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Freedom of design and the cost-effective production of structural parts have led to much research interest in Wire Arc Additive Manufacturing (WAAM). Nevertheless, WAAM is subject to design constraints and fundamentally differs from other additive manufacturing processes. Consequently, design guidelines and supporting design evaluation tools adapted to WAAM are needed. One geometric approach to design evaluation is the use of a three-dimensional medial axis transformation (3D-MAT) to derive local geometry indicators. Previous works define the thickness and radius indicators. In this work, the angle between opposing faces and a mass gradient indicator are added. To apply the literature design rules regarding wall thickness, clearance, bead angle, and edge radius to specific geometry regions, features are classified by the indicators. Following a literature suggestion, wall and corner regions are differentiated by the angle indicator. An angle of 65° is identified as an effective separation limit. Additionally, the analogy of Heuvers’ spheres to the MAT helps estimate a limit of kH−1kH+1 for the mass gradient (kH: Heuvers’ factor). Finally, tests on example parts demonstrate the method’s effectiveness in verifying compliance to the specified rules. With a numerical complexity of O(n2), this method is more efficient than finite element analyses, providing early feedback in the design process.

The current education landscape is marked by the growing integration of artificial intelligence technologies, which seek to improve interaction and efficiency in educational environments. However, many of these tools operate on separate platforms, complicating their use and reducing their potential effectiveness. This study introduces InteractiveClass, an innovative tool that fully integrates with Microsoft Teams, facilitating automated assessment and student interaction without requiring multiple interfaces. InteractiveClass encourages active student participation through real-time questions, quizzes, discussion forums, and other activities. In addition, it uses AI capabilities to offer immediate and personalized feedback and perform automatic evaluations. This integration improves usability and promotes student engagement in hybrid or fully online environments. Study results reveal significant improvements in assessment efficiency and student satisfaction. Students who used the tool showed a 30% increase in class participation and improved their grades by 25% compared to those who did not use it. Additionally, the tool demonstrated high consistency in assessments, with a precision of 95% compared to manual assessments. These findings underline the potential of InteractiveClass to transform education through AI technology, offering a practical and effective solution to the challenges of modern education.

In the field of Cooperative Intelligent Transport Systems (C-ITSs), the traditional approach to testing often emphasizes technological parameters, leaving the validation of message content insufficiently addressed. Since the content of these messages is crucial for the correct functioning of C-ITS, this article demonstrates the potential for automated evaluation of C-ITS message content against relevant standards. It leverages our novel tools, Karlos and C-ITS SIM, to facilitate this process. Through detailed laboratory testing and data analysis, the study showcases the effectiveness of these automated solutions in enhancing the accuracy and reliability of message content validation.

Architectural spatial layout configurations are the result of a complex design process aiming at managing the most advantageous location of all spaces with certain objectives and constraints. In the presence of broadening the scope of understanding spatial phenomenon, its role, and its composition in scope of various programmatic, ideological, formal, and engineering aspects, embedded in a complex theoretical background. The aspect of evaluation is the least apparent and there are significant limitations to what can be achieved there. This paper is aiming at evaluating functionality (such as quality of space, use, Access, adjacency, non-adjacency, proximity etc.), build quality (such as performance, efficiency, cost, etc.), impact (such as user performance, internal quality, urban, social, and cultural integration, etc.), indication of the quality of the architectural space design and the quality of the layout configuration. To achieve this research goal, we devised all possible spatial relation, affecting these qualities, as inputs for a given architectural space using descriptive rule blocks. We define this fuzzy logic system for residential spaces that's been blended into a layout to evaluate the layout configuration. We define all input variables, output variables, and fuzzy sets, and present space-space relations using membership functions. The paper proposes a framework based on fuzzy logic approach for automated evaluation of architectural spatial layout configurations.

