Reviewerly/exHarmony huggingface dataset:
IMPLEMENTASI KNOWLEDGE MANAGEMENT SEBAGAI ELEMEN JAWA TENGAH CORPORATE UNIVERSITY DI BADAN PENGEMBANGAN SUMBER DAYA MANUSIA DAERAH PROVINSI JAWA TENGAH IMPLEMENTASI KNOWLEDGE MANAGEMENT SEBAGAI ELEMEN JAWA TENGAH CORPORATE UNIVERSITY DI BADAN PENGEMBANGAN SUMBER DAYA MANUSIA DAERAH PROVINSI JAWA TENGAH: IMPLEMENTASI KNOWLEDGE MANAGEMENT SEBAGAI ELEMEN JAWA TENGAH CORPORATE UNIVERSITY DI BADAN PENGEMBANGAN SUMBER DAYA MANUSIA DAERAH PROVINSI JAWA TENGAH

This year, Central Java Province, Human Resources and Development Body (BPSDMD) was revised the 2018-2023 Strategic Plan (Renstra) document that focused on programs and activities that will strengthen the implementation of the Central Java Corporate University which has been launched since 2017. This research aimed to analyze the application of Knowledge Management as one of the requirements for the realization of Central Java Corporate University at BPSDMD of Central Java Province. This research used a descriptive inductive qualitative method that described everything related to the KM process and its implementation at BPSDMD in its realization as a Corporate University institution, by analyzing using the factors that were the key to the success of KM implementation in an organization or KM Critical Success Factors.The implementation of KM in BPSDMD from the process side was seen from the Central Java Corpu roadmap document, which has been integrated into annual programs and activities. As for the organizational structure, there was no special HR (Chief Knowledge Officer) to support KM and also the reward system for KM involvement was not well structured. In terms of implementing technology for knowledge management, especially information technology, BPSDMD already has an LMS-based and infrastructure network that was connected to all employees. Aspects of Human Resources in knowledge management, all employees have been involved in knowledge management under their duties.
Implementasi Algoritma Massey-Omura Cryptosistem Dalam Pengamanan Dokumen

A data transmission security system (secure data communication) is installed to prevent theft, damage, and misuse of data sent via computer networks. In practice, data theft takes the form of reading by unauthorized parties usually by tapping public channels. Computer network technology has been able to reduce and even eliminate the possibility of data damage due to poor physical connectivity, but interference can still occur because there is an element of intent that leads to misuse of the system from certain parties. This cryptosystem is an algorithm that provides a fairly high security which is not based on the secrecy of the algorithm (restricted algorithm), but is more emphasized on the security/confidentiality of the key used (modern cryptographic algorithms). The restricted algorithm is usually used by a group of people to exchange messages with each other, they create an encryption algorithm that is only known to members of that group, so that every time a group member leaves, the restricted algorithm must be replaced because of the possibility that group members who leave the group can leaking the algorithm. So every time a group member leaves, the algorithm used does not need to be changed, but only changes the key. Therefore, the author tries to use the Massey-Omura Algorithm whose implementation uses the ThreePass Protocol to generate prime numbers because the Massey-Omura algorithm is one of the asymmetric algorithms that factorizes large numbers to get the private key
Collaborative Representation for Deep Meta Metric Learning

Most metric learning methods utilize all training data to construct a single metric, and it is usually over-fitting on the "salient" feature. To overcome this issue, we propose a deep meta metric learning method based on collaborative representation. We construct multiple episodes from the original training data to train a general metric, where each episode consists of a query set and a support set. Then, we introduce a collaborative representation method, which fits the query sample with the support samples per class. We predict the query sample's label via the optimal fitness among the query sample and the support samples in each specific class. Besides, we adopt a hard mining strategy to learn a more discriminative metric according to increasing the training tasks' difficulty. Experiments verify that our method achieves state-of-the-art results on three re-ID benchmark datasets.
EFEKTIVITAS SISTEM PENERIMAAN PESERTA DIDIK BARU (PPDB) SECARA ONLINE DI SMPN 21 BATAM KEPULAUAN RIAU

The purpose of this study was to determine the effectiveness of the online New Student Admission System (PPDB) at SMPN 21 Batam in Batam City and to determine the factors that support and hinder its implementation. The research approach used to examine the effectiveness of the New Student Admission System (PPDB) at SMPN 21 Batam is qualitative. Data collection techniques used are interviews and documentation. Admission of new students online is quite efficient, but when viewed from the effectiveness point of view, it is actually effective because there are still many people who do not understand the procedure for registering online. Based on the results of interviews conducted by researchers with several research informants, it can be seen that the community has been able to adjust to the online new student registration system. The continuation of PPDB online, it was concluded that the implementation or continuity of online PPDB at SMP Negeri 21 Batam is getting better, people are increasingly understanding.
Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation

