Reviewerly/exHarmony huggingface dataset:
[Prediction of Response to Neoadjuvant Chemotherapy for Breast Cancer Based on Histomorphology Analysis of Needle Biopsy Images].

The deep learning method was used to automatically segment the tumor area and the cell nucleus based on needle biopsy images of breast cancer patients prior to receiving neoadjuvant chemotherapy (NAC), and then, the features of the cell clusters in the tumor area were identified to predict the level of pathological remission of breast cancer after NAC.68 breast cancer patients who were to receive NAC at Jiangsu Province Hospital were recruited and the hematoxylin-eosin (HE) stained preoperative biopsy sections of these patients were collected. Unet++ was used to establish a segmentation model and the tumor area and nucleus of the needle biopsy images were automatically segmented accordingly. Then, according to the nuclei in the automatically segmented tumor area, the features of the cells in the tumor were constructed. After that, effective features were selected through the feature selection method and the classifier model was constructed and trained with five-fold cross validation to predict the degree of post-NAC pathological remission.Predictions were made based on the needle biopsy images of the 68 patients. The model that combined the 10-dimensional features selected with the minimal redundancy-maximum-relevancy approach (mRMR) and training with the random forest (RF) classifier had the highest prediction accuracy, reaching 82.35%, and an area under curve ( AUC) value of 0.908 2.This model automatically segments tumor areas and cell nucleus on the biopsy images. The features of the cell clusters which are analyzed and identified in the tumor area can be used to predict the pathological response of the patient to NAC. The method is reliable and replicable. In addition, we found that the textural features of cells in the tumor area was a useful predictor of patient response to NAC, which further confirmed that cell cluster in the tumor area is of great significance to the prediction of treatment outcome.
The Effect of Social Studies Instruction based on Universal Learning Design on the Academic Achievement and Interests for General Students and Students with Difficulties in Social Studies, Basic Achievement, and Intercultural Disabilities

The purpose of this study is to investigate the effects of social studies classes based on universal learning design (including graphic organizers) and is based on the academic achievement and interest of students in high school inclusion classes. 77 boys and 111 girls from six classes in the first year of high school participated. The intervention period was from May 2019, right after the first paper-delivered examination, to June 2019; a total of 14 classes were held three times a week. The intervention was conducted by the lead author and the main findings are as follows. There were statistically significant differences in both the academic achievement and interests among all students in this study, showing that social classes based on universal learning design had a positive effect. Results were derived that showed a much higher improvement rating post-test, than what was observed pre-test. Based on these findings, the possibility of including learners with various academic needs for universal learning (design-based instruction) in inclusion classes was discussed.
LibGuides: RDA 3R and RDA Toolkit: RDA 2019

Information and links to information, web sites, webinars, etc. on RDA 3R and the Beta RDA Toolkit Fall 2019
Entropy Methods for the Confidence Assessment of Probabilistic Classification Models

Many classification models produce a probability distribution as the outcome of a prediction. This information is generally compressed down to the single class with the highest associated probability. In this paper, we argue that part of the information that is discarded in this process can be in fact used to further evaluate the goodness of models, and in particular the confidence with which each prediction is made. As an application of the ideas presented in this paper, we provide a theoretical explanation of a confidence degradation phenomenon observed in the complement approach to the (Bernoulli) Naive Bayes generative model.
A Study on the Analysis of the Expected Effect of Smart Factory Technologies Using Modeling and Simulation

The Smart factory is currently being proposed as solutions to rising manufacturing costs, shrinking labor populations, and energy problems in global manufacturing. Examples of improvement in quality and productivity through smart factory construction are can be found out in many domestic and foreign enterprises. However, small and medium-sized enterprises are having difficulty to construct smart factory due to problem with an analysis of expected effects and burden of investment costs. In addition, while research on the development of smart factory technologies is relatively active, research regarding quantitative performance prediction of introduction of smart factory technologies is lacking. In this paper, a framework is designed to analyze the effects of introducting smart factory technologies, and the framework consist of the selection of technologies to be introduced, quantitative analysis of expected effects and qualitative analysis phases of expected effects. A quantitative analysis phase of expected effects uses simulation and present simulation model construction procedures and methodologies. A qualitative analysis phase of expected effects predicts the level of effectiveness of each technology through a case study of the application of smart factory technologies.
Effect of Extreme Negative Rating Review on Review Helpfulness: Moderate Effect of Reviewer Attributes

