Reviewerly/exHarmony huggingface dataset:
Federated Learning for Brain Tumor Segmentation on the Cloud

With groundbreaking innovations in healthcare due to advancements in machine learning and deep learning, the need for computationally efficient and privacy-preserving solutions is exigent. Modern healthcare systems collect healthcare data in huge volumes. However, this data resides in different locations and is held by different institutions. This hinders its utilization by machine learning algorithms since they require large data sets from training. Moreover, accessing sufficient data from varied data silos is not possible due to various constraints like ethical, legal, economic, and technical challenges. Since medical data is highly sensitive, privacy concerns assume paramount importance. While dealing with similar scenarios, Federated Learning has shown promising results and could also be used in the healthcare domain for solving these issues. To explore the feasibility of federated learning in medicine by facilitating multi-institutional collaborations, the problem of brain tumor segmentation is undertaken. With the help of federated learning, training of models collaboratively from multiple parties owning the data while keeping privacy in check can be achieved. An aggregate ensemble of four different segmentation U-Net models for Cloud-based horizontal federated learning architecture with a FedProx algorithm is suggested to tackle the problem. In order to locate the area where the tumor is present, an average of codes is considered after every result to form the end MRI. This approach brings the model to the sensitive data owners and requires only the model updates to be sent to the central server, thereby preventing leakage of data and preserving privacy. While doing so, faulty updates from malicious clients can be discarded, thereby preventing them from hindering the central model. The challenges and considerations that need to be addressed while dealing with healthcare data for brain tumor segmentation are also highlighted in the chapter.
PENERAPAN ALGORITMA DJIKSTRA PADA PENCARIAN JALUR TERPENDEK

The development of the times demands an effective and efficient method of activity. One of them is the method for determining the path. Dynamic human activities and being required to make displacement require a method that helps in determining the shortest path. Determining the shortest path has a reason to save fuel, time and power. One method that can be used for closest distance search is to use Dijkstra's algorithm. Dijkstra algorithm is an algorithm that applies a graph of direction and weight, where the distance between points is the weight of each arrow. This algorithm will look for the path with the minimum cost between one point and another. In addition, Dijkstra's algorithm can also be used to calculate the total cost or cost of the shortest trajectory that has been formed
L’eros e il desiderio. Tradurre l’intraducibile?

Introduction to the annual supplement “Volti del tradurre” edited by Helena Aguila Ruzola and Donatella Siviero. The section includes a selection of papaers presented at the 5th International Translation Day, held on 3-4 December 2018 at the University of Catania, in collaboration with the Universitat Autonoma de Barcelona and the University of Messina.
Diagnóstico psicopedagógico y socioemocional en adolescentes de 15 a 18 años en tiempo de pandemia por covid-19. Psychopedagogical and socio-emotional diagnosis in adolescents aged 15-18 in time of COVID-19 pandemic

The objective of the article is to diagnose psychopedagogically and socio-emotionally adolescents aged 15 to 18 years, from Spain, Panama, Argentina, Chile, USA, Brazil, Mexico, Portugal, Italy, Haiti, Romania, Colombia and Japan, in time of a COVID-19 pandemic. This research has a quantitative approach, it is descriptive, field and transactional. The questionnaire-type survey was used for data collection. The results show that, in the aforementioned period, 54.3% of the respondents had little or no contact with the school environment; 76, 3% show a lack of motivation towards learning; 72% associated their health status with negative valence emotions; 61% define an improvement in family relationships. In conclusion, the pandemic has had serious repercussions on learning, breaking with an educational structure that reaffirms the fruitful interrelation of students with their teachers, peers and school.
Index Ranking of Tweets Based on Content-Relevance

Twitter is a standout amongst the most well known smaller scale blogging administrations, gives extensive amounts of crisp data including constant news, remarks, discussions, futile prattle and advisements. In this flooding there is a great deal of trivial tweets. The positioning procedure we offer uses a technique where the positioning of the tweets is finished utilizing distinctive highlights of tweets.The system thinks about that specialist of tweet, url joins incorporating into tweets and other tweet particular highlights. This methodology can be answer for this issue of silly tweet data and offers the client get most applicable substance as it were.
Pengaruh Motivasi, Minat, dan Intensitas Belajar Terhadap Hasil Belajar Siswa Pada Pengantar Akuntansi dan Keuangan

