Reviewerly/exHarmony huggingface dataset:
Herbarium book: Learning media in medicinal plants lecture

&lt;p&gt;This study aims to (1) determine the types of medicinal plants used in Teluk Kayu Putih village, (2) describe the development of the herbarium book media for medicinal plants lecture, &lt;br /&gt; (3) determine the validity and (4) the readability test of the herbarium book of medicinal plants as a learning media. The ADDIE development model research consists of 2 stages of research. The first stage of qualitative research is to obtain data on the types of medicinal plants in Teluk Kayu Putih Village. The second stage of media development is making a herbarium book. Field data collection methods include observation and documentation (first stage) and questionnaire (second stage). The results obtained are: (1) The types of plants used as medicine in Teluk Kayu Putih Village are 27 species grouped into 25 families; the most plant species came from Family Euphorbiaceae, Myrtaceae, and Zingiberaceae, each with 2 species, (2) The media developed are specimens of medicinal plants originating from Teluk Kayu Putih village, including plant parts that have been dried using a pressing technique, arranged in a scrapbook with a black base color derived from black cardboard, the spesimens are pasted one by one and then identified, as well as put together and bound in a spiral to form a book, (3) The validity test from material experts and media experts on the media produced obtained a score of 81,35% and 85,26%, while the validity test score obtained a score of 86,31% (very feasible), (4) The readability test of the herbarium book by 23 respondents obtained an average percentage score of 92,6%, means that the media is suitable to use.&lt;/p&gt;
MidFusNet: Mid-dense Fusion Network for Multi-modal Brain MRI Segmentation

The fusion of multi-modality information has proved effective at improving the segmentation results of targeted regions (e.g., tumours, lesions or organs) of medical images. In particular, layer-level fusion represented by DenseNet has demonstrated a promising level of performance for various medical segmentation tasks. Using stroke and infant brain segmentation as example of ongoing challenging applications involving multi-modal images, we investigate whether it is possible to create a more effective of parsimonious fusion architecture based on the state-of-art fusion network - HyperDenseNet. Our hypothesis is that by fully fusing features throughout the entire network from different modalities, this not only increases network computation complexity but also interferes with the unique feature learning of each modality. Nine new network variants involving different fusion points and mechanisms are proposed. Their performances are evaluated on public datasets including iSeg-2017 and ISLES15-SSIS and an acute stroke lesion dataset collected by medical professionals. The experiment results show that of the nine proposed variants, the ‘mid-dense’ fusion network (named as MidFusNet) is able to achieve a performance comparable to the state-of-art fusion architecture, but with a much more parsimonious network (i.e., 3.5 million parameters less compared to the baseline network for three modalities).
Application of Project Schedule Management in Teaching Field

In the age of information 2.0, digital penetration shows the characteristics of all-round, multi-level and wide fields.In the field of education, although the application of new technology and new equipment is more popular, teaching methods are more flexible, teaching means are more diverse, and teaching platforms are more intelligent, teachers still face a series of difficulties in improving their digital competency, such as inconsistent competency standards, low level of data awareness, single ability of data application and practice, and insufficient basic guarantee of school informatization.Therefore, this paper proposes a new idea to improve teachers' digital competence with the goal of cultivating and establishing teachers' project management thinking.It specifically takes project schedule management as a breakthrough, combines it with teachers' daily work, and implements it into specific case scenarios.From a small point of view, it hopes to solve some practical problems in the application of information technology for teachers.From the large aspect, it is expected to provide some reference value for the establishment of the digital competence training system of teachers in the future.
Local Data Spaces: Leveraging trusted research environments for secure location-based policy research in the age of coronavirus disease-2019 – CORRIGENDUM

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Chatbots - The AI-Driven Front-Line Services for Customers

The provision of high-quality and reliable customer service around the clock is essential to any business today regardless of size or location. The rapid technological advancements in the Internet, computing and artificial intelligence, and humanoid robotics have pushed the edge of research, innovation, and development of smart technologies such as chatbots. This book offers comprehensive and up-to-date information about chatbots, including basic principles, applications, and future technological trends. It is an excellent reference for any businessperson and decision-maker, as well as scholars, researchers, and developers in business, academia, government, and computing and information technology.
Fraud Detection in E-Commerce Using Machine Learning

A rise in transactions is being caused by an increase in online customers. We observe that the prevalence of misrepresentation in online transactions is also increasing. Device learning will become more widely used to avoid misrepresentation in online commerce. The goal of this investigation is to identify the best device learning calculation using decision trees, naive Bayes, random forests, and neural networks. The realities to be utilized have not yet been modified. Engineered minority over-testing stability information is made utilizing the strategy framework. The precision of the brain not entirely settled by the disarray network appraisal is 96%, trailed by naive Bayes (95%), random forest (95%), and decision tree (92%).
Semi-implicit back propagation