This study examines how extreme negative rating reviews affect the usefulness of reviews among the factors that affect the usefulness of reviews, and analyzes how the characteristics of reviewers affect the usefulness of reviews in terms of the effects of extreme negative rating reviews on the usefulness of reviews. The results of the analysis were as follows. First, extreme negative reviews were found to have a positive effect on the usefulness of reviews, and H1 was adopted. Second, when extreme negative rating reviews affect the usefulness of reviews, we looked at the adjustment effect of reviewer reputation and found that the adjustment effect of reviewer
Processing Croatian Aspectual Derivatives

The main objective of this paper is to detect and describe major derivational processes and affixes used in the derivation of aspectually connected Croatian verbs. This kind of analysis is enabled by previous detection of verbal derivational families, i.e. families of verbs with the same root as well as the derivational affixes they contain. Using NooJ, we automatically detect such derivational processes and assign the aspectual tag to derivatives. The procedure is based on the list of selected base forms and derivatives, on the list of derivational affixes and their allomorphs, and on the set of derivational rules. For this objective we selected 15 verbal derivational families comprising app. 250 derivatives in total. The output is being used for the development of a large on-line database of Croatian aspectual pairs, triples and quadruplets. Such a resource will be valuable for various research works in lexicology and lexicography.
Preparing students for professional activities based on a competency approach

The article presents an investigation of the issue of proficient competence; a methodological premise of shaping proficient competence of college understudies as future teachers is set up. The pith of proficient competence is characterized. The structure has been tentatively demonstrated and created, the substance, criteria and levels of proficient competence have been characterized. The adequacy of the distinguished methodological premise ofproficient preparing that gives the shaping of proficient competence of understudies. A methodological show of shaping of proficient competence of college understudies as future instructors has been hypothetically demonstrated, for all intents and purposes created and tentatively approbated.
Αυτόματη σύνοψη κειμένων με χρήση μηχανικής μάθησης

A synopsis is a short, precise representation of the content of a document. At its best, it summarizes the basic content of the document while also indicating the structure, functioning somewhat as a substitute for it. Given the difficulty of such a process being performed by the machine, automatic text summary can be defined as a software-generated text which, being consistent in structure and relevance, contains a significant amount of informational content from the original. In this paper, we will first explore ways of representing the semantics of words, phrases and sentences appearing in a given corpus, as well as the semantic correlations that emerge between them, using shallow neural networks according to the concept of vector representation. Then, each time starting from a given query text to be summarized and using once more machine learning algorithms, we will export, in accordance with the vector abstractions already formulated as sentence vectors, the information necessary to initially group them in terms of semantics and then to extract, maintain and paraphrase the key points of the text so that the produced summary, ideally, achieves coherence and does not substantially lag regarding the information content.
Improving Students’ Writing Procedure Text Through Make A Match Technique At Tenth Grade Of MAS Al-Manaar PTPN IV Pulu Raja In Academi Year 2020/2021

Writing is one of the things that are difficult for students to do. Students’writing ability still low, lack of vocabularies and confused to develop ideas inwriting is difficulty of students to write, especially writing procedure text. Thisresearch discussed the difficulties faced by students at tenth grade of MAS AlManaar PTPN IV Pulu Raja. This research was conducted by using Classroomaction Research. It taken from one class at tenth grade consists of 28 students. Theresearcher taken from two cycles.In collected the data, the researcher was taken byquantitative and qualitative data. In qualitative was taken by observation sheet,interview, and documentation. And in the quantitative data was taken by Pre-test,Post-test I and Post-test II. The score of students’ in pre-test 0%, from 28 studentsno students can answer the test. In Post-test I there were improvement fromstudents, it can be seen from the score of students increase to 69,43% from 28students, 9 students can passed the text to achieved Passing Grade, and in Post-testII almost all of them can passed the test because the score of students 84,42% and25 students passed the test and only 3 students still failed, the Minimum PassingGrade up 75. Meanwhile in qualitative data, they were so enthusiast and activewhen teaching learning about writing procedure text. They follow the instructionwell. So, Make a Match technique can improve students’ writing procedure text atTenth Grade of MAS Al-Manaar PTPN IV Pulu Raja.
Highly-Error Enhanced Smartly-Algorithmic Structured Impedance Fuzzy Controllers for A SCARA Redundant Manipulator

