Reviewerly/exHarmony huggingface dataset:
STATUS OF CANADA’S GEOSCIENTIFIC SITE EVALUATIONS FOR A DEEP GEOLOGICAL REPOSITORY FOR USED NUCLEAR FUEL

The Nuclear Waste Management (NWMO) is responsible for implementing, collaboratively with Canadians and Indigenous people, Canada’s plan for the safe, long-term management of used nuclear fuel. The NWMO is working to implement Canada’s plan, in a manner that protects both people and the environment. Canada’s plan calls for containment and isolation of used nuclear fuel in a deep geological repository, which is made up of a series of natural and engineered barriers. This facility will be located in an area with informed, willing hosts within a suitable rock formation. In 2010, the NWMO initiated a nine-step site selection process to seek an informed and willing community to host Canada’s deep geological repository. The geoscience site evaluation process includes three main technical evaluation steps to assess the suitability of candidate areas in a stepwise manner. By the end of 2012, twenty-two communities had expressed interest in learning more about the project. As of 2021, two areas remain in the site selection process. The NWMO is on track to identify a single, preferred location for this facility by approximately 2023. This paper describes the approach, methods and criteria being used to assess the geoscientific suitability of communities currently involved in the site selection process. Activities to interweave Indigenous Traditional Knowledge with western science are also discussed.
MENDETEKSI AREA PLAT KENDARAAN MENGGUNAKAN METODE MAXIMALLY STABLE EXTREMAL REGION DAN STROKE WIDTH TRANSFORM

The increase in the number of vehicles in Indonesia occurs very rapidly every year. With the large increase in the number of vehicles, it can cause several problems such as the process of making new plates, extending the validity period of vehicle plate numbers, identifying vehicle accidents, falsifying vehicle numbers, identifying cases of vehicle theft, and violating traffic signs. This research was conducted to detect the vehicle plate area of ??a car. Vehicle plate area detection is carried out with three conditions, namely: fully detected condition, partially detected condition (partial), and undetected condition. The method used to detect the vehicle plate area of ??a car using two methods, namely: the Maximally Stable Extremal Region method and the Stroke Width Transform method. The test results showed a fully detectable accuracy rate of 80%, a partial detectable accuracy rate of 13.3%, an undetectable accuracy rate of 6.67%.
Observation of Nursing Care of Patients with Acute Severe Pulmonary Embolism after General Surgery under Microscope

Acute pulmonary embolism (APE) is one of the common acute and critical illnesses in clinical medicine, and it is another high cause of death after heart disease, cancer and cardiovascular disease. Despite the unremitting research and exploration of many relevant experts in recent years, major progress has been made in diagnosis and treatment, but the clinical manifestations of acute pulmonary embolism are not specific, and there is a lack of effective and definite methods for diagnosis. The mortality rate of patients with acute pulmonary embolism remains high. Furthermore, the combination of multiple postoperative diseases caused by general surgery can also increase the mortality of patients. Based on this, this article uses microscope technology to study and analyze the pretreatment methods and nursing methods of patients with acute severe pulmonary embolism after general surgery to improve the condition of patients with acute pulmonary embolism and increase their recovery rate, hoping to be the domestic acute pulmonary embolism The treatment provides reference and reference. This article first summarizes the relevant theories of surgery and acute pulmonary embolism, and then uses experimental methods, data analysis methods, survey methods and comparison methods, and SPSS 22.0 statistical analysis software technology to observe the efficacy of patients after thrombolytic therapy through a microscope. It is concluded that in the sample data of 50 cases, the significant rate accounts for 58%, the effective rate accounts for 36%, and the inefficiency accounts for 6%, confirming the positive impact of early thrombolytic therapy on patients with acute pulmonary embolism. Finally, through the microscope observation and comparison of the patient’s physical signs before and after nursing, it is concluded that timely and effective nursing after surgery has a great effect on improving the treatment rate of patients.
Educational practitioners as designers of seamless learning : Lessons from a seamless learning scenarios design experience

In theory, seamless learning design and research with its focus on bridging gaps in learning across contexts can help formulate answers to educational challenges. The recent mass lockdown due to the Covid-19 pandemic causing education to urgently switch from school-based to online teaching is just one of the many examples in support of design for continuity of learning. In over twenty years of its history, seamless learning has accumulated a substantial body of knowledge of what learning across contexts entails and how bridges across boundaries can be designed. However, seamless learning principles and guidelines to design for continuity of learning with the help of e.g., ubiquitous mobile technologies still need to find their way into educational practice. The study focuses on the outcomes of a hands-on activity in designing seamless learning scenarios. This activity included getting acquainted with the basics of seamless learning and designing a seamless learning scenario. It was part of an event organized for educational practitioners interested in the topic of seamless learning. Analysis of the seamless learning scenarios collaboratively designed during this activity demonstrated that teachers build on inquiry-based learning and problem-based learning paradigms to design learning that combines in-school, out-of-school and online contexts. They were able to include location-based content in school and teacher-led scenarios, however, ideas on the use of mobile technology were still described rather vaguely. Crossing boundaries and removing seams between contexts, did not yet become apparent in these initial teachers’ designs.
Semantically Secured Non-Deterministic Blum–Goldwasser Time-Based One-Time Password Cryptography for Cloud Data Storage Security

