Reviewerly/exHarmony huggingface dataset:
DEVELOPING LEADERSHIP CAPACITY IN APPLYING INFORMATION TECHNOLOGY IN TEACHING FOR PRINCIPALS OF ETHNIC MINORITY BOARDING SCHOOLS IN THE CENTRAL HIGHLANDS REGION - SITUATION AND SOLUTIONS

School leaders in the 21st century demand new knowledge, skills and ethical qualities. They need leadership in IT application in teaching. The leadership competence in IT application of school leaders is one of the focus currently emphasized when talking about the leadership capacity of school leaders in the 21st century. Teaching for principals is one of the important factors to develop human resources ready to meet the requirements of educational innovation.The author of the article through surveying the situation of leadership capacity development in applying information technology in teaching for the principals of ethnic minority boarding schools in the Central Highlands region, analyzing strengths and weaknesses, from there propose a system of solutions to develop leadership capacity in applying information technology in teaching for principals of ethnic minority boarding schools in the Central Highlands region in the context of the industrial revolution 4.0 and comprehensive fundamental innovation for general education in Vietnam in the current period.
Zambal_Lect Android Based Application

Information Technology (IT) plays an important role in the lives of every Filipino. In learning, IT offers tutorials, which includes e-books, computer aided instructions and others that promotes knowledge. IT affects the culture of Filipino people which includes language and innovations like electronic dictionaries.In Zambales the dialect used by the people is what they called Sambali, the dialect spoken primarily in municipalities of Zambales and in some other areas such as Infanta in Pangasinan, Panitian in Quezon, Palawan and Barangay Mandaragat or Buncag of Puerto Prinsesa. Another prominent dialect is known as Sambal Botolan, Ilocano and Tagalog were also used.The main objective of the study is to construct an android application that can store Tagalog words, provide its definition and as well as translation to other locale dialects currently used in Zambales such as Sambal Tina, Sambal Botolan, Ilocano and English.Majority of the respondents are students of IT related course. With the level of acceptance of Zambal_Lect Tagalog Dictionary Android application measured in terms of information in the app, user interaction, technical aspects and local dialect development and learning.There is a significant difference in learning words between the traditional dictionary and Zambal_Lect in Tagalog words translated in Sambal Tina, Sambal Botolan, Ilocano and English. The major factor that affects the interest and level of learning of respondents includes the following; age, type of smartphone used, length of smartphone usage and the major dialect used by respondents.
Class-incremental Learning using a Sequence of Partial Implicitly Regularized Classifiers

In class-incremental learning, the objective is to learn a number of classes sequentially without having access to the whole training data. However, due to a problem known as catastrophic forgetting, neural networks suffer substantial performance drop in such settings. The problem is often approached by experience replay, a method that stores a limited number of samples to be replayed in future steps to reduce forgetting of the learned classes. When using a pretrained network as a feature extractor, we show that instead of training a single classifier incrementally, it is better to train a number of specialized classifiers which do not interfere with each other yet can cooperatively predict a single class. Our experiments on CIFAR100 dataset show that the proposed method improves the performance over SOTA by a large margin.
중국과 베트남 결혼이주여성의 임신과 산후적응 요구 비교

Purpose: To identify needs for pregnancy and postpartum adaptation of Chinese immigrant women and Vietnamese immigrant women in South Korea.Methods: A descriptive research design was employed. Data were collected from 244 Chinese immigrant women and Vietnamese immigrant women from 3 provinces, 20 health care centers, and multi-cultural family support centers. Data were analyzed with descriptive statistics, t-test and ANOVA.Results: An average score for needs perceived by Chinese immigrant women was significantly higher than that perceived by Vietnamese immigrant women. There were significantly differences in physical and emotional adaptation after childbirth, nutrition during pregnancy, cross cultural understanding and personal respect, and adaptation daily activity during pregnancy between the 2 groups. The highest score of needs in Chinese immigrant women was for nutrition during pregnancy and that in Vietnamese immigrant women was for baby rearing and family support.Conclusion: Based on needs of pregnancy and postpartum adaption, nursing intervention program in consideration of cultural characteristics of Chinese immigrant women and Vietnam immigrant women need to be developed for their pregnancy and postpartum health care.
한국어 교사와 학습자의 이독성 요인에 대한 인식 차이

