Reviewerly/exHarmony huggingface dataset:
Assessing the quality of national youth strategies

The OECD Secretariat has conducted an assessment of the quality of national youth strategies on the basis of the extent to which they meet the principles of good governance included in the OECD framework of quality standards of national youth strategies (Chapter 2). The assessment is based on the data collected from government entities in charge of youth affairs in the 2019 OECD Youth Governance Surveys (Survey 1).
Performance Evaluation of Best Path Selection using Multi Hop Decode and Forward Cooperative system

In this method , examined that Multibounce correspondence is the most ideal route for improving the inclusion region with decreased transmitted power. From this, we can without much of a stretch finding a way determination dependent on multi-jump translate and forward (DF) agreeable framework. At that point, it is said to be a basic parallel multibounce ways based agreeable correspondence framework. Assumed all jumps on the whole agreeable ways are presenting to allowed Rayleigh blurring. Picking the better way in the greatest multi-jump interface between the source and goal is determined by choosing the max-min determination criterion. The transfers which are found in the chose helpful way to utilize the image astute DF convention in the demodulate to get the information from the previous hub with the assistance of image astute way and it is sent to the succeeding hub. A systematic structure is progressed to locate an exact blunder execution of the given framework. In ongoing we determine a right articulation for the normal piece blunder rate of the maximum min foundation based upon the best way choice plan, all together with the united power arrangement. The coding gain and the assorted variety request of the plan are moreover determined with the assistance of the explanatory strategy.
QuitaUp – a tool for quantitative stylometric analysis (Announcement)

Corpus and University of Ostrava.The QuitaUp application, created by
An Efficient Data Integrity using Attribute Based Encryption for Cloud Computing System

The new and efficient method determinedly concentrates on the data processing, store and access the information which will be intended to make sure the users for legal powers should get equivalent information and also will confine the normal and unofficial legal users get admittance of the information which make suitable for those mobile cloud computing. There are various parameters with assess those execution of the active Attribute-Based encryption (ABE) method over cloud computing as takes after: cipher text measure (communication cost), private key span (storage cost), public key size (“Required storage on store public key in about powers in the ABE method”), re-keying extent (the size of the rekeying message that could make used to identify the user revocation for every attributes in the ABE system), calculation expense on the information manager (required time to encrypt the information by owner), calculation cost on the user (required run time to decrypt the information by a user). Our research work effort likewise analyses the vitality of the information security in the cloud. Purpose behind picking symmetric encryption algorithms are proficient to handle encryption and decryption to substantial measure about information and powerful speed about storing information and gaining access to those information in the cloud system.
Review of « Estimating Solar Irradiance Using Sky Imagers » by Dev et al.

This paper presents a method to quantify the solar irradiance by using an all-sky imager with a fish eye lens.This uses data sampled in Singapore, with variations in cloudy scenes, and is aimed at better prediction of photovoltaic energy production.This paper describes a model by which a sky image's individual pixels, from compressed jpg, are used to related to a The paper is mostly well written, and concise, bordering on too short.The approach is interesting, and the applications may be wide ranging for energy forecasting.That said, the model is not well described, with major issues concerning the non-linearity and the normalization factor, that seems to make the model results look better than actuality.Model here is also a bit of a stretch as it is simply an empirical fit of the measured values.The actual evaluation of the model requires a normalization C1
Selection of informative features to highlight areas of waste disposal on high spatial resolution satellite imagery

The paper deals with the problem of integrated interpretation of waste disposal facilities according to satellite imagery and ground truth monitoring, features of space images of landfills from various points of view: texture analysis, statistical properties, fractal analysis, color features, and the possibility of using machine learning methods. The main visual interpretive signs of landfills on optical and radar images of high spatial resolution are given. The fractal dimension of landfills was calculated for high resolution images using two models.
Performance analysis of hybrid classification system model for big data stream using internet of things

Big data and internet of things (IoT) have become the world's prominent technology and reached a high impact on millions of people's daily life that helps in managing environmental and physical systems processed in real-time. In this research, we proposed a hybrid classification system model named multi-output regression with deep belief networks (MOR-DBN) to improve the performance of the classifier when huge amount of streaming data is transferred from IoT devices. Moreover, the improved privacy-preserving rotation based condensation algorithm (P2RoCAl) with Geometric Transformation is also used for obtaining high utility for data streaming to protect from various kinds of attacks during data reconstruction. The simulation results show that proposed framework obtains a high accuracy when compared with other existing algorithms in terms of precision, recall, and F-measure. Overall the proposed MOR_DBN model outperforms by obtaining a 96.21% for SSDS dataset, 97.89% for FRDS dataset, 95.7% for HPDS dataset, and 99.23% for ESDS dataset.
AUTOMATION OF DATA PREPARATION FOR THE GEOGRAPHIC BLOCK OF THE ARCHIVAL DATABASE

