Reviewerly/exHarmony huggingface dataset:
RANCANG BANGUN PERANGKAT LUNAK UNTUK PERHITUNGAN SEL DARAH MERAH NORMAL DAN TERINFEKSI MALARIA

Malaria is a serious global health problem. Calculation of normal and malaria-infected red blood cells is manually calculated on image of the blood taken by the light microscope. The calculation of the normal and the malaria-infected red blood cells is to know the percentage of parasites and their growth. In addition, it was used to determine the percentage of inhibition parasite growth. The aim of this study is to automatically calculate a total, normal and malariainfected red blood cells. The steps for the calculation of the total of red blood cells: normalization, thresholding, separation and calculation of the red blood cells by labeling. The steps of calculation of malaria-infected red blood cells: converting RGB image to grayscale and to binary image, sweeping, and the calculation of malaria-infected red blood cells. The normal red blood cells can be determined by subtracting the total of the red blood cells with the malaria-infected red blood cells. This software is able to automatically calculate the total, normal and malaria-infected red blood cells. The results of automated calculation with the developed software are not different from a manual calculation. The calculation error of the program compared to the manual calculation is only one or two of the red blood cells for each image. Keywords : malaria, calculation of blood cell, infected blood cell.
Strategy Design to Protect Personal Information on Fake News based on Bigdata and Artificial Intelligence

The emergence of new IT technologies and convergence industries, such as artificial intelligence, bigdata and the Internet of Things, is another chance for South Korea, which has established itself as one of the world’s top IT powerhouses. On the other hand, however, privacy concerns that may arise in the process of using such technologies raise the task of harmonizing the development of new industries and the protection of personal information at the same time. In response, the government clearly presented the criteria for deidentifiable measures of personal information and the scope of use of deidentifiable information needed to ensure that bigdata can be safely utilized within the framework of the current Personal Information Protection Act. It strives to promote corporate investment and industrial development by removing them and to ensure that the protection of the people’s personal information and human rights is not neglected. This study discusses the strategy of deidentifying personal information protection based on the analysis of fake news. Using the strategies derived from this study, it is assumed that deidentification information that is appropriate for deidentification measures is not personal information and can therefore be used for analysis of big data. By doing so, deidentification information can be safely utilized and managed through administrative and technical safeguards to prevent re-identification, considering the possibility of re-identification due to technology development and data growth.
PENGAMBILAN KEPUTUSAN PENENTUAN GURU BERPRESTASI PADA MA AL MAHFUZHIYAH MENGGUNAKAN METODE TOPSIS

Computer-based information system (Computer Based Decision Support System) is currently developing very rapidly along with the progress of the development of people's lives, one of which relates to the provision of relevant systems in decision making. MA Al Mahfuzhiyah is one of the madrassas in Central Lampung District that tries to improve the quality of education by prioritizing the quality of educators and education personnel. Provide added value and enthusiasm the MA Al Mahfuzhiyah teachers give awards to outstanding teachers. In the selection of high achieving teachers, assessment needs to be done so that the objectives give satisfaction to those who will be given an award. Selection of topical methods as a media for evaluating teacher performance to determine teacher achievement Based on the results of these calculations, then a large sample taken in this study determined 3 people. From the results of topsis test with 3 samples obtained V3 or the sample of having the highest value then V1 with sequence number two and V2 has the lowest value and placed number three.
USE OF MOBILE ASSISTED LANGUAGE LEARNING (MALL) IN TEACHING COMMUNICATION SKILLS AT UNIVERSITY LEVEL IN PAKISTAN

Mobile learning is undergoing rapid evolution. Mobile phones can support many kinds of learning, including language learning. Mobile technologies offer numerous practical uses in language learning. A computer is better than a mobile phone for handling various types of information such as visual, sound and textual information, but mobile phone is superior to a computer in portability. They can be just as easily utilized outside of the classroom as they can in it; learners can study or practice manageable chunks of information in any place on their own time, thereby taking advantage of their convenience. This article discuss the use of Mobile for learning a language.
Effect of Organizational Ethics On Service Delivery of Employees in The Public Sector: A Nigerian Perspective

