Reviewerly/exHarmony huggingface dataset:
Autonomy Stemmer Algorithm for Legal and Illegal Affix Detection use Finite-State Automata Method

Stemming is the process of separating words from their affixes to get a basic word. Stemming is generally used when preprocessing in text-based applications. Indonesian Stemming has developed research which is divided into two types, namely, stemming without dictionaries and stemming using dictionaries. Stemming without dictionaries has a disadvantage in the results of removal of affixes which are sometimes inappropriate so that it results in over stemming or under stemming, while stemming using dictionaries has a disadvantage during the stemming process which is relatively long and cannot eliminate affixes to compound words. This study proposes a new stemming algorithm without a dictionary that is able to detect legal and illegal affixes in Indonesian using the Finite-State Automata method. The technique used is rule-based Stemmer based on Indonesian language morphology with Regular Expression. Test results were carried out using 118 news documents with 15792 words. The first test results on the autonomy stemmer algorithm obtain the correct word which amounts to 10449 of the total number of words processed, which means getting an average accuracy of 66%. The second test results on the autonomy stemmer algorithm get the results of the average speed of 0.0051 seconds. The third test result is being able to do the elimination of affixes to compound words.
AN ANALYSIS OF SPEECH ACT CLASSIFICATION IN BEAUTY AND THE BEAST

Pragmatics is study of significance aspects and language use which are dependent to the speaker, the addressee and other characteristics about the context of utterance. Along with communication, we are as humans do it as speakers who deliver utterance or anything to the addressee. Therefore communication and language are related to another one with pragmatics. Usually people utilize language in spoken and written, for instance conversation writing ideas, thoughts and so on in the book. For example cerebration contained in fairy tale stories were poured through the writer that one may be understood by readers. These ideas are expressed in the form about speech acts as described in Yule's theory in his book Pragmatics: Speech Act Classification (1996), there are five classifications of speech act pragmatically that can be proposed with a speaker such as representatives, directives, commissives, expressives, and declarations. The researchers used Beauty and the Beast short story to be analyzed classification about speech act. The method used in this analysis is a descriptive qualitative method. The results in this study, there are 10 speech act in short story Beauty and the Beast. In the outcomes of this study, that speech act classified into 4 types. Speech act classification is mostly Directives (50%); Representatives (30%); Declarations (10%); and Commissives (10%). The classification type unfound in the story above is Expressives.
U-control Chart Based Differential Evolution Clustering for Determining the Number of Cluster in k -Means

Determining the cluster number in k-means is problematic since it affects the quality of cluster for numerous applications in the data mining.The automatic clustering differential evolution (ACDE) is one of the most used clustering methods that are able to determine the cluster number automatically.However, ACDE still makes use of the manual strategy to determine a value k activation threshold thereby affecting its performance.In this study, the u-control chart (UCC) method use to tackle the ACDE method problem.UCC method used for the initial step to get a value of the variables sought before initialization of the variable vector on ACDE.The UCC is a method from statistical process control (SPC) field which has proved to be effective in solving the problem of management control attributes.The performance of the proposed method was tested using seven public datasets from the UCI repository and Clustering basic benchmark repository and evaluated with Davies Bouldin Index (DBI) and CS measure.The results show that, the proposed method yields excellent performance compared to prior researches for most datasets with optimal cluster number yet lowest DBI and CS measure.It can be concluded that the UCC method is able to determine k activation threshold in ACDE that caused effective determination of the cluster number for k-means clustering.
Analysis of Queuing Applications Performance using MatLab

Cloud computing is the technology that was gaining the attention of the most of the companies in market and utilization also increasing day to day by almost from companies to the common people.The working of these cloud models is very simple.A huge number of servers are used to store the data and a vast amount of data and the service of providing data to the customers staying at remote locations too.Almost all cloud based models are not free and users need to pay reasonable amount to use the services of these clouds.As the huge data is stored in these servers and the usage of this data by a huge number of customers, there is a chance of overcrowded at servers.Important data or the hot data like the new movies, exam results or bank transactions, etc. can have the most of the crowds at various time intervals.Hence, it is required to analyze the number of customers are being using the current cloud models at different intervals of time.Based on the results, the adjustments or the changes in the network model can be completed.In the current article, an attempt has been made to analyze a cloud model by considering the model working in study state and the performance was analyzed for two queuing models.Several queuing models are available in research to analyze the performance of a queuing model.In the current article, the queuing models considered are M/M/1 and M/M/c models.The performance of the queuing models are analyzed with various performance metrics of a network or the cloud model are arrival rates to the model, service rates to the model, traffic density, throughput etc.The results are displayed in the results section.
Lijunyi at SemEval-2019 Task 9: An attention-based LSTM and ensemble of different models for suggestion mining from online reviews and forums