The design of efficient representations is well established as a fruitful way to explore and analyze complex or large data. In these representations, data are encoded with various visual attributes depending on the needs of the representation itself. To make coherent design choices about visual attributes, the visual search field proposes guidelines based on the human brain’s perception of features. However, information visualization representations frequently need to depict more data than the amount these guidelines have been validated on. Since, the information visualization community has extended these guidelines to a wider parameter space.This paper contributes to this theme by extending visual search theories to an information visualization context. We consider a visual search task where subjects are asked to find an unknown outlier in a grid of randomly laid out distractors. Stimuli are defined by color and shape features for the purpose of visually encoding categorical data. The experimental protocol is made of a parameters space reduction step (i.e., sub-sampling) based on a machine learning model, and a user evaluation to validate hypotheses and measure capacity limits. The results show that the major difficulty factor is the number of visual attributes that are used to encode the outlier. When redundantly encoded, the display heterogeneity has no effect on the task. When encoded with one attribute, the difficulty depends on that attribute heterogeneity until its capacity limit (7 for color, 5 for shape) is reached. Finally, when encoded with two attributes simultaneously, performances drop drastically even with minor heterogeneity.

The use of online tools is a common practice for evaluating the accessibility of a website, identifying problems, and providing useful feedback on how to fix detected issues. For ease of accessibility validation, many tools have been developed and implemented successfully over the years. Yet, the results of these tools show differences in terms of coverage, correctness, and reporting-related issues. In this study, we compared online accessibility evaluation tools to understand to what extent they differ in detecting accessibility problems in websites. A total of 41 government websites of different countries were tested for violations of accessibility guidelines using six evaluation tools. We observed that each tool generated different evaluation data for the same websites. As some of the tools are complementary to each other, meaning the highest coverage and completeness can be possible with the right combination of evaluation tools. Therefore, we suggest different tools should be utilized to provide consistency and obtain reliable data from online evaluation tools, thereby improving tool effectiveness.

Electrospun nonwovens are widely applied in biomedicine and various other fields. For control of the manufacturing process and quality assurance Scanning electron microscopy (SEM) imaging is one standard practice. In this study, statistical datasets of 60 SEM images of three nonwoven samples were evaluated using Gaussian fit to obtain numerical results of their fiber diameter distributions. The question of how much effort is required for acceptable imaging and processing is being discussed. As determined here, for reliable statistics, a minimum surface area of the nonwoven has to be evaluated. The fiber diameter should be in a range of approximately 2 - 3% of the edge length of the square equivalent of the evaluated image area, using sufficiently magnified SEM images, in which the fiber diameter is imaged over at least 30 pixels.

Introduction. Being an essential part of teaching and learning, feedback in close connection with evaluation is the focus of many researchers. Their interest lies mainly in automated systems, learners’ and teachers’ perceptions of writing feedback and feedback on feedback, new forms of feedback and their efficacy for motivation and writing performance. The review aims to identify the prevailing directions of research in the field. Methods. The review is based on 194 documents extracted from the Scopus database. The ultimate results of the search for “writing feedback” were limited to a field filter (social sciences, arts & humanities), a language filter (English), a document type (article, review, book chapter, conference paper) as well to manual screening in accordance with the inclusion criteria and relevance to the theme. Results and Discussion. Seven directions of research were identified: automated and non-automated evaluation; feedback on writing: general issues; automated feedback; peer review and teacher feedback on writing; perceptions and emotions relating to writing feedback; feedback on scholarly writing; evaluation and improvement in Chinese calligraphy. The reviewed documents proved the prominence of the topic and greater interest in new computer-mediated forms of feedback on writing. Conclusion. The results of the review may serve as a guidance for researchers at large and potential JLE authors focused on teaching and learning writing. The limitations of the review are linked to the scope and methods applied.

INTRODUCTION: Tuberculosis (TB) is a chronic, progressive infection that often has a latent period after the initial infection period. Early awareness from those period to have better prevention steps becomes an indispensable part for patients who want to lengthen their lives. Hence, applying cutting-edge technologies to support the medical business domain plays a key role in improving speed and accuracy in methods of diagnosis. Deep Neural Network-based technique (DNN) is one of such methods which offers positive results by leveraging the advantages of analyzing deeply the data, especially image data format via tons of deep layers of the neural networks. Our study was wrapped up by objectively assessing the performance of modern Deep Neural Network approaches and suggesting a model offering good results in terms of the selected metrics as defined later. In order to achieve optimized results, the chosen model must adapt well to the datasets but require less hardware and computational resources. OBJECTIVES: Our objective is to pick up and train a Deep Neural Network architecture which is highly trusted and flexibly fitted and applied to various datasets with minimum configurations. This will be used to produce good predictions based on the input data which are Chest X-ray images retrieved from the published datasets. METHODS: We have been approaching this problem by using the recognized datasets which have already been published before, then resizing them to the consistent input data for training purposes. In terms of Deep Neural Networks, we picked up VGG16 as the baseline network architecture, then use other ones which are state-of-the-art networks for comparison purposes. After all, we recommend the neural network architecture offering the most positive results based on accuracy and recall measurements. So that, this network architecture will show flexibility when fitting into diverse datasets representing different areas in the world that suffered from Tuberculosis before. RESULTS: After conducting the experiments, we observed that the Mobilenet model produced great results based on the predefined metrics for most of the proposed datasets. It shows the versatility which is applicable to all CXR datasets, especially for the Tuberculosis ones. CONCLUSION: Tuberculosis is still one of the most dangerous illnesses in the world that needs vital methods to prevent and detect soon so that patients are able to keep their lives longer. After this research, we are constantly improving the current accuracy of the models and applying the current results of this research for later problems such as detecting the Tuberculosis areas in real-time and supporting doctors to make decisions based on the current status of patients.

