Reviewerly/exHarmony huggingface dataset:
The New-Normal of Talent & Knowledge Management – A Framework towards Virtual Learning – Post- COVID-19

Indian economy since the pre and post-independence period has witnessed a drastic transformation from an agrarian economy to a knowledge-based economy thus creating a knowledge-based workforce and organisations. With the change of time, the learning became more complex and necessity thus creating havoc and high-pace change in the character of the job in an organisation even creating a situation where artificial intelligence is replacing human intelligence.Today’s employees are more competitive in terms of skills, pay-packages, and also work challenges. Amidst of all these changes, the present uncertainty and crisis hovering the entire world i.e .the Corona Virus pandemic which has forced almost all organizations to accept virtual learning and virtual knowledge sharing as a competitive edge and adapting virtual-cost-effective learning and communication system. It is prime time when the management of the organisation has to initiate a holistic approach towards virtual learning and knowledge sharing with a clear objective of up-skilling its workforce to new normals during and post-pandemic. The new normal norms will bring in new challenges of a new set of skills and competencies and operational processes to revive the broken economy and business setbacks.This paper further concentrates and focuses on applying and improving virtual knowledge management practices in organisation. It also focuses on effective talent up-gradation and management systems which most important in the present scenario to have a ‘Fact-Based Communication' And 'Virtual Connectivity'.Here, Descriptive Research is adopted for the study. Literature review of articles and research papers is analytically conducted to develop a significant process for crucial talent management systems that will aid in the up-skilling workforce through virtual mode to combat and resurgence the Post- COVID-19.
Penerapan Metode Iteratif Lanczos–Hybrid Regularization Pada Restorasi Citra Digital Hasil Scan

Digital image management generally refers to processing two-dimensional images using a computer in a broader context. Image restoration is image pemamangan by eliminating or reducing degradation of the image that occurs due to the process of image acquisition. The scanned image is the process of moving images (images) using a scanner which often experiences a decrease in image quality (degraded). This results in inaccurate results in digital image processing such as blur / blur, spots, dual images, over saturated colors, and pixel errors. Caused by external factors (noise). Iterative lanczos-Hybrid Reqularization method is one of the choices of effective methods in solving the blur or noise problem that causes the image quality to decrease or not match the original image. In the process of digital image restoration scan results that have degraded can be maximized well from the original image, in this study the Iterative lanczos-Hybrid Reqularization method of image restoration used can provide more optimal results with more effective and efficient time.
Open Web Ontobud: An Open Source RDF4J Frontend (Short Paper)

Nowadays, we deal with increasing volumes of data. A few years ago, data was isolated, which did not allow communication or sharing between datasets. We live in a world where everything is connected, and our data mimics this. Data model focus changed from a square structure like the relational model to a model centered on the relations. Knowledge graphs are the new paradigm to represent and manage this new kind of information structure.Along with this new paradigm, a new kind of database emerged to support the new needs, graph databases! Although there is an increasing interest in this field, only a few native solutions are available. Most of these are commercial, and the ones that are open source have poor interfaces, and for that, they are a little distant from end-users.In this article, we introduce Ontobud, and discuss its design and development. A Web application that intends to improve the interface for one of the most interesting frameworks in this area: RDF4J. RDF4J is a Java framework to deal with RDF triples storage and management.Open Web Ontobud is an open source RDF4J web frontend, created to reduce the gap between end users and the RDF4J backend. We have created a web interface that enables users with a basic knowledge of OWL and SPARQL to explore ontologies and extract information from them.
Crowd Counting via Hierarchical Scale Recalibration Network

The task of crowd counting is extremely challenging due to complicated difficulties, especially the huge variation in vision scale. Previous works tend to adopt a naive concatenation of multi-scale information to tackle it, while the scale shifts between the feature maps are ignored. In this paper, we propose a novel Hierarchical Scale Recalibration Network (HSRNet), which addresses the above issues by modeling rich contextual dependencies and recalibrating multiple scale-associated information. Specifically, a Scale Focus Module (SFM) first integrates global context into local features by modeling the semantic inter-dependencies along channel and spatial dimensions sequentially. In order to reallocate channel-wise feature responses, a Scale Recalibration Module (SRM) adopts a step-by-step fusion to generate final density maps. Furthermore, we propose a novel Scale Consistency loss to constrain that the scale-associated outputs are coherent with groundtruth of different scales. With the proposed modules, our approach can ignore various noises selectively and focus on appropriate crowd scales automatically. Extensive experiments on crowd counting datasets (ShanghaiTech, MALL, WorldEXPO'10, and UCSD) show that our HSRNet can deliver superior results over all state-of-the-art approaches. More remarkably, we extend experiments on an extra vehicle dataset, whose results indicate that the proposed model is generalized to other applications.
Academic and Administrative Attitude of Prospective Teachers Towards Teaching Profession

