Reviewerly/exHarmony huggingface dataset:
BITCOIN PRICE PREDICTION USING MACHINE LEARNING

After the boom and bust in cryptocurrencies’ prices in recent years, Bitcoin has been totally regarded as an investment asset. As it is highly volatile in nature, there has been a need for good predictions for carrying base investment decisions. Although current study has used machine learning for more accurate Bitcoin price prediction, some of them did focused on the feasibility of applying different modeling techniques to the samples that has different data structures and dimension features. To predict Bitcoin price on different frequencies after using machine learning techniques, firstly we have to classify the Bitcoin price with daily price and high-frequency price. Here, we attempt to predict Bitcoin price as accurately as possible by taking into consideration various protocols that affect the Bitcoin value. Using the provided data we would predict the sign of daily price change with highest possible accuracy. We have used Random Forest Classifier and compared with benchmark results as daily price prediction, we achieve a better performance, with the highest accuracies of the statistical methods and machine learning algorithms of 99%. my investigation in Bitcoin price prediction can be considered as a pilot study for the importance of the sample dimension in the machine learning techniques. Keywords Bitcoin, Crypto Currency, Machine Learning, Blockchain, Long Short Term Memory(LSTM), Recurrent Neural Network(RNN), Prediction
Comparative analysis of sentiment classification using machine learning techniques on Twitter data

Sentiment analysis, a track of Natural language processing field, which is used to categorize the online content into positive, negative and neutral comments. In this pandemic situation people order various products through online and there is an option to share their feedback. People refer ratings and reviews of other customers, before buy the product .The ecommerce field has reached next level of growth .The opinion or view of the customers play vital role in the growth of a business. The organization analyzes negative comments and predicts expectation of the customers, to develop their business. With the help of this analysis, effective decisions can be made to manage critical situations in business. In recent years various methods and techniques are used to analyze customer views. Machine learning techniques are well suited for sentiment analysis and achieved effective results .In this paper, support vector machine and Naive Bayes methods are used in sentiment classification with twitter data.
Research on the Construction of Electronic Intelligent Manufacturing Specialty Group in Higher Vocational Colleges under the Background of "Double- High Plan"

Higher vocational colleges should build a high-level professional group from the perspective of professional group and Industrial Synergy according to the changes in the demand for technical talents due to economic, social and industrial development, so as to improve the adaptability and pertinence of talent training. The electronic intelligent manufacturing professional group of Chongqing C Vocational College explores the modern apprenticeship system and "1 + X" certificate system in the talent training mode. Build a "platform + module" curriculum system on the curriculum system. Curriculum resources: colleges and enterprises jointly build, open and share high-quality curriculum resources, virtual teaching resources and teaching resource library. Enhance the industry influence of professional group leaders, cultivate backbone teachers of technical experts, and build a team of high-quality part-time teachers. Build a productive training base and virtual factory with industry-leading enterprises, and build a practical teaching base combining education and training. Deepen the integration of industry and education by building a four party collaborative education management mechanism of "government, administration, enterprises and colleges", a college enterprise collaborative education management mechanism, promoting the coordinated development of professional chain and industrial chain, and creating a platform for the integration of industry and education. The construction scheme of professional group is effective.
Database security framework design using tokenization

One of the challenging tasks in database management system today is protecting sensitive data that are complex in the database system. Most organization opt for implementation of data encryption which is one of the most effective security control mechanism, but data encryption only render information unreadable to those that do not have the secret decryption key. The core issue with data encryption techniques is that, it is reversibly. In these regards, sensitive data need to be tokenized first before encrypting for better security. Therefore, this work is introducing tokenization technique. Tokenization means replacement or substitution of sensitive data with a token, as an additional technique on database system for protecting sensitive data in all higher institutions and other firms that deal with sensitive data. A database security framework using tokenization was design, implemented using NetBeans 8.1 IDE, Java Platform SE binary (jdk-8u91-windows-x64) and xampp-windows-x64-7.3.7-0-VC15 (Apache and MySQL), an official IDE for Java 8 and then encrypt the tokenized data using AES before storing it in server 127.0.0.1 a localhost phpMyAdmin Database tools and evaluated with other security systems (encoding, hashing and encryption) on student database. Results shows that tokenization technique has 95% capacity to protect sensitive data compare to other security systems.
The Attitudes of English as Foreign Language Undergraduates towards Learning Basic Writing Skills through the Using of Blackboard at the University of Tabuk