Living in the COVID-19 era, the various advanced industrial automated production lines demand anAI and Machine learning research in Robotic. Thus, an AI fuzzy-based control algorithms need to be developed.Consequently, a generalized Selective Compliance Assembly Robot Arm (5-Dof SCARA) dynamic model hasbeen derived. This 5-Dof SCARA model is inherently nonlinear, hence, to be controlled by a smart nonlinearcontroller of fuzzy type at the highest error enhancement. The smart nonlinear fuzzy controllers have beendeveloped in unified FLC type-1 and type-2 architectures. Firstly, an impedance controller deals with the endeffectors forces and its position tracking error. Secondly, a position controller is FLC type-1 PD and FLC type-2PID. The two controllers have been tested using half- elliptic and full-elliptic trajectory, then, compared to existrelated works. Accordingly, the obtained results of the smart controllers have a maximum percentage PD ofenhancements in comparison with previous works by the position responses. The FLC type-1 impedancecontroller has accomplished a 93.273% and 33.333% error enhancement for the position response of the X andY axis respectively. Comparably, higher error enhancement has been obtained using the FLC type-2 PIDimpedance controller of a 95.574% and 38.887% with the same axes. Hence, the designed smart controllershave a potential future application in advanced and critical trends.
Comparation analysis of naïve bayes and decision tree C4.5 for caesarean section prediction

The development of technology can be used to facilitate many matters.One of them is childbirth in the medical fields.Maternal mortality rate (MMR) is the number of maternal deaths during pregnancy to postpartum caused by pregnancy, childbirth or its management.There are several methods of labors that can be done.The determination of the labor is based on many factors and must be in accordance with the conditions of pregnant patient.Caesarean birth is the last alternative in labor, due to high risk factors.The objective of this research is to predicte and analyse caesarean section using C4.5 and Naïve Bayes classifier models.For experimentation the dataset is collected from UCI Machine Learning Repository and the main attributes represented in this dataset are age, delivery number, delivery time, blood of pressure, and heart problem.The accuracy using C4.5 by 80 training cases is 45% And the accuracy using Naïve Bayes is 50%.
Conceptualization of improvements in the Slovenian primary and lower secondary school

The present master's thesis examines possible improvements to the existing systemic elements of the basic education in Slovenia. The main interest lay in the quality of the compulsory and extended primary school syllabus, other organizational and pedagogical components, as well as potential changes related to them. The thesis focused on the quality of elective subject. The international PISA survey found, inter alia, that with regard to the financial literacy assessment, Slovenian students performed much below the OECD average, therefore this topic could be considered for inclusion as an independent elective subject.Since reading literacy is a key competence with a strong impact on social and work integration, it will need to be determined how best to improve reading literacy skills in the future. The right mechanisms need to be applied to reduce the variation in reading literacy performance between boys and girls, and to close the gap with other countries. The choice of the right mechanisms is largely influenced by social and gender differences that affect the final results. Many results point to the fact that the speech of infants, toddlers and children of early age is a good indicator of reading literacy, which leads to the pertinent question wheather children's speech competence is being promoted early enough. The European Reference Framework of Key Competences for Lifelong Learning suggests that young people should be helped to develop social and civic competences, which are defined by knowledge, skills and attitudes, during their basic education. To this aim, the subject of Civic and Homeland Education and Ethics was included in the curriculum, which is being taught to the Slovenian 7th and 8th grade pupils. Our research has found a difference between the intended and achieved curriculum. The curriculum expects teachers to follow a certain set of goals and content, but research has shown civic education to be one of the areas where the differences between the officially intended curricula and their actual implementation in the classroom are the most significant.The research has also revealed that most teachers believe upskilling to be important. We found that in Slovenia several further education and training programmes are beingoffered to the education staff.All our findings may give rise to further reflection on how to plan changes and approaches in a basic education system. The analysis will help experts and the professional public interested in the basic education guidelines, and can serve to support teachers' self-evaluation and pedagogical training.
A Study on Chinese Idioms into the Education Plan by Using Methods Semantic Compositionalit

This essay is a Semantic Compositionality study on the meaning of Chinese idioms. idioms are not only that the meaning of idiom can"t be composed of its words" meaning, but also that the meaning of idiom can be composed of its words" meaning which are motivated. And on the basis of this definition, I prescribed that the semantic properties of idiom are compositionality of idiom"s meaning, degreed of idiom"s meaning. Then I confirmed that the idioms which have compositionality of idiom"s meaning or ganized into three idiom groups. Those are the idiom group showed metaphoricity, the idiom group showed metonymicity, and the idiom group that idiom"s meaning was motivated conventional knowledge. Also I demonstrated that degreed of idiom"s meaning was showed among each idiom group members. Next, each forty-five idioms are analyzed from the cognitive semantic point of view which is the kinds of motivation which is idiom"s meaning. I verified that this theoretical study that the category structure of idiom"s meaning. In consequence of this survey, it corresponds with the theoretical study. The validity is verified with the experiment and the investigation targeting the learner. lastly, Based on this, the purpose of this study is to suggest a more systematic and effective idiom education plan.
Research on multi-feature human pose model recognition based on one-shot learning

