Reviewerly/exHarmony huggingface dataset:
Study on the combination of Delphi method and analytic hierarchy process to construct the competency evaluation index of psychiatric nursing staff

Objective To explore the effect of using Delphi method and analytic hierarchy process to construct the competency evaluation index of psychiatric nursing staff. Methods Using the questionnaire designed by the research team,the Delphi expert consultation was conducted on 23 experts who directly or indirectly engaged in psychiatric nursing work in Beijing. The weight of each index was calculated by analytic hierarchy process, and the evaluation index system of core competence of psychiatric nursing staff was established. Results The authority coefficient of the two rounds of consultation was 0.848 and 0.888 respectively, and the coordination coefficient of expert opinions in the two rounds of consultation was statistically significant(P<0.05). The competency evaluation index system of psychiatric nursing staff includes 5 first-class indicators, 15 second-class indicators and 64 third-class indicators. The importance score of all the indicators ranges from3.12 to 4.97. Conclusion It is scientific enough to use Delphi method and analytic hierarchy process successively to establish working competence evaluation index of psychiatric nursing staff, which is in line with the requirements of the development of this work. However, it still needs to be further verified by practitioners on a larger scale.
A NOVEL CODE COMPRESSION APPROACH FOR EMBEDDED RISC PROCESSOR

Now a days most of the processors are high performance RISC processors .This paper introduces a novel code compression approach for embedded RISC processor, which reduces the code size and improves the compression ratio. Code compression is the technique to reduce the program size using various code compression algorithms to original instruction sets. There are two methods of compression is used in this paper. One is Dictionary based and the other is statistical compression. Our implementation is assessed through various benchmarking performed on embedded programs. In this approach, an efficient code compression is achieved using lookup table and Canonical Huffman decoder.
Seeking coherence and switching reasoning after forgetting an equation

Selection and application of an appropriate equation is a key step in instructional problem-solving strategies.But what if one cannot exactly recall the relevant equation?We are currently investigating how coherence between physical and mathematical reasoning opens multiple solution pathways for qualitative physics problems.In one-on-one interviews, community college students, 4-year college undergraduates, and graduate students solved qualitative introductory-level E&M questions.Analysis of 18 interviews showed that while many students had initial difficulty in recalling a relevant equation, they demonstrated strategies for making progress.We present two cases from the data corpus.One interviewee was unsure whether the time constant for an RC circuit is RC or 1/(RC) and sought coherence with qualitative reasoning to determine the correct expression.Another student switched to reasoning qualitatively from a physical model after noting that they could not recall a relevant equation.These examples show how mathematical and physical reasoning is opportunistically incorporated in students' problem solving.
Direct Differentiable Augmentation Search

Data augmentation has been an indispensable tool to improve the performance of deep neural networks, however the augmentation can hardly transfer among different tasks and datasets. Consequently, a recent trend is to adopt AutoML technique to learn proper augmentation policy without extensive hand-crafted tuning. In this paper, we propose an efficient differentiable search algorithm called Direct Differentiable Augmentation Search (DDAS). It exploits meta-learning with one-step gradient update and continuous relaxation to the expected training loss for efficient search. Our DDAS can achieve efficient augmentation search without relying on approximations such as Gumbel Softmax or second order gradient approximation. To further reduce the adverse effect of improper augmentations, we organize the search space into a two level hierarchy, in which we first decide whether to apply augmentation, and then determine the specific augmentation policy. On standard image classification benchmarks, our DDAS achieves state-of-the-art performance and efficiency tradeoff while reducing the search cost dramatically, e.g. 0.15 GPU hours for CIFAR-10. In addition, we also use DDAS to search augmentation for object detection task and achieve comparable performance with AutoAugment, while being 1000x faster.
Deep Learning Approach for Submerged Image Enhancement

Abstract: Because of underwater pictures application in ocean engineering, ocean research, marine biology, and marine archaeology to name a few, underwater picture enhancement was widely publicized in the last several years. Underwater photos frequently upshot in low contrast, blurred, color distortion, hazy, poor visible images. This is because of light attenuation, absorption, scattering (forward scattering and backward scattering), turbidity, floating particles. As a result, effective underwater picture solution must be developedin order to improve visibility, contrast, and color qualities for greater visual quality and optical attractiveness. Many underwater picture enhancing approaches have been proposed to overcome these challenges; however they all failed to produce accurate results. Hence for this we first undertook a large scale underwater image dataset which is trained by convolution neural network (CNN) and then we have studied and implemented a deep learning approach called very deep super resolution (VDSR) model for improving the color, contrast, and brightness of underwater photos by using different algorithms such as white balance, histogram equalization, and gamma correction respectively. Moreover, our method is compared with the existing method which reveals that our method surpassesthe existing methods Keywords: CNN, gamma correction, histogram equalization, underwater image enhancement, VDSR, white balance
IoT based Smart Face-Mask Dispensing Machine for Public

