Reviewerly/exHarmony huggingface dataset:
Amazigh-Sys: Intelligent system for recognition of amazigh words

&lt;span id="docs-internal-guid-0264fec3-7fff-a3e5-94ef-c25bcfddc65d"&gt;&lt;span&gt;Amazigh-sys is an intelligent morphological analysis system for Amazigh language based on xerox’s finite-state transducer (XFST). Our system can process simultaneously five lexical units. This paper begins with the development of Amazigh lexicon (AMAlex) for attested nouns, verbs, pronouns, prepositions, and adverbs and the characteristics relating to each lemma. A set of rules are added to define the inflectional behavior and morphosyntactic links of each entry as well as the relationship between the different lexical units. The use of finite-state technology ensures the bidirectionality of our system (analysis and generation). Amazigh-sys is the first general morphological analysis system for Amazigh based on xerox finite state able to process and recognize all lexical units and ensures a high recognition rate of input words. This contribution facilitates the implementation of other applications related to the automatic processing of the Amazigh language.&lt;/span&gt;&lt;/span&gt;
Publisher Correction: Similarity-driven multi-view embeddings from high-dimensional biomedical data

A Correction to this paper has been published: https://doi.org/10.1038/s43588-021-00049-4.
Optimized Extreme Learning Machine for Forecasting Confirmed Cases of COVID-19

Recently, a new challenge to the researchers has been emerged due to the spread of a new outbreak called novel corona-virus (COVID-19) to portend the confirmed cases.Since discovering the first certain cases in Wuhan, China, the COVID-19 has been widely spreading and expanding to other provinces and other countries via travellers into various countries around the world.COVID-19 virus is not a problem of only developing countries, but also of developed countries.Artificial Intelligence (AI) techniques can be profitable to predict such; parameters, risks and influence of an outbreak.Therefore, accurate prognosis can be helpful to control the spread of such viruses and provide crucial information for identifying the type of virus interventions and intensity.Here are develop an intelligent model depicting COVID-19 transmission and resulting confirmed cases.The epidemic curve of COVID-19 cases was modelled.The main key idea of predicting the confirmed cases is based on two factors 1) cumulative number of confirmed cases and 2) the daily confirmed cases instead of using only one factor as previous research.In this study, a comparison between different intelligent techniques has been conducted.To assess the effectiveness of these intelligent models, a recorded data of 5 months has been used for training in various countries.Results obtained show the superiority of ELM model in accurate prediction and outperforms other intelligent techniques.We have used a Social Spider Optimization (SSO) method to optimize the ELM parameters.The prediction results show the superiority of the proposed intelligent predictors with accuracy greater than 93%.Therefore, medical personnel can take defensive steps earlier.
Decision Support System Determining Computer Virus Protection Applications Using Simple Additive Weighting (SAW) Method

The use of information technology devices such as computers or laptops is currently increasing. The increased use is due to the fact that these devices are very supportive of our daily work activities. With the increasing use of these computers, data security on a computer or laptop device must be completely safe from virus attacks. To ward off viral attacks m aka requires the application of anti-virus to inhibit and prevent a variety of viruses that enter into the computer system so that the computer user's activity was not bothered by the many viruses are easily spread. Because there are too many antiviruses on the market, it is necessary to choose a good antivirus. One of the ways to choose antivirus is the existence of a decision support system . In this study, the Simple Additive Weighting (SAW) method was applied for the anti-virus application selection system. This data assessment analysis aims to produce the best anti - virus application options that computer users can use to secure their computer data. The criteria and weights used are K1 = application rating (5%) , K2 = completeness of features (30%) , K3 = price / official license (5%) , K4 = malware detection (45%) and K5 = blocking URL (15%). Of the 25 alternatives used, the results of the study, namely alternative A1 = Kaspersky anti-virus get the highest ranking result.
Computational immunohistochemistry staining on lung tissues based on Mueller matrix microscopy

We propose a cross-modality method that translates polarimetric images into bright-field. In the lung tissue histological analysis, immunohistochemical (IHC) staining of tissues is widely used to specify particular cellular events especially in precision medicine. In this work, we measured hematoxylin and eosin (HE) stained slices by Mueller matrix (MM) microscopy and then fed polarimetric data into a well-designed generative adversarial network (GAN). The network can generate images that are equivalent to the IHC stained from bright-field microscopy. This will assist pathologists with the real IHC staining procedure and pathological diagnosis. Instead of preparing specimens from scratch, we collected already existing specimens, i.e., the adjacent HE and IHC stained slices from the same tissue volume. We adopted the CycleGAN to learn the translation between unaligned images from two domains. We used a U-Net based generator and a PixelGAN based discriminator in the model. The efficacy of this method was demonstrated on smooth muscle actin (SMA) staining in lung tissue. The results are evaluated by three image quality assessment methods by comparing the generated and real staining images.
Content Characteristics of Independent Work of Students (IWS): Modern Conditions and Problems