With the development of human-computer interaction, virtual reality, and other related fields, human posture recognition has become a hot research topic. Since the human body belongs to a non-rigid model and has time-varying characteristics, the accuracy and robustness of recognition are not ideal. Based on the KinectV2 so-matosensory camera to collect skeletal information, this paper proposes a one-shot learning model matching method based on human body angle and distance characteristics. First, feature extraction is performed on the collected bone information, and the joint point vector angle and joint point displacement are calculated and a threshold is set. Secondly, the pose to be measured is matched with the template pose, and the recognition is successful if the threshold limit is met. Experimental results show that the method can detect and recognize human poses within the defined threshold in real-time, which improves the accuracy and robustness of recognition.
Sentiment Analysis of Snack Review Using the Naïve Bayes Method

Fast food is a product that we often encounter in stores such as convenience stores. Ready-to-eat products can now be easily found by consumers. One of the reason is due to the expansion of minimarkets in areas that are easily reached, such as housing complexes, school areas, and offices. Sentiment analysis is used to determine whether an opinion or comment on a product has a positive or negative interest and can be used as a reference in improving service, or improving product quality. In this research, we study the sentiments of consumers towards snack food products as a reference to improve the level of service and quality of these products..&#x0D; We classify the sentiment of a review on snack food products as positive and negative. To classify the sentiments we apply the Naïve Bayes and Multinomial Naïve Bayes methods. We compare the two methods to study the most effective and efficient method for classifying sentiments on reviews of snack food products.&#x0D; Keywords: Sentiment Analysis, TF-IDF, Naïve Bayes,Multinomial, Review, Snack, Preprocessing
Embedding Function Icons into QR Codes

This paper proposes an approach to produce high-quality visual QR codes introducing the concept of function icons (FI)—images embedded into QR code. FI design resembled abstract symbols, like identifiable and memorable smartphone app icons or logos. The embedding visually points to the function of a QR code and therefore is more attractive to the end-user than the traditional QR code. Also, the FI perceptual simplicity increases users’ navigation and accessibility over different media. For optimization, the proposed FI design was altered by pixel size, color, and luminance modification, without affecting the decoding reliably. The contrast between dark and light modules of the FI color tone was determined to a minimum of 70% to enable the code reader’s conversion of the image to grayscale and then segmentation it into black and white pixels. The eye-tracking research on QR codes with implemented icons confirmed the subjective attractiveness evaluation. The technical quality of the proposed design was verified with a QR code readability test. Since more than 95% of examinees successfully recognized the content behind a QR code before scanning and evaluated the design as more attractive than a traditional solution, we demonstrated that our approach produces high-quality results for a variety of FI designs.
The Importance of Using a Web-Based Learning Model to Prevent the Spread of COVID 19

Online learning is known that is learning that is connected to a computer or android network. In addition to Online there are also many learning using the internet such as WEB-based learning, Hybrid Learning and E-Learning. The author's objectives are (1) knowing WEB-based learning models, (2) to find out the Implementation of WEB-Based Learning, (3) prevention of the spread of COVID-19. The research used is Quantitative Research and using WEB-based learning models. Therefore it is very important WEB learning model to prevent the spread of COVID - 19. From the results that can be seen in using this learning model, students sometimes find it difficult to understand the explanation given by educators. Due to internet limitations or android usage. So it is recommended for students with the use of online learning models students can reduce activities outside the home and can help reduce the distribution chain of COVID-19. Keywords: WEB Based, Implementation, COVID prevention - 19
APLIKASI ADMINISTRASI KEANGGOTAAN PENDONOR DARAH SUKARELA PADA UNIT KEGIATAN MAHASISWA KORPS SUKARELA PALANG MERAH INDONESIA STMIK NURDIN HAMZAH JAMBI

Android is one of the smartphone operating system that is developing at this time, Android has many advantages over other operating systems. Student Activity Unit of the Indonesian Red Cross Volunteer Corps STMIK Nurdin Hamzah Jambi is one of the student activities unit engaged in social and humanity one of the routine agenda that is run the blood donation activities. The process of finding voluntary blood donors that matches the patient's criteria is often difficult to do, due to blood proofing procedures, limited space and time constraints regarding patient safety. While obtaining blood in a short time is expected by every doctor in dealing with patients. If the replacement donor does not meet the criteria of the patient, then the last alternative is to find a volunteer donor who is also looking for a blood donor to the Student Unit of the Indonesian Red Cross Volunteer Corps STMIK Nurdin Hamzah Jambi. The current system is a book agenda where the search process of blood donor data is still done manually. The advantages of the built application is its android-based operating system, which is android smartphone operating is very popular community. The advantages of android one of them can help doctors and patients who need blood donors quickly based on the background and the above solutions, then conducted thesis research in the Student Activity Unit of the Indonesian RedCross Volunteer Corps STMIK Nurdin Hamzah Jambi.