Reviewerly/exHarmony huggingface dataset:
Bluestacks-All Versions

The Bluestacks for Windows Vista is designed to be the most functional, easy to use program for Vista that is available today. The program works ...
Automatic Speech Recognition in Somali

The field of speech recognition during the last decade has left the research stage and found its way into the public market, and today, speech recognition software is ubiquitous around us. An autom ...
LibGuides: AHE Master's Program (Ecampus): Distance Libraries

This guide supports the AHE 500-level courses in the Master of Education in Adult and Higher Education program.
Increasing transparency in the supply chain with blockchain technology : A case study of small and medium sized South African wine producers

The world is facing new challenges caused by global warming and is puttingpressure on governments, companies and the civil society to act fast. Like all industries, the wine industry is affected by ...
Discriminative Representation Loss (DRL): A More Efficient Approach than Gradient Re-Projection in Continual Learning

The use of episodic memories in continual learning has been shown to be effective in terms of alleviating catastrophic forgetting. In recent studies, several gradient-based approaches have been developed to make more efficient use of compact episodic memories, which constrain the gradients resulting from new samples with those from memorized samples, aiming to reduce the diversity of gradients from different tasks. In this paper, we reveal the relation between diversity of gradients and discriminativeness of representations, demonstrating connections between Deep Metric Learning and continual learning. Based on these findings, we propose a simple yet efficient method -- Discriminative Representation Loss (DRL) -- for continual learning. In comparison with several state-of-the-art methods, this method shows effectiveness with low computational cost on multiple benchmark experiments in the setting of online continual learning.
Awareness about and Success of Memes Pages on Social media Platforms

Memes have hugely become a form of social currency in recent years. But, how far have the Memes pages on social media platforms likes Facebook, Instagram and Whats app, etc have been successful? if they have been successful, why have they been successful? These are the questions that this paper attempts to find out.
Cointegration among cryptocurrencies : A cointegration analysis of Bitcoin, Bitcoin Cash, EOS, Ethereum, Litecoin and Ripple

The purpose of this paper is to examine if there is cointegration between the daily closing price of the cryptocurrency Bitcoin and five other cryptocurrencies; Ethereum, Ripple, Bitcoin Cash, EOS ...
Grey Wolf Optimizer: Theory, Literature Review, and Application in Computational Fluid Dynamics Problems.

This chapter first discusses inspirations, methematicam models, and an in-depth literature of the recently proposed Grey Wolf Optimizer (GWO). Then, several experiments are conducted to analyze and benchmark the performance of different variants and improvements of this algorithm. The chapter also investigates the application of the GWO variants in finding an optimal design for a ship propeller.
Grammatica della lingua italiana Per Stranieri 1

Grammatica della lingua italiana Per Stranieri  1 Author: Roberto Tartaglione, Angelica Benincasa Alma Edizioni New Italian Grammar with exercises, tests, real-life examples, and digital content. (Level A1 - A2) Free Pick up at School *Due to major USPS delays, Speakitaly NYC is not responsible for any lost or damaged packages once they are shipped and the tracking number is provided.
Re-engineering of IKAPCR Scholarship Information System

The Politeknik Caltex Riau’s Alumni Association (IKAPCR) has a scholarship information system that contains a Decision Support System (DSS) and scholarship financial management. The IKAPCR scholarship information system requires a reengineering process of several features to meet the needs of system users at the management level. Evaluation of beta testing on IKAPCR scholarship information system shows that the system runs normally as it should based on user requirements, it is informative and innovative, and able to accelerate the scholarship acceptance selection process. While its weaknesses are the process of data integration with the academic system of Politeknik Caltex Riau (PCR), regular reminder donation services via e-mail and SMS, data management on semester payments for scholarship recipients and additional variations graphic info for the analysis process. Therefore, this system needs a reengineering process to improve efficiency at each mechanism of the process. Testing with WebQual of 117 students and 33 PCR alumni, the accuracy of the student respondents was 79.7% which showed that respondents agreed that the quality of the web was good and 80.2% of the alumni respondents indicated that respondents strongly agreed on good web quality.&#x0D;
CREATING THE SITUATION OF SUCCESS IN THE HUMAN SCIENCES – A PREREQUISITE FOR THE HUMANIZATION OF EDUCATION