In this paper, we describe a suggestion mining system that participated in SemEval 2019 Task 9, SubTask A -Suggestion Mining from Online Reviews and Forums.Given some suggestions from online reviews and forums that can be classified into suggestion and nonsuggestion classes.In this task, we combine the attention mechanism with the LSTM model, which is the final system we submitted.The final submission achieves 14th place in Task 9, SubTask A with the accuracy of 0.6776.After the challenge, we train a series of neural network models such as convolutional neural network(CNN), TextCNN, long short-term memory(LSTM) and C-LSTM.Finally, we make an ensemble on the predictions of these models and get a better result.
Team Taurus at SemEval-2019 Task 9: Expert-informed pattern recognition for suggestion mining

This paper presents our submissions to SemEval-2019 Task9, Suggestion Mining.Our system is one in a series of systems in which we compare an approach using expertdefined rules with a comparable one using machine learning.We target tasks with a syntactic or semantic component that might be better described by a human understanding the task than by a machine learner only able to count features.For Semeval-2019 Task 9, the expert rules clearly outperformed our machine learning model when training and testing on equally balanced testsets.
Towards a Deep Speech Model for Romanian Language

Automatic speech recognition systems have gained popularity due to their gain in terms of usability and integration in cross domain applications. While traditional approaches are developed over elaborated pipelines that need specific pre-trained models for a language (acoustic model, a phonetic dictionary, etc.), deep learning architectures like Recurrent Neural Networks have been trained for automatic speech recognition using only large datasets of speech corpora (audio and aligned transcript files). Starting from the DeepSpeech architecture, we present the performance of the model trained for Romanian language over the SWARA speech corpus which contains almost 21 hours of speech data using 17 different speakers. The experiments were focused on obtaining the best performance of the network in terms of Word Error Rate by tweaking the parameters of the model on the SWARA dataset. We present preliminary results obtained for this Romanian dataset, alongside with the encountered limitations while training the model on other languages besides English.
KEBUTUHAN INFORMASI GURU DI ERA DIGITAL: STUDI KASUS DI SEKOLAH DASAR LABSCHOOL UNIVERSITAS PENDIDIKAN INDONESIA

This research was conducted with the aim to find out what information is needed by the teacher in supporting teaching and learning activities, to find out the use of Internet-based information sources, and to find out the obstacles that arise in searching information what is done to overcome obstacles in conducting information searches. The method used in this study is a descriptive method. The Informant in this study were teachers of SD Laboratorium School, Indonesia University of Education. The results of the study found that the information needs of teachers were four aspects. Aspects of learning planning, information needs include RPP planning, teacher learning objectives, competencies, indicators, and material scope. Content or material aspects or learning experiences of information needs include student characteristics, forms of learning activities, learning strategies, and learning outcome evaluation tools. The aspects of choosing learning strategies and methods of information needs include learning objectives, students' initial knowledge, student characteristics, time allocation, supporting facilities, and the surrounding situation. The aspect of media selection, information needs include learning objectives, material scope, student characteristics, supporting features and technological development. Obstacles in information retrieval include time, ICT skills, weak and lazy search techniques.
An Ontology for Transportation System

In this work, we present a domain ontology for Transportation System. We have developed an ontology for a semantics-aware transportation system from the perspective of a traveler user, capable of answering general competence queries like the nearest bus stop to a particular place, the nearest parking slots available, etc. We have studied the transportation system of some of the big cities of the world and have tried to come up with a vocabulary that can be applied to any city with little modifications. This vocabulary is further aligned with an upper-level ontology to have a common starting point.
Geochemical study of alteration zones around Au-bearing silicic veins at Zailic, East of Ahar, East- Azarbaidjan Province