In Centrifugal Partition Chromatography, two immiscible liquids are used as mobile and stationary phases. During operation, bleeding of the stationary phase cannot be eliminated completely. For optimal separation performance, however, it is crucial to maintain sufficient amounts of stationary phase in the system, which is quantitatively measured by the retention value. With an online measurement of that retention value, it is possible to make predictions about the separation performance of the system. Therefore, an image processing algorithm was developed in this study, allowing quick and effortless online evaluation of retention by image analysis. Finally, the results were compared with proven analysis methods to evaluate the measurements’ validity. With the help of the new algorithm, it was possible to improve the number of pictures analyzed per time and the precision compared to the previously used technique.

Purpose: Size and density measurements of the ablation zones on contrast-enhanced computed tomography (CT) after radiofrequency ablation (RFA) of hepatic metastases of primary breast or colorectal cancer were acquired over time. Materials and Methods: Twenty-five liver metastases [colorectal cancer (CRC): n = 16; mean size: 19.6 ± 8.5 mm; breast cancer (BC): n = 9; 27.9 ± 13.6 mm] in 15 patients (CRC: n = 11; age: 65.4 ± 6.5 years; BC: n = 4; 62.0 ± 13.8 years) treated by RFA were included in this retrospective study. All patients had undergone postinterventional serial follow-up using multidetector CT (MDCT) (1 day/1/4/7/10/14/18/23/>24 months) without evidence of local tumor recurrence during the follow-up. The ablation zones were evaluated using a commercial software tool (Syngo CT Oncology) in order to determine volumetric, RECIST-, WHO- and density changes over the course of time. Results were compared by applying repeated measures analysis of variance and displayed graphically. Results: The RF ablation zones demonstrated significant shrinkage (P ≤ 0.05) over the first 7 months (volume, RECIST, WHO) of the follow-up. Follow-up after 7 months did not show any significant changes in size (P > 0.05) (mean volume (ml): 55.2/34.7/26.3/16.5/12.7/10.0/8.9/8.1/7.5; RECIST (mm): 58.7/49.3/43.7/37.8/34.2/31.3/29.1/27.3/24.8; WHO (mm2): 2458.3/1769.3/1341.8/1027.1/870.1/720.2/649.0/570.4/511.3). Mean density values decreased significantly between 1 day (58.9 HU) and 1 month (47.5 HU) after the procedure. Conclusion: Typical changes in size and density values of RF-induced, recurrence-free ablation zones after RFA of hepatic metastases of colorectal and breast cancer were acquired, showing a significant decrease in density of the ablation zone within the first month and significant shrinkage within the first 7 months after RFA.

Automation of descriptive answers evaluation is the need of the hour because of the huge increase in the number of students enrolling each year in educational institutions and the limited staff available to spare their time for evaluations. In this paper, we use a machine learning workbench called LightSIDE to accomplish auto evaluation and scoring of descriptive answers. We attempted to identify the best supervised machine learning algorithm given a limited training set sample size scenario. We evaluated performances of Bayes, SVM, Logistic Regression, Random forests, Decision stump and Decision trees algorithms. We confirmed SVM as best performing algorithm based on quantitative measurements across accuracy, kappa, training speed and prediction accuracy with supplied test set.