Education seeks to develop the innate inner capacities of man. The ultimate goal of education is to prepare the students to be responsible and mentally healthy person to live on this earth. In order to achieve this, students are to be molded only by making them experience the significance of values in the school itself. In most of the cases education takes place under the guidance of teachers. Teachers are the biggest influencers in a student’s life. Their personality and attitudes contribute to a great extend in students learning. In this respect, determining the attitude of prospective teachers towards teaching profession is of great importance. The main objectives of this paper are to test: academic attitude of prospective teachers towards teaching profession; and administrative attitude of prospective teachers towards teaching profession. Tool used for the study was ‘attitude scale towards teaching’, developed by Dr. (Mrs.) Ummen Kulsum. In order to analyze the data, Z-score in terms of standard deviations from the mean was used. The study was delimited to West Garo Hills District of Meghalaya.
IMPLEMENTING COMMUNICATIVE FLUENCY ACTIVITIES AS LEARNING TECHNIQUE TO PROMOTE THE STUDENTSâ€™ ABILITY IN WRITING DESCRIPTIVE TEXT

This research explores the ability of students to write descriptive scripts through communicative fluency activities (CFA) as learning techniques. This study aims to determine whether the Communicative Fluency Activitie has improved the ability second grade students of Politeknik Negeri Ambon in academic year 2019-2020. The method used is pre-experimental by providing two types of tests, namely pre-test and post-test. The research sample was selected using random selection. The number of samples is 27 students from class TKJJB. The instrument used was writing test. The data obtained were analyzed using t-test. The result of the research showed the students' writing ability after being taught with the CFA technique is better than before. This can be proven by the value of t-test (13.48) higher than the value of t-table (1.721) where (df) = (N-1) = (22-1) = 21 with a significant level of 0.05. That means that teaching through communicative fluency techniques can improve the writing ability of second grade students of Politeknik Negeri Ambon. Keywords: descriptive text, communicative fluency activities (CFA), learning technique
Knowledge and Awareness About Thrombocytopenia Associated with Covid-19

Thrombocytopenia is a condition in which the platelet count is low. Some cancers, such as leukemia, can cause thrombocytopenia. Platelets are colourless blood cells and their physiological role is to clot blood. Dangerous, internal bleeding can occur when the platelet count falls below 10,000 platelets per microliter. Where severe thrombocytopenia can cause bleeding into the brain, which can be fatal. In that Novel virus, COVID-19 is associated with thrombocytopenia. The aim of this study is to study the knowledge and awareness about thrombocytopenia associated with COVID-19. The questionnaire was prepared and circulated among adults of hundred participants through Google forms an online website. The questionnaire was prepared to analyse the knowledge of thrombocytopenia associated with COVID-19. Results were analysed by using SPSS software version 20. From this study, 100% of the participants gave a positive response when asked about thrombocytopenia associated with COVID-19 and nd also aware of thrombocytopenia associated with COVID-19, 77% of the population think that thrombocytopenia is associated with COVID-19. This study gives an insight on the public perception towards thrombocytopenia associated with COVID-19.
Evaluation of Frequent Itemset Mining Algorithms-Apriori and FP Growth

Nowadays the Frequentitemset mining (FIM) is an essential task for retrieving frequently occurring patterns, correlation, events or association in a transactional database. Understanding of such frequent patterns helps to take substantial decisions in decisive situations. Multiple algorithms are proposed for finding such patterns, however the time and space complexity of these algorithms rapidly increases with number of items in a dataset. So it is necessary to analyze the efficiency of these algorithms by using different datasets. The aim of this paper is to evaluate theperformance of frequent itemset mining algorithms, Apriori and Frequent Pattern (FP) growth by comparing their features. This study shows that the FP-growth algorithm is more efficient than the Apriori algorithm for generating rules and frequent pattern mining.
LIFE SKILLS EDUCATION IN INCREASING THE INDEPENDENCE OF STUDENTS PURSUING PACKAGE C THROUGH THE SPNF SKB TRENGGALEK