Geochemical study of alteration zones around Au-bearing silicic veins at Zailic, East of Ahar, East- Azarbaidjan Province
Hardware and Software Architecture for Accelerating Hash Functions Based on SoC

This paper presents an architecture for fast prototyping of hardware designs aiming to accelerate cryptographic hash functions on Xilinx ZYNQ SoC. The design include both hardware and software components, using DMA and custom AXI4-Stream IPs for maximum performance and easy integration. The communication link between the hardware module that accelerates hash functions and the processor running Linux is accessible directly from the user-space, providing fast debugging/benchmarking capabilities. As a proof-of-concept, a custom, pipelined and optimized bitcoin miner module was developed in order to demonstrate the feasibility of this infrastructure, and to evaluate its performance. The proposed solution was implemented on an Arty Z7-20 development board.
Audit System Development for Government Institution Documents Using Stream Deep Learning to Support Smart Governance

Document audit system is a means of evaluating documents on the results of delivering information, administrative documentary evidence in the form of texts or others. Currently, these activities become easier with the presence of computer technology, smartphones, and the internet. One of the examples is the documents created by various government institutions whether local, city and central government. The instance is online-published documents that are shaded by certain government institutions. Before the documents are published or used as an archive or authentic evidence for reporting or auditing activities, the documents must go through the editing stage to correct if there are errors and deficiencies such as spelling errors or incomplete information. In the editing process, however, a person may not be able to escape from making mistakes that result in the existence of writing errors after the editing process before the submission. Word spelling mistakes can change the meaning of the conveyed knowledge and cause misunderstanding of information to the readers, especially for assessors or the audit team. Based on the problem, the researcher intends to assist the work of the audit preparation team in document analysis by proposing a system capable of detecting word spelling errors using the Dictionary Lookup method from Information Retrieval (IR) and Natural Language Processing (NLP) science combined with Stream Deep Learning algorithms. Dictionary Lookup method is considered effective in determining the spelling of words that are true or false based on Lexical Resource. In addition, String Matching method that has been developed can correct word-writing errors correctly and quickly.Keywords: spelling mistake detection, dictionary lookup, audit of government institution documents, stream deep learning
Enhancing understanding of analytic geometry by augmented reality

An augmented reality (AR) system is a technology which combines computer-generated representations or information and reality in real-time. Instead of substituting the real situation, as it is possible with dynamic geometry systems (DGS), AR adds virtual objects or information to reality to make the situation experiential. The project MalAR aims at investigating the impact of an augmented reality (AR) learning environment in the subject area of analytic geometry. The focus of the AR learning environment is an AR-App, which supports learners understanding of mathematics situations usually given through textbook tasks. Mathematics situations are implemented in an AR-App such that the situation gets visually and enactively explorable by changing perspectives using the own body movement. The added value of integrating AR in mathematics classes is worked out and based on different learning theories like embodied cognition. The AR-App and first results of the pilot study will be demonstrated and presented. With the findings and results of the study evidence-based didactical insights in the teaching and learning with AR in mathematics instruction may be identified and needs for future AR-supported learning scenarios can be revealed.
Adaptive Content-Based Medical Image Retrieval Based On Local Features Extraction In Shearlet Domain

Image retrieval system is an urgent issue for in medicine.In the past, traditional image retrieval system based solely on the label of images and gave limited results.To reduce this disadvantage, the content-based medical image retrieval has been developed.However, this system still has many challenges.In this paper, we proposed a new method for content-based medical image retrieval.The proposed method includes two stages: the offline task and online task in medical image database.In the first stage, we extracted local object features of medical images in shearlet domain.Then, we detect the contour of object in images by active contour model.In the second stage, we make online task for content-based image retrieval in database.Our system receipts a query image and shows the similar in images by similarity comparison with the information collected from the first stage.Experimental results have shown that the proposed method is better than the other methods.
Pengembangan Media Pembelajaran Elektronik Berbasis Masalah pada Mata Pelajaran Komputer dan Jaringan Dasar