Student learning outcomes at this time are the effect of multiple factors which can be internal and external. The purpose of this study is to analyze the effects of variables (learning motivation, interest in learning, and learning intensity) in class XI students of Introduction to Accounting and Finance at SMK Negeri 10 Surabaya. The type of this research is quantitative. The population in this study were 144 students of class XI SMK Negeri 10 Surabaya and were sampled by means of Non Probability Sampling or sampling techniques that did not provide equal opportunities / opportunities for each element or member of the population to be selected as samples and the sampling technique used was used was purposive sampling with certain criteria, namely students of class XI Accounting. After conducting the research, the conclusions are (1) The results of this study indicate a significant value of less than 5% (0.007 &lt;0.05) that the learning motivation of students has a positive and significant effect on learning outcomes introducing accounting and finance (2). This also shows a significance value of less than 5% (0.000 &lt;0.05) which means that the learning motivation of students has a positive and significant effect on learning outcomes introducing accounting and finance (3) in research research shows the significance value also shows less than 5 % (0.008 &lt;0.05) that the learning intensity of students has a positive and significant effect on learning outcomes introducing accounting and finance (4) For the results of hypothesis testing, the F test shows a significance value of less than 0.05, namely 0.000. The results of this study indicate that the variables of learning motivation (X1), Learning Interest (X2), and Learning Intensity (X3) simultaneously have a positive effect on learning outcomes introducing accounting and finance (Y) in class XI students of SMKN 10 Surabaya.
Policy Implementation of 9 Years of Compulsory Learning Program and Eradication of Illute Illusion In Nabire District

Education has an important role in the process of improving the quality of human resources.  Improving the quality of education is an integrated process in the process of improving the quality of human resources. The role of education is very much needed and demands attention and participation from all parties.  In Article 31 of the 1945 Constitution, education is a right for every citizen, the Government is well aware of the need to improve the quality of education as a tool to improve the quality of human resources.  Through Law No. 20 of 2003 concerning the national education system and Presidential Instruction No. 5 of 2006 2006 concerning the National Movement for the Acceleration of Completion of Compulsory Education for Nine Years of Basic Education and Eradication of Illiteracy. Therefore, there are still many children who drop out of school, especially in Nabire Regency.  Most children drop out of school because of a lack of awareness of the importance of education and the role of parents in encouraging their children.  In addition, the school environment that affects student learning includes classroom infrastructure, inadequate and inadequate building conditions. In this study using qualitative research methods, namely a study aimed at describing and analyzing phenomena, events, social activities, attitudes, beliefs, perceptions, thoughts of people individually and in groups. Qualitative research, data collection is carried out in natural conditions, primary data sources, and data collection techniques are mostly on instrumental observation, as well as in-depth interviews. This study concludes that the implementation of the 9-year compulsory education program policy in Nabire sub-district has not been implemented effectively due to inconsistency.  Then policy implementers have not given a positive attitude which is marked by weak coordination in policy implementation.
Comparison of peripheral blood smear examination with automated haematology analyzer for diagnosing different types of anemia.

Objective: This study aims to determine diagnostic accuracy of peripheral blood smear and automated haematology analyzer and to determine frequency of different types of anemia diagnosed by peripheral blood smear and automated hematology analyzer. Study Design: Cross Sectional study. Setting: Department of Pathology, Rawal Institute of Health Sciences, Islamabad. Period: November 2015 to April 2016. Material &amp; Methods: Sample size of 149 suspected anemia patients was calculated using WHO calculator with 95% confidence interval. Research approval was taken from hospital ethical board. Patients were approached through non probability consecutive sampling method. Both peripheral blood smear examination and automated haematology analysis of each sample was performed. Diagnostic accuracy and frequency of anemia types was measured. Data analysis was done with the help of SPSS version 25. Chi-square and fissure exact test and ROC curve analysis was applied and significant (p&lt;0.05) results were reported. Results: Total 149 patients were included in study. There were 42(28.2%) male and 107(71.8%) female. Mean age of patients was 35.1±2.1SD. Peripheral blood smear and automated haematology analyzer showed sensitivity (68% vs 92%), specificity (59% vs 88%), PPV (72% vs 92%), NPV (55% vs 88%) and diagnostic accuracy (64% vs 91) respectively. Most common type of anemia diagnosed with peripheral blood smear was microcytic hypochromic anemia with raised RDW 36.7% followed by normocytic normochromic anemia with raised RDW 13.3% and macrocytic anemia (p=0.001) while in automated haematology analyzer microc ytic hypochromic anemia with raised RDW54.4% followed by normochromic normocytic anemoia with normal RDW 11.1% (p=0.000). Conclusion: Automated haematyology analyzer had high diagnostic accuracy for diagnosis of anemia. Microcytic hypochromic anemia and normocytic normochromic are most common anemias diagnosed by peripheral blood smear and automated hematology analyzer and peripheral blood smear cannot be completely replaced by automated haemolytic analyzer. However, if both methods are used simultaneously, more accurate results can be obtained.
Digital transformation and assessment of quality of educational activity of the University