Organizational ethics is an emerging field in human resources, which focused on the study and practice of the ethical behavior of employees within an organization.The main purpose of this research work is to empirically investigate the influence of organizational ethics on the service delivery level of employees in the National Assembly in Nigeria.The dependent variables employed in this study are integrity, self-discipline and organizational values.The survey research design was adopted.The target population of this study comprises of 885 employees in the committees of the Senate and House of Representatives.Multi-stage sampling technique was adopted and a sample size of 171 employees was used to collect data through a closed-ended questionnaire designed on a Five-Point Likert scale.Multiple regression analysis was employed to analyze data.The study found that there is a significant and positive relationship between organizational ethics dimensions of integrity, self-discipline organizational values on service delivery of employees of the Nigerian National Assembly on the other hand.In line with the findings, it was discovered that integrity and organizational values affect employee performance more than self-discipline.The study recommended that the management of the Nigerian National Assembly Service Commission should implement the National Assembly regulations and Code of Conduct.Nigerian National Assembly Service Commission should ensure that their organizational values are well communicated to all employees in the organization for effective service delivery practices necessary to achieve organizational goals.
LMI-based Design of State-Derivative Feedback Control for Takagi-Sugeno Fuzzy Descriptor Systems

This paper is concerned to present design conditions for state-derivative feedback control for Takagi-Sugeno fuzzy descriptor models.The main contribution is to derive a PDC control law without the requirement to rewrite the fuzzy model to fit in some specific format.We propose sufficient conditions as Linear Matrices Inequalities with or without the decay rate constraint in the trajectories, assuming that all eigenvalues of the fuzzy plant models are notnull.Three examples illustrate the effectiveness the proposed conditions to derive gains for the state-derivative control law to stabilize nonlinear descriptor systems.
평생교육 관점의 중등학교 문법 교육 내용의 구조

The purpose of this study is to discuss what changes will be made in the structure of contents in secondary school grammar education when introducing the perspective of lifelong education. For this purpose, the concept of ‘lifelong education in a broad sense’ was adopted, and ‘the perspective of secondary education’ and ‘the perspective of lifelong education’ were regarded as a layered view. In addition, from the perspective of lifelong education, we set the educational human being sought after in grammar education as ‘a continually growing human’. By using the concept of meta-education, we discussed that grammar education takes the form of a “double meta experience” in terms of lifelong education. In conclusion, we designed the overall structure of the content of grammar education including meta-education.
PEMANFAATAN DAN PELATIHAN PENGGUNAAN TEKNOLOGI INFORMASI DALAM PENGOLAHAN DATA INDUSTRI KULINER “ROSA CAKE”

Partners in the activities of the Stimulus Community Partnership Program (Program Kemitraan Masyarakat Stimulus/PKMS) is a home industry engaged in the culinary field, Rosa Cake. Rosa Cake offers products in the form of goods and services like ordering culinary products or organizing training in making food. The process of recording the order and registration of training in Rosa Cake is still done manually so that it is susceptible to data loss or damage in the recording which results in a decrease in the production process and the level of public confidence. This PKMS activity analyzes further the process of recording experienced by partners, as well as offering solutions by utilizing the use of information technology that is increasingly developing, especially in terms of system developers (developers). The data processed is the product order data and training registration organized by Rosa Cake. The research methods used adopting the system development methods that are commonly carried out, namely conducting socialization (needs analysis), system development (system design and manufacturing), training (as well as system testing), submission (sending the system to users), and evaluation (and maintenance). The results of this activity in the form of a system that can be a solution to the problem and in accordance with the needs of partners.
Research Guides: Virtual Reality at PUL IS SUSPENDED UNTIL FURTHER NOTICE, AS A TOOL FOR SOCIAL DISTANCING.: Recommended apps

Virtual reality (VR) is a realistic and immersive simulation of a virtual environment, experienced through interactive software and hardware. VR technology is available to the Princeton University community at the Stokes Library in Wallace Hall.
The Effectiveness of Quantum Teaching and Learning Model Against PAI Learning Motivasion for Class IV Students

In this study aims to determine the effect of learning motivation on PAI students in grade IV who have implemented the Quantum Teaching and Learning learning model with the motivation to learn PAI in fourth grade students who apply Conventional learning models. The method used in this study is a quasi-experimental method, the data collection technique uses a questionnaire, and to determine the control and experimental classes used the pretest-posttest control group design, which class is of low value and will be used as the experimental and class high grades will be used as a control class. The object of his research was fourth grade students of SDN Tegal Sawah I, which numbered 40 people, divided into 2 classes, experimental class 20 people and classes. Control 20 people. Based on the results of research and data analysis, the average experimental class pretest was 49.4 and the control class was 48.25. After being given treatment and posttesting that the results of the experimental class were 68.1 higher than the control class average value of 54.75. Calculation of hypotheses using the t-test is a paired sample T test and obtained at a significant level of 0.05 shows that the probability value (significance) is 0.00. because of the significance value, then Ho is rejected. This proves that the use of the Quantum Teaching and Learning learning model influences the learning motivation of PAI students in fourth grade SDN Tegalsawah I.
Transcrição paleográfica de documentos da Colônia Blumenau (1866-1867)