The purpose of this study is to examine the difference of recognition on the factor of Korean readability between Korean language teachers and academically-oriented foreign Korean language learners. To look into the difference of recognition on the factor of readability between the two groups, first, this author carried out a survey employing Likert’s scale, and the results of it underwent exploratory factor analysis by using SPSS 21. According to the analysis results, the difference of recognition was found between the two groups about the readability factor. Education on the readability of Korean language is distinctive from that about readability in either English or Korean because the subjects of learning are second language learners. If teachers properly understand the difference of those learners’ recognition and their distinctiveness, they will be able to provide efficient education for Korean reading. (Busan University Of Foreign Studies)
Sales and print publications prediction using fuzzy regression neural network

One of the main problems in predicting artificial neural networks is to provide the necessary data for prediction because neural networks need a lot of data to obtain accurate results. However, it should be noted that collecting the data required by the network is firstly very expensive and secondly requires a long time. Therefore, due to rapid changes in real environments, especially economic and financial systems, forecasting in these environments with a small amount of data must be effective and efficient. Fuzzy forecasting methods require less data than other methods due to the use of fuzzy numbers instead of definite numbers, but their performance is not always satisfactory. In this paper, artificial neural networks have been proposed by fuzzy regression to limit the amount of data required for networking and to obtain more accurate results for predicting publication sales. Experimental results show 95% of the effect in the proposed method and in predicting sales.
Cloud Data Security in Multi Model Attributes For Randomized Key Service Using Encryption Techniques

The growing size of information, security became the risk of access from centralized resource providers deploy them into cloud, where authorized users could access them. The nearly combined nature of cloud environment does not yet allow users to perceive the cloud resources and services in a split second. At the same time, they are upgrading. Also, attribute based encryption techniques are used towards the security development in few methods. Also, profile based approaches are used which uses different encryption keys according to user profile. However, all the methods suffer to achieve higher performance in datasecurity. To solve this issue and to improve the security performance, an efficient Service LevelAttributeBasedEncryption (SLABE)ispresented.Inthisapproach,themethoduses different key set of different services. For each attribute, the method maintains different keys for various services. According to the key belongs to the attributes and service, the method performs encryption and decryption. The method improves the performance in security and increases the throughput aswell. Further to improve the security performance, a multi attribute randomized key Service Level Encryption (MARK-SLE) scheme has been presented. In this approach, the method classifies the service and for each service, the method generates different key set according to the attributes accessed. The method selects the keys in a randomized approach and chooses the keys at different time session. Generated key has been used to perform encryption or decryption where the schemes of encryption also selected in a random manner. The proposed MARK-SLE algorithm improves the security performance than previous SLABEalgorithm. Third, a Service Level Scheduler Based Encryption (SLSBE) Scheme is presented. In this approach, the security in service level and scheduling strategy is considered. For each service available, the method maintains the set of attributes being accessed. For each level of service and attributes, the method uses different keys and encryption standards. At the reception of user request, the method identifies the service claimed and set of attributes.&#x0D;
PENGARUH PENGGUNAAN CODEC STANDART ITU G.729 TERHADAP SISTEM KOMUNIKASI VOIP

Voice over Internet Protocol (VoIP) is a technology that is capable of passing voice traffic, in the form of packets through the network Internet Protocol (IP). IP network itself is a data communications network based packet-switch. The voice signal before experiencing bundled voice coding or format conversion of sound into digital form that can be passed over an IP network. Telephony, Internet telephony, or termed VoIP (Voice Over Internet Protocol.This communication system use VoIP (Voice over Internet Protocol), ie voice calls over data services (internet). This communication was developed using Android-based devices. Based on characteristics, android devices are open source, so users do not need to have a license to be able to have android-based devices. In addition, the android device that must be connected to a SIP (Session Iniation Protocol) is a data service that can be done with a paid subscription of the user of the operator using a conventional pulse. Telecommunications designed will use a hybrid system, the merger between VoIP communications with data communications GSM network. With basic calculations where Coding standards G 729, is a standard that can be used for voice communication system through data networks with rate of 8 Kbps. The implementation of the G729 codec is effect on communication systems VOIP.
Maintaining The Status of Hydration on Mr. G With Pneumonia in Fatmawati Hospital

