Attachment scale and the Academic Self-Regulation scale. Data analysis technique uses the correlation of pearson product moment using computer assistance, using the SPSS 23 for windows program. Based on the results of the data analysis showed that there was a significant positive relationship in Secure Attachment Parent-child and Academic Self-Regulation in SMK Negeri 1 Jabon. Based on the results of the correlation test known significance value of 0.000 because the value sig &lt;0.05 then there is a relationship between variable X and Y and strengthened by the results of the analysis that the influence of variable X contributes effectively 50.2% to variable Y. The results show that the higher secure attachment of parents-children then the higher the academic self-regulation of students and vice versa if secure attachment parents-children are low then the student's Academy Self Regulation also low.

Pengaruh Profitabilitas Dan Leverage Terhadap Nilai Perusahaan Dengan Kinerja Keuangan Sebagai Variabel Intervening dimasa Pandemi

The purpose of this study was to determine how big the influence of profitability and leverage on firm value with financial performance as an intervening variable during the pandemic in the Property &amp; Real Estate Industry Sector Period (2016-2020). in property &amp; real estate companies listed on the Indonesian stock exchange in 2016-2020 a total of 65 companies. While the sample of this study consisted of 38 companies included in property &amp; real estate companies and were selected by purposive sampling. The analytical method used is multiple linear regression data analysis, using computer assistance with SPSS 21 software program. There is no significant effect between profitability and financial performance variables on firm value. And there is a significant influence between the leverage variables on firm value. There is a significant influence between profitability variables on firm value through financial performance as an intervening variable. And there is no significant effect between leverage variables on firm value through financial performance as an intervening variable

Pengaruh Profitabilitas Dan Leverage Terhadap Nilai Perusahaan Dengan Kinerja Keuangan Sebagai Variabel Intervening dimasa Pandemi

The purpose of this study was to determine how big the influence of profitability and leverage on firm value with financial performance as an intervening variable during the pandemic in the Property &amp; Real Estate Industry Sector Period (2016-2020). in property &amp; real estate companies listed on the Indonesian stock exchange in 2016-2020 a total of 65 companies. While the sample of this study consisted of 38 companies included in property &amp; real estate companies and were selected by purposive sampling. The analytical method used is multiple linear regression data analysis, using computer assistance with SPSS 21 software program. There is no significant effect between profitability and financial performance variables on firm value. And there is a significant influence between the leverage variables on firm value. There is a significant influence between profitability variables on firm value through financial performance as an intervening variable. And there is no significant effect between leverage variables on firm value through financial performance as an intervening variable

Digital TKA Alignment Training with a New Digital Simulation Tool (Knee-CAT) Improves Process Quality, Efficiency, and Confidence

Individual alignment techniques have been introduced to restore patients' unique anatomical variations during total knee arthroplasty. The transition from conventional mechanical alignment to individualised approaches, with the assistance of computer and/or robotic technologies, is challenging. The objective of this study was to develop a digital training platform with real patient data to educate and simulate various modern alignment philosophies. The aim was to evaluate the training effect of the tool by measuring the process quality and efficiency, as well as the post-training surgeon's confidence with new alignment philosophies. Based on 1000 data sets, a web-based interactive TKA computer navigation simulator (Knee-CAT) was developed. Quantitative decisions on bone cuts were linked to the extension and flexion gap values. Eleven different alignment workflows were introduced. A fully automatic evaluation system for each workflow, with a comparison function for all workflows, was implemented to increase the learning effect. The results of 40 surgeons with different experience levels using the platform were assessed. Initial data were analysed regarding process quality and efficiency and compared after two training courses. Process quality measured by the percentage of correct decisions was increased by the two training courses from 45% to 87.5%. The main reasons for failure were wrong decisions on the joint line, tibia slope, femoral rotation, and gap balancing. Efficiency was obtained with a reduction in time spent per exercise from 4 min 28 s to 2 min 35 s (42%) after the training courses. All volunteers rated the training tool as helpful or extremely helpful for learning new alignment philosophies. Separating the learning experience from OR performance was mentioned as one of the main advantages. A novel digital simulation tool for the case-based learning of various alignment philosophies in TKA surgery was developed and introduced. The simulation tool, together with the training courses, improved surgeon confidence and their ability to learn new alignment techniques in a stress-free out-of-theatre environment and to become more time efficient in making correct alignment decisions.