The creation of archival information retrieval systems is one of the actual directions of the development of the Ukrainian archival system.However, its implementation requires entering a huge amount of information into databases.Moreover, this process is not currently automated and therefore requires significant human resources to enter data manually.The work aims to study the automation of the data preparation process for the geographical block of the archival information retrieval system from sources of various formats: electronic registers, web pages, paper books, handwritten archival documents, etc.A subsystem for data preparation is proposed.It consists of modules for searching for information sources, data extraction, data identification, and entering information into the database.Much of the work in the subsystem is automated and does not require manual data entry.The choice of method of data extraction and pre-processing depends on the source of information.Given the specifics of the task, it can be assumed that the vast majority of sources will be either printed publications or handwritten archival documents.Therefore, the first step to their processing should be scanning and text recognition using common software or neural network.Unstructured text obtained from sources is automatically transformed by syntactical analysis into structured text, which is entered in the table of a certain template.The extracted data must be identified, information about identical administrative units must be combined and entered into a database.The proposed subsystem of data preparation was implemented on the example of the preparation of geographical information for the Mykolayiv region.The significance of the obtained results is that the use of the proposed algorithm will automate the filling of the geographical block with data from other regions for use in regional thematic archival databases and the national archival information retrieval system.
A COMPARATIVE STUDY ANALYZING COMPUTER PROGRAMMING COLLEGE STUDENTS' PRE-KNOWLEDGE AND POST-KNOWLEDGE OF SOFTWARE APPLICATION SECURITY USING OWASP

Software application security has become increasingly important in a society that relies heavily on information systems and technology.Business organizations and consumers alike have suffered great losses as a result of compromised web applications.One of the steps towards reducing software application security vulnerabilities is to familiarize computer programming students to the Open Web Application Security Project (OWASP) proactive controls of secure coding best practices.In this study, faculty conducted a survey of 37 computer programming college students to evaluate their knowledge of software application security before and after being educated on the OWASP Top Ten proactive controls best practices.The data gathered in this study were collected between February 2019 and March 2019 through SurveyMonkey.The participants in the survey were college students pursuing an undergraduate degree in computer programming and were in their first year of the program.
Peran Sistem Volunteered Geographic Information (VGI) Sistem dalam Pengurangan Risiko Bencana: Konsep dan Implementasi

There have been a lot of geospatial technologies implemented to support disaster management into a more effective way and achieve disaster risk reduction. One of these technologies is the use Volunteered Geographic Information (VGI). VGI refers to the volunteered activities by anyone to create geographic information. The recent development of VGI is obviously supported by the development technology itself such as social media, Global Positioning System (GPS) with acceptable accuracy. In addition, it is also supported by mostly unlimited cloud-based storage as well as smartphones. In the phenomena of natural disater such as flood, landslide, earth quake, tsunami, and other phenomena, the need of geospatial data and the availability in timely manner becomes important and crucial at all disaster management aspects. The availability of geographic information is very much critical at the time the disaster occurs compared to normal situation. Therefore, VGI is necessary in supporting near real time information. In this case, VGI has a key role in disaster management particularly to reduce disaster risk.
Fuzzy Logic Based Voice Recognition as per Their Gender and Age Group

Human voice is the very important field in digital speech processing. In the coming technologies every system will be based on the human voice. The system will be locked and unlocked by human voice. In this research, we classify the voice ac-cording to their age groups. We can recognize the voice by calculating many various parameters such as pitch, power amplitude and THD and many more. There are many approaches through which we can recognize the gender’s voice such as Hidden Markov Model [HMM], Dynamic Time Warping [DTW] etc. This paper is basically depending on the voice perception system which helps in to differentiate the voice between the gender’s voice and also differentiate the voice depends on age gp to 12yrs children voice with the use of SVM and Gaussian membership function
Evaluasi Electronic Health Record (EHR) dengan Metode PIECES di Unit Rekam Medis Pusat RSUPN dr. Cipto Mangunkusumo