Pneumonia is a health problem in the world with a high mortality rate both in developing countries and in developed countries such as America, Canada and European countries. In Indonesia, the number three cause of death after cardiovascular disease and tuberculosis. Low socioeconomic factors increase mortality. This infection is generally spread from someone who is exposed in the neighborhood or has direct contact with infected people through their hands or by breathing air (droplets) due to coughing or sneezing. In the pandemic era, pneumonia is very feared because it is related to respiratory diseases which are becoming a trend and issue, so it requires special treatment in this case. This case report aims to improve the provision of nursing care for pneumonia patients to mantaining hydration status with airway clearance problems. Nursing assessment of pneumonia patients was carried out on September 13, 2020, a 52-year-old man who has a history of DM and smoking comes with complaints of coughing but no phlegm, fever since one week ago has disappeared, the patient has diarrhea since 2 days before entering the house pain and stomach pain, the patient also has nausea and vomiting and has no appetite. Nursing intervention for 3 days in accordance with the established outcome criteria. From the nursing intervension carried out, the problem of clearing the airway was resolved, marked by no coughing, normal breathing, no ronchi, moist mucosa and no cyanosis. Nursing intervention to maintaining the patient's adequate hydration status can overcome the problem of ineffective airway clearance.&#x0D; &#x0D; Keywords: Pneumonia, Airway Clearance, Hydration Status
Data repositories in information and communication sciences. An empirical study

This article offers a contribution to the ongoing debate within the Information and Communication Sciences community concerning the emergence of Open science. We present the results of an empirical study on digital devices implemented by and for researchers in Information and Communication Sciences in the field of research data management. What are the thematic and disciplinary data repositories in this discipline, and what are the generic repositories for the preservation and dissemination of research data? After a conceptual analysis of research data and warehouses, the article presents the results of an empirical study based on the Cat-OPIDoR and re3data directories, with information about their contents, metadata, disciplinary dimensions and geographic location. The discussion focuses on three aspects: certification and standardization; the issue of management, archiving and/or dissemination of data; and the impact of data management on the disciplinary community. By way of conclusion, the article offers some recommendations for the positioning of Information and Communication Sciences and for future research.
Penerapan Metode Dikte 听写 (Tīngxiě) dalam Peningkatan Kosakata Bahasa Mandarin

Abstract. This study aims to determine the planning process, implementation and results of the application of the Dictation 听写 (Tīngxiě) method in improving the vocabulary of Mandarin for grade VII students of SMP Kalam Kudus Makassar. Data collection methods used were tests, observation and documentation. This research consists of two types, namely qualitative and quantitative. This study consisted of two cycles and each cycle there were two meetings. The results showed that the average score obtained by students in the first cycle reached 75.28% and the second cycle reached 90.42%. These results indicate that the vocabulary of the seventh grade students of SMP Kalam Kudus Makassar increased by using the Dictation Method 听写 (Tīngxiě).
LibGuides: Library Tutorial Videos at YouTube Channel: Home

These tutorial video clips are created to give LTC students a library research orientation.
Homonymy and Polysemy Detection with Multilingual Information

Deciding whether a semantically ambiguous word is homonymous or polysemous is equivalent to establishing whether it has any pair of senses that are semantically unrelated. We present novel methods for this task that leverage information from multilingual lexical resources. We formally prove the theoretical properties that provide the foundation for our methods. In particular, we show how the One Homonym Per Translation hypothesis of Hauer and Kondrak (2020a) follows from the synset properties formulated by Hauer and Kondrak (2020b). Experimental evaluation shows that our approach sets a new state of the art for homonymy detection.
Image Super-Resolution Using Hybrid Attention Mechanism

Deep Convolutional Neural Networks (CNNs) show encouraging performance in image super-resolution (SR) by learning a nonlinear mapping function from low-resolution (LR) images to high-resolution (HR) images. The latest SR method focuses on the design of a deeper network structure. However, deeper network training is usually more difficult. In this paper, we propose a new end-to-end residual attention network (RAN). RAN is composed of a series of residual attention modules. We use two types of attention modules in the network, which can better explore the feature correlation in the channel and spatial dimensions and focus on learning high-frequency information. Experimental results show that our RAN is superior to the most state-of-the-art SR methods in terms of quantitative indicators PSNR and SSIM and visual perception.
Multi-layer Authentication Technique for Medical Image Authentication in Cloud Computing

Healthcare experts require propelled image processing programming to improve the nature of clinical decisions. Be that as it may, any interest in refined nearby applications would drastically build medicinal services costs. The healthcare data management system comprises records in various formats, for example, pictures, numeric, text, and video recordings prompting information which is enormous and unstructured. To address this issue, medical providers are keen on embracing cloud computing. This new concept targets boosting the incorporation of the latest information and communication technology in the medicinal service sectors. Innovations in the healthcare industry with new technology and populace development have offered to ascend to security threats to our personal information. One of the significant concerns of a cloud-based healthcare framework is the security aspect. However, guaranteeing security and elite needs more enhancements to meet the healthcare service prerequisites. To this end, a framework dependent on image processing for the authentication in the healthcare system is proposed.
Integrating Higher-Level Semantics into Robust Biomedical Name Representations