Deep neural network (DNN) has been attracting a great attention in various applications.Network training algorithms play essential roles for the effectiveness of DNN.Although stochastic gradient descent (SGD) and other explicit gradient-based methods are the most popular algorithms, there are still many challenges such as gradient vanishing and explosion occurring in training a complex and deep neural networks.Motivated by the idea of error back propagation (BP) and proximal point methods (PPM), we propose a semi-implicit back propagation method for neural network training.Similar to the BP, the update on the neurons are propagated in a backward fashion and the parameters are optimized with proximal mapping.The implicit update for both hidden neurons and parameters allows to choose large step size in the training algorithm.Theoretically, we demonstrate the convergence of the proposed method under some standard assumptions.The experiments on illustrative examples, and two real data sets: MNIST and CIFAR-10, demonstrate that the proposed semi-implicit BP algorithm leads to better performance in terms of both loss decreasing and training/test accuracy, with a detail comparison to SGD/Adam and a similar algorithm proximal back propagation (ProxBP).
ISSUES OF SCIENTIFIC PRIORITY AGAINST THE BACKGROUND OF TWO PHILOSOPHICAL CONCEPTS OF SCIENTIFIC KNOWLEDGE

The article explores 2 opposite approaches to the authorship of the special theory of relativity. The first assumes that Albert Einstein is the only scientist whose contribution to the development of science allowed the creation of SRT. The second approach proclaims that the theory of relativity is the product of the collective activity of many scientists who have been working on its creation for decades.
RANDOM HILBERT SPACE AND WIENER’S INTERPRETATION OF QUANTUM MECHANICS

The special representation of quantum mechanics suggested by Wiener is studied, the wave function being considered as Gaussian random variable, i. e. the vector of the random Hilbert space. The connection between this representation and the well-known Einstein’s program aiming at creating the consistent field formulation of particle physics is revealed, with particles being represented as solitons, clots of some material field satisfying nonlinear equations.
CORRESPONDENCE OF HEISENBERG’S VIEWS WITH THE MULTIMODULAR CONCEPT OF A.V. AND L.A. BUROV

This article is devoted to a brief analysis of the views of the German physicist in their comparison with the concept of the metaphysical foundations of the universe of modern physicists Alexei Vladimirovich and Lev Alekseevich Burov. The object of the study is the main philosophical work of Heisenberg - the treatise “The Order of Reality” - and the work of the Drillers called “Metaphysical Status of physical Laws”. The metaphysical concepts of the multimodular reality of the mentioned authors are compared, and a brief historical basis for the emergence of these concepts is given. The substantiation of the importance of philosophical research in the field of physics and mathematics, and quantum physics is given - in particular. The necessity of further research of the issue is postulated considering the latest concepts in natural science within the framework of binary geometrophysics of Yu.S. Vladimirov. In conclusion, the importance of the modal (or multimodular) nature of reality is argued for the construction of a new, comprehensive picture of the world, within which it would be possible, finally, to understand the essence of quantum processes that determine reality, and to reach a fundamentally new level of philosophy of natural science.
VERIFIKASI DOKUMEN TRANSKRIP NILAI SEMESTER MENGGUNAKAN METODA OPTICAL CHARACTER RECOGNITION

At the Ambon State Polytechnic, students' semester grade reports are still manually typed. This causes frequent typo errors which can result in the invalidity of the document, let alone incorrect grades, student identification numbers and many other label values. Here a java application has been implemented to detect these errors. This application is primarily intended for officials of the Head of Study Program, Head of the Department before signing and validating the report. Officials who legalize it will be greatly assisted because tedious validation work can be replaced by computers. The validation process is carried out by utilizing the optical character recognition technique from the open source library Tesseract-OCR. From the experimental results the verification process can be improved by using OCR specific on specific regions of interest (ROI) after using template matching method from OpenCV. The consideration of the Levehnstein distance in the comparison of label values against the reference database also improves the success rate of the algorithm. The database used has been tested for about 800 grade report documents, with successful verification result above 90%.
On the "Rough Use" of Machine Learning Techniques

Machine learning is everywhere, but unfortunately, we are not experts of every method. Sometimes we "inappropriately'' use machine learning techniques. Examples include reporting training instead of test performance and comparing two methods without suitable hyper-parameter searches. However, the reality is that there are more sophisticated or more subtle examples, which we broadly call the "rough use'' of machine learning techniques. The setting may be roughly fine, but seriously speaking, is inappropriate. We briefly discuss two intriguing examples.
Category Shift in Novel After You by Jojo Moyes