The article discusses the problem of organizing independent work under the guidance of a teacher, which can be considered effective only if the educational process is organized as a holistic system in each classroom and in extracurricular activities of students. However, these types of work can be partially interconnected with each other, and several types of classroom training on credit training technology have different goals, each of which has its own goal and is an ideal opportunity to perform the above training tasks. The work of independent students under the guidance of a teacher (IWS) focuses on classroom activities. At the same time, the analysis of normative documents and scientific and methodological literature, the description (IWS) are presented in the same sense in different sources, but nevertheless the main aspects of this concept are defined, and (IWS) is a joint training of students and teachers . type of activity (type of training), which is one of the aspects of ensuring the individual work of the student based on the installation, configuration and control of the teacher.&#x0D;
Wankelmut: A Simple Benchmark for the Evolvability of Behavioral Complexity

In evolutionary robotics, an encoding of the control software that maps sensor data (input) to motor control values (output) is shaped by stochastic optimization methods to complete a predefined task. This approach is assumed to be beneficial compared to standard methods of controller design in those cases where no a priori model is available that could help to optimize performance. For robots that have to operate in unpredictable environments as well, an evolutionary robotics approach is favorable. We present here a simple-to-implement, but hard-to-pass benchmark to allow for quantifying the “evolvability” of such evolving robot control software towards increasing behavioral complexity. We demonstrate that such a model-free approach is not a free lunch, as already simple tasks can be unsolvable barriers for fully open-ended uninformed evolutionary computation techniques. We propose the “Wankelmut” task as an objective for an evolutionary approach that starts from scratch without pre-shaped controller software or any other informed approach that would force the behavior to be evolved in a desired way. Our main claim is that “Wankelmut” represents the simplest set of problems that makes plain-vanilla evolutionary computation fail. We demonstrate this by a series of simple standard evolutionary approaches using different fitness functions and standard artificial neural networks, as well as continuous-time recurrent neural networks. All our tested approaches failed. From our observations, we conclude that other evolutionary approaches will also fail if they do not per se favor or enforce the modularity of the evolved structures and if they do not freeze or protect already evolved functionalities from being destroyed again in the later evolutionary process. However, such a protection would require a priori knowledge of the solution of the task and contradict the “no a priori model” approach that is often claimed in evolutionary computation. Thus, we propose a hard-to-pass benchmark in order to make a strong statement for self-complexifying and generative approaches in evolutionary computation in general and in evolutionary robotics specifically. We anticipate that defining such a benchmark by seeking the simplest task that causes the evolutionary process to fail can be a valuable benchmark for promoting future development in the fields of artificial intelligence, evolutionary robotics, and artificial life.
Evaluation of Attention and Concentration Using Mobile Computing

The educational trend toward personalized learning requires the teacher to monitor the learning process continuously. This article presents mobile computing to administer a battery of cognitive tests based on a standard neuropsychological assessment of attention and concentration derived from Neuropsi ©. Currently, specialists perform this test by observing, measuring time, and taking notes of the process to obtain the final scores. Considering the use of this test as an assessment of students' cognitive abilities in a class, the time required for application and evaluation is a challenge itself. As for overcoming this difficulty, the process has been automated through the development of software. The goal is to provide the test to several users simultaneously on their own mobile devices. Then, it is evaluated both attention and concentration on the subject during the solution of the exercises. Variants of the exercises were provided to extent the Neuropsi options. All the collected information is stored on a server. Moreover, the system provides individual and group profiles to the evaluator, such as a teacher or instructor. Likewise, the provided compendium allows the specialist to identify changes in attention and concentration performance and supports their additional recommendations, as well as to go in deep in the research of the cognitive process providing an initial condition evaluation. This work proved that the concept raised by software specialists, designers, and psychologists is feasible into an interdisciplinary team.
Desain Aplikasi Sistem Informasi Akuntansi untuk Usaha Bengkel Studi Kasus pada AA Cempaka Auto Service