This study aims at examining the attitudes of English as a foreign language undergraduates’ towards learning basic writing skills through using Blackboard at the University of Tabuk for the academic year 2022/2023. The sample included 30 undergraduates selected purposively. It was distributed over two groups each 15 undergraduates (experimental and control groups). The theoretical framework of the study was based on Tubaishat and Lansari‘s (2011) Model of E-learning. The researcher used SPSS (Version.26) for data analysis. Findings showed statistically significant differences at level (0, 05) for the means of the achievement test for the two groups in favor of the experimental group that was taught using blackboard. Also, findings revealed statistical significance differences at level (0, 05) in developing the correlation between English as foreign language undergraduates towards basic writing skills as a result of the use of blackboard. This research recommends that the blackboard be activated in teaching all the subjects because of its positive effect on the achievement of the faculty members and developing their attitudes towards teaching English as a foreign language.
DEVELOPMENT OF YOUTH'S CREATIVE ABILITIES SCHOOLCHILDREN BY BYOD TECHNOLOGY

Modernization of the modern primary education system of Ukraine is aimed at developing creative abilities of primary school students. Development of the creative abilities is one of the components of soft skills of an individual, they affect the successful establishment in society. A creative person is able to generate new ideas, think original, make non-standard decisions, confidently achieve their goals. Creativity is an integrative multicomponent quality that covers various areas of students’ activity. Due to the digitalization of the educational process, information and communication technologies are being rapidly implemented in primary school. Accordingly, the authors of the article analyzed the features of the use of innovative technology BYOD ("bring your own device") for the development of creative abilities of students, identified its positive aspects, outlined ways to use it by teachers. The purpose of the article is to reveal the educational potential of BYOD technology for the development of creative abilities of junior schoolchildren. An experimental study was conducted, the respondents of which were students of primary school in Vinnytsia region and determined the leading level of development of their creative abilities. The results of lessons observation in primary school on the use of innovative technologies for the formation of creative abilities of primary school students are analyzed. The results of the survey of primary school teachers on the use of innovative BYOD technology in the educational process are presented. It is proved that the use of smartphones in primary school lessons promotes the development of creative abilities of primary school children and their imagination, and change of the educational vector of primary school from reproductive learning to creative understanding of information and competent growth (formation of digital competence and organization of students’ independent research).
Towards Answering Open-ended Ethical Quandary Questions

Considerable advancements have been made in various NLP tasks based on the impressive power of large language models (LLMs) and many NLP applications are deployed in our daily lives. In this work, we challenge the capability of LLMs with the new task of Ethical Quandary Generative Question Answering. Ethical quandary questions are more challenging to address because multiple conflicting answers may exist to a single quandary. We explore the current capability of LLMs in providing an answer with a deliberative exchange of different perspectives to an ethical quandary, in the approach of Socratic philosophy, instead of providing a closed answer like an oracle. We propose a model that searches for different ethical principles applicable to the ethical quandary and generates an answer conditioned on the chosen principles through prompt-based few-shot learning. We also discuss the remaining challenges and ethical issues involved in this task and suggest the direction toward developing responsible NLP systems by incorporating human values explicitly.
Sampling of high-nugget conglomerates from the Western Australian Pilbara: bulk sampling at the Beatons Creek gold project, Nullagine

Many styles of gold mineralisation pose challenges during sampling because of the presence of coarse gold and high natural heterogeneity (“nugget effect”). The gold-bearing conglomerates of the Western Australian Pilbara provide some challenges. Novo Resources Corporation has addressed many of these over the last five years. Its Beatons Creek open pit operation is the first Pilbara conglomerate to go into production (January 2021) based on a total oxide Mineral Resource of 316,000 oz Au (5.2 Mt at 1.9 g/t Au at a 0.5 g/t Au cut-off). Mineralisation occurs within the Beatons Creek conglomerate member of the Hardey Sandstone formation, which constitutes part of the Fortescue Group. Gold is present within the matrix of multiple, narrow stacked and un-classified ferruginous-conglomeritic reef horizons, which are interbedded with un-mineralised conglomerate, sandstones and grits with minor intercalations of shale, mudstone, siltstone and tuffs. The gold occurs as free particles up to 5 mm across within the ferruginous matrix of the conglomerates. It is closely associated with detrital pyrite and authigenic nodules. Previous owners and Novo have employed several sampling techniques across the project including diamond and RC drilling, trench channel sampling and bulk sampling. Assay methods included fire assay, LeachWELL and more recently PhotonAssay. As part of its 2018 evaluation programme, fifty-eight c. 1-4 t bulk samples were collected from accessible oxide mineralisation and processed via a pilot plant. This paper presents some of the issues and solutions applied by Novo, which have wider implications and impact on the sampling of other heterogeneous orebodies.
E-Learning System Design using Software Requirement Specification (SRS) Case Study: Unhar Medan