This study aimed to analyze the types of category shifts that can be found in this novel and translated novel. In this study, the translator uses category shifts for several sentences, words, clauses, and phrases, as evidenced by the 100 data the researcher collected. It has been proven that 35 data use the Category Shift technique, and 15 use the Class Shift technique. Furthermore, 25 data using the unit shift technique and 25 data using an intra-system shift in this study also analyzed whether shifting in translation would affect the quality of the translation. The quality of the translation was measured using parameters from Nababan and the obtained results. The use of shifting techniques on the quality of translation, as measured through Nababan's theory, produces an average score on aspects of accurate 3, aspects of accelerable 3, and readable 3.
Prediksi Jarak Luncur Longsoran berdasarkan Parameter Geometri Lereng dan Tipe Batuan

landslide disaster. Based on this fact, a method is needed to predict the range of landslides to minimize the impact of disaster losses. The empirical statistical method is one of the methods that can be used to predict landslides by taking input data from the history of previous landslide events. This research aims to find the best modeling form for sliding distance prediction and which parameters influence a landslide's sliding distance prediction. This study used multiple linear regression methods. The data used in this study are geometric slope parameters in the form of slope height (H), original slope (θ), landslide area (A), and rock type (RT). The data was taken from the 2015-2021 PVMBG landslide investigation report and used the Google Earth and Global Mapper program. Based on the analysis of the best empirical model that can predict the sliding distance of a landslide log Lmax = 0,387 – 0,097 RT + 0,230 log H + 0,458 log A – 0,220 tan θ with an R2 value of 0,94 and an average estimated error of 31,56%. The parameter that has the most influence on the prediction of sliding distance is the area affected by the landslide (A).
PENGEMBANGAN MEDIA GAME PEMBELAJARAN IPAS MATERI TRANSFORMASI ENERGI DISEKITAR KITA MENGGUNAKAN APLIKASI WORDWALL KELAS IV SDN 108/VIII SARI MULYA

This research is motivated by the lack of use of interesting learning media to support the learning process, especially in class IV A SD N 108/VIII Sari Mulya. So, it takes effort to develop learning media. This study aims to produce learning media that have valid, practical and effective criteria. This research is a development research. The model used for this development is the ADDIE development model. The ADDIE development stages consist of: Analysis Stage, Design Stage, Development Stage, Implementation Stage, and Evaluation Stage. The results of the learning game media validation research were carried out by three validators, namely: validator I was 83.33%, validator II was 83.33%, and validator III was 100% which had an average value of 88.88% with a very valid category seen from the suitability of language, content and media graphics. The results of the practicality assessment of the learning game media were carried out by two practitioners, namely: practitioner I was 75% and practitioner II was 100%, which had an average of 88% in the very practical category. The results of the effectiveness of the learning game media obtained from the response questionnaire of class IV A students at SD N 108/VIII Sari Mulya have a value of 94% with a very effective category. The results of the study can be concluded that the development of learning game media has valid, practical and effective criteria.
PENINGKATAN HASIL BELAJAR TEMA 8 MELALUI MODEL PEMBELAJARAN NUMBERED HEAD TOGETHER (NHT) BERBANTUAN MEDIA TEKA-TEKI SILANG DI KELAS V SDN WIRUN

This study aims to determine the increase in learning outcomes in theme 8 through the Numbered Head Together (NHT) learning model assisted by crosswords in class V SDN Wirun. The research method used was classroom action research (PTK) conducted in 2 cycles. The research design is based on planning, action, observation, and reflection. Data obtained through documentation techniques, interviews, observations, and tests. The results showed that the Numbered Head Together (NHT) learning model assisted by crosswords media could improve student learning outcomes with the average class I cycle PPKn content reaching 70.62 while the IPS content reached 65.37. Then the learning outcomes of students in cycle II increased with the average learning outcomes for PPKn content reaching 82.37 while the IPS content reached 79.87. Based on the results of the study, it can be concluded that the application of the Numbered Head Together (NHT) learning model assisted by crosswords media is able to improve the learning outcomes of class V SDN Wirun on PPKn and Social Studies content.
Peningkatan Kemampuan Membaca pada Siswa SDN 121/I Muara Singoan Kelas Rendah sebagai Bagian Integral dari Perkembangan Bahasa