The background of the research in this thesis is based on population data in Trenggalek district, it is found that the population of productive age with low education (not graduating from school) has an unemployment rate that is higher than those who have completed education. The research focuses in this thesis are: (1). How is the personal skills ordering system in increasing the independence of package C students at SPNF SKB Trenggalek (2). How is the social skills booking system in increasing the independence of package C students. (3). What is the system for ordering intellectual skills in increasing the independence of package C students (4). How is the vocational proficiency ordering system in increasing the independence of package C students. The results of the research are (1). The personal skill formation system in increasing the independence of package C students at SPNF SKB Trenggalek is a very important skill, even the first and foremost skill that students must have, where personal skills are behaving in accordance with religious, social, and religious norms. law, have faith in God Almighty, have noble character, are just, honest, commendable, have a work ethic, are responsible and can be trusted. (2).Social skills formation system in increasing the independence of package C students: Social skills for students have characteristics, namely being open, easy to socialize / communicate well with others, superiors, customers / customers and relate to their environment / community the surroundings. (3). The system for building intellectual skills in increasing the independence of package C students: Where this skill implies the ability to analyze simply, think logically, the ability to make decisions, explore good ideas, the ability to dare to try in their field scientifically . (4). Vocational skills formation system in increasing the independence of package C students: Vocational skills (vocational skills), namely the ability to choose jobs, job training, mastering competencies, mastering skills, applying technology, carrying out work processes and producing goods and services that can ultimately improve their standard of living and be able to compete with DU / DI.
EVALUASI DAN PERANCANGAN SISTEM PENGENDALIAN INTERN PENJUALAN JASA HOTEL (Studi Kasus Pada Bandung Giri Gahana Golf and Resort)

The sale of services is a determining factor in the leisure business, because it is the company's main source of income. In order for maximum income to be obtained, an effective and efficient Internal Control System (SPI) is needed to reduce fraud that occurs in the company so that revenue can be maximized. SPI at Bandung Giri Gahana Golf &amp; Resort is still ineffective because it lacks supervision and does not implement Standard Operating Procedures (SOP) by the frontliners. Therefore it is necessary to conduct an evaluation to assess how effective and efficient the existing SPI is and what recommendations are needed to improve it. This study aims to evaluate and analyze and design SPI at Bandung Giri Gahana Golf &amp; Resort. The research was conducted using a qualitative descriptive method with a case study approach. Data collection was carried out by documentation, observation and interviews.
An analytical survey on the role of image cryptography and related computational methods

In the current scenario data security is an important and crucial aspects. It is crucial in terms of different domains and application areas like banking, enterprises, educational institutes, etc. In this paper a survey and analysis have been presented on the role of image cryptography and related computational methods. This paper covers and highlighted different cryptography, steganography and related computational methods in case of image data security. It also covers the areas of applicability and the gaps in the previous methods. The impact of the current results has been analyzed also along with the implication.
Head-mounted, wireless eyetracker for real-time gaze prediction utilizing machine-learning

Eyetracking opens new possibilities for people with physical disabilities, enabling them to explore new ways of communication and interaction with their environment. However, this field of assistive technology is not available to everyone in need and still faces substantial obstacles: high-cost devices for use in real-world environments, difficulty in enhancing the performance of a calibrated system, difficulty in providing a personalized, adaptive setup. The aim of this work is to provide a lightweight, low cost, wireless device with a software performing real-time 2-D gaze prediction in a fixed coordinate system, and the possibility of enhancing performance by recalibration.
Lattice-Based Information Flow Control-by-Construction for Security-by-Design.

Many software applications contain confidential information, which has to be prevented from leaking through unauthorized access. To enforce confidentiality, there are language-based security mechanisms that rely on information flow control. Typically, these mechanisms work post-hoc by checking whether confidential data is accessed unauthorizedly after the complete program is written. The disadvantage is that incomplete programs cannot be interpreted properly and information flow properties cannot be built in constructively. In this work, we present a methodology to construct programs incrementally using refinement rules to follow a lattice-based information flow policy. In every refinement step, confidentiality and functional correctness of the program is guaranteed, such that insecure programs are prohibited by construction. Our contribution is fourfold. We formalize refinement rules for the constructive information flow control methodology, prove soundness of the refinement rules, show that our approach is at least as expressive as standard language-based mechanisms for information flow, and implement it in a graphical editor called CorC. Our methodology is also usable for integrity properties, which are dual to confidentiality.
Automated Dependence Plots.

In practical applications of machine learning, it is necessary to look beyond standard metrics such as test accuracy in order to validate various qualitative properties of a model. Partial dependence plots (PDP), including instance-specific PDPs (i.e., ICE plots), have been widely used as a visual tool to understand or validate a model. Yet, current PDPs suffer from two main drawbacks: (1) a user must manually sort or select interesting plots, and (2) PDPs are usually limited to plots along a single feature. To address these drawbacks, we formalize a method for automating the selection of interesting PDPs and extend PDPs beyond showing single features to show the model response along arbitrary directions, for example in raw feature space or a latent space arising from some generative model. We demonstrate the usefulness of our automated dependence plots (ADP) across multiple use-cases and datasets including model selection, bias detection, understanding out-of-sample behavior, and exploring the latent space of a generative model.
An Analysis of English Students’ Motivation in Reading Academic Articles at English Education Program of Universitas Negeri Padang