The security level of outsourced data is significant in cloud storage. Few research works have been designed for secured cloud data storage. However, the data security level was lower because the authentication performance was not effective. In order to overcome such drawbacks, a Semantically Secured Non-Deterministic Blum–Goldwasser Time-Based One-Time Password Cryptography (SSNBTOPC) Technique is proposed. The SSNBTOPC Technique comprises three steps, namely key generation, data encryption and data decryption for improving cloud data storage security with lower cost. Initially, in SSNBTOPC Technique, the client registers his/her detail to the cloud server. After registering, the cloud server generates the public key and secret key for each client. Then, clients in cloud encrypt their data with the public key and send the encrypted data to the cloud server for storing it in the database. Whenever the client needs to store or access the data on cloud storage, the client sends the request message to the cloud server. After getting the requests, cloud server authenticates the clients using their secret key and Time-based One-Time Password (TOTP). After the verification process, SSNBTOPC Technique allows only authorized clients to get data on cloud storage. During data accessing process, the client data is decrypted with their private key. This helps for SSNBTOPC Technique to improve the cloud storage security with a minimal amount of time. The SSNBTOPC Technique carried outs the experimental evaluation using factors such as authentication accuracy, computational cost and data security level with respect to a number of client and data. The experimental result shows that the SSNBTOPC Technique is able to increases the data security level and also reduces the computational cost of cloud storage when compared to state-of-the-art works.
Tag generation method based on topic information

The traditional tag generation method of text resources is only based on the information of the text itself. However, it ignores words with low frequency but high topic relevance, resulting in low accuracy of tag generation. So, this paper bases on the traditional TextRank model, using the document-topic distribution and the distribution of words under the corresponding topics to measure the importance of words in the document, to adjust the random jump probability of nodes. Then, the similarity between word vectors and statistical feature information are used to update the weight of word nodes iteratively. As a result, a new word graph model is constructed to generate text tags. Compared with the traditional TF-IDF, TextRank and other related algorithms, the experimental results of our model on real datasets demonstrate the effectiveness of our proposed method, which has a certain improvement in accuracy, recall and F value.
Saliency-Guided Deep Learning Network for Automatic Target Delineation in Post-Operative Stereotactic Partial Breast Irradiation

To accommodate an efficient clinical workflow in partial breast irradiation (PBI), fast, accurate and automated target delineation is desired. In this study, we develop a saliency-based deep learning segmentation (SDL-Seg) algorithm by incorporating prior domain knowledge for automatic gross tumor volume (GTV) delineation in post-op breast irradiation.Our approach incorporates saliency information into a deep learning model U-Net for target delineation. The level of saliency of image regions are described as how likely that region would attract physicians' visual attention. The visual saliency maps were generated using the surgical clip's location identified on CT images. A distance-transformation coupled with a Gaussian filter were then adopted to convert markers' locations to probability maps. The CT images and the corresponding probability maps form a two-channel input for the first convolution layer of the segmentation network. Such design forces the model to encode the location-related features guiding the network to focus on regions with high saliency levels and suppresses low saliency regions. The dataset used for model training, validation and testing (19:5:5) is comprised of 145 prone CT images from 29 post-operative breast cancer patients, who had implanted markers and received 5-fraction PBI regimen on GammaPod. We used the Dice similarity coefficient (DSC), 95 percentile Hausdorff distance (HD95) and average symmetric surface distance (ASD) to assess segmentation results by SDL-Seg and compared it with those generated by basic U-Net.Our model achieves mean (standard deviation) of 76.4% (2.7%), 6.76 (1.83) mm, and 1.9 (0.66) mm for DSC, HD95, and ASD, respectively, outperforming basic U-Net by 13.8%, 1.63 mm, and 0.9 mm. For all 5 testing cases, the saliency-guided U-Net showed increased DSC compared to basic U-Net. Table1, demonstrates the DSC results for 5 test cases using our SDL-Seg and basic U-Net.We developed a deep learning model integrating visual saliency information into the network for GTV delineation. Results demonstrate that SDL-Seg outperforms basic U-Net and is a promising approach for efficient and accurate target delineation in PBI. Such real-time delineation tool is highly desired by the on-line treatment planning workflow, such as GammaPod.
Awareness and use of Open Access (OA) Publishing Platforms by Faculty members of Imo State University, Owerri, Nigeria