The problem of success became relevant at the beginning of the XXI century. Everyone strives to succeed, to be confident in themselves and in the future. Success is recognized as one of the needs of the individual. Reforming modern education is designed to make it human-centered, effective, close to the practical needs of the learner. The humanization of education is impossible without creating situations of success in learning. Such situations activate a person's cognitive motivation, reveal his creative potential, make a person strong and confident. To create situations of success, teachers use a variety of methods and tools that enhance the cognitive activity of students.
Barriers in Reading Comprehension of University Students: Analysis of the Complicated Words Annotated in the VYTEDU-CW Corpus

Students often require a greater understanding of the lexicon that teachers use when dictating an assignment in class or in written texts as supporting material. Identifying and labelling difficult words has allowed us to examine the problem. A sample of students from the University of Guayaquil (Ecuador) was taken to experiment in a corpus of video transcripts that correspond to the different careers. After performing the analysis of the tagged words, the conclusions reached by other research papers in lexical simplification are confirmed and corroborates the recommendations of the Easy Reading guide prepared by Inclusion Europe in 2009. The investigation determined that the words labeled as difficult were specialized words, common lexical words, slang, English words, acronyms, among others. It was difficult for students to understand its meaning; in some cases, they either ignored its definition or just had the wrong idea of the lexicon. This work aims to be a contribution to future research in the area of lexical simplification applied to the development of solutions for detecting difficult words in the university academic field. Also, the type of complex expressions identified in the VYTEDU-CW corpus were characterized by the software, which enriches this resource while opening the possibility to organize a workshop where to promote research in the detection of difficult words to the Spanish. The support to validate these solutions is available to the scientific community.
From Geometries to Contact Graphs

When a robot perceives its environment, it is not only important to know what kind of objects are present in it, but also how they relate to each other. For example in a cleanup task in a cluttered environment, a sensible strategy is to pick the objects with the least contacts to other objects first, to minimize the chance of unwanted movements not related to the current picking action. Estimating object contacts in cluttered scenes only based on passive observation is a complex problem. To tackle this problem, we present a deep neural network that learns physically stable object relations directly from geometric features. The learned relations are encoded as contact graphs between the objects. To facilitate training of the network, we generated a rich, publicly available dataset consisting of more than 25000 unique contact scenes, by utilizing a physics simulation. Different deep architectures have been evaluated and the final architecture, which shows good results in reconstructing contact graphs, is evaluated quantitatively and qualitatively.
Investigation on Large Vocabulary Continuous Kannada Speech Recognition

The proposed work carried out to convert the Kannada speech signal to a text document using Sphinx tools. The system is implemented for the large vocabulary of the Kannada speech signal by using the acoustic model (AM) and language model (LM) with the decoder. The AM extracted the Mel frequency cepstral coefficients (MFCC) of the speech signal successfully and trained these coefficients using hidden Markov model (HMM) and tweak the estimation of the AM using Baum-Welch method. The required language model (LM) format is built for the decoder using n-gram count. The decoder is configured to create a text file to the corresponding input speech signal using Sphinx3. The proposed automatic speech recognition (ASR) system achieves a better recognition rate with less word error rate (WER) with AM and LM adaptation using Sphinx3 for large vocabulary and Pocket Sphinx implemented on RasberryPi3 results better accuracy than the other ASR system.
Hybridized White Learning in Cloud-Based Picture Archiving and Communication System for Predictability and Interpretability

A picture archiving and communication system (PACS) was originally designed for replacing physical films by digitizing medical images for storage and access convenience. With the maturity of communication infrastructures, e.g. 5G transmission, big data and distributed processing technologies, cloud-based PACS extends the storage and access efficiency of PACS across multiple imaging centers, hospitals and clinics without geographical bounds. In addition to the flexibility of accessing medical big data to physicians and radiologists to access medical records, fast data analytics is becoming an important part of cloud-based PACS solution. The machine learning that supports cloud-based PACS needs to provide highly accurate prediction and interpretable model, despite the model learning time should be kept as minimum as possible in the big data environment. In this paper, a framework called White Learning (WL) which hybridizes a deep learner and an incremental Bayesian network which offer the highest possible prediction accuracy and causality reasoning which are currently demanded by medical practitioners. To achieve this, several novel modifications for optimizing a WL model are proposed and studied. The efficacy of the optimized WL model is tested with empirical breast-cancer mammogram data from a local hospital.
Improved Deep Learning Architecture For Depth Estimation

