Reviewerly/exHarmony huggingface dataset:
A Novel Approach For Frequent Itemset Mining Using Geometric Progression Number Labeling

The task of finding Frequent Item Sets is a very important and time-consuming process in the field of data mining. In the process of Knowledge discovery from data (KDD), the analysis of Frequent Itemset Mining (FIM) produces very use full information like how the items or data are correlated with each other and how frequently it is being found in the database especially in the transaction data, its report plays a vital role for the decision-makers to procure items and to stock it. Since the stock is the asset of the business and the profit of the business depends on the liquidity of the asset, more importance was given to Frequent Itemset mining. In this present Big data era, the variety and volume of data are growing tremendously; it is a challenging situation to mine the valuable information in a faster manner. Even though many researchers proposed many different kinds of algorithms for Frequent Item Set Mining it suffers defeat against either the size of frequent itemset or the time taken to finish the task. From this point of view, this paper proposes a new approach to mine the frequent items by using the Geometric progression series number as a label for each item and making its sum of items in the subset as a single value to find its frequency.
Implementation of blockchain technologies in the non-financial area

This thesis is devoted to the analysis of the application of blockchain technology in non-financial areas. The distributed ledger functionality coupled with security of BlockChain, makes it very attractive technology to solve the current Financial as well as non-financial business problems.Bitcoin, with its phenomenal popularity, has aroused interest among almost all financial institutions and businessmen. There is enormous interest in BlockChain based business applications and hence numerous Start-ups working on them. Today, there are several successfully implemented systems based on blockchain technology. Some such systems are mentioned in this thesis. Their activities, achievements, advantages and disadvantages are listed.
Impacto de comunidades educativas virtuales: el caso de Educar Ecuador

The virtual educational community Educar Ecuador is an initiative of the Ministry of Education for the integration of technologies in education. About its impact, there are multiple studies, but at the macro level, which has limited data on its effects by areas and subjects. On this basis, a transversal study (2017-2018) was developed to analyze the statistical correlation between the implementation of the educational community and the academic performance in the mathematics subject. The sample was 150 students of Accounting and Systems Administration. A survey was applied, and for the analyses it was decided to apply linear regressions. The simple regression analyses between the performance and the factors associated with the use of ICT, in the last two school years, show that the incidence variable of face-to-face classes with the use of technologies within the classroom, had a high impact on the final academic performance.
The Effect of Educational Dynamics and Educational Brand on Perceived Public Trust and Self-developmental Behavior of Faculty Members

Decreasing the efficiency of universities and increasing distrust have reduced the attractiveness of universities and weakened the demand for them. Therefore, trying to create more educational dynamics and acquire an educational brand that is dependent in one dimension on the self-developed behaviors of faculty members and can improve the level of educational trust. Therefore, the purpose of this study was to investigate the effect of educational dynamics and educational brand on perceived public trust and self-development behavior of faculty members of Sistan and Baluchestan University. The statistical population includes all faculty members of Sistan and Baluchestan University (380). Samples were selected by stratified random sampling using 191 Morgan table. Standard questionnaires of educational dynamics of Shafipour Motlagh and Moosivand (2018); Educational brand Shafipour Motlagh and Moosivand (2018); the general trust of Gharakhani et al. (2014) and the self-developmental behavior of Ahmadi et al. (2017) were used. Their validity of questionnaires was calculated and confirmed through confirmatory factor analysis and Cronbach's alpha test and combined reliability. Data analysis tools were SPSS 20 and Smart Pls software. Structural equation modeling was used to analyze the data. The results showed that educational dynamics and educational brand affect perceived public trust and self-development behavior of faculty members of Sistan and Baluchestan University.
Security and Privacy using Two Fold Encryption Protocol Techniques in Edge Computing

With deployments of IoT devices and the arrival of 5G fast wireless, placing compute and analytics close to where data is created is making the case for edge computing. Edge computing is transforming the way data is being handled, processed, and delivered from millions of devices around the world. The explosive growth of internet-connected devices – the IoT – along with new applications that require real-time computing power, continues to drive edge-computing systems. Due to several advantages like low latency, Real-Time Availability. Real-time Data Transmission, brings Company and customer together, Edge Computing is used. To overcome several problems regarding security and privacy concerns, this paper provides solution by introducing Secured Two Fold Encryption Protocol in Edge Computing (STFC) based on two encryption schemes namely proxy re-encryption and searchable encryption. This paper particularly focus on securing the data from attackers by providing double encryption scheme. In this paper, Resource Manager is introduced in order to reduce the computational overhead in the encryption process.
Improving Speaking Abilityby Using Blindfold

