Reviewerly/exHarmony huggingface dataset:
Sistem Pengelolahan Data Surat Masuk dan Surat Keluar Kelurahan Curug

An accurate and efficient application of incoming and outgoing report reports at the Curug Kelurahan Office, making an effective and efficient application of incoming and outgoing mail management in accordance with the needs of the Curug Kelurahan office, making applications that facilitate administration in mail management, making incoming mail applications and the user's outgoing mail, making an application for incoming and outgoing mail that is easily used by the user. The research method used to design this data processing application is the method of library study, observation and interviews to get more complete data. After the author designs and makes this data processing application, the writer can draw the conclusion that with this application can provide solutions in helping Curug Kelurahan in recording incoming and outgoing letters, with the application already made, the duties of the Administration and Secretary of the Village Head can be easier and better recorded because it is assisted by a computerized system.&#x0D; Keywords: System Design, Data Processing, Incoming and Outgoing
A Deep Learning for the Generation of Textual Story Corresponding to a Sequence of Images

Generating a short story for a sequence of images is much more interesting than generating a single line textual description for an image. Story generation involves relating the meaning of the previous image and the current image and continuing this through out the sequence of images. This can be helpful for better understanding of the situation. In this paper we present our idea of generating story using a CNN model which is pre trained on MSCOCO dataset that can detect objects and concepts of language modelling and NLP text pre-processing techniques . We used a custom stories dataset in which we manually labelled every sentence in every story. Number of sentences in the generated story is equal to the number of images. The results are quite accurate in many cases for a small custom stories dataset and the performance is expected to increase with a bigger dataset.
ТВОРЧЕ МИСЛЕННЯ ПЕДАГОГА, ЯК ОСНОВА ПРОФЕСІЙНОГО ВДОСКОНАЛЕННЯ

Introduction The problem of self-development and personality creativity has always been of interest to researchers. It can be argued that self-development and creativity can be taught. The solution of this problem is rational, while the process of creativity is irrational.The desire for constant self-improvement and development of creative thinking is important for the profession of a teacher. After all, the teacher could never consider his/her professional development to be complete. And in this fundamental openness, incompleteness, the fundamental feature of the development of his/her personality, the formation of his/her individual experience, professional self-consciousness and categorical structures of professional thinking is reflected. Particular importance of this problem comes at the stage of primary professionalization, while studying in high school.Purpose To study the psychological peculiarities of the development of the teacher's thinking and his/her self-improvement.Methods. The following research methods were used such as theoretical analysis of literature, generalization, observation and methods of A.V Lazukin, N.F Kalina to determine the level of self-actualization.Results It is proved that there are shortcomings in the psychological preparation of the future teacher, and it is stated that the university does not teach the future teacher to solve pedagogical problems.Originality The solution of the problem of reconstruction of constructive schemes requires from the teacher awareness (reflection) of its own categorical apparatus, its strengths and weaknesses, rethinking of the developed criteria for the analysis and assessment of educational phenomena on the basis of psychological and pedagogical theory. Thus, we proceed to one more, fundamentally significant, feature of pedagogical activity.Acquiring a teacher theoretical knowledge and accumulation of practical experience is a necessary, but insufficient professionalism. Only constant reflection, analysis and generalization of own experience allow the teacher to develop as a professional. The reflexive attitude of the teacher's competence to one's own activities is one of the most important psychological conditions for her in-depth awareness, critical analysis of constructive perfection. It is reflection that provides the opportunity to get out of the full hole in the immediate process, to take a position over it, beyond it to judge it Conclusion Formation of readiness for future professional-pedagogical activity involves the formation of thinking, which is based on the system of theoretical knowledge and manifests itself in the ability to use this knowledge, operate its in practice - in the process of decision-making in specific pedagogical circumstances, during training.
Design and Implementation of Task Scheduling Model for Cloud Computing Using Simevents

CONCLUSION AND FUTURE WORK1.The results of the research show that it is possible to design a simulation model for cloud computing systems using the Simevents program easily and exploit the possibilities of this program in testing different types of algorithms, as this program proved efficient in obtaining results matching the results of the program Cloudsim.2. We observe the superiority of the SJF algorithm on the FCFS algorithm.3. It is possible to design and study the status of change of tasks during the implementation of (dynamic) in future research.
SISTEM INFORMASI PEMINJAMAN DAN PENGEMBALIANREKAM MEDIS DENGAN BARCODE DAN NOTIFIKASI WHATSAPP DI RUMAH SAKIT WIJAYA KUSUMA LUMAJANG