This study aimed to find out the motivation of the English Education 2016 Universitas Negeri Padang in reading academic articles and factors influenced their motivation. This research was done through descriptive qualitative method with 84 populations. The samples of this study were 84 students chosen by using total sampling techniques. The data were collected through a questionnaire adapted from Reading Motivation Questionnaire by Wigfield and Guthrie (1997). The findings of this research indicate that: (1) English Education 2016 students have high motivation because 66 students are in 2,51 – 3,25 mean range. It means that half of the samples are at high level motivation to read academic articles and there are only 6 samples that have low level motivation in reading academic articles (the mean score is 1,76 - 2,50). Moreover, 12 students have very high motivation in reading academic articles (the mean score is in 3,26 - 4,00 range); (2) factors that influenced the motivation of English Education 2016 students’ in reading academic articles are dominated by intrinsic factors.
PTangle: A Parallel Detector for Unverified Blockchain Transactions

Tangle is a novel directed acyclic graph (DAG)-based distributed ledger preferred over traditional linear ledgers in blockchain applications because of better transaction throughput. Earlier techniques have mostly focused on comparing the performance of graph chains over linear chains and incorporating the Markov Chain Monte Carlo process in probabilistic traversals to detect unverified transactions in DAG chains. In this paper, we present a parallel detection method for unverified transactions. Experimental evaluation of the proposed parallel technique demonstrates a significant, scalable average speed-up of close to 70%, and a peak speed-up of approximately 73% for a large number of transactions.
Is Impredicativity Implicitly Implicit

Of all the threats to the consistency of a type system, such as side effects and recursion, impredicativity is arguably the least understood. In this paper, we try to investigate it using a kind of blackbox reverse-engineering approach to map the landscape. We look at it with a particular focus on its interaction with the notion of implicit arguments, also known as erasable arguments.More specifically, we revisit several famous type systems believed to be consistent and which do include some form of impredicativity, and show that they can be refined to equivalent systems where impredicative quantification can be marked as erasable, in a stricter sense than the kind of proof irrelevance notion used for example for Prop terms in systems like Coq.We hope these observations will lead to a better understanding of why and when impredicativity can be sound. As a first step in this direction, we discuss how these results suggest some extensions of existing systems where constraining impredicativity to erasable quantifications might help preserve consistency.
A Study on the Educational Relationship in University Education

This study verified the effect of the educational relationship between teacher and student on the overall satisfaction of university education. The survey was conducted on college students from October 22 to December 20, 2019, and a total of 305 samples were used for the final analysis. The analysis results showed that the factors of educational relationship had significant impacts on students' overall satisfaction. Specifically, the most influential factor was the professor's trust and enthusiasm among the factors. It was also the most significant factor in the analysis results considering the students' gender, grade and disposition. First, female students were influenced by all factors of the educational relationship on the satisfaction. And in the case of first and second graders, the professor's attention played an important role. The third and fourth graders were affected by the professor's expectation and interaction. Finally, considering the students' propensity, both introverts and extroverts had significant impacts on their satisfaction by the professor's trust and enthusiasm. Therefore, the most important point in the educational relationship means that the trust and enthusiasm of the professor's teaching should be equipped with the most basic requirements.
Anchored Causal Inference in the Presence of Measurement Error.

We consider the problem of learning a causal graph in the presence of measurement error. This setting is for example common in genomics, where gene expression is corrupted through the measurement process. We develop a provably consistent procedure for estimating the causal structure in a linear Gaussian structural equation model from corrupted observations on its nodes, under a variety of measurement error models. We provide an estimator based on the method-of-moments, which can be used in conjunction with constraint-based causal structure discovery algorithms. We prove asymptotic consistency of the procedure and also discuss finite-sample considerations. We demonstrate our method's performance through simulations and on real data, where we recover the underlying gene regulatory network from zero-inflated single-cell RNA-seq data.
A PatchMatch-based Approachfor Matte Propagation in Videos

This thesis presents a temporally-coherent matte-propagation method for videos based on PatchMatch and edge-aware filtering. Given an input video and trimaps for a few frames, including the first and last, our approach generates alpha mattes for all frames of the video sequence. We also present a user scribble-based interface for video matting that takes advantage of the efficiency of our method to interactively refine the matte results. We perform quantitative comparisons against the state-of-the-art sparse-input video matting techniques and show that our method produces significantly better results according to three different metrics. We also perform qualitative comparisons against the state-of-the-art dense-input video matting techniques and show that ours produces similar quality results while requiring less than 7% of their user input.