This study aims to design an accounting information system application in AA Cempaka Auto Service workshop. Case study used as research approach. The application design process begins with studying the forms and reports that are required by the workshop business i.e purchasing form, sales form, general journal form, vehicle service record, debt payment and receivables. Required reports consist of transaction journal records, general ledger, balance sheet, income statement, balance sheet, inventory position, and vehicle service record. Application development stage using Microsoft Access 2007 software and VBA facilities for automation of journal posting and inventory cost calculation based on moving average method. The next step is to test the application to get sufficient confidence in transaction processing by comparing the results of the processing with the manual calculations performed. The implementation process is carried out by converting the initial data on the conversion date and inputting the transaction up to the company's operating date. After carrying out the implementation and conversion, the final stage is to carry out training to users and carry out the process of improvement and adjustments to the application based on feedback received from the user. The system design and implementation process have been deemed successful after the user has stated that the application has met all user needs and is operating properly.
Cooperative Motion Planning for Multiple UAVs via the Bézier Curve Guided Line of Sight Techniques

Multiple motion planning plays an essential role in several vehicle motions. This paper proposes a cooperative method between the Line of Sight techniques and the Bézier curve, applying this to motion planning for unmanned aerial vehicles. The experiment is implemented using the AirSim plugin on Unreal Engine 4. The results of the proposed method are compared with those for the conventional Line of Sight techniques to control multiple unmanned aerial vehicles. The results illustrate that the proposed method takes more time to process than the conventional one. However, the proposed method can reach a higher performance by addressing the target unmanned aerial vehicles and the pre-defining path more than the conventional method does, which is shown in all three simulation cases.
Measure of genuine coherence based of quasi-relative entropy

We present a genuine coherence measure based on a quasi-relative entropy as a difference between quasi-entropies of the dephased and the original states. The measure satisfies non-negativity and monotonicity under genuine incoherent operations (GIO). It is strongly monotone under GIO in two and three dimensions, or for pure states in any dimension, making it a genuine coherence monotone. We provide a bound on the error term in the monotonicity relation under GIO in terms of the trace distance between the original and the dephased states. Moreover, the lower bound on the coherence measure can also be calculated in terms of this trace distance.
APLIKASI KAIDAH KEBAHASAAN BAHASA INDONESIA DALAM TAJUK BERITA SURAT KABAR SEBAGAI KONSUMSI INFORMASI PUBLIK DI KOTA MAKASSAR

The purpose of this research is to determine the use of Indonesian standard in headline news in newspaper discourse relate to the diction/vocabulary; writing; sentence structure; and use of vernacular languages, and foreign terms. This research focuses on the use of Indonesian standard in the headline newspaper of Harian Fajar newspaper. This research is a qualitative method of content analysis. The source data are from daily Harian Fajar Tajuk Newspaper. The result showed that the diction or vocabulary in the discourse of headline news used language hyperbole, oxymoron, and personification. The writing word such as acronyms, technical terms. The majority of the style of language used by the writer is hyperbole. The writer used many acronyms. The technical terms are dominated by English vocabulary. The writing is not appropriate, namely: the writing of the word, the error in the writing of letters, capital letters, the compound word, and preposition di. Particle that often arise in the writing errors is pun. These of punctuation is not appropriate, namely the use of comma, in the details of words and the use of hyphen in the decoding in the words. The sentence structure in the form of the head line news of Harian Fajar is to be a symbol (+), proverbs, advice, and imperative sentence. The ambiguous sentence, conjunction occur due to improving is not appropriate, ie: untuk kemudian, padahal agar, mesti, sehingga, jadi, karena, disebabkan oleh, dan bahwa. Many sentences found in the data are ineffective. One of the reasons is became of a combination of the two ideas in a sentence. There is a tendency of the writer to write down his words affix me- writer the based words only and many sentences do not have clear subject.
Designing Digital Educational Environment for the Individualization of Learning and the Development of Gifted Children

The article presents the authors’ project of designing a digital educational environment for the actualization and development of creative giftedness in primary school children by means of a network of project activities. The educational environment was designed within the conceptual framework proposed by E. D. Patarakin and based on his idea of using network interactions to support the project method. This approach enables a transition from the concept of "educational environment" to the concept of “educational ecosystem". The model of an ecological system is used in the article to analyze the contemporary educational environment. The empirical material presented in the paper can be implemented in developing new forms of interaction between educational process participants in the context of e-learning.
The adoption of cloud computing in business organizations for an immediate tactical advantage or making it part of their long-term strategic I.T. plan

The Information Technology (IT) business ceaselessly endeavours to enhance regarding deploying products or offering services with the approach of new technology, and cloud computing is quickly moving in the promotion cycle because it will reshape the method of delivering services of data innovation.Decisionmakers still have numerous worries that could drop the adoption of cloud computing.This paper will show a systematic literature review to investigate the present situation related to cloud computing adoption.This is done by analysing 25 studies published about cloud computing adoption.The results show that businesses face critical problems before they choose to adopt cloud computing.
An Analysis of Jargon Used on Facebook Found in Account “Mark Zuckerberg”