The medical record file control activity at Wijaya Kusuma Lumajang Hospital has not been well implemented.This is evidenced by the absence of the use of tracers as a substitute for files that leave the medical recordrack and the use of expedition books only on borrowing inpatient medical record files. This study aims todesign and create a medical record lending and return information system with a barcode and web-basedWhatsApp notification at Wijaya Kusuma Lumajang Hospital that produces patient labels, tracers, reports onborrowing and return of medical records. This type of research is the development of a prototype method withqualitative data collection techniques in the form of interviews, observation, documentation, and brainstorming.The stages of the prototype method include analyzing user needs, making prototypes, adjusting prototypes tothe user's wishes, creating new systems, testing systems, adjusting the system to the user's wishes, andusing the system. The results of this study are information systems for borrowing and returning medicalrecords with a web-based barcode and WhatsApp notification system that facilitates the process of trackingfiles and overcoming problems in the process of borrowing and returning medical records
Integration of the PageRank Algorithm, Sequence Processing, and CPT+ for Webpage Access Prediction

In this article, we provide a novel model to address the issue of webpage access prediction. In particular, the main approach we propose aims to reduce execution time by reducing the sequence space. This solution combines calculation of PageRank values of sequences in sequence databases and analysis of sequences from these shortened sequence databases. To evaluate the solution, we chose K-fold validation with K = 10 by randomizing the dataset 10 times; then the system calculated the average PageRank values of sequences. Next, with acceptable accuracy (when the size of datasets was reduced by up to 30% by PageRank calculation), we performed next access page prediction by analysing 1000 sequences. Experimental results for the real FIFA dataset show that our new proposed approach is much better than previous approaches in terms of prediction execution time.
Identification and Contextual Semantic Retrieval of Polysemy Words

Polysemy is a spectacle where an individual word is associated with two or more different meanings. The distinction between polysemy and monosemy is that in monosemy, there is no presence of semantic ambiguity in language that is a word will have only one meaning. Polysemy escalates in natural language: pragmatically every word is polysemy up to a certain extent. This paper attempts to disambiguate a polysemy word and classify it to its correct sense based on its use in particular context. By taking into account the words which surround the polysemy word, the article tries to get the right sense out of it. Oxford dictionary is used to fetch the meaning of polysemy word. In this article, we use the information rich phrase or sentence as a key to identify polysemy word and illuminate it to its appropriate sense. The article is a novel approach to identify a polysemy word just like how hearers effortlessly reach at the contextually appropriate sense of word on a given occasion of use
High-precision earthquake location using source-specific station terms and inter-event waveform similarity

Earth and Space Science Open Archive This work has been accepted for publication in Journal of Geophysical Research - Solid Earth. Version of RecordESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary. Learn more about preprints. preprintOpen AccessYou are viewing the latest version by default [v2]High-precision earthquake location using source-specific station terms and inter-event waveform similarityAuthorsAnthonyLomaxiDAlexandrosSavvaidisiDSee all authors Anthony LomaxiDCorresponding Author• Submitting AuthorALomax ScientificiDhttps://orcid.org/0000-0002-7747-5990view email addressThe email was not providedcopy email addressAlexandros SavvaidisiDUniversity of Texas at AustiniDhttps://orcid.org/0000-0001-6373-5256view email addressThe email was not providedcopy email address
Ai &amp; Ml Based Advising System for Farmers Crop Production

The motivation behind a chatbot framework is to reproduce a human discussion; the chatbot design coordinates a language model and computational calculations to copy casual visit correspondence between a human client and a PC utilizing normal language. The assistant performing through chatbot by voice assisting to farmers for their queries. So, farmer talk with online assistant helps the farmer to ask details and purpose of product. The Agriculture is an only source for food production. The people who illiterate &amp; also literate difficult to use pesticides in farming due to not aware on fertilizers. There are millions of pesticide products are available in market for the agriculture based on needs like disease, insects, crop production growth. Some of them don’t know the purpose and uses of the pesticide. Every farmer first prefers top-most &amp; regularly using popular companies. This list of fertilizer products in the market is built on the basics of crop production growth or disease and insects. By using the technology to provide aware in farmer. If a farmer needs to know about a detail of product need to consult an agent or a fertilizer shop near are far away from farmers home-town farmer should travel, waste their money and time. Sometimes farmer wants product details So, AI &amp; ML are used built the assistant to provide awareness in farmers on fertilizers. By this assistant gave the detail of pesticides available in the market and save the farmer money no need to travel to consult an agent and fertilizer shop. AI &amp; ML of a chatbot store a products detail and an assistant interact the PC with farmer in their natural language.
Speaker Identification using Machine Learning