National Center General Hospital Dr. Cipto Mangunkusumo is one of the hospitals whose services haveused Hospital Management Information System (SIMRS). The SIMRS used in RSCM is called the ElectronicHealth Record (EHR). In its application, there were still obstacles that made the staff less satisfied with theEHR, one of which was the loading of the EHR. The purpose of this study is to evaluate the EHR in termsof user satisfaction using the PIECES method (performance, information, economic, control, efficiency,service). This type of research is qualitative research, by describing the results of interviews andobservations that have been conducted by researchers and assessed by the PIECES method. Respondentsin this study were 1 filling officer, 1 reporting officer, 1 warehouse officer, and 1 expedition officer. The resultsobtained in this study are that the EHR performance has produced data according to user needs and thereis still a fairly long loading. EHR is able to provide quality information that is easily understood and has beenintegrated with BPJS. that the EHR can produce data according to user needs and the EHR still needs timeif the officer inputs or loads. The EHR has a use value because it is integrated with BPJS Health and alsohas an EHR officer or improvement team. EHR users feel that having an EHR makes it easy for EHR userswhen performing health services such as searching for patient files and making reports. The conclusion isthat the EHR makes it easy for users to do their work. Suggestions given by researchers are to the UMSI toupdate the EHR and perform maintenance on the system and hardware.
A Knowledge Representation Model using Concept-Relation Graph

Huge volume of relevant and irrelevant information is available from different sources for gaining knowledge about a system. If the required data is in a structured form, then the fact can be easily understood otherwise the process becomes laborious and results are vague after intense analysis. In this paper, we are proposing a framework for fetching knowledge from unstructured source of data. The algorithms proposed identifies the concepts and separates the concepts and relation words, enables to add new concepts and also modify the old concept word with new concept and locate the concept. This Concept-Relation Model enables the system to work according to the users’ connivance and deliveries accurate knowledge. This model does not manipulate or interpret the information provided but only represent and share the desired knowledge.
Linked Lists

This chapter will cover linked lists. A linked list is a data structure in which each node points to another node. Unlike arrays, which have a fixed size, a linked list is a dynamic data structure that can allocate and deallocate memory at runtime. By the end of this chapter, you will understand how to implement and work with linked lists.
El saber pedagógico, de una situación educativa analógica a la digital, a propósito de la pandemia por el COVID-19

A brief exposition and reflection on the meaning of the construction of pedagogical knowledge for the analog teacher, in a conventional classroom, converted into a digital one, due to the preventive isolation in the face of the pandemic contingency resulting from COVID-19. This research bets on the linkage of the actors of the educational community (parents, guardians and students) who at times have remained distant from the new pedagogical trends in the global context. Therefore, the methodology used is the collection and analysis of pedagogical experiences mediated by information technologies. Analysis from experiences that involve students and their families in new learning scenarios.
Child Abuse Arrest Technique with Victims using Imageprocessing

In this methodology, attempts to manage a generous extent of human facial lead by seeing facial muscle exercises that produce expressions.Virtually most of the present vision systems for facial muscle movement area deal just with frontal-see face pictures and various wellsprings of photographic evidence are normally used by police forces to recognize suspects and setbacks of both on the web and disengaged crimes.Human properties, for instance, age, stature, weight, sex, hair shading, etc., are as often as possible used by cops and eyewitnesses in their depiction of unidentified suspects.In certain conditions, the age of the shocking loss can result in the affirmation of the bad behavior's grouping, e.g., tyke abuse investigations.Various motorized AI based techniques have been realized for the examination of automated pictures to distinguish fragile biometric attributes, for instance, age and sexual introduction, and hence help criminologists and masters in propelling their cases.
Robust anomaly detection methods for contamination network data

Recently, latent representation models, such as Shrink Autoencoder (SAE), have been demonstrated as robust feature representations for one-class learning-based network anomaly detection. In these studies, benchmark network datasets that are processed in laboratory environments to make them completely clean are often employed for constructing and evaluating such models. In real-world scenarios, however, we can not guarantee 100% to collect pure normal data for constructing latent representation models. Therefore, this work aims to investigate the characteristics of the latent representation of SAE in learning normal data under some contamination scenarios. This attempts to find out wherever the latent feature space of SAE is robust to contamination or not, and which contamination scenarios it prefers. We design a set of experiments using normal data contaminated with different anomaly types and different proportions of anomalies for the investigation. Other latent representation methods such as Denoising Autoencoder (DAE) and Principal component analysis (PCA) are also used for comparison with the performance of SAE. The experimental results on four CTU13 scenarios show that the latent representation of SAE often out-performs and are less sensitive to contamination than the others.
Peramalan Jumlah Kasus COVID-19 Menggunakan Joint Learning