This study discusses An Analysis of Jargon Used on Facebook Found in account “Mark Zuckerberg”. Hopefully, this study useful for students of English Education, particularly to help them understand the jargon that is used in social media especially on Facebook. The goal of this study to find out the jargon used by "Mark Zuckerberg" in account Facebook. This analysis used the descriptive method because it is to describe the jargon meaning in the "Mark Zuckerberg" account on Facebook. The procedure of collecting the data are: (1) Reading and finding the status of “Mark Zuckerberg” account, (2) Identifying the jargon used in the status, (3) Marking and finding the meaning of jargon found in the status, and (4) Concluding the data analysis. Based on the finding, the writer found Fifteen jargons, ten jargons abbreviation, one jargon phrase, three jargon words, and one jargon acronym in the edition of January till May in 2020.
Implementasi Algoritma Haar Cascade pada Aplikasi Pengenalan Wajah

The large number of citizens in an organization makes the development of an attendance system or citizen detection in a place important in the running of work activities in the organization. Utilization of an IP Camera which is only used for regular monitoring without further detection of the needs of citizens in the organization made the development of personnel detection developed for monitoring the presence of personnel. With the development of a face detection system, it is hoped that the facial algorithm development system will be developed using an IP Camera. Face detection has been developed which has many and special features which aim to determine whether or not a face has been detected in an image. With image management that is developed in face detection, detection will be faster and more accurate because the color is processed into gray degrees so that there are fewer color pixels than those with colors. By using the Python programming language and an image detection library called OpenCV, less code will be designed. This study uses the Viola Jones method, which is a fast and accurate face detection method developed by Paul Viola and Michael Jones. In this study, the Viola Jones method uses the Haar Cascade algorithm which functions as a detection feature in the system and is combined with the internal image process and the AdaBoost Learning and Cascade Classifier so that the detected face object will easily classify whether the object is a face or not. In this case the Cascade Classfier used in this study is the face and eyes. The development of this algorithm is carried out for face detection and recognition. The detection is done by taking pictures with the process taken using a webcam. The system will take several pictures and then the image data will be stored in a folder called dataSet. After that, all data is trained so that it can be recognized by the system. With retrieval, detection and recognition limitations that can only be taken from a distance of less than three meters, face detection on the IP Camera can still read objects other than faces. With recognition and accuracy on the webcam camera, about 80,5% this system can be developed with the Haar Cascade algorithm and the Haar Cascade algorithm precisely to be applied to the development of faced detection and face recognition. By developing the Haar Cascade algorithm for face detection, problems and utilization of an organization's data can be more easily detected and used by IP cameras that can support the performance process of face detection and recognition
Comparison K-Medoids Algorithm and K-Means Algorithm for Clustering Fish Cooking Menu from Fish Dataset

Abstract The production of fish-based food processing has become a commodity for restaurants, restaurants, catering and home consumption, but there are still many people who don’t know how fish can be processed in various dishes for their daily needs. To find out how to make fish-based dishes, the researchers provide a solution to cooking any kind of food, starting from the grouping of types of dishes, the basic ingredients that must be prepared, how to cook them, to the address of the cooking link with ingredients from fish. This study aims so that people can cook various menus whose basic ingredients come from fish. This research uses clustering algorithm, k-means and k-medoids. The stages of this research consisted of data collection, data selection, modeling, data training, data testing and evaluation. The object in the study of menu data for various processed fish dishes consisted of 978 datasets of processed fish dishes. The data used for data relating to fish food ingredients with fish food attributes and the number of likes via the website, the fish dataset is sourced from https://ipm.bps.go.id/data/dataset/ikan. From the two algorithms, the best accuracy results are -1.777 for the k-means algorithm, while -1.535 results are obtained for the accuracy of the k-medoids algorithm.
Web-Based Turkish Automatic Short-Answer Grading System

In this paper, a web-based Turkish automatic short answer grading system (TASAG) is developed to score exam questions and to generate online exams for automatic scoring of short-answer questions.The novelty of this study is that TASAG is the first software of its kind for the Turkish language.The algorithm of the TASAG software is a hybrid that determines which method will be used at runtime based on the word number dimensions to achieve accurate scoring.To measure the software's accuracy, a case study is performed for computer engineering.Instructors' scoring results and the TASAG software scoring results were compared.Two instructors prepared different answer keys for the same exam to increase the accuracy of the scoring.The scoring results, which are compared in the figures, are very close to each other, which indicate the effectiveness of the TASAG software.Moreover, the TASAG arithmetic mean scores for each answer key are calculated and given as the final score for the exam.According to the results, the TASAG software can be used for automated short answer grading system in Turkish with a 92% success rate.