Prior studies on text-to-text generation typically assume that the model could figure out what to attend to in the input and what to include in the output via seq2seq learning, with only the parallel training data and no additional guidance.However, it remains unclear whether current models can preserve important concepts in the source input, as seq2seq learning does not have explicit focus on the concepts and commonly used evaluation metrics also treat concepts equally important as other tokens.In this paper, we present a systematic analysis that studies whether current seq2seq models, especially pre-trained language models, are good enough for preserving important input concepts and to what extent explicitly guiding generation with the concepts as lexical constraints is beneficial.We answer the above questions by conducting extensive analytical experiments on four representative text-to-text generation tasks.Based on the observations, we then propose a simple yet effective framework to automatically extract, denoise, and enforce important input concepts as lexical constraints.This new method performs comparably or better than its unconstrained counterpart on automatic metrics, demonstrates higher coverage for concept preservation, and receives better ratings in the human evaluation. 1
Visualizing the Academic Performance of Tertiary Student Using Sashimi Model

Data visualization made use of grade records and output charts that provide insights into the trends and ratios of the students' academic performance. Using Sashimi Model, the system exhibited efficiency despite the bulkiness of data. The researcher allocated databases for the imported data, for all the necessary, filtered data, and system housekeeping. Algorithms are created to develop several designs like data flow diagrams, entity-relationship diagrams, and architectural design. The results showed taken from the charts that many students successfully passed the subjects enrolled during the second semester class compared to the first semester and summer.
A BRIEF VIEW ON CULTIVATING STUDENTS' CREATIVE ABILITY IN COLLEGE CHINESE TEACHING

Chinese is one of the most important courses in China's educational subjects, a very important basic discipline. College Chinese language and literature, this course should be energetic, learning of college students' love and positive input. However, the innovation ability of Chinese teaching in China is still insufficient and lacks vitality. College Chinese teaching has not yet become a fortress that can provide talents for our country, and has not yet played a vanguard and exemplary role. This paper puts forward corresponding suggestions and suggestions on the problems existing in the current stage of cultivating students' innovative ability in college Chinese teaching classroom, so as to promote the better development of college Chinese education in China.
Deep 3D face recognition using 3D data augmentation and transfer learning

Abstract. Deep convolutional neural networks (DCNNs) have achieved humancomparable performance on challenging 2D face databases, outperforming all previous shallow methods. However, current 3D face recognition research still focuses on non-deep-learning methods due to the lack of large-scale 3D face databases. To address this, this paper proposes new 3D data augmentation methods: pose-based and channel-based augmentation. Experiments on three databases show that deep convolutional neural networks can be used effectively for 3D face recognition. Using a pose-augmented training set, an eight-layer convolutional neural network achieved 100%, 99% and 99% of validation accuracy on Photoface-10, FRGC-10 and Photoface-50 databases respectively. Also, successful channel-based augmentation, with five more artificial sessions per a three-channel image, showed that feature extraction in DCNNs is channel-invariant. It was found that transfer learning from a pre-trained deep neural network (e.g. VGG19) works for 3D face recognition, by fine-tuning the last few fully connected layersusing 3D facial scans. The performance of a bespoke DCNN was compared to a fine-tuned pre-trained DCNN. The bespoke DCNN could achieve competitive performance if enough training data were provided; however, transfer learning from a pre-trained model provides an advantage in training time, being at least 3times faster
Do Rameau's dances ‘impose physical movement’? A collaborative exploration

Girdlestone is far from alone in responding to the kinesthetic qualities in Rameau’s dance music; his statement, however, goes beyond an admiration of expressivity, and attributes to Rameau the role of choreographer as well as composer. Furthermore, Girdlestone accepts an aesthetic of literalism between music and dance that, in the view of many people today – scholars and performers alike – seems so redundant as to be implausible. In the absence of choreographies from the period, authors have aimed to test Girdlestone’s claim by evaluating the evidence in librettos and scores, and by using Rameau’s fullest set of choreographic annotations to construct hypothetical choreographies. Their perspective is historical; authors are not considering the choreographic choices being made today, but rather the question of what Rameau’s music might tell them about the movements of the dancers in his own day, when they pay close attention to his musical choices.
Junk Mail Analysis And Blocking