The COVID-19 pandemic has set the public eye on researchers, scientists and doctors who are working meticulously care for Covid patients, research on medicines and to develop vaccine for the virus and formulate health and safety conventions.Along with these people, innovative engineers who are being a part of the cause by inventing several interesting designs and products to make the combat the virus easier and to treat people safer.The usage of masks is very much essential for everyone nowadays to protect ourselves.The timely availability is much important.In schools and colleges or in public places like railway stations, airports, bus stations while travelling people might find it difficult to find the stores or shops selling to get a mask.Hence it is necessary to have a vending machine for easy access and availability at all times.This paper discusses the concept of an automated smart vending machine.The flexible Internet of Things (IoT) platform involves high customizability with a good Prognostics & Health Management media.An implementation of the framework is worked upon, discussing the design of a mask-dispensing unit that can be used in schools, colleges and other public places of medium to a large gathering.The mask can be dispensed without any human intervention at the same time as maintaining high levels of well-being and reducing the cause of virus spread.
An Optimal Approach to Detect the Human Heads using H-MTF in Crowded Scenes

Due to the increase in the number of people at crowded places leads to some disaster events, there is a necessity to detect the human heads and estimate the crowd density. The counting of the human heads is quite an immense topic in computer vision and digital image processing. This paper focuses on sample frames that are to be extracted from the crowd video UCF_HDDC and S_HOCK datasets. Our proposed Hybridization-Multiple Target Features (H-MTF) method, detects head objects using three prominent features: texture, color, and shape (T, C, and S). With the help of H-MTF, the optimal value can be estimated to detect the exact spot of the head in a crowded place. By applying two evaluation metrics: (i) Average Precision metric (AvP) and (ii) Average Recall metric (AvR), H-MTF has been compared with the existing methods using 2 different datasets. The results are shown in terms of AvP and AvR and our H-MTF method outcomes best from the existing methods.
PENGARUH PENGGUNAAN MODEL GIVING QUESTION AND GETTING ANSWER (GQGA) DENGAN PERMAINAN KREATIF DALAM PEMBELAJARAN PKn PADA SISWA KELAS XI SMA NEGERI 2 SIBORONGBORONG TAHUN PELAJARAN 2019/2020

This research is motivated by the low student learning outcomes in Civics subjects because teachers still use the lecture method more often so that the activeness and creativity of students to ask and answer questions in the learning process is still not optimal so that students are less motivated in learning and it is not in accordance with the objectives of the 2013 curriculum. The purpose of this research is to determine the effect of using the Giving Question and Getting Answer (GQGA) model with creative games in civics learning in class XI students of SMA Negeri 2 Siborongborong in the 2019/2020 academic year. The method used in this research is classroom action research which lasts for two cycles consisting of four stages, namely planning, implementing, observing, and reflecting. Data collection was carried out through observation, tests and a list of questions.From the results of the data analysis, it shows that learning using the giving question and getting answer (GQGA) model has a positive impact in improving student learning outcomes in Civics subjects on Strengthening National Unity and Unity in the Unitary State of the Republic of Indonesia (NKRI). This can be seen from the increasing percentage of student learning completeness from before the treatment (Pre Cycle) the class average value was only 64.11%, after the application of the learning model giving questions and getting answers in cycle I the class average value increased to 72. , 79%, Then in cycle II the average value increased significantly to 83.73%.Thus, it can be concluded that learning activities using the giving question and getting answer (GQGA) model with creative games can improve learning outcomes for class XI students of SMA Negeri 2 Siborongborong in the 2019/2020 Academic Year of North Tapanuli Regency for the 2019/2020 Academic Year.
Using Board Games Activities in Developing Iraqi EFL Preparatory School Students' Performance in Reading Skills

Learning a second language can be challenging and demanding, especially for teachers, as they are required to continuously innovate and improve their teaching by integrating new strategies and techniques into the classroom environment. Hence, the present study intents to examine the effect of board games activities on Iraqi Preparatory school students’ reading skills. A quantitative research method is adopted, and a sample of (30) preparatory school students is randomly chosen to exemplify the two sets of the research (the control and experimental groups). The study adopts a pre-test post-test design to measure the influence of the strategy. The first hypothesis is accepted, and the researcher concluded that indeed board games activities help in developing the students’ reading skills; however, other studies could concur or find different results.
Teaching Practice as the Basic Nucleus of Research, Innovation and Professional Skills