Whatever the modern achievement of deep learning for several terminology processing tasks, single-microphone, speaker-independent speech separation remains difficult for just two main things. The rest point is that the arbitrary arrangement of the goal and masker speakers in the combination (permutation problem), and also the following is the unidentified amount of speakers in the mix (output issue). We suggest a publication profound learning framework for speech modification, which handles both issues. We work with a neural network to project the specific time-frequency representation with the mixed-signal to a high-dimensional categorizing region. The time-frequency embeddings of the speaker have then made to an audience around corresponding attractor stage that is employed to figure out the time-frequency assignment with this speaker identifying a speaker using a blend of speakers together with the aid of neural networks employing deep learning. The purpose function for your machine is standard sign renovation error that allows finishing functioning throughout both evaluation and training periods. We assessed our system with all the voices of users three and two speaker mixes and also document similar or greater performance when compared with another advanced level, deep learning approaches for speech separation.
Introduction

The diversity of skills, knowledge, and experience exhibited by librarians in the digital humanities continues to extend, deepen, and evolve. The Digital Humanities: Implications for Librarians, Libraries, and Librarianship is a special issue of College and Undergraduate Libraries that reflects some of the challenges that occupy librarians who are engaging the academic community in the digital humanities. Librarians are discovering scholarly opportunities by transforming traditional physical collections into digital projects that highlight new insights. A major theme that permeates any discussion of digital humanities work is the concept of collaboration in that there is a variety of challenges in working with the stakeholders involved. Developing planning and project management skills is part of the traditional librarian education yet such skills are essential for developing successful digital humanities projects and are often learned ‘on the job.’ Many librarians courageously have moved beyond the one-time, 50-minute information literacy session.
Distributed Architecture for Secure, Attack-Resilient Crypto Currency Transactions for the Classified Temporal and Text Data

In the digital world, the crypto currency has to do with the use of tokens based on the distributed ledger technology in a secure manner. Crypto currency can be a resource on a block chain network or can be seen as a tool to perform the transactions ensuring the privacy and security. Data may be available in temporal or text format. This paper describes about the distributed architecture for secure and attack-resilient bit coin-based crypto currency transactions for classified temporal and text data. The temporal data may be voice, sound or graphical information basing on the time series. If the data available is temporal this work describes about how it can be classified into a processed form. In this context, this paper describes the process of converting temporal data into text data. Further, the paper describes about the process of ensuring the security. This paper describes about the methodologies of cryptography-based hashing, attack-resilient nonce generation and verifiable encryption techniques for the construction of resilient transactions against stealthy data-integrity attack.
EEG-based identification of evidence accumulation stages in decision making

Dating back to the 19th century, the discovery of processing stages has been of great interest to researchers in cognitive science. The goal of this article is to demonstrate the validity of a recently developed method, hidden semi-Markov model multivariate pattern analysis (HsMM-MVPA), for discovering stages directly from EEG data, in contrast to classical RT-based methods. To test the validity of stages discovered with the HsMM-MVPA method, we applied it to two relatively simple tasks where the interpretation of processing stages is straightforward. In these visual discrimination EEG experiments, perceptual processing and decision difficulty were manipulated. The HsMM-MVPA analysis revealed that participants progressed through five cognitive processing stages while performing these tasks. The brain activation of one of those stages was dependent on perceptual processing, while the brain activation and the duration of two other stages was dependent on decision difficulty. Additionally, evidence accumulation models (EAMs) were used to assess to what extent the results of HsMM-MVPA are comparable to standard RT-based methods. Consistent with the HsMM-MVPA results, EAMs showed that non-decision time varied with perceptual difficulty and drift rate with decision difficulty. Moreover, non-decision and decision time of the EAMs correlated highly with the first two and the last three stages of the HsMM-MVPA analysis, respectively, indicating that the HsMM-MVPA analysis gives a more detailed description of stages discovered with this more classical method. The results demonstrate that cognitive stages can be robustly inferred with the HsMM-MVPA analysis.
Refiguring Bodies