Email is one of the important tools used to send and receive the information.  Through email the internet users can send and receive images, text files, audio and video images.  Comparing other communication medium email is the simple and easiest way with low cost. Spam is the one type of the email message.  Spam is the unwanted message.  From 2004 onwards this unwanted messages are spread through internet. The advertisers send about their product and services through internet to multiple groups of peoples. The social problems are also sending to this type of spam mails.  Most of the internet users are affected by this type of spam messages. Sometimes this spam messages contains malwares.  If the user opens this malware spam message, the device entirely crashed.  Hackers also try to collect the confidential information from the users through spam mail.  To avoid such kind of problem various filter concepts are used.  This article proposed a Naive Bayes concept to filter the unwanted messages. Compared with other classifiers Naive Bayes approach provides better result.
A Machine Learning-based Decision Support System for Disaster Response: A Mobile Approach

Machine learning has become one of the most evolving innovations in the field of technology which has a great wide variety of applications. While disaster management, in the hope of the urgent response to the affected communities, the concept of the latter is attributed. The disaster is a serious disturbance in a society that causes human life, physical resources, financial and environmental losses that result from concerns on the ability of the community to handle using its own means and properties. Generally, the objective of this research is to develop a machine learning mobile-based system for disaster management that can respond in a timely manner and provides decision support on evacuation mapping, relief good operations, school allocation, and job assistance. The proponents considered the existing process of the various local government agencies on reaching out to the affected communities. The Agile method was employed on system development to ensure the efficiency and transparency of the actual system design. Based on system and unit testing, it was revealed that the system meets the specified requirements of the various agencies. Hence, the K-Means Clustering was utilized to produce information that enables the organization to efficiently make decisions, validate the results and improve the activities that support the risk reduction management. The study proved that the application of machine learning in Disaster Management can dramatically improve the actions and can manage the data in decision making for future references.
On the $(4nu,3)$-arcs in $PG(2,q)$ and the related linear codes

In this paper, we use an irreducible plane-cubic curves in the projective plane $PG(2,q)$ to construct (k,3)-arcs of size $4nu$ where $lceil frac{q+1-2sqrt{q}}{4}rceilleqnuleqlfloor frac{q+1+2sqrt{q}}{4} rfloor$. Each of these arcs gives rise to an error-correcting code that corrects the maximum possible number of errors for its length. Furthermore, we discuss the completeness of each arc. The isotropy subgroup of each arc are determined. All Griesmer codes that correspond to plane-cubic curves are given for $7leq qleq 37,q$ is a prime.
以“学”为中心的基因工程实验混合式教学设计与实施

Teaching in experiments of biology is important for the cultivation of life science talents. In view of the rapid development of life science and the increasing demand for research-oriented talent training, teaching in experiments of biology should set up a variety of learning outcomes: to train experimental skill, to cultivate students' experimental design and operation abilities, and to improve students' scientific thinking and innovative consciousness. We have carried out an educational reform on experimental genetic engineering blended course. In this paper, we introduced our methods of organizing online materials, the curriculum design of the blended course, the implementation details, and a preliminary analysis of teaching effects. We found that experimental genetic engineering blended course could support students' active learning and a learning-centered teaching model. Moreover, it could facilitate students' achievement of improving experimental skills, cultivating a rigorous scientific attitude, professional research quality and academic innovation ability.
Long-term Cross Adversarial Training: A Robust Meta-learning Method for Few-shot Classification Tasks

Meta-learning model can quickly adapt to new tasks using few-shot labeled data. However, despite achieving good generalization on few-shot classification tasks, it is still challenging to improve the adversarial robustness of the meta-learning model in few-shot learning. Although adversarial training (AT) methods such as Adversarial Query (AQ) can improve the adversarially robust performance of meta-learning models, AT is still computationally expensive training. On the other hand, meta-learning models trained with AT will drop significant accuracy on the original clean images. This paper proposed a meta-learning method on the adversarially robust neural network called Long-term Cross Adversarial Training (LCAT). LCAT will update meta-learning model parameters cross along the natural and adversarial sample distribution direction with long-term to improve both adversarial and clean few-shot classification accuracy. Due to cross-adversarial training, LCAT only needs half of the adversarial training epoch than AQ, resulting in a low adversarial training computation. Experiment results show that LCAT achieves superior performance both on the clean and adversarial few-shot classification accuracy than SOTA adversarial training methods for meta-learning models.
AN ENHANCEMENT OF TEXT TO SPEECH (TTS) SYSTEM USING RASPBERRY PI