This research aimed to find out the improvement of the students’ speaking ability in terms of accuracy dealing with vocabulary and fluency dealing with smoothness through Blindfold Technique at Eight Grade I of SMP Negeri 2 Sungguminasa. The method in this research, the researcher used a pre-experimental research which Eight Grade Students of SMP Negeri 2 Sungguminasa with the number of the subject 30 students with 15 women and 15 man. Instruments are Speaking test and observation. The result of the data indicated that there was difference between students pre- test and post-test. The mean score of the students speaking ability also was greater than the mean score of pre-test (4,11 . 3,37), from t-test researcher found, the value of t-test (6,25) was greater that t-table (2,045) at the level of significance 0,05 with degree of freedom (df) = 29, it means that there was significant difference between student speaking ability before and after using Blindfold Technique.It is also said that the null hypothesis (H0) was rejected and alternative hyphotesis (H1) was accepted. The result of the research, Blindfold Technique improved the students’ speaking ability. There was significant improvement with students’ speaking ability, especially improved the student ability in accuracy and fluency.
Reading Comprehension Strategies Used by Students in Different Grades at MA Darul Ishlah (Al-Azhaar Boarding School Lubuklinggau)

This study aimed to find out and investigate the use of reading strategies used by students in different grades of MA Darul Ishlah (Al-Azhaar Boarding School Lubuklinggau). The study employed a mixed method (quantitative and qualitative). The total number of the participants in this study was 108 students which come from class X is 53 students, class XI is 25 students, and the last class XII is 30 students. The instruments of this research were questionnaire and interview. The data were analyzed by using percentage formula. The major findings are, first, all students in different grades were medium in level of use for all the strategies. Second, they only used some strategy in reading comprehension, because there are some strategy was difficult for them to apply in reading comprehension and the strategy was not teach explicitly. For instance, in the first grade students in global reading strategy rarely used memorized, read aloud, guessing, and summary. Meanwhile, While, the most frequently reading strategy used by students in different grade is global reading strategy, then following by problem-solving reading strategy and the last is support reading strategy.
Development of Learning Achievement in English for Marketing Subject by Using Project Work “B.E. Hometown Products Fair"

The purposes of this research were (1) to study the learning achievement of the second year Business English students, the Faculty of Humanities and Social Sciences, Suan Dusit University in English for Marketing subject after using project work “B.E. Hometown Products Fair” to have an average score at 70% or more, and (2) to study the students’ satisfaction toward the learning through project work “B.E. Hometown Products Fair” in English for Marketing subject. Quantitative research was used and research instruments were (1) the progress test and (2) the satisfaction questionnaire. Data collected from the sampling group who was 76 second year Business English students, the Faculty of Humanities and Social Sciences, Suan Dusit University. The statistics used for data analysis were frequency, means, and the Standard Deviation (S.D.). The findings revealed that the average scores of the students in English for Marketing subject were 73.25% and the students’ satisfaction of learning through project work was 87.98%.
Inferring Visual Contracts from Java Programs.

Visual contracts model the operation of components or services by pre- and post-conditions formalised as graph transformation rules. They provide a precise intuitive notation to support testing, understanding and analysis of software. Their detailed specification of internal data states and transformations, referred to as deep behavioural modelling, is an error-prone activity. In this paper we propose a dynamic approach to reverse engineering visual contracts from Java based on tracing the execution of Java operations. The resulting contracts give an accurate description of the observed object transformations, their effects and preconditions in terms of object structures, parameter and attribute values, and their generalised specification by universally quantified (multi) objects, patterns, and invariants. While this paper focusses on the fundamental technique rather than a particular application, we explore potential uses in our evaluation, including in program understanding, review of test reports and debugging.
Survey form and methods for second CASC survey of academic research computing and data center usage

Full analysis paper is in the ACM PEARC'21 Proceedings: ACM ISBN 978-1-4503-8292-2/21/07.https://doi.org/10.1145/3437359.3465589
The Impact of Organizational Climate on the Enhancement of Belonging in the Hospitality Sector: The Saudi Context

Organizational climate is an approach used regarding organizational behavior that distinguishes an organization from others and highlights it in a better and more positive manner when compared to its competitors. This study aims to assess the degree of organizational climate dimensions (clarity of goals, effectiveness of communication, balance of power, use of resources, cohesion, morale, creativity, independence, adaptation, and problem-solving) present in five-star hotels within the regions of Makkah and Madinah in Saudi Arabia, and the impact it has on enhancing the sense of belonging in employees. To achieve the goal of the study, the researcher distributed a questionnaire to a random sample of employees selected from those hotels, and 882 questionnaires were valid for analysis. The study discovered that all organizational climate dimensions in the five-star hotels within the regions of Makkah and Madinah are clearly present, in addition to employees practicing the method of enhancing the sense of belonging correctly. The results also highlighted the significant and positive impact that the organizational climate and its ten dimensions had on enhancing the sense of belonging among employees in those hotels.
Predicting Lead and Nickel Contamination in Soil using Spectroradiometer