This study aims to obtain valid, practical, and effective problem-based electronic learning media on the computer and basic network subjects. Problem-based electronic learning media is designed to be able to improve student understanding and activities so as to improve learning outcomes. This research uses Research and Development (R and D) research method with 4-D development procedures (define, design, develop, and disseminate). Data analysis techniques used descriptive analysis techniques to describe the validity, practicality, and effectiveness of problem-based electronic learning media. The results obtained from this development research: (1) the validity of problem-based electronic learning media is declared validly on media aspects and material aspects (2) the practicality of problem-based electronic learning media based on teacher and student responses is declared very practically (3) the effectiveness of learning media Problem-based electronics are declared effective in improving learning outcomes and learning motivation. Based on the findings of this study concluded that the problem-based electronic learning media is declared validly, practical and effective to be used as teaching materials in the Computer and Basic Network subjects
Automatic Color Edge Detection with Similarity Transformation

Edge detection is an important step in image processing. As edge is intensity variation with spatial coordinates, the similarities between neighboring pixels could be used for edge detection. It has been observed that the effective results could be attained by thresholding the homogeneity images generated by means of the similarity transformation. Nevertheless, the user-defined normalization coefficient in similarity transform stage seriously effects edge detection performance and it needs to be automatically selected for every particular image. In this study, a new approach in which the normalization coefficient is automatically determined has been presented. The automating process of the similarity transform has been performed according to the gray level values of the neighboring pixels. The gray level differences of the central pixel and other neighboring pixels have been used to determine the similarity coefficient. Subsequently, the binarization process of the homogeneity images obtained with proposed algorithm have been completed with different thresholding techniques. Additionally, the F-score of the proposed edge detection has been obtained with 200 images in the BSDS training dataset. The achieved F-score values have showed that the performance of automatic approach is quite high.
INNOVATIVE CONCEPT OF "SPACE" IN THE TRANSFORMATION MODEL OF THE UNIVERSITY

The article formulates the methodological foundations of the fourth generation university model. A university is understood as a social institution that performs the function of human development. The problem that the thoughts given in the article are focused on is the lack of a philosophical level university model developed in the current discussion field that meets the target indicators of the national projects “Science”, “Education” and “Digital Economy”. The research methodology is development schemes in the theory of knowledge, the theory of activity and the philosophy of technology. The result is a demonstration of an ontological scheme for constructing a transformational model of a university, allowing verification of the current state of affairs in the processes of reforming higher education in Russia, guaranteeing the coherence of the university’s development standards as a social institution. In the first three paragraphs, the basic ontological prerequisites for the interaction of man and the cosmos are formulated, the content of the concepts of space, scientific knowledge and technical creativity is revealed, and the stages of the development of artificial nature are demonstrated. An ontological scheme is given that fixes the knowledge and action of a person in the actual and potential cosmos. In the fourth paragraph, the thesis is defended that the university is a form of social organization that performs the function of managing the interaction of space and man and that is developing in proportion to the level of science and technology. The fifth and sixth paragraphs discuss the so-called “generations” of universities, the transformation of the university is described as the consistent emancipation and institutionalization of the self-government functions of the social subject: the second generation of universities forms research management structures in the third generation - the structures for implementing research results in the real economy. In the seventh paragraph, the thesis is formulated that the fourth generation university synthesizing the forms of a research and entrepreneurial university in order to correspond to the current state of the artificial habitat of mankind must create in itself a goal setting management structure and learn to work with a new level of uncertainty.
Effect of Lean Accounting on the Effectiveness of Internal Control in Jordanian Industrial Companies

The study aimed at explaining the effect of the use of lean accounting on the internal control components, namely accounting control and administrative control.A questionnaire was designed to achieve the objectives of the study.The study community shall be the internal auditors of the Jordanian industrial companies, which shall participate in the primary market only.The most important results of the study The industrial companies are based on the restructuring of their products from time to time based on customer requests, and this contributes to the achievement of financial control and accounting for production costs, and The industrial companies shift the reduction of production costs by reducing the cost of inventory to the lowest levels in order to control the assets and safety of the company and maintain a certain level of quality in the financial statements.the most important recommendations of the study: The need to achieve self-control of manufacturing processes by taking the target price and target cost, and the necessity of achieving the best product for the customers in terms of quality and the appropriate price, which affects positively on the achievement of cost control through the work of planning budgets.