The matter/form distinction is refigured in terms of the distinction between substance and accident and between a God-given soul and a mortal, lustful, sinful carnality. Within the Christian tradition, the separation of mind and body was correlated with the distinction between what is immortal and what is mortal. The body has been regarded as a source of interference in, and a danger to, the operations of reason. The humanities reduce the body to a fundamental continuity with brute, inorganic matter. For Locke and the liberal political tradition more generally, the body is seen as a possession, a property of a subject, who is thereby dissociated from carnality and makes decisions and choices about how to dispose of the body ad its powers. Some models, including Descartes’, construe the body as a self-moving automaton, much like a clock, car, or ship according to the prevailing modes of technology.
A Dynamic Sliding Window based Balanced Parallel Frequent Itemset Mining Algorithm in Data Stream

Frequent itemset mining algorithms are one of the most interesting research issues in recent years.They play an important role in finding association rules from a continuous massive data stream such as: customer behavior tracking, retail sales, network monitoring, etc.In this paper, a novel approach will be introduced to remove some drawbacks in parallel FP-Growth and enable it to handle the data stream.The proposed algorithm DSW-BPGFP (Dynamic Sliding Window -Balanced Parallel Graph Frequent Pattern) will improve space and time required based on a compact data structure, called FP-Graph to maintain and store dynamic sliding window transactions.The algorithm dynamically reconstructs and compresses directed graph data structure to control the amount of space usage, and the size of dynamic window will be adjusted by the concept change detection.Moreover, DSW-BPGFP will distribute loads between Hadoop cluster nodes equally, by introducing load balancing strategy.The experiments show that the proposed algorithm can achieve a good speedup, a good degree of balance between nodes and efficiently process large dynamic datasets.In addition, it achieves improvement in memory consumption to store frequent patterns and in time complexity.
Generation of Keystream for Symmetric Cipher using U-Matrix

Symmetric-key cryptography is a classical cryptography in which both sender and receiver use the same key K to encrypt and decrypt the message. The main challenge between sender and receiver is to agree upon the secret-key which should not be revealed to public. Key management is the major issue in symmetric-key cryptosystem. To avoid these, a novel approach in generating the keystream Ks for any symmetric-key algorithms using U-matrix is proposed in this paper. The advantage of this method is generation of key K from Ks is based on some deterministic procedure which is then applied to DES algorithm and K is not necessarily remembered by both sender and receiver. Further, in each round different key is used as opposed to usage of single key in classical DES. Experimental results clearly show the security is increased when it is compared with classical DES.
Automatically Prospecting Feature for Queries from Their Search Impact

We recommend that you compile the duplicate lists in the top search engine results to track the aspects of the query and implement a method known as QDMiner. More specifically, QDMiner extracts free text lists, HTML tags and re-regions the top search engine results, combining them with groups according to the products they contain, then line up the blocks and products, depending on how the conversation and products are included in the best results. The recommended approach is generic and does not depend on understanding any area. The main purpose of the extraction side differs from the query recommendations. We recommend a structured solution, described as QDMiner, to trace query aspects immediately by removing and grouping repetitive lists in free text results and HTML tags and repeating search engines. We continue to evaluate the support of the list and discover better search queries by looking for exact similarities between menus and penalizing duplicate lists. Experimental results reveal that there are many listings available and QDMiner can find useful queries. The proposed approach is general and does not depend on understanding a particular area. As a result, it can handle open-domain queries. The query supports. Instead of a static system for your problems, we extract the sides of the uploaded document above each query.
Query Based Text Summarization

Now a day’s, The advancement of technology implies the large amount of online textual Information, this leads to a need for Text Summarizers which can provide important textual data from large data source like www, into a well-structured document formats. It becomes an alive analysis activity to specify the related data that is retrieved from huge set of documents which are established from various sectors like social media. Text summary is the action of precise the documents by protecting the key concepts of the text. This process can be accomplished via extractive summary and abstractive summary. In this paper, we suggested summarization technique that is to be applied on online information depending upon the User required Document.
Staller Game for Vocabulary Building

This study aimed at: 1) developing Staller Game Board in building English vocabulary to the learners.2) knowing the quality of developed Staller Game.This study was a RnD (Research and Development).The subjects of this study were the 8th grade students.The object of this study was the Staller Game.This study used several instruments namely interview guide, field note, observation checklist, expert judgment rubric, and questionnaire.The data were analyzed by qualitatively and quantitatively.The result showed that: 1) Staller game board is a game that was played on a board by rolling the dice and taking cards to solve.This game provides 4 different kinds of card and 3 kinds of challenges in it.Those cards are Ordering Story, Answering Question, and Solving Challenge, and provide a Bonus card.The game takes a theme 'Thing around you' (related to descriptive text).The game was also equipped with a manual book.2) The judges agreed that the game is categorized as an excellent game.