In the geosciences, visible–near–short-wave infrared reflectance spectroscopy seems to have the capability to become a helpful technique for soil classification, mapping, and remote confirmation of soil characteristics and mineral composition. Focus on improving the spatial resolution of soil maps in order to better deal with localized problems like soil pollution. A variety of physio-chemical properties were measured in long-term spiked soils with a range of lead and nickel concentrations and also their spectral reflectance between 400 and 2500 nm at three different locations in the agricultural region of MIDC, Aurangabad, Maharashtra, India. Principle component analysis (PCA) used for feature extraction of soil were partial least squares regression (PLSR) method is used for classification. To measured amount of lead and nickel in soil sample, thirteen features of soil samples are calculated. The main aim of this study was to use statistical methods to calculate the lead and nickel concentrations in soil, as well as to assess the efficiency of VNIR-SWIR reflectance spectroscopy for heavy metal estimation in soil using the ASD FieldSpec4 Spectroradiometer. R2 = 0.96 provides the best precision for lead content and R2 = 0.95 for nickel content in soil, according to the findings. Lead and nickel have RMSEs of 3.396 and 2.680, respectively. The outcomes show that the proposed method is capable of accurately forecasting lead and nickel concentrations.
A Study on Suffix Trees and Their Applications in Genome Sequences Using MUMmer

A suffix tree is a data structure that stores a string of text. In bioinformatics, the suffix trees can be used as a tool to align the entire genomes of closely related organisms, to compare sequence assemblies at different phases and to compare and analyze the results. This paper focuses on the aligning of various whole genome sequences, using suffix trees. In the present investigation, the implementations of the suffix trees are discussed, focusing on two models for comparison and alignment. The first model is multiple sequence alignment based on a suffix tree and center-star strategy (MASC), which is a leading method to find solutions for the alignment of evolutionarily related sentences, considering evolutionary events like mutations, insertions, deletions and rearrangement. MASC applies to deoxyribonucleic acid (DNA), ribonucleic acid (RNA) and protein sequences. The second model maximal unique match (MUMmer) is discussed. Multiple genome alignment tools (Clustal Omega, Clustal W, MUSCLE, MAFFT and Mauve) are compared with MUMmer and are proving the efficiency of MUMmer, because of the use of the suffix trees.
Active Testing: Sample-Efficient Model Evaluation

We introduce a new framework for sample-efficient model evaluation that we call active testing. While approaches like active learning reduce the number of labels needed for model training, existing literature largely ignores the cost of labeling test data, typically unrealistically assuming large test sets for model evaluation. This creates a disconnect to real applications, where test labels are important and just as expensive, e.g. for optimizing hyperparameters. Active testing addresses this by carefully selecting the test points to label, ensuring model evaluation is sample-efficient. To this end, we derive theoretically-grounded and intuitive acquisition strategies that are specifically tailored to the goals of active testing, noting these are distinct to those of active learning. As actively selecting labels introduces a bias; we further show how to remove this bias while reducing the variance of the estimator at the same time. Active testing is easy to implement and can be applied to any supervised machine learning method. We demonstrate its effectiveness on models including WideResNets and Gaussian processes on datasets including Fashion-MNIST and CIFAR-100.
Pemodelan Mesin Pendeteksi Ujaran Kebencian di Sosial Media Indonesia

This research discusses the development of a model that can be used to detect hate speech in Indonesia's popular social media. Several methods are collected, analyzed, and implemented to build a framework that is practical and can be used to detect hate speech. The research methodology starts with the study of literature, analysis, and design of the model. From the analysis results, N-Gram, Word2vec, LSTM and emotion classification is used as part of the process of the model. This model consists of ten processes that are carried out sequentially so that comments collected through Facebook and Whatsapp social media can be identified when they contain hate speech. The model also considers the applicable law in Indonesia to facilitate the legal handling of perpetrators.
Perancangan Aplikasi Game Edukasi Pengenalan Hewan Dan Tanaman Langka Berbasis Android