Neural encoders of biomedical names are typically considered robust if representations can be effectively exploited for various downstream NLP tasks. To achieve this, encoders need to model domain-specific biomedical semantics while rivaling the universal applicability of pretrained self-supervised representations. Previous work on robust representations has focused on learning low-level distinctions between names of fine-grained biomedical concepts. These fine-grained concepts can also be clustered together to reflect higher-level, more general semantic distinctions, such as grouping the names nettle sting and tick-borne fever together under the description puncture wound of skin. It has not yet been empirically confirmed that training biomedical name encoders on fine-grained distinctions automatically leads to bottom-up encoding of such higher-level semantics. In this paper, we show that this bottom-up effect exists, but that it is still relatively limited. As a solution, we propose a scalable multi-task training regime for biomedical name encoders which can also learn robust representations using only higher-level semantic classes. These representations can generalise both bottom-up as well as top-down among various semantic hierarchies. Moreover, we show how they can be used out-of-the-box for improved unsupervised detection of hypernyms, while retaining robust performance on various semantic relatedness benchmarks.
Research on the Development of Colleges and Universities Poetry Education in the Era of Media

As an important manifestation of Chinese excellent traditional culture, Chinese classical poetry has received increasing attention and recognition from all walks of life. In the context of the era of media, how to play the role of inheritance of poetry by universities can be explored through innovative teaching models. In order to inherit the traditional culture of poetry and give play to its practical guiding significance, colleges and universities should insist on creative transformation and innovative development, boldly explore new models of poetry education, offer extensive poetry courses, conduct in-depth poetry activities, vigorously create a poetry atmosphere, and continuously create new glories of Chinese culture.
Individual Features Of Development Of Information And Communicative Competence In Masters Of Higher Pedagogical Education

The article discusses some issues of the development of information and communication competence of masters of pedagogical sciences, modern methods of effective use of computer technologies and information, the use of programs for the use of information materials based on intellectual abilities in social and personal activities.
Robust Learning under Strong Noise via SQs

This work provides several new insights on the robustness of Kearns' statistical query framework against challenging label-noise models. First, we build on a recent result by \cite{DBLP:journals/corr/abs-2006-04787} that showed noise tolerance of distribution-independently evolvable concept classes under Massart noise. Specifically, we extend their characterization to more general noise models, including the Tsybakov model which considerably generalizes the Massart condition by allowing the flipping probability to be arbitrarily close to $\frac{1}{2}$ for a subset of the domain. As a corollary, we employ an evolutionary algorithm by \cite{DBLP:conf/colt/KanadeVV10} to obtain the first polynomial time algorithm with arbitrarily small excess error for learning linear threshold functions over any spherically symmetric distribution in the presence of spherically symmetric Tsybakov noise. Moreover, we posit access to a stronger oracle, in which for every labeled example we additionally obtain its flipping probability. In this model, we show that every SQ learnable class admits an efficient learning algorithm with OPT + $\epsilon$ misclassification error for a broad class of noise models. This setting substantially generalizes the widely-studied problem of classification under RCN with known noise rate, and corresponds to a non-convex optimization problem even when the noise function -- i.e. the flipping probabilities of all points -- is known in advance.
Analisis Faktor – Faktor Penyebab Banjir Di Kota Bekasi

Bekasi City is an area whose physical condition supports local floods, especially during the rainy season. This study has the following objectives: (1) Mapping the flood-prone areas in Bekasi City and analyzing the flood-prone areas in Bekasi City, (2) Knowing the dominant aspects that influence the occurrence of flood disasters in Bekasi City. The method used is descriptive quantitative analysis. Data analysis was conducted to determine the distribution of floods by scoring and overlapping: land use, slope, rainfall, and soil type. Knowing the dominant factors causing flooding using the correlation test. The results of the study concluded that: (1) The distribution of floods in Bekasi City was divided into 4 classes including very vulnerable classes with an area of 19.02 km² (9.03%) covering Jatisampurna, Jatiasih, Pondokgede, and Bantargebang Districts. The vulnerable class with an area of 23.47 km² (11.15%) includes Jatiasih, Pondokgede, Bantargebang, Rawalumbu, and West Bekasi Districts. Medium vulnerable class 117.17 km² (55.66%) covers the entire area of Bekasi City. Safe class 34.64 km² (78.66%) includes Bantargebang, Mustika Jaya, North Bekasi, West Bekasi, and Medan Satria Districts, (2) The dominant factor causing flooding in Bekasi City is known through a correlation test that the slope parameter is the dominant one. because the results of the correlation test get the highest value followed by land use, soil type, and rainfall that get the lowest score and the correlation value is weak.