Researched are issues of assessing the quality of educational activities in the context of digital transformation. The relevance of the study is due to the digital transformation of education, increased requirements for the level of quality of training of university graduates, the complication of the conditions for organizing the educational process, which determines the need to search for new approaches and technologies. Assessment of the quality of educational activities in the context of digital transformation requires the creation of the necessary infrastructure, the formation of an appropriate regulatory and educational framework. When considering the indicated problem, the methods of systematization and generalization were used, which make it possible to consider this problem, taking into account many factors that affect the assessment of the quality of educational activities in the context of digital transformation. The article highlights the main approaches to the process of assessing the quality of educational activities using the electronic information and educational environment, implemented by universities. The practical significance of the research results is determined by the fact that the conclusions drawn and the proposed scientific and theoretical provisions can be useful to the heads of educational organizations and have the ability to adapt to the conditions of the educational process. The article will be useful for administrative and pedagogical workers of universities, as well as for everyone interested in researching the quality of educational activities in the context of digital transformation.
Chapter 2. Getting Started with Cloud Services

Cloud services provide a wide range of tools and services that can be used to create a digital repository. Software subscriptions, development platforms, and virtual infrastructure services can provide libraries with the specific tools they need to develop a repository to any specification.
Feature based Opinion Mining using Convolutional Neural Networks

Opinion mining refers to the use of natural language processing, text analysis to identify and extract user’s opinion through their reviews. Now a day’s people before purchasing any product they are reading reviews given by earlier customers, based on these reviews they are making decision to purchase the product. Opinion mining is the automatic process of determining the polarity of the product review. To get the exact polarity Feature based opinion mining works prominently than Document and Sentence level. Feature Based Opinion Mining (FBOM) is the task of classifying the sentiment of a specific feature in a text. Because a single text usually has multiple aspects which are expressed independently, FBOM is an important task for in-depth opinion mining. Opinion mining is the improvement of granularity at feature level, representing two distinct aims: aspect extraction and sentiment classification of product and sentiment classification of target-dependent tweets. However, it is problematic to depend solely on attention mechanisms to achieve this, because most sentiment expressions such as ‘nice’ and ‘bad’ are two general to be aligned with a proper feature event through an attention mechanism. To full fill this task, this paper proposes a convolutional neural network (CNN) which is a deep learning model based feature level sentiment classification model, which consists of two CNNs. The first CNN extracts the positional information of feature expressions for a target feature. The second CNN classifies the sentiment of the target feature in text.
استفاده از گروه‌‌‌‌های مجازی آموزشی (VLT) جهت بهبود سواد ارزشیابی زبان (LAL) برای مدرسان انگلیسی به‌‌‌‌‌عنوان زبان خارجی

Although education and assessment are inseparable, many capable teachers find themselves ill-equipped to develop/use assessment activities for their classes. Language teachers, similarly, may be familiar with language teaching methodology and second language acquisition theories, but may still have little or no savoir-faire regarding educational assessment. In fact, many studies indicate that the majority of language teachers are lacking in Language Assessment Literacy (LAL). Therefore, and in line with current educational theories which encourage collaboration and team work, a Virtual Learning Team (VLT) was proposed as a potential solution for this and similar teacher education problems: In the current study, a VLT aimed at enhancing EFL teachers' Language Assessment Literacy (LAL) was created and employed, using a Do-It-Yourself Learning Management System (DIYLMS) as the technological venue. The success of the VLT was ascertained and the factors affecting its efficacy were identified through a researcher-made pre- and post-course survey (Appendix A), as well as post-course semi-structured interviews (Appendix B). The results of the study indicated that there four factors which affect the efficacy of a VLT, namely; technology, instructor/team leader, interaction, and enhancement of knowledge/skills (both course-content and digital literacy). It was also revealed that these four factors do not work in isolation, and interact with each other in complicated ways. It is believed that the results of the current study can be beneficial for future teacher professional development programs.
Deep learning-based single-shot spatial frequency multiplexing composite fringe projection profilometry