The pedagogical practice or pre-professional practice in teacher training, constitutes the ideal and necessary basic nucleus in the development of educational research, pedagogical innovation and professional competences, since through practice these are integrated into a single process pedagogical, since it allows the research to be carried out as part of the teaching activity, in such a way that the educational activity is constituted in the real and concrete object of study, simultaneously the teaching practice as creative development is constituted in a singular form of pedagogical innovation by the teacher or practitioner, who applies the theory of education to real events, in the classroom or school; Thus, jointly, research and innovation are part of the development of the professional competences of the future teacher and / or perfect the teacher's abilities in the exercise of their pedagogical work; in such a way that, the strategies, methods and / or techniques of the teaching activity are at the same time strategies, methods and / or techniques of pedagogical innovation and research instruments, as pedagogical innovation is constituted in the test model or test, as a process of experimentation; the class, the lesson or the pedagogical activity of the teacher are constituted in the research laboratory. The purpose of this document is to describe and illustrate this singular phenomenon, about how research, innovation and professional competences are articulated through pre-professional teaching practice.
Improved Algorithm for the Incremental Assignment Problem

The Assignment Problem is a basic combinatorial optimization problem. In a weighted bipartite graph, the Assignment Problem is to find the largest sum of weights matching. The Hungarian method is a well-known algorithm, which is combinatorial optimization. Adding a new row and a new column to a weighted bipartite graph is called the Incremental Assignment Problem (IAP). The algorithm of the Incremental Assignment Problem utilizes the given optimal solution (the maximum weighted matching) and the dual variables to solve the matrix after extending the bipartite graph. This paper proposes an improvement of the Incremental Assignment Algorithm (IAA), named the Improved Incremental Assignment Algorithm (IIAA). The improved algorithm will save the operation time and operation space to find the optimal solution (the maximum weighted matching) of the bipartite graph.
Two-Fold Security Model Using 2D-Vector Key Bunch and Privacy Preservation of the EHRs in the Distributed Network Involving Blockchain

With the promising features of decentralization offered by distributed ledgers such as blockchain, they are exceedingly useful in storing the give-and-take particulars of contractual interactions. The distinct characteristics of immutability, high security, transparency, and tamperproof data present in the blockchain make the technology sought after for applications dealing with information exchange over public channels. The use of blockchain as a substitute for the database in applications has cut down the third-party interference while exchanging the contents of the database or appending the information in the database are made, thereby reaching a consensus in the trustless conditions. The operational inefficiencies are reduced to a large extent, thereby saving money. Among other potential use-cases, the healthcare industry is one of the foremost sectors, wherein the private and sensitive details of the persons undergoing medical treatments for their ailments are staged in the databases managed by healthcare agencies like hospitals, clinics, nursing homes, diagnostic centers, etc. The key role of managing and sharing of the patients’ details are with the primary agency where the data has originated. Patient records contain attributes which reveal the identity of the patient, medical condition, and social security and economic status. The fields of a hospital dataset, like the social security number, specific medical treatment details, past medical case-sheet, insurance agency and claims particulars, occupation, and financial status, are vulnerable to attacks and misuse. In this chapter, a permissioned blockchain-based technique is developed for preserving the privacy of the electronic healthcare data of the patients and giving access rights to the owner of the data—that is, the patient—to assign the privileges to the trustworthy entities in the network of the patient’s choice. The sensitive parameters of electronic health records (EHRs) are encrypted using the computationally fast and strong cipher involving the key bunch matrix. The cipher under discussion is also easily adaptable in the environments with low computing configurations. Unlike most of the classical block ciphers, which depend upon the length of the key size in binary bits, the blockchain-based privacy preservation system provides further flexibility of enhancing the key size with minimal additional computational cost. The inherent features of the blockchain-involved information exchange, additionally with the security and privacy preservation techniques, enable the application to be readily adapted to the public networks as well as public/open blockchains.
Attention-based Multi-Reference Learning for Image Super-Resolution

This paper proposes a novel Attention-based Multi-Reference Super-resolution network (AMRSR) that, given a low-resolution image, learns to adaptively transfer the most similar texture from multiple reference images to the super-resolution output whilst maintaining spatial coherence. The use of multiple reference images together with attention-based sampling is demonstrated to achieve significantly improved performance over state-of-the-art reference super-resolution approaches on multiple benchmark datasets. Reference super-resolution approaches have recently been proposed to overcome the ill-posed problem of image super-resolution by providing additional information from a high-resolution reference image. Multi-reference super-resolution extends this approach by providing a more diverse pool of image features to overcome the inherent information deficit whilst maintaining memory efficiency. A novel hierarchical attention-based sampling approach is introduced to learn the similarity between low-resolution image features and multiple reference images based on a perceptual loss. Ablation demonstrates the contribution of both multi-reference and hierarchical attention-based sampling to overall performance. Perceptual and quantitative ground-truth evaluation demonstrates significant improvement in performance even when the reference images deviate significantly from the target image. The project website can be found at this https URL
Penerapan Dupak Online bagi pustakawan di Kementerian Pertanian