The development of science, especially in the use of the internet is increasing, in the world of internet education it is used as a remote teaching and learning process using electronic devices called E-Learning. The process of developing E-learning needs to be carried out considering the need for current technological developments, learning is limited due to the pandemic situation which does not allow face-to-face learning but with E-Learning learning can be accessed anywhere and anytime. Implementation of eLearning Universitas Harapan Medan has not been optimally implemented. To meet E-learning standards, it is generally necessary to design specifications in building E-learning. The application of the Software Requirement Specification (SRS) is one way to detail various documents that will explain the various requirements that must be met by an E-learning software. The design of the E-learning system using the Software Requirement Specification (SRS) can facilitate the learning process in E-learning with a system that suits the needs of the user.
Improving expressive communication in children with autism using social story and picture exchange communication system

In everyday human activities, both social and personal interrelations require communication.Cognitive abilities influence the communication process.Cognitive disorders in children with autism lead to communication problems.Communication disorders in children with autism lead to emotional changes.In the learning process, children with autism can overcome communication disorders by maximizing their visual potential.In this article, we study that a review of the visual media literature can improve visual abilities of children with autism.The method used is a narrative review with steps to 1) determine the scope, 2) search literature, and 3) analyze the findings.The results found that to improve communication skills and basic behavior in children with autism, the Picture Exchange Communication System (PECS) can be used.PECS can get used to communicating with children with autism by using symbols that are appropriate to their daily activities.To increase the effectiveness, the implementation of PECS can be combined with the Social Story Model.Social stories can help students with autism interpret and understand social situations with therapy using short stories.By using PECS and SS, student with autism can increase their positive social behavior and the development of receptive and expressive communication.It also can improve structured speech skills and stimulate language.
Optimal trade strategy based on RNN-LSTM deep learning method

With the development of economy, financial market has gradually become an important part of economic development. In this paper, by incorporating the financial time series data dependencies and the local correlation characteristics of the time series data of the two financial markets of gold and Bitcoin into the same model, the LSTM neural network price prediction model is constructed and the parameters are optimized to make it more accurate to predict gold, Bitcoin price trend. At the same time, using the integrated empirical mode decomposition and run-length determination method, the time series data of gold and bitcoin are divided into cycles, and the LSTM neural network model is trained and verified, and finally the gold bitcoin price prediction model is obtained, the mean absolute error and root mean square error of Bitcoin are significantly larger than those of gold, and the price volatility of Bitcoin is known to be higher than that of gold, so the instability of Bitcoin is weaker than that of gold.
JOINT ESTIMATION OF DEPTH AND ITS UNCERTAINTY FROM STEREO IMAGES USING BAYESIAN DEEP LEARNING

Abstract. The necessity to identify errors in the context of image-based 3D reconstruction has motivated the development of various methods for the estimation of uncertainty associated with depth estimates in recent years. Most of these methods exclusively estimate aleatoric uncertainty, which describes stochastic effects. On the other hand, epistemic uncertainty, which accounts for simplifications or incorrect assumptions with respect to the formulated model hypothesis, is often neglected. However, to accurately quantify the uncertainty inherent in a process, it is necessary to consider all potential sources of uncertainty and to model their stochastic behaviour appropriately. To approach this objective, a holistic method to jointly estimate disparity and uncertainty is presented in this work, taking into account both aleatoric and epistemic uncertainty. For this purpose, the proposed method is based on a Bayesian Neural Network, which is trained with variational inference using a probabilistic loss formulation. To evaluate the performance of the method proposed, extensive experiments are carried out on three datasets considering real-world indoor and outdoor scenes. The results of these experiments demonstrate that the proposed method is able to estimate the uncertainty accurately, while showing a similar and for some scenarios improved depth estimation capability compared to the dense stereo matching approach used as deterministic baseline. Moreover, the evaluation reveals the importance of considering both, aleatoric and epistemic uncertainty, in order to achieve an accurate estimation of the overall uncertainty related to a depth estimate.
TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pages