This article deals with the transcription and paleographic analysis of documents of the Blumenau Colony between the years of 1866 and 1867 that are under the custody of the Rare Works Sector, located in the Central Library of the Federal University of Santa Catarina (UFSC). This research was carried out during the Paleography classes, in the second semester of 2018, a course offered for the undergraduate course in Archivology at UFSC and taught by Professor Aline Carmes Kruger. The study and transcription of twenty-one (21) manuscripts of the time, mostly written by Hermann Wendeburg, director of the Colony, was done. In the course of the text, the origin of the Paleography, a brief historical report about the Colony Blumenau, the norms and the conventions used as basis, a summary, preceding each transcription, informing the subject, place of origin, date, who signed him and his place of custody and the transcripts.
Direct quantum error detection in multiplexed photonic transmission channels

The detection of quantum errors is of particular importance to the development of reliable engineered quantum systems. Whereas previous error-detection schemes were mostly developed for π phase-flip associated with solid-state qubits, here we introduce a protocol for direct detection of arbitrary continuous phase errors in the transmission of multiphoton spatially entangled quantum states. We present a design and experimental evidence for its realization in an integrated photonic circuit using gradually coupled waveguides with specially detuned propagation constants. We anticipate that our approach will facilitate the development of error-robust photonic devices for the processing and communication of quantum information.
Automatic Template-style Social Magazine Generation Service and Video Content Synthesis

This paper deals with the social magazine creation service using chatbot and video creation based on the contents of the social magazine. The social magazine service is to provide a story-formatted magazine from particular topic with a variety of articles, through a series of processes such as collecting and analyzing user conversations, extracting keywords appropriate to the situation, eliminating duplicated contents, and summarizing text. Reprocessing the social magazine in the form of video is also provided using speech synthesis, subtitle generation, and some effects with images and text information. The proposed system is tested in the real environment and found that it works well.
A plug-and-play LSTM-based attention module for person re-identification

Spatial attention mechanism is widely used to extract local feature in person re-identification. However, some existing multi-stage spatial attention structures lack flexibility and require complicated training process. In this paper, a plug-and-play LSTM-based Attention Module(LAM) is proposed to enhance flexibility of the multi-attention mechanism. First, we employ the single-stage multi-attention structure to replace the traditional multi-stage multi-attention structure. Our structure encapsulates multiple attention machines in single module and thus the module can be added to any backbone networks without any modification directly. Then, correlation is introduced to spatial attention machines through LSTM. Correlation between different attention machines preserves diversity of the local feature and exploit the capacity of multi-attention mechanism. Moreover, the LAM is added to the backbone network in the form of residual, which enables the LAM to be trained with the backbone network synchronously. Therefore, the training process is simplified effectively. Experiments on CUHK03, Market-1501 and DukeMTMC-ReID datasets demonstrate the advantage of the proposed method.
HUIM-SMP: High utility itemset mining based stock market analogy

Stock market prediction is a method of predicting the futuristic value of a company stock. The predictive analysis can be performed using fundamental, technical, or data mining techniques. One of the most prominent method of data mining is high utility itemset mining which yields the profit of itemsets in a transaction database equal or more than a user-defined minimum utility threshold. HUI-miner is a one phase HUI mining algorithm which uses a novel list structure called utility-list. Utility-list stores the information to apply the pruning method and utility check. In this paper, we mainly focus on prediction through HUI mining algorithms. We introduce a new method called HUI Miner for Stock Market Prediction (HUIM <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SMP</inf> ) to predict stockset from a stock dataset that yields the maximum profit. HUIM <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SMP</inf> uses utility-list structure to store the utility and heuristic information of a stockset to prune weak candidates from search space. The proposed application revolves around the issues of a customer regarding a safe investment in the stock market with high profits. Extensive experiments are conducted to evaluate the performance of HUIM <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SMP.</inf> The results show that the proposed algorithm reduces the number of candidates and runs effectively when a database contains number of long transactions.
Implementation of Automatic Connecting System with Wheelchair Traveling Supportive Robot

This paper presents a method of automatically connect the wheelchair with the traveling support robot for usual manual wheelchair. This robot has been developing for a purpose of reducing burden on caregivers. In order to use this robot, caregivers or wheelchair users have to move the wheelchair closer to robot and manually connect. Therefore, we aim to implement the function that the robot automatically moves to the position where it can be connected with the wheelchair. In this paper, for planning robot movement route to handle an arbitrarily located wheelchair, we propose a method to estimate the posture and handle position of a wheelchair by using a vision sensor mounted on the robot．Also we propose a control method for moving the robot toward the rear of the wheelchair using three-dimensional interpolation curve.
Verifying Implicitly Quantified Modal Logic over Dynamic Networks of Processes