Numerous benefits of depth estimation from the single image field on medicine, robot video games, and3D reality applications have garnered attention in recent years. Closely related to the third dimension of depth, this operation can be accomplished using human vision, though considered challenging due to the various issues when using computer vision. The differences in the geometry, the texture of the scene, the occlusion scene boundaries, and the inherent ambiguity exist because of the minimal information that could be gathered from a single image. This paper, therefore, proposes a novel depth estimation in the field of architecture, which includes the stages that can manage the depth estimation from a single RGB image. An encoder-decoder architecture has been proposed, based on the improvement yielded from DenseNet that extracted the map of an image using skip connection technique. This paper also takes on the reverse Huberloss function that essentially suits our architecture hand driven by the value distributions that are commonly present in-depth maps. Experimental results have indicated that the depth estimation architecture that employs the NYU Depth v2 dataset has a better performance than the other state-of-the-art methods that tend to have fewer parameters and require fewer training time.
New Configurations for the Correction of the RDF knowledge bases

In each RDF knowledge base, several errors must be corrected by correction methods. Correction methods can be divided into three classes for the correction of outliers, inconsistencies, and erroneous relations. RDF knowledge base outliers can be considered as two types of outlier entities and triples. Inconsistent triples are corrected by inconsistency correction methods and there are many erroneous relation correction methods that each of them is used for a special objective. The variety of these errors is so wide so that no correction method could be able to cover them all. Most of the correction methods have been focused only on some of these errors, so a comprehensive study is mandatory to cover all of these elements for different objectives. Nevertheless, a couple of survey articles on the RDF knowledge base correction exist, but they are out-dated and did not present different configurations of these errors for various objectives. Since there is no configuration in this field, a new general configuration of the RDF knowledge base correction for a different objective is proposed here that can cover these various errors. In this configuration, a new classification of the errors is presented in which they are divided into three classes. The correction of each class is performed in a separate step. Finally, the state-of-the-art approach of each step is identified for each objective and a different configuration of these methods will be proposed for various objectives.
2021 Conference Announcement on Cyber Security and Ethical Hacking and Its Applications

We are pleased to welcome you to the “International conference Announcement on Cyber Security and Ethical Hacking “after the successful completion of the series of Cyber Security Congress. The Conference is scheduled on November 18-19, 2021 Paris time zone. This Cyber Security 2021 Conference will provide you with an exemplary research experience and huge ideas. The perspective of the Cyber Security and Ethical Hacking Conference is to set up technology research to help people understand how Technology techniques have advanced and how the field has developed in recent years. Cyber Security s the state or process of protecting and recovering networks, devices and programs from any type of cyber-attack. Cyber-attacks are an evolving danger to organizations, employees and consumers. They may be designed to access or destroy sensitive data or extort money. They can, in effect, destroy businesses and damage your financial and personal lives — especially if you’re the victim of identity theft. A strong cyber security system has multiple layers of protection spread across computers, devices, networks and programs. But a strong cyber security system doesn’t rely solely on cyber defense technology; it also relies on people making smart cyber defense choices. Biometric identification has a growing role in our everyday security. Physical characteristics are relatively fixed and individualized — even in the case of twins. Each person’s unique biometric identity can be used to replace or at least augment password systems for computers, phones, and restricted access rooms and buildings. Once biometric data is obtained and mapped, it is then saved to be matched with future attempts at access. Most of the time, this data is encrypted and stored within the device or in a remote server. Biometrics scanners are hardware used to capture the biometric for verification of identity. These scans match against the saved database to approve or deny access to the system. The Cloud Security & Virtualization track includes sessions on the security aspects of using and leveraging cloud services, virtualization technologies/services, segmentation, deployment models, network function virtualization.
Teachers' attitudes towards reading literacy in the first three years of primary school

Developing reading literacy is a fundamental task in the first educational period of primary school. There are several factors that influence the development of reading literacy, but the most important are the home environment, interest in reading and the school environment. The latter includes mainly competent teachers who are aware of the importance of developing reading literacy, promote its development through various strategies and design lessons to meet children's learning potentials, which is possible through individualization and differentiation of lessons. Since the results of international research on reading literacy are not very encouraging in our country, but we are aware of the importance of early development of reading literacy, we decided to check the attitudes of teachers towards reading literacy in the first educational period. The study also included primary school teachers who participated in experimental NPZs in the 3rd grade of schools in 2017/18 and 2018/19. Our research showed that most teachers believe that development of reading literacy in students is very important even though they do not understand the concept of reading literacy very well. Reading literacy is developed through different reading strategies and in all subjects. Teachers often differentiate lessons, especially by adjusting the scope and difficulty of texts and tasks. The frequency of differentiation of lessons for gifted students gets lower by grades. Teachers are not in favor of NPZ in 3rd grade as this presents to much stress for teachers and students and they also believe that such tests are not appropriate for such an early age. There is also no statistically significant difference in the development of reading literacy compared to teachers who do not participate in NPZ. However, teachers show a very positive attitude towards further education on reading literacy.
LibGuides: Newspapers: Home