The blind man suffered greatly until the famous French inventor Louis Braille developed Braille, a form of writing invented to enable the blind to read. It did this by making characters prominent symbols on paper, allowing reading to become simple. There are already many systems that read images and give voice output. More recently, since the computer appeared in the twentieth century, things became easier for our daily life. This coincided with the beginning of the disappearance of the book as a hard copy, and electronic copy books became an urgent need in the development of reading, writing to help the visually impaired. The main problem encountered with this project was: the difficulty in the recognition of handwriting, and changes in the forms of handwriting, size and the number of paragraphs, as well as the recognition hard to extract letters containing noise from the document. The goal of this work-design system was to design a system able to extract and recognize handwriting for the visually impaired, with improved portability, to recognize the font size of lines from 8 to 10 PT handwriting using the hardware of a Raspberry Pi3 device. Another goal was to increase the valid ability of the blind people to read handwritten text. The method of work first the hardware platform used: Raspberry Pi 3 model B with inbuilt 5 MP camera, headphone; a 3D printed reader arm; second the software used: python language for after image capture of handwriting, grey scale image processing, followed by a Tesseract algorithm for sampling characters, followed by OCR and TTS, adding pronunciation capability to recognized characters. The result of this project is the ability to recognize handwriting types successfully without errors, on the condition that they are regular, as well as the ability to read capital letter and small letter handwriting without errors, and to read size 8pt text successfully.
Development of the Medical Record File Folder Design in Medical Record Unit RSUD dr. H. Slamet Martodirdjo, Pamekasan city

All records of the patient's history of health service activities in the medical record file must be documented in a map or medical record document that can be a safeguard from loss, data leakage, data exchange, or damage. Fulfillment of needs and planning for the use of a medical record map is very important in documentation, because the planning of fulfilling the needs of the medical record map is expected to produce a good map design so that it can support the patient's clinical documentation quality.               The type of this research is descriptive analytic qualitative research with the subject of research in the form of filing officers and heads of medical record units and research objects in the form of medical record file folders. Data analysis using descriptive analysis.               The results showed that the medical record file folder in the RSUD Dr. RSUD dr. H. Slamet Martodirdjo Pamekasan Regency needs to develop the design because the medical record map currently used tends to have slippery material so that the map falls easily if it is arranged in a storage rack and the use of material is too thick so that it takes up a lot of space when stored on the medical record rack by observing aspects physical and content aspects.
Chinese Language Interference of Smart Vocational School Students in Written English

This research aims at investigating and describing the interference of Chinese Language (L1) in Written English (L2) by Smart Vocational School Chinese Students. The present study is limited to the discussion of syntactic interference instead of others such as lexical, phonological, and discourse interference. Qualitative data were collected from ten Chinese students at Smart Vocational School. The data were analyzed by using Miles and Huberman theory – data collection, data reduction, data display, and conclusion drawing. The findings of the present study are eight syntactic interferences occur in the English text written by Chinese students.  They are the syntactic interference on parts of speech (noun, adjective, verb), syntactic interference on tense, syntactic interference on pronoun, syntactic interference on auxiliary, syntactic interference on article (definite and indefinite), syntactic interference on noun indicating possession, syntactic interference on noun plurality, and syntactic interference on impersonal ‘there’ as sentence subject. The interferences occur either as the L1 rule is applied in L2 or the deviation of L2 as its non-existence in L1.
Culturology: conceptual and categorical framework in the research process logic

The purpose of the article is to analyze the conditions and stages in the formation of the conceptual-categorical framework of cultural sciences. The methodology is based on general scientific approaches such as terminological and systematic. The purpose and objectives of the publication define the use of such research methods as analysis, synthesis, generalization, which made it possible to clarify the meaning of a number of concepts and terms. Scientific Novelty. The degree of scientific research of the topic is concentrated in identifying the problems of interaction between the conceptual and categorical frameworks in various scientific fields, namely, history, philosophy, philology, aesthetics, ethics, art history, and logic, to shape up the research space. We conceptualize the idea of "formal logical structures": that is not a mechanical combination of concepts or categories, but developing a new system adapted to solving theoretical problems of cultural studies. The question about the validity of the ―borrowing‖ process that allows cultural studies to analyze theoretical problems related to other humanitarian fields is also touched upon. Conclusion. So, among the other Ukrainian human sciences, cultural studies are developing quite actively and dynamically, constantly expanding its research space; its activity and dynamism of the cultural knowledge ―accumulation‖ determine those problems requiring special attention of modern scientists; in particular, the identification of the structural layering of the conceptual and categorical framework of cultural sciences.
Students Experience on Reading Story Book About Medicinal Plants: A Survey Study

Children's storybooks can provide a variety of information in a series of fantasy stories. One example is health information which contains knowledge about medicinal plants which is packaged with a specific theme according to student interests. However, there are still few students who know about medicinal plants. The research objective was to find out students' experiences about the storybooks they had read, especially about medicinal plants. This research uses a quantitative approach and uses a survey method. A total of 86 students of grade IV SD were selected by random sampling. The results showed that 57% of respondents or as many as 49 students had never read a health-themed storybook containing information about medicinal plants, 34.9% of respondents or 30 students had read it, and 8.1% or seven people. students hesitate. So, from the research data, it can be concluded that there is a need to introduce storybooks about medicinal plants to students.