A New Bound for Hadwiger’s Covering Problem in \(\boldsymbol{\mathbb{E}}^3\)

We show that every three-dimensional convex body can be covered by 14 smaller homothetic copies. The previous result was 16 established by Papadoperakis in 1999, while a conjecture by Hadwiger is 8. We develop a discretization technique showing that it suffices to verify the feasibility of a number of linear programs with rational coefficients, which is done with computer assistance using exact arithmetic.

Robotics and computer-assisted procedures in cranial neurosurgery

The medical technical innovations over the last decade have made operations in the highly sensitive regions of the brain much safer. Presentation of how far computer assistance and robotics have become incorporated into clinical neurosurgery. Evaluation of the scientific literature and analysis of the certification status of the corresponding medical devices. The rapid development of computer technology and the switch to digital imaging has led to the widespread introduction of neurosurgical planning software and intraoperative neuronavigation. In the field of robotics, the penetration into clinical neurosurgery is currently still largely limited to the automatic setting of trajectories. The digitalization of imaging has fundamentally transformed neurosurgery. In the field of cranial neurosurgery, computer-assisted procedures can now be distinguished from noncomputer-assisted procedures only in ahandful of cases. In the coming years important innovations for the clinical implementation can be expected in the field of robotics.

MPCNet: Improved MeshSegNet Based on Position Encoding and Channel Attention

In the process of orthodontic treatment, it is a very important step to accurately segment each tooth and jaw model with computer assistance. The use of deep learning technology methods for tooth segmentation can not only save a lot of manual interaction and time cost but also improve the treatment effect. 3D tooth segmentation is a hot topic of interest for international related scholars, and some end-to-end tooth segmentation methods based on dental mesh scanning models have been emerging in recent years. Due to the limited variety of existing models, they are not well suited for different 3D segmentation scenarios, and the feature extraction capability and segmentation effect of these models still need to be improved. In this paper, we propose a novel end-to-end tooth segmentation method, MPCNet, which adds multi-scale mesh density information to the input layer, uses position encoding and channel attention mechanism to improve MeshSegNet, and uses graph-cut post-processing to perform 3D tooth segmentation in real scenes. The effectiveness of MPCNet is evaluated on a real 3D scanned tooth segmentation dataset, which significantly outperforms the current mainstream segmentation methods.

A SARS-CoV-2 neutralizing antibody discovery by single cell sequencing and molecular modeling.

Although vaccines have been developed, mutations of SARS-CoV-2, especially the dominant B.1.617.2 (delta) and B.1.529 (omicron) strains with more than 30 mutations on their spike protein, have caused a significant decline in prophylaxis, calling for the need for drug improvement. Antibodies are drugs preferentially used in infectious diseases and are easy to get from immunized organisms. The current study combined molecular modeling and single memory B cell sequencing to assess candidate sequences before experiments, providing a strategy for the fabrication of SARS-CoV-2 neutralizing antibodies. A total of 128 sequences were obtained after sequencing 196 memory B cells, and 42 sequences were left after merging extremely similar ones and discarding incomplete ones, followed by homology modeling of the antibody variable region. Thirteen candidate sequences were expressed, of which three were tested positive for receptor binding domain recognition but only one was confirmed as having broad neutralization against several SARS-CoV-2 variants. The current study successfully obtained a SARS-CoV-2 antibody with broad neutralizing abilities and provided a strategy for antibody development in emerging infectious diseases using single memory B cell BCR sequencing and computer assistance in antibody fabrication.

Hipermediji u nastavi Prirode i društva

Hyper medias make multi medial systems allowing non-linear connection i.e. texts exposure. It is the way users can combine, edit and process logically sounds, graphics, movable pictures and a computer software. It designates multi media's characteristics of a hypertext and union of three industries: TV, computer and publishing one. Hyper media are non-linear presentation of symbols (text, graphics, pictures, software code) with computer assistance. The contents of the subjects World around Us and Nature and Society, regarding their nature and character, require a need for different ways of introducing and preparing of pupils for new learning material processing, since they are complex, interdisciplinary and they belong to different areas of a curriculum. Besides finished multi media games that can be used, it is often very appropriate to create similar games in PowerPoint Program and enrich them with the contents, like films, cartoons, education series, news and audiovisual songs on the terms being studied within teaching of the subject Nature and Society (animals, plants, traffic and similar).