Recently, the structural reading comprehension (SRC) task on web pages has attracted increasing research interests.Although previous SRC work has leveraged extra information such as HTML tags or XPaths, the informative topology of web pages is not effectively exploited.In this work, we propose a Topological Information Enhanced model (TIE), which transforms the token-level task into a tag-level task by introducing a two-stage process (i.e.node locating and answer refining).Based on that, TIE integrates Graph Attention Network (GAT) and Pre-trained Language Model (PLM) to leverage the topological information of both logical structures and spatial structures.Experimental results demonstrate that our model outperforms strong baselines and achieves state-ofthe-art performances on the web-based SRC benchmark WebSRC at the time of writing.
EFFECT OF EMPLOYEE AGILITY ON ORGANIZATIONAL PERFORMANCE (A CASE STUDY OF THE STATE DEPARTMENT FOR LABOUR, KENYA)

Purpose: The research sought to assess the effect of employee agility on organization performance with a specific study by the State Department for Labour.&#x0D; Methodology: The data for this study were collected at the State Department for Labour. The respondents included a sample of the employees working at the department as of the end of 2020. The study population comprised 484 employees working at the State Department for Labour. This study adopted ten percent of the target populace, which translates to 59 participants. Therefore, the sample scope for the research was 59 respondents. The research employed stratified random sampling techniques. In addition, the study depended on key information that was assembled by a designed data assortment tool that was accurately created. Descriptive measurements such as percentages, frequencies, standard deviations, and mean were utilized to summarize composed data. Likewise, inferential tools of regression and correlation analysis were utilized to create the connection between employee agility and organizational performance. The study results were offered using bar charts, tables, pie charts, and graphs.&#x0D; Results: From the findings of this study, it was resolved that employee agility positively influences organizational performance. The State Department for Labour is critical since its mandate, among others, is to ensure there are harmonious industrial Labour relations. The economic growth and development of the country rely on it to enhance Labour productivity through its Labour dispute resolving mechanism. Therefore the performance of the state Labour department is essential. There is a link between operative agility enablers and general internal performance.&#x0D; A unique contribution to theory, practice and policy: This study would inform policymakers and Human Resource Practitioners on various approaches to improving employee agility in order to enhance Organizational Performance.
An E-Library System Integrated with Bookshelf and Recommendation Components

Apparently, most students in Nigeria are facing challenges as regards to the lack of portability, stress, time wastage and inadequate resources in terms of accessing the school libraries, as well as the inefficiency of the existing e-library, leading to the reduction in the number of students that do access the libraries. Research has shown that most students no longer believe in the physical libraries and have developed interest in electronic resources. Hence, an e-library system enhanced with book recommendation component could serve as a solution to these problems. Several researchers have repeatedly attempted to develop various solutions to this problem using various methodologies and approaches in order to provide a digital library that could address the aforementioned problems. In this work, an e-library system integrated with recommendation component was designed and implemented to help students locate relevant books. Also, an additional feature which adds books to the shelf for future reference was included to enhance accessibility and efficiency of the system. The web application was implemented on a live server (Namecheap) which is one of the most effective live servers in Nigeria. Furthermore, the system was evaluated with one hundred and fourteen (114) students, and the results of the evaluation carried out on the system emphasized its usefulness in terms user friendliness (77%), user experience (86%), interface appearance (75%), system loading speed (82%), platform compatibility (78%), recommendation accuracy (80%) and recommendation reliability (84%). Therefore, the system could be used to solve students’ problems with regards to the challenges faced with the use of physical and conventional e-libraries.
Water Quality Assessment at Tanggulangin Cultural Park

Tanggulangin Cultural Park is a new facility provided by the local government as a recreational facility for residents. Along the way, many people use the area to boost the economy, by selling food, drinks, and so on. So it can be ascertained that water is a material that is used every day. Many residents use water from the Tanggulangin Cultural Park area for the production process of food, beverages, and other purposes, so it is necessary to know the water quality in the park, physically, chemically, and microbiologically. This research was conducted in October-November 2021 by testing the parameters of temperature, turbidity, pH, water hardness, and total coliform. The results obtained are water temperatures of 34.6 and 31.6oC, turbidity of 2.87 NTU and 3.08 NTU, pH of 7.08 and 6.92, water hardness of 1.28 mg.L-1 and 1.32 mg.L-1, and total coliforms of 7.8 CFU/100 ml and 6.8 CFU/100 ml. In general, all these parameters are still below the standard of the Regulation of the Minister of Health of the Republic of Indonesia. No. 32 of 2017. However, attention must be paid to the presence of total coliform content in water.