Fringe projection profilometry (FPP) has been widely used in high-speed, dynamic, real-time three-dimensional (3D) shape measurements. How to recover the high-accuracy and high-precision 3D shape information by a single fringe pattern is our long-term goal in FPP. Traditional single-shot fringe projection measurement methods are difficult to achieve high-precision 3D shape measurement of isolated and complex surface objects due to the influence of object surface reflectivity and spectral aliasing. In order to break through the physical limits of the traditional methods, we apply deep convolutional neural networks to single-shot fringe projection profilometry. By combining physical models and data-driven, we demonstrate that the model generated by training an improved U-Net network can directly perform high-precision and unambiguous phase retrieval on a single-shot spatial frequency multiplexing composite fringe image while avoiding spectrum aliasing. Experiments show that our method can retrieve high-quality absolute 3D surfaces of objects only by projecting a single composite fringe image.
Graduate Students’ Perceived Self-Efficacy in Task-Based Learning

Self-efficacy is very important for graduate students and therefore has to be strongly instilled in order to encourage them to achieve their learning goals successfully including using English to communicate academically. Students are required to be studious and robust in learning and doing assignments. Nevertheless, many students feel anxious about their ability to perform their tasks moreover task-based learning. Conducted during the pandemic situation, this research aimed to investigate graduate students’ perceived self-efficacy in task-based learning. One research question was formulated: How does self-efficacy assist English Education Master Students in TBL learning? This research employed a mixed-method utilizing survey and interview to gather data from English Education Master Students, who had experienced task-based learning in Sanata Dharma University. The result shows that the students’ self-efficacy assisted them to be dare and confident in using the second language as the communicative tool in the TBL approach and achieve their learning goals
Feature Extraction Of Ultrasound Prostate Image Using Modified Vgg-19 Transfer Learning

Feature extraction plays a vital role in classification, clustering, diagnosis, and recognition. For the classification process, feature extraction is very important to embody the content of images accurately. The extraction of features from Transrectal Ultrasound (TRUS) is complex as it contains speckle noise, low dissimilarity, the fuzzy region between the object and background. To solve this problem, Ultrasound (US) prostate images are preprocessed and segmented by the Ant Colony Optimization-Boundary Complete Recurrent Neural Network (ACO-BCRNN) method. To extract the relevant features many techniques are applied by the researchers. Recently, transfer learning methods are used for feature extraction. Transfer learning is a machine learning technique in which a trained model in one problem is used in the development of another related problem. Transfer learning consists of various pre-trained models such as VGG16 (Visual Geometry Group), VGG19, Resnet50, InceptionV3, Xception, MobileNetV2, DenseNet, and ResNetV2. The modified VGG-19 model is proposed to extract the features of the prostate ultrasound image. The proposed method was compared with other pre-trained models and its performance is evaluated by using Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Grid Search. The experimental results demonstrated that the pre-trained model VGG19 is superior to other models in terms of Precision, Recall, Accuracy, and F1 Score
LAWS and Lawyers: Lethal Autonomous Weapons Bring LOAC Issues to the Design Table, and Judge Advocates Need to be There

This article discusses how risks normally associated with battlefield considerations of the Law of Armed Conflict must be considered and addressed during the design of autonomous platforms' underlying algorithms, how the current acquisition system inadequately controls for this, and what changes need to be made to ensure fully autonomous weapon systems actually do have appropriate levels of human judgement once deployed. The views expressed here are the author's personal views and do not necessarily reflect those of the Department of Defense, United States Army, The Judge Advocate General's Legal Center and School, or any other department or agency of the United States Government.
DIDACTIC POTENTIAL OF MODERN INFORMATION TECHNOLOGIES OF RADIATION DIAGNOSTICS TRAINING

This article proposes the structure of the digital educational environment for radiation diagnostics, highlights a list of operating conditions, interrelated components, didactic principles of learning, organizational and pedagogical conditions. The results of the analysis of the didactic potential of modern information technologies for radiation diagnostics training, obtained using SWOT-strategy, allowed us to establish the strengths (S) and weaknesses (W) of the introduction of information technologies in the educational process in radiology, as well as opportunities (O), risks and threat methodology (T). In turn, this allowed distinguishing qualitative level`s indicators of efficiency using cloud technologies in educational activities in radiology and the factors of successfulness using information technology training.