COVID-19 is a dangerous illness because it spreads quickly and easily. Vaccines are already available but the pandemic isn’t likely to end soon. Forecasting is hoped to help handle the pandemic. Deep learning, specially LSTM, has been used to forecast COVID-19 case count in some regions. However, deep learning models generally need a lot of training data while COVID-19 daily data are scarce. However, COVID-19 pandemic happens in many regions. This research aims to use joint learning with data from other regions to improve model performance with fewer data and to use the model to forecast until 9 months since the date of last data taken. Joint learning was done by making models share some parts and training the models together. To overcome the different data scale and pandemic age in the regions, the data was first transformed into discrete SIRD variables and was evaluated using RMSSE. Joint learning failed to improve the model performance in this research. The proposed model performance was signficantly better than ARIMA-SIRD and SIRD model but wasn’t better than normal encoder-decoder LSTM. The models only reached RMSSE below one occasionally. Additionally, it was found that doing joint learning with all regions without selecting them by clustering can make the model performance worse instead. It was also found that RMSSE is too sensitive to a mostly stagnant time-series due to its division by the error of one-step naïve forecast.
A Path Planning Strategy of Wearable Manipulators with Target Pointing End Effectors

End effectors like firearms, cameras and fire water guns can be classified as pointing end effectors. When installed on wearable manipulators, a new function can be given to the wearer. Different from gripper end effectors (GEEs), target pointing end effectors (TPEEs) have different working tasks, and the requirements for path planning are also different. There is very limited research on wearable manipulators with TPEEs. Meanwhile, manipulator with GEE path planning tends to be mature, but with a relatively low efficiency concerning its algorithm in solving high-dimensional problems. In this paper, a degree of freedom (DOF) allocation scheme and a path planning strategy (unlike manipulator with gripper end effector) were proposed for manipulators with a target pointing end effector in order to reduce the difficulty of path planning. Besides, this paper describes a new algorithm-dimension rapid-exploration random tree (dimension-RRT) to divide the manipulator DOFs into groups and unify DOFs groups by adding a fake time. The dimension-RRT was compared with the rapid-exploration random tree star algorithm (RRT*) in the same simulation environment; when there are 500 random points, the dimension-RRT time consumption is 0.556 of RRT* and the path length is 0.5 of RRT *. To quickly obtain a path that can avoid the human body, dynamic movement primitives (DMPs) were used to simulate typical spatial motion path and obstacle avoidance path efficiently.
NILAI KARAKTER TANGGUNG JAWAB DALAM BUKU CERITA ANAK KELUARGA CEMARA KARYA ARSWENDO ATMOWILOTO

This study aims to analyze the value of the character of responsibility in the Cemara Family Children's Storybook by Arswendo Atmowiloto. This type of research is a qualitative research with descriptive method. The data in this study was carried out using the Cemara Family story book which contains character values. The sample was taken using purposive sampling, namely from thirty-nine subtitles, fifteen subtitles were taken from 3 sets of titles as samples. Based on the results of the analysis of research data through descriptions, it was found that the character values ​​in the Cemara Family children's story book by Arswendo Atmowiloto were found. The value of the character is shown through the sentences in each story. Of all the stories analyzed, there are 12 stories that show the value of the character of responsibility.
Design and build online citizens complaint system in Labuhanbatu using Waterfall Method

The rapid development of ICT has opened up opportunities for citizens to submit opinions and complaints to the Government, which facilities are guaranteed by law. The provision of these facilities is in the form of implementing e-Government. The government must provide an application that is Government to Citizens/Consumers (G2C) which aims to bring the government closer to the community interactively through access channels that can be reached by the community. Labuhanbatu is a district located in North Sumatra Province with a population of 493,899 people. However, until now there is no facility for the public to submit aspirations or complaints based on e-Government applications. This study aims to create a web-based online application for aspiration and complaint services for the people of Labuhanbatu Regency. This application is called LAPO, which stands for Online Aspirations and Complaints Service. The method used in this research is the Waterfall model. This research has succeeded in creating a web-based online aspiration and complaint service system for Labuhanbatu residents that shows the compatibility between the expected results and the actual results. The results of the study have proven that to design and build this system, the following stages are carried out: analyzing system requirements, system design, implementing the system, and conducting system testing. With this research, it is hoped that it can become one of the e-Government applications for aspiration and complaint services that can be used by the Labuhanbatu Regency Government easily and with low infrastructure costs by utilizing existing human resources.