The study examined awareness and use of open access publishing platforms by faculty members of Imo State University, Owerri (IMSU), Nigeria. The study adopted the descriptive survey design. Findings of the study revealed acceptable level of awareness and usage of open access publishing platforms by faculty members of Imo State University, Owerri; possession of skills and knowledge of access and usage of open access platforms; factors facilitate the use of open access platforms by the faculty members; confidence and willingness amongst  faculty members in using open access platforms; reasons for failure to use open access platform by lecturer of the university.
The Networked Smart Gadgets and Their Role(s) in Enhancing Learning Autonomy in Higher Education’s EFL Context

The present study explores the perceptions of EFL teachers in higher education on the role of handheld networked devices in promoting autonomous learning. In this project 43 male teachers from King Abdulaziz University (KAU) and the University of Jeddah (UJ) in Saudi Arabia (KSA) responded to a survey. Qualitative data, on the other hand, was gathered through a silent interview where informants answered five open-ended questions related to study’s research questions. The findings revealed the participants value the usefulness of smartphones in enhancing autonomy in language learning. They were also of the view that smartphones have beneficial characteristics when used in actual classroom. In addition, the results show that most of the participants are for a purposeful and guided integration of this type of technology in order to help learners develop the required linguistic and extra-linguistic skills. Equally important was the finding that use the of smartphones along well-developed L2 learning applications in language learning cannot replace the teachers’ vital and crucial role in the whole learning process.
The scenario of reducing peak discharge on Sampean River using natural reservoir in Situbondo regency

The flood often occurs in several regions in Indonesia, one of which is the Sampean River which flows from the Bondowoso Regency and has an estuary in Situbondo Regency. Situbondo Regency, located at the estuary, has been flooded in recent years due to the overflow of the Sampean River. This study aims to reduce flood discharge in the Sampean River by planning the usage of several reservoir scenarios that utilize the natural reservoir. Scenario A is planned by utilizing 1 reservoir, scenario B is planned by utilizing 2 reservoir, scenario C is planned by utilizing 3 reservoirs. Based on the maximum capacity of the Sampean River, the C scenario reservoir which has a total flow capacity of 1149.2 m3/second is used, so that the overflow can be reduced from 1985.1 m3/second to 835.9 m3/second. On the other hand, in scenario A and scenario B show the total capacity to hold the discharge is 542.9 m3/second and 915.5 m3 s/second respectively. All reservoir scenario plannings are able to reduce flood discharge with a percentage of 27.3% for scenario A, 46.1% for scenario B, and 57.9 for scenario C.
Analysis of Institut Ruangrupa’s Alternative Art Education During 2015-2018

Since 2000, ruangrupa (Jakarta-based art collective) has had an alternative art informationdistribution (alternative of the formal art education). They offer values which arise fromcollective processes such as mutual sharing. The establishment of Institut Ruangrupa in2015-2018 focused on the topic of art education through discursive and collaborative artspractices. The collaboration carried out with Dewan Kesenian Jakarta at the Jakarta Biennale2015 produced a program called ‘Maju Kena Mundur Kena Academy’. This paper will analyzethe method of the Institut Ruangrupa’s alternative art education which utilize a joint networkwith Arts Collaboratory (an art organization consisted of more than 20 organizations fromAfrica, Asia, Latin America and the Middle East). The purpose of this research is to provide adetailed description of the background and methods of ruangrupa’s alternative art education.This research built upon the theory of collaborative learning initiated by John Dewey, alearning concept that place community as the center. Ruangrupa through dynamic educationstyles exercise collaborative artistic projects with already established national and internationalconnections and resources. In conclusion, the art education practice of Institut Ruangrupa byplacing collectivism as the main idea, utilizing communication network relationships andcollaborative work that is oriented towards problem solving, is able to become one of thealternative methods in an effort to reformulate the practice of art education, especially inIndonesia.Keywords: art education; collaborative; ruangrupa.
Path finding and guidance algorithms for autonomous mobile robots in a tree structure network