Purpose—The paper is aimed towards the problem of automated evaluation of computer programs designed by students during competitive events where the participants have to design an algorithm and to implement it as a working program, which has to be evaluated. A similar evaluation has to be performed at universities by the lecturers teaching basics of programming. The purpose of this paper is to investigate the automated evaluation applied to computer programs designed by the university students, and to analyze the suitability of such methods for evaluation of computer programs designed by high school students in competitive events.Design/methodology/approach—Comparative analysis is the main approach used in this paper.Findings—The educational and technical goals that seek evaluation of computer programs at the university level are different from those in informatics contests. Therefore the majority of approaches applied at universities have led to development of automated evaluation systems with functionalities different than the ones required by informatics contests, and in the opinion of the author cannot be easily transferred to informatics contests. We identified one area where such transfer might be possible: automated evaluation of programming style.Research limitations/implications—The experience of automated evaluation of programming style applied at the universities has a potential to be transferred to informatics contests; however the universities may ask their students to apply specific programming style, while informatics contests should accept a very broad range of reasonable programming styles. Additional investigation is required to answer the question in which way and to which extent the experience gained at the universities can be applied in informatics contests and the maturity exam.Practical implications—This paper is a step towards developing a fair and motivated evaluation scheme in informatics contests. The paper would be useful for the researchers as it gives guidelines for future research.Originality/Value—It is very important to apply fair and motivated evaluation in informatics contests as they involve the majority of high-school students interested in computer science in Lithuania and some other countries as well and may motivate them to study computer science at the university. To the knowledge of the author, this is the first paper analyzing the suitability of automated evaluation methods developed at the university level, to be applied for the evaluation at high school level in particular in informatics contests. On the other hand, the evaluation in informatics contests is an issue that attracts the interest of international community of informatics contests.

Automated documents processing allows production of large amount of documents. Formal quality of the documents is very important as it contributes to better understanding and information transmission. The paper deals with the automated documents quality evaluation. This requires a design of a document model. The model contains the objects of which the pages are compiled, the types of objects and, the most important, the objects’ parameters. The parameters of the object are very important as they are inputs for the document evaluation according to the typographical rules. The parameters are an important part of the model which should reliably describe the document. A set of criteria is designed, which are used to describe the requirements on appropriate methods for model formation. From large amount of methods, methods that meet the criteria can be applied to the document. The result is a model of a real document which can be used for the automatic evaluation based on the typographical rules.

Purpose—The paper is aimed towards the problem of automated evaluation of computer programs designed by students during competitive events where the participants have to design an algorithm and to implement it as a working program, which has to be evaluated. A similar evaluation has to be performed at universities by the lecturers teaching basics of programming. The purpose of this paper is to investigate the automated evaluation applied to computer programs designed by the university students, and to analyze the suitability of such methods for evaluation of computer programs designed by high school students in competitive events. Design/methodology/approach—Comparative analysis is the main approach used in this paper. Findings—The educational and technical goals that seek evaluation of computer programs at the university level are different from those in informatics contests. Therefore the majority of approaches applied at universities have led to development of automated evaluation systems with functionalities different than the ones required by informatics contests, and in the opinion of the author cannot be easily transferred to informatics contests. We identified one area where such transfer might be possible: automated evaluation of programming style. Research limitations/implications—The experience of automated evaluation of programming style applied at the universities has a potential to be transferred to informatics contests; however the universities may ask their students to apply specific programming style, while informatics contests should accept a very broad range of reasonable programming styles. Additional investigation is required to answer the question in which way and to which extent the experience gained at the universities can be applied in informatics contests and the maturity exam. Practical implications—This paper is a step towards developing a fair and motivated evaluation scheme in informatics contests. The paper would be useful for the researchers as it gives guidelines for future research. Originality/Value—It is very important to apply fair and motivated evaluation in informatics contests as they involve the majority of high-school students interested in computer science in Lithuania and some other countries as well and may motivate them to study computer science at the university. To the knowledge of the author, this is the first paper analyzing the suitability of automated evaluation methods developed at the university level, to be applied for the evaluation at high school level in particular in informatics contests. On the other hand, the evaluation in informatics contests is an issue that attracts the interest of international community of informatics contests.

This paper presents a comparison of some methodologies for the automatic construction of video summaries. The work is based on the simulated user principle to evaluate the quality of a video summary in a way that is automatic, yet related to the user′s perception. The method is studied for the case of multiepisode video, where we do not describe only what is important in a video but rather what distinguishes this video from the others. Experimental results are presented to support the proposed ideas.