AbstractAndroid is an information technology that is currently being developed. Indonesia is listed as a country in Southeast Asia where the majority of its citizens use Android, namely 94% of users. The use of Android-based smartphones among children is now starting to increase. In general, the use of smartphones among teenagers is used to play games. Along with the development, various games have emerged that attract schoolchildren or students, one of which is an educational game on the introduction of rare animals and plants in Indonesia. Educational game applications are divided into 3 game stages, namely for early childhood from 3-7 years old, for elementary school (SD) children aged 7-12 years and general 13 years and over. Games for early childhood are with a game model that adjusts animal sounds and pictures, games for elementary school children are in the form of puzzles and quizzes while for the general public, they are in the form of puzzle games and quizzes with a time limit. From the results of direct analysis, observation and testing, educational games on the introduction of rare animals and plants can run well in accordance with the original purpose of making the application, with the application it can help in recognizing rare animals and plants in Indonesia which refers to the tendency of humans to be more receptive. information in the form of pictures and writing and at the same time the presence of this application can be a means of learning knowledge and playing that are effective, interesting, practical and educational.
Measurement Effectiveness, Efficiency, and Satisfaction of E-Commerce Using Usability Evaluation

Current business developments, enlivened by industries that peddle their products via theinternet, both through websites and social media. Shopee is a mobile application based E-commerce,which is developing in Indonesia. Shopping websites that are accessed by online shoppers are required to have a high level of reusability to make it easier for users to shop online. This researchentitled Measurement Effectiveness, Efficiency, and Satisfaction of E-Commerce Using Usability Evaluation. This study aims to analyze the usability for measuring levels, where a product can beused by certain users to achieve its goals more effectively, efficiently, and satisfy users of Shopee web applications. The research instrument was in the form of a questionnaire as a way to collectdata using the Think Aloud method. After processing the questionnaire data, it will be analyzed using the SUS method. Obtained the results of the analysis using the SUS method of each parameter, forthe effectiveness parameters with an average value of 53, efficiency with an average of 51 and satisfaction with an average of 61.
Inverting Adversarially Robust Networks for Image Synthesis

Despite unconditional feature inversion being the foundation of many image synthesis applications, training an inverter demands a high computational budget, large decoding capacity and imposing conditions such as autoregressive priors. To address these limitations, we propose the use of adversarially robust representations as a perceptual primitive for feature inversion. We train an adversarially robust encoder to extract disentangled and perceptually-aligned image representations, making them easily invertible. By training a simple generator with the mirror architecture of the encoder, we achieve superior reconstruction quality and generalization over standard models. Based on this, we propose an adversarially robust autoencoder and demonstrate its improved performance on style transfer, image denoising and anomaly detection tasks. Compared to recent ImageNet feature inversion methods, our model attains improved performance with significantly less complexity. Code available at https://github.com/renanrojasg/adv_robust_autoencoder .
Local stereo matching algorithm using modified dynamic cost computation

Stereo matching is an essential subject in stereo vision architecture. Traditional framework composition consists of several constraints in stereo correspondences such as illumination variations in images and inadequate or non-uniform light due to uncontrollable environments. This work improves the local method stereo matching algorithm based on the dynamic cost computation method for depth measurement. This approach utilised modified dynamic cost computation in the matching cost. A modified census transform with dynamic histogram is used to provide the cost in the cost computation. The algorithm applied the fixed-window strategy with bilateral filtering to retain image depth information and edge in the cost aggregation stage. A winner takes all (WTA) optimisation and left-right check with adaptive bilateral median filtering are employed for disparity refinement. Based on the Middlebury benchmark dataset, the algorithm developed in this work has better accuracy and outperformed several other state-of-the-art algorithms.
Management of coping with the risks of COVID-19 in an onco-hematological outpatient clinic: an experience report/ Gestión del afrontamiento de los riesgos de COVID-19 en una red oncohematológica ambulatoria: relato de experiencia/ Gestão do enfrentamento dos riscos da COVID-19 em uma rede ambulatorial onco-hematológica: relato de experiência

ABSTRACT Objective: to describe the experience of a private outpatient network for hematology and oncology treatment in the adoption of management tools to face the risk of contamination by SARS-CoV-2. Method: an experience report on the use of a root cause analysis method to identify potential risks of contamination by COVID-19 among patients and employees. Through the risks identified through the Ishikawa Diagram, we built an action plan, linked to the 5W2H tool, for planning and decision-making implemented. Results: the number of attendances in person and people circulating in the units was reduced, protective distance measures and new protection barriers were fundamental to control the risks of spreading COVID-19 in patients and employees. Final considerations: the management tools served as a valuable tool in the construction of measures, making the measures in question more clearly and applicable.