Domain generalization improves end-to-end object detection for real-time surgical tool detection.

Computer assistance for endoscopic surgery depends on knowledge about the contents in an endoscopic scene. An important step of analysing the video contents is real-time surgical tool detection. Most methods for tool detection nevertheless depend on multi-step algorithms building upon prior knowledge like anchor boxes or non-maximum suppression which ultimately decrease performance. A real-world difficulty encountered by learning-based methods are limited datasets. Training a neural network on data matching a specific distribution (e.g. from a single hospital or showing a specific type of surgery) can result in a lack of generalization. In this paper, we propose the application of a transformer based architecture for end-to-end tool detection. This architecture promises state-of-the-art accuracy while decreasing the complexity resulting in improved run-time performance. To improve the lack of cross-domain generalization due to limited datasets, we enhance the architecture with a latent feature space via variational encoding to capture common intra-domain information. This feature space models the linear dependencies between domains by constraining their rank. The trained neural networks show a distinct improvement on out-of-domain data indicating better generalization to unseen domains. Inference with the end-to-end architecture can be performed at up to 138 frames per second (FPS) achieving a speedup in comparison to older approaches. Experimental results on three representative datasets demonstrate the performance of the method. We also show that our approach leads to better domain generalization.

Technology as a Method of Teaching and Learning Foreign Languages

Technology is by far an inseparable tool to foreign language learning. Computer assistance language learning, (CALL) presented in the sixties was only the beginning of a new era in foreign language learning, to be ensued by information and communication technology (ICT) in the form of e-learning and the Internet in the recent decades. This paper aims at investigating how commonly is technology used in the foreign language classes in Albanian education system and what English language teachers (ELT) state about digitalisation effect in the learning environment and the students` performance according to personal experience. By using “ Eight Questions to Ask Yourself”, (Hockly N., 2011b) questionnaire adopted into test mode, comprising eight items to respond in a Likert scale, coded from 1-6, it resulted that the vast majority of ELT (91-95%) state that digitalization is time and effort effective and it facilitates the lesson presentation and is a crucial tool to enhance the foreign language environment. 42 % of ELT have a range of tools and repertoire of techniques to draw on and only 33 % design effective task types for the tool. They rely on internet application as a resource in foreign language classes. However they consider that technology is both stimulating and distracting to students, who are reportedly digital natives.

Improved Differential and Linear Trail Bounds for ASCON

Ascon is a family of cryptographic primitives for authenticated encryption and hashing introduced in 2015. It is selected as one of the ten finalists in the NIST Lightweight Cryptography competition. Since its introduction, Ascon has been extensively cryptanalyzed, and the results of these analyses can indicate the good resistance of this family of cryptographic primitives against known attacks, like differential and linear cryptanalysis.Proving upper bounds for the differential probability of differential trails and for the squared correlation of linear trails is a standard requirement to evaluate the security of cryptographic primitives. It can be done analytically for some primitives like AES. For other primitives, computer assistance is required to prove strong upper bounds for differential and linear trails. Computer-aided tools can be classified into two categories: tools based on general-purpose solvers and dedicated tools. General-purpose solvers such as SAT and MILP are widely used to prove these bounds, however they seem to have lower capabilities and thus yield less powerful bounds compared to dedicated tools.In this work, we present a dedicated tool for trail search in Ascon. We arrange 2-round trails in a tree and traverse this tree in an efficient way using a number of new techniques we introduce. Then we extend these trails to more rounds, where we also use the tree traversal technique to do it efficiently. This allows us to scan much larger spaces of trails faster than the previous methods using general-purpose solvers. As a result, we prove tight bounds for 3-rounds linear trails, and for both differential and linear trails, we improve the existing upper bounds for other number of rounds. In particular, for the first time, we prove bounds beyond 2−128 for 6 rounds and beyond 2−256 for 12 rounds of both differential and linear trails.