Abstract Considering an autonomous mobile robot that has to navigate indoor and outdoor from a certain point towards another certain point in a tree structure, the paper is giving a solution for finding the path and navigation. The mathematical model is proposed for a number n DP of departure/destination points (DP), a number n IP of intersection points (IP) and connections between them in a tree structure. Based on mathematical model, the problems solved and presented in this paper are i) to find a path from any departure point to any destination point, ii) to generate an algorithm for guidance of an autonomous robot to follow the path. Both algorithms were tested on Matlab Simulink® environment. An implementation of algorithms in a pseudocode is presented. The algorithms were adapted to be implemented on a microcontroller based board. The advantage of algorithms and implementation is simplicity. The outcome is less memory consumption and increased computing and execution speed.
Computer Aided Diagnosis (CAD) Untuk Usus Besar Berdasarkan Citra Colonoscopy

The intestine is part of the human digestive system which starts from the stomach to the anus which consists of two parts, namely the small intestine and the large intestine (colon). Many types of diseases and inflammation that occur in the large intestine are caused by many factors, where if the inflammation gets worse it can cause colon cancer. In the medical world, conventional disease detection is based on detection by taking blood tests or tissue samples using a microscope that can be seen visually with the human eye. Taking a test like this may result in errors that will affect the final diagnosis of the disease. So in the final project, a Computer Aided Diagnosis (CAD) system was made to be able to detect and classify the types of diseases in the large intestine from the colonoscopy image using the Adaptive Neuro Fuzzy Inference System (ANFIS) method quickly and accurately so as to ease the work of medical professionals.
Socially Psychological Education of Self-Development Skills in Future Teachers Functions

The article is devoted to the socio-psychological aspects of the development of the ability for self-development in future teachers. The article also discusses issues such as psychological foundations, socio-psychological determinants, professional motivations formed by teachers, tolerance and empathic abilities that affect the ability to work on oneself in pedagogical activity.
Reflections on Using the Blockchain for Logistics and Supply Chain Management.

In an environment characterized by far-reaching digital mutations, connected objects, big data, platforms, etc., blockchain technology may lead to profound changes in the management of the logistics chains. This raises the question of the potentialities of such an innovative technology for logistics and, more generally, for SCM and its principles for managing flows and processes. This article proposes a forward-looking viewpoint on the uses of this technology for logistics and Supply Chain Management.
Redundancy in ELF: A Corpus-Based Study on Negative and Modal Concord

English as a lingua franca (henceforth ELF) is a contact language that has attracted great attention due to its unique global role. Thus, numerous studies have been conducted to determine its characteristics, among which research on such processes as, for example, simplification, added prominence or redundancy underlying language use in the ELF context is of the main interest. Therefore, the paper aims to broaden the per- spective on redundancy in ELF, focusing on negative and modal concord in spoken and written data. With the reliance on VOICE, ELFA, and WrELFA corpora, the analysis shows that both phenomena are noticeable in ELF; however, while redundancy in terms of modal concord appears in spoken and written ELF, negative concord is characteristic only of spoken data.
Retrieval of Java Program Code Components using Case Based Reasoning CBR

Object Oriented Programming (OOP) facilitates to create libraries of reusable software components. The reusability approach in developing a new system can be applied to an existing system with prior modifications. The reusability definitely decreases the time and effort required for developing the new system. To support reusability of program code, a proper code retrieval process is necessary. It makes possible to search the similar code component of java programming environment. OOP paradigm has specific style of writing the program code. The program code is a collection of objects, classes and methods. It is very easy to store the cases and reuse or revise wherever necessary. To get the similarity between the program code components, it is necessary to have an efficient retrieval method. The retrieval phase can retrieve the program code components as classes, methods, and interfaces depending on components selection by the user. A purely case-based approach is adopted for revising or reusing the existing cases to solve the new problems. Case Based Reasoning (CBR) is the process of solving new problems based on the experience coming from similar past problems.
Visualização temporal no ensino de história: uma análise gráfica de ferramentas visuais didáticas de representação do tempo

didactic tools for representing time
A Novel Deep Residual Attention Network for Face Mosaic Removal

Deep learning used to achieve face mosaic removal is in full swing. In this paper, a novel deep residual attention network (DRAN) is proposed for face mosaic removal. Inspired by the application of attention mechanism, we apply channel attention (CA) and pixel attention (PA) to DRAN to make the network focus on more informative information. In addition, we improve the conventional pixel attention which we superimpose three convolutional kernels of different sizes. DRAN consists of an encoder and a decoder, which the clean and real face image is reconstructed by convolutional neural network. In the encoder, the feature maps of each convolutional layer are used as the input of CA, the output of CA is sent to PA, and the output of PA is directly concatenated with the corresponding feature maps of the decoder. As the same time, inspired by the residual learning, we propose the parallel residual block for more detailed feature extraction. Extensive experiments show that DRAN performs better than state-of-the-art methods, the best PSNR (peak signal-to-noise ratio) and SSIM (structural similarity index) based on the test set are 20.67 dB and 0.8509, respectively.