When we consider systems with process creation and exit, we have potentially infinite state systems where the number of processes alive at any state is unbounded. Properties of such systems are naturally specified using modal logics with quantification, but they are hard to verify even over finite state systems. In [11] we proposed $$\textsf {IQML}$$, an implicitly quantified modal logic where we can have assertions of the form every live agent has an $$\alpha $$-successor, and presented a complete axiomatization of valid formulas. Here we show that model checking for $$\textsf {IQML}$$ is efficient even when we consider systems with infinitely many processes, provided we can efficiently present such collections of processes, and check non-emptiness of intersection efficiently. As a case study, we present a model checking algorithm over systems in which at any state, the collection of live processes is regular.
Apache NetBeans Sources Overview

As we have seen in this book, there are many ways to contribute to Apache NetBeans. You can help by writing documentation, blogging about NetBeans, participating in the NetCAT program, or even by fixing bugs and becoming an Apache committer.
RECOGNITION OF ONLINE HANDWRITTEN TELUGU LETTERS FOR DIFFERENT DOMAINS AND ORGANIZATIONS

Machine learning and neural networks are trending technologies used in different kinds of handwritten (HW) pattern recognition of various research areas. Therefore it is very hard to distinguish and recognise the hand written characters of different persons. Recognition of characters related to telugu language is a part of pattern reorganisation that happen to the idea of research during the past some years. Neural networks (NN) are playing a significant role in telugu HW character recognition. HW detection is the capability of a digital computer to receive and understand intelligible HW input from documents, images, touch screens and other electronic devices etc. These all may be online or offline, in this context online recognition includes conversion of pen tip digital movements into a list of originates used as input for the categorization system where as offline recognition uses images of characters like input. For HW reorganization NN has been achieved and improve the efficiency up to 98.3% this is good achievement.
Image super-resolution reconstruction based on multi-scale feature loss function

In the image super-resolution reconstruction, many methods based on deep learning mostly adopt the traditional mean squared error (MSE) as the loss function, and the reconstructed image is prone to the problem of fuzzy details and too smooth. In order to solve this problem, this paper improves the traditional mean square error loss function and proposes an image super-resolution reconstruction method based on multi-scale feature loss function. The whole network model consists of a DenseNet-based reconstruction model and a convolutional neural network which is used to optimize the multi-scale feature loss function. Taking the reconstructed image and the corresponding original HD image as the input of the convolved neural network in series, the mean square error of the different scale feature images obtained by convolution of the reconstructed image with the corresponding original HD image was calculated. Experimental results show that the method in this paper is improved in subjective vision, PSRN and SSIM.
Features detection based blind handover using kullback leibler distance for 5G HetNets systems

&lt;p&gt;The Fifth Generation of Mobile Networks (5G) is changing the cellular network infrastructure paradigm, and Small Cells are a key piece of this shift. But the high number of Small Cells and their low coverage involve more Handovers to provide continuous connectivity, and the selection, quickly and at low energy cost, of the appropriate one in the vicinity of thousands is also a key problem. In this paper, we propose a new method, to have an efficient, blind and rapid handover just by analysing Received Signal probability density function instead of demodulating and analysing Received Signal itself as in classical handover. The proposed method exploits KL Distance, Akaike Information Criterion (AIC) and Akaike weights, in order to decide blindly the best handover and the best Base Station (BS) for each user&lt;/p&gt;
Use Cases for Cognitive Virtual Bots

In this chapter, we describe use case configurations for various domains and learn how to use IBM Cloud to accomplish a particular goal, such as integrating the Watson Assistant with external APIs. IBM Cloud Functions is a serverless execution environment for building and connecting cloud services. A cloud function lets you focus on writing code and building solutions without building or maintaining a complex infrastructure.
A comparative study of similarity measurement in a new neural model of Unsupervised clustering

The clustering is one of the most active research and application areas of neural networks. Moreover, it is widely used in many disciplines as data mining, machine learning, decision-making, bioinformatics, image segmentation, and many other areas. The big challenge for clustering data is to choose the right criterion of resemblance for a given data set, which makes distance measure an important factor. In this paper, we present a new statistical neural clustering approach based on Hebbian competitive training and we study three distance measures: Euclidean, Mahalanobis and Manhattan, and their effect on the clustering of different unlabeled data sets forms. Compared to classical approaches such as K-means, this approach has the advantage of high speed because of using a neural network equipped with parallel information processing. Additionally, the proposed procedure does not pass by any thresholding and does not require any information a priori on the number of classes nor on the structure of their distributions in the sample.