Reading proficiency is a key competence in language development for children at the primary school level. This study aims to explore the efforts undertaken by SDN 121/I Muara Singoan in improving the reading abilities of elementary school students and understanding its integral role in overall language development. Through a qualitative research approach, data were collected through classroom observations, interviews with teachers, and analysis of curriculum-related documents and teaching strategies. The results of this study indicate that SDN 121/I Muara Singoan has implemented various specific learning strategies to enhance students' reading abilities. Some of these strategies include the use of engaging textbooks, group reading activities, and a library program that expands students' access to reading materials. Additionally, the role of teachers and parents is recognized as a crucial factor in improving students' reading abilities. Teachers provide continuous support through training and guidance, while parents are involved in supporting reading practices at home and providing positive reinforcement. The improvement of reading abilities among lower-grade students at SDN 121/I Muara Singoan has significant impacts on overall language development. In addition to enhancing reading skills, students also demonstrate improvements in content comprehension, critical thinking abilities, and written expression.
Procedural Semantics and its Relevance to Paradox

Two semantic paradoxes, the Liar and Curry’s paradox, are analysed using a newly developed conception of procedural semantics (semantics according to which the truth of propositions is determined algorithmically), whose main characteristic is its departure from methodological realism. Rather than determining pre-existing facts, procedures are constitutive of them. Of this semantics, two versions are considered: closed (where the halting of procedures is presumed) and open (without this presumption). To this end, a procedural approach to deductive reasoning is developed, based on the idea of simulation. As is shown, closed semantics supports classical logic, but cannot in any straightforward way accommodate the concept of truth. In open semantics, where paradoxical propositions naturally ‘belong’, they cease to be paradoxical; yet, it is concluded that the natural choice—for logicians and common people alike—is to stick to closed semantics, pragmatically circumventing problematic utterances.
Guidance and Counseling Information Technology Module Based on Guided Discovery Learning

Skills in using information technology are an important requirement in this era. For this reason, it is necessary to prepare guidance and counseling students to have adequate skills in using various information technology applications. These skills are needed to meet students' needs according to technological developments. This research aims to test the feasibility of the developed module. This research belongs to the type of development research which was developed using the Borg &amp; Gall model. The subjects involved in this study were media design experts and material experts. The data collection in the study was carried out using observation, interview, and questionnaire methods, with research instruments in the form of design expert validation questionnaires, material expert validation questionnaires, and guidance and counseling student response questionnaires. The data obtained in the study were then analyzed using the percentage formula. The research analysis showed that the design expert obtained 92.2% in the validation test, which was in the very valid category. The results of the material analysis validation expert, with a percentage of 94.4%, were in the very valid category, and the results of the analysis of student responses, with a percentage of 98 %, are also in the very valid category. Based on these results, the information technology course module in guidance and counseling that was developed is in the valid category and is very feasible to develop.
Music teaching in primary schools of Albacete, Spain, during the COVID-19 pandemic

Abstract The role, functions and duties of teachers have dramatically changed with the COVID-19 pandemic. This sudden change has posed enormous challenges for schools, students and teachers. This article deals with the situation of music teaching in the Spanish province of Albacete (Castilla-La Mancha) 1 in the first two terms of the course 2020–2021 through face-to-face lessons. A questionnaire, created on music teaching in elementary schools, was answered by 96 teachers, teaching an amount of 35,365 primary education pupils in Albacete. The results of this research show that the everyday teaching has experienced relevant changes, especially in instrumental practice.
Saliency Prediction in 360º Videos with Transformers

We present a model for saliency prediction in 360º videos based on the Transformer architecture. Our model leverages the global attention mechanism in order to represent the temporal dependencies that drive human attention. We compare our model with a current state-of-the-art model and outperform it for all metrics measured.
In-the-wild Material Appearance Editing using Perceptual Attributes

Intuitively editing the appearance of materials, just from a single image, is a challenging task given the complexity and ambiguity of the interactions between light and matter. This problem has been traditionally solved by estimating additional factors of the scene like geometry or illumination, thus solving an inverse rendering problem where the interaction of light and matter needs to be modelled. Instead, we present a single-image appearance editing framework that allows to intuitively modify the material appearance of an object by increasing or decreasing high-level perceptual attributes describing appearance (e.g., glossy or metallic). Our framework uses just an in-the-wild image as input, where geometry or illumination are not controlled.&#x0D; We rely on generative neural networks and, in particular, on Selective Transfer Generative Adversarial Networks (STGAN) that allow to preserve high-frequency details from the input image in the edited one. To train our framework we combine pairs of synthetic images, rendered with physically-based ray tracing algorithms, and their corresponding ratings of the high-level attributes, given by humans through crowd-sourced user studies. Last, although trained on synthetic images, we demonstrate the applicability of our method on synthetic video sequences; and real-world photographs downloaded from online catalogs and manually taken using our mobile phones.