To highlight the Reed Database Subscriptions that contain or are Newspapers in a digital format.
Focus on TrioTRAIN Project (Total Regulatory Acceptance for an Interoperable Network) – UIC Communications

When certifying a rail vehicle according to European regulation two elements constitute a significant challenge: vehicle cost and time-to-market. A large part of vehicle certification mandates…
Evolution of Naturalistic Programming: A Need

For years, researchers and programmers have studied, proposed, and reflected on how to enhance the expressive power of programming languages. One of the most popular thoughts on this matter is that natural language can be used as a programming tool. In this work, we review the state-of-the-art of naturalistic programming, whose goal is to achieve greater expressiveness in programming languages and better approach the user domain. We review the only three naturalistic general-purpose languages that can generate executable code by comparing them concerning a conceptual model – Pegasus, Cal-4700, and SN. We discuss the similarities and differences between each language. Then, we introduce and discuss some examples of computer programs developed with these languages, showing their level of expressiveness. Finally, we reflect on the findings that show the need for the paradigm to evolve having a software development method, to be considered as a formal proposal in Software Engineering.
La estructuración de una herramienta para la enseñanza de la química de bachillerato (EduQuim) utilizando la plataforma Moodle

The EduQuim tool has been structured in Moodle with the B-learning modality in order to carry out research in the teaching and learning of Chemistry in high school students. In this tool the theories of learning are implemented through animated lessons, mini-games, interactive exercises, formal evaluations, surveys, chats and forums, which gives it a dynamic, participatory and communicative nature with the students. In addition, an evaluation of the attitude and perception of the students and teachers in relation to the animated lesson, Matter, was carried out through surveys and interviews. The results showed very favorable opinions regarding clarity, understanding and explanations, both for students and teachers. The students suggested corrections to the sound and the characters.
Exhaustive Entity Recognition for Coptic: Challenges and Solutions

Entity recognition provides semantic access to ancient materials in the Digital Humanities: it exposes people and places of interest in texts that cannot be read exhaustively, facilitates linking resources and can provide a window into text contents, even for texts with no translations. In this paper we present entity recognition for Coptic, the language of Hellenistic era Egypt. We evaluate NLP approaches to the task and lay out difficulties in applying them to a low-resource, morphologically complex language. We present solutions for named and non-named nested entity recognition and semi-automatic entity linking to Wikipedia, relying on robust dependency parsing, feature-based CRF models, and hand-crafted knowledge base resources, enabling high accuracy NER with orders of magnitude less data than those used for high resource languages. The results suggest avenues for research on other languages in similar settings.
Low Latency Fog Computing Architecture for a Fire Safety Application

This thesis presents an architectural design for location-aware fire safety application (Fire-fly) based on cloud and fog computing. The Fire-fly application is designed to assist the residents of ...
PENINGKATAN KEMAMPUAN MENULIS LAPORAN ILMIAH SEDERHANA BERDASARKAN STRATEGI PEMODELAN BAGI SISWA KELAS VIII A SMP NEGERI 20 PALU

This research aims to: (1) improve writing simple scientific report ability through modeling strategy for the students of class VIII A at SMP Negeri 20 Palu Central Sulawesi and (2) describe the improvement of writing simple scientific report ability based on modeling strategy. This research was a classroom action research conducted in two cycles. The subjects of this research were 20 students of class VIII A at SMP Negeri 20 Palu. Procedures for implementing a classroom action research: (1) action planning, (2) action implementation, (3) observation, and (4) reflection. Based on the results of the research on improving writing simple scientific report ability through modeling strategy, it is concluded that there is a significant improvement. The result of the research on pre-action is 58 with the percentage of 18% classical learning achievement. Next, an action is implemented in cycle I with the average score is 71.5 with 50% classical learning achievement percentage. Then proceed to cycle II with the average value of 84.42 and the percentage of 92.85. Based on the result, it can be concluded that using modeling strategy can improve the ability of students in class VIII A at SMP Negeri 20 Palu in writing simple scientific report. Improving students' ability to write simple scientific reports through modeling strategy deserves to be considered as a classroom action material for teachers and subsequent researchers. The final result of this research shows that the application of modeling strategy in learning to write simple scientific report can improve students ’ competence. Aspects assessed include; systematic of writing, grammar, effective sentences and neatness of writing.