The achievements of librarians' work are shown by their success in carrying out every item of activities as stated in Permenpan no. 9 of 2014 and the regulation of the Head of the National Library No. 11 of 2015. To get credit numbers, each librarian must make a list of proposals for credit number submission (DUPAK). During this time, dupak proposals made by librarians vary greatly. There are librarians who quickly collect dupak, there are librarians who have difficulty making DUPAK so that it takes a long time for many years, some are at all up to the end of dupak's proposed tolerance, which is five years still can’t make dupak even end up with dismissal as a functional official librarian. This paper aims to provide an explanation of the use of online DUPAK applications for librarians in compiling DUPAK. To improve the ease and speed of the process of preparing and collecting DUPAK librarians, DUPAK online can help librarians in the Ministry of Agriculture. For the TPJP secretariat the application can accelerate the delivery of DUPAK from librarians and the provision of librarian staffing administration needs. But to achieve this, the assessment team needs to improve its competence in computerized operations. Librarians must be disciplined in compiling DUPAK in the way every completed work is immediately presented into the system, and more socialization is needed for librarians, assessment teams and members of the TPJP secretariat before dupak online application is applied to all librarians.
ANALYSIS OF HEAVY METALS POLLUTION USING POLLUTION LOAD INDEX (PLI) AND GEOACCUMULATION INDEX (I-GEO) IN THE VICINITY OF BUDDHA NULLAH STREAM IN LUDHIANA, PUNJAB

Heavy Metals are natural constituents of soils and their concentration varies depending on parental materials. The content of heavy metals in soils has increased due to human activities as distribution of fertilizers, pesticides, industries, waste disposal and air pollution. Due to these activities the life capacity of soils decreased, especially where the natural background is already high because of natural parental richness in heavy metal. As a matter of fact it is very important to distinguish between the natural background values and anthropogenic inputs, and to understand that the background values change from area to area and with the scale of the area investigated. Five stations along Buddha Nullah River in Ludhiana region were chosen to collect and assess the Mn, Ni, Pb, Cu and Cd contamination in sediments by using pollution load index (PLI) and geo-accumulation index (I-geo). Cd was found at the most reduced focus went between 0.5-1.4 µg/g dry weights. While, Mn was the most noteworthy running between 147-343 µg/g dry weight. Geo-aggregation record shows that the dregs in the greater part of considered stations were marginally contaminated (grade 1) as for Pb and Cd, while the residue in completely examined stations were unpolluted (grade 0) as for Mn, Cu and Ni. The upsides of Pollution Load Index (PLI) were observed to be exceptionally low, and shifted between 0.41-0.97, demonstrating that the contemplated stations in Buddha Nullah stream were unpolluted by absolute of studied heavy metals.
THE PROCESS OF FORMATION OF VALUE ORIENTATIONS PERSONALITIES IN PRACTICAL TRAINING

The article considers the process of formation of personality value orientations in practical activities during higher education, identifies the stages of this process, analyzes each stage, offers a theoretical analysis of practical activities for the formation of personality value orientations in the educational process. The phenomenon of culture as a second nature, which is created by man and in turn is its product, constantly brings to life many theories that try to understand the diversity of cultures, to determine the patterns of its development. They explain the features of the cultural-historical process, the role played by art and its integrative part – music, which is a necessary component of knowledge and value understanding of the world around us. The mechanisms of value orientation formed in pedagogy contradict the regulatory activity of teachers, who continue to offer means of mastering the world «in the finished form», which hinders the development of the process of ascent of the individual to the values ​​of life and culture. Practical activity on the formation of personality value orientations in music pedagogy can be defined as the formation of a creative personality, which strives for a holistic understanding of the musical space, occurs in several stages, each of which corresponds to the periodization of the process of personality value orientations. The formation of value orientations of the individual in practice is based on the concept of dialogic communication and is based on the formation of value orientations of the individual in the development of modern music, is built through the use of associative, genre-style and intonation-style approaches. The set of these approaches forms an evolutionary-synergetic method, which treats the object of study music culture – as a self-developing system, and the subject– the emerging personality – as a self-developing and self-tuning system. The formation of the mechanism of orientations is at the same time the formation of the mechanism of self-adjustment, which allows empathy, and this opens the way to co-creation.