Reviewerly/exHarmony huggingface dataset:
예체능계열 학습자들의 영어글쓰기와 피드백에 대한 인식

The purpose of this study was to find out the perceptions of English writing and feedback from college students majoring in arts and physical education. Students received feedback on their English writing three times: once from their teacher and twice from their peers. The students were asked to correct their writing after receiving the feedback. The findings were as follows: First, the learners were not interested and confident in English writing, but they recognized the need to write in English. Second, learners wanted to write English reports or resumes that would help them get a job in the future. Third, as the need for writing increased, learners showed different aspects in their preferences for the types of writing class activities. Finally, the learners recognized the importance of feedback from both their peers and their teacher. According to the survey, the learners answered that the teacher feedback was more helpful than the peer feedback.
IMPROVED MOBILE ROBOT MOTION PLANNING ALGORITHM BASED ON DIFFERENTIAL EVOLUTION

In this paper, we present an improved differential evolution (DE) approach to optimize path planning for mobile robots. A path should have optimum length and be easy to traverse for non-holonomic robots. Therefore, the path smoothing B-spline technique is integrated with the DE approach to plan traversable paths for mobile robots. We evaluated our system’s ability to plan the path of an Aria mobile robot in both simulated and real environments. The results indicate that our approach can lead to an optimum and easily traversable path without requiring considerably more computing resources than the conventional methods.
Embodied Reasoning for Discovering Object Properties via Manipulation

In this paper, we present an integrated system that includes reasoning from visual and natural language inputs, action and motion planning, executing tasks by a robotic arm, manipulating objects, and discovering their properties. A vision to action module recognises the scene with objects and their attributes and analyses enquiries formulated in natural language. It performs multi-modal reasoning and generates a sequence of simple actions that can be executed by a robot. The scene model and action sequence are sent to a planning and execution module that generates a motion plan with collision avoidance, simulates the actions, and executes them. We use synthetic data to train various components of the system and test on a real robot to show the generalization capabilities. We focus on a tabletop scenario with objects that can be grasped by our embodied agent i.e. a 7DoF manipulator with a two-finger gripper. We evaluate the agent on 60 representative queries repeated 3 times (e.g., ’Check what is on the other side of the soda can’) concerning different objects and tasks in the scene. We perform experiments in a simulated and real environment and report the success rate for various components of the system. Our system achieves up to 80.6% success rate on challenging scenes and queries. We also analyse and discuss the challenges that such an intelligent embodied system faces.
An overview of sentiment analysis using Azure Cognitive Services

Machine Learning (ML) and Artificial Intelligence (AI) are infiltrating each and every industry these days. Not just industries these fields have become a crucial part of all the technology prone human beings. Right from activity trackers to virtual assistants we have smoothly transitioned into the Artificial Intelligence era and all these small techno gadgets have become the crucial parts of our life. In the disruptive world of Artificial Intelligence the main focus is on understanding the patterns and processing it to solve the real world problems through designing and developing the smart or learned models. In this paper, we are going to look one of the interesting topics from Natural Language Processing (a subfield of Artificial intelligence) called sentiment analysis. The paper will also explain how we can use Azure Cognitive Services to solve real world problems and its applications.
Village Service System Based online

The village government has a function and purpose to serve the community. The current population of the village of tanjungmekar is 4,993 29 RT and 9 RW. The village government is required to have a service system that is good and right. the problem in Tanjungmekar village is that it is necessary to pay attention to the service to the community that still uses a manual system, the service of which requires the community to come to the village office and must directly face to face with the village apparatus. In the era of technology such as now a system can be made to facilitate the performance of government. On the basis of these problems, the purpose of this study is to create an online-based village service system. This system is made using the prototype method, Prototyping model is a software development process that begins with gathering the needs of the system, followed by making prototypes and evaluating the users. The framework used is CodeIgniter with UML (Unified Modeling Language) design which includes use case diagrams, class diagrams, activity diagrams and sequential diagrams. The results obtained in building this system are online-based village service websites that can help the performance of the village government in carrying out its duties to serve the community. The conclusion obtained in the creation of this system is the creation of an online-based village service system to facilitate the public in submitting applications for making letters, online complaints and online information services
Scientific Workflow Scheduling Based on Data Transformation Graph for Remote Sensing Application

As the amount of data and computation of workflow applications continue to grow, the inter-cloud environment provide with a great amount of computing resources to respond to the increasing demand, but how to effectively map workflow sub tasks to cloud service providers for better QoS(quality of service) performance is a question. Remote sensing applications have massive data, frequent and large data transfers across the cloud could cause huge performance bottlenecks, will seriously affect the result of QoS such as makespan and cost. By using DTG(data transformation graph) model to study the data transmission process of global drought monitoring application, an optimized scientific workflow scheduling based on genetic algorithm is proposed for inter-cloud environment, experimental results show that this method can significantly optimize makespan and cost for data-intensive applications like remote sensing application and can effectively reduce the impact of performance bottlenecks.
Image Forgery Detection Using Adaptive Oversegmentation and Feature Point Matching

From the early days, images are generally accepted as a proof of occurrence of the past events. Digital image is a part of the real world which is generated after many processes of image generation. The availability of low cost hardware and software tools makes easy to create and manipulate digital images with no traces. This has led to the situation where one can no longer take the integrity and authenticity of the digital images for granted. So it is important to have an image forgery detection tools to know whether the digital image is authentic or not. In this regard, adaptive oversegmentation and feature point matching is used to detect copy move forgery. First, adaptive oversegmentation algorithm segments the source image into nonoverlapping and irregular blocks. Then, block feature extraction algorithm extracts the feature points from each image block as block features using SIFT(Scale Invariant Feature Transform) and SURF (Speed Up Robust Features) methods and find the matched feature points by matching the feature points with one another by using block feature matching algorithm. After that, forgery region extraction algorithm is used, which replaces the feature points with small superpixels and merges the neighboring blocks which is having similar local color features to generate the merged regions. Lastly, morphological operation is applied to generate the forged regions. Based on precision, recall, F1measure and accuracy parameters obtained from different detection methods, the comparative analysis of copy-move forgery detection method is performed.
droidlet: modular, heterogenous, multi-modal agents

In recent years, there have been significant advances in building end-to-end Machine Learning (ML) systems that learn at scale. But most of these systems are: (a) isolated (perception, speech, or language only); (b) trained on static datasets. On the other hand, in the field of robotics, large-scale learning has always been difficult. Supervision is hard to gather and real world physical interactions are expensive.In this work we introduce and open-source droidlet, a modular, heterogeneous agent architecture and platform. It allows us to exploit both large-scale static datasets in perception and language and sophisticated heuristics often used in robotics; and provides tools for interactive annotation. Furthermore, it brings together perception, language and action onto one platform, providing a path towards agents that learn from the richness of real world interactions.
PENERAPAN SISTEM DAN PROSEDUR AKUNTANSI PERSEDIAAN DALAM UPAYA MENINGKATKAN PENGENDALIAN INTERN PADA PT.BUMI SARANA BETON

This research aims at analyzing the application of inventory accounting systems and procedure in improving the internal control at PT. Bumi Sarana Beton. This research used qualitative data that taken from primary and secondary data. Data were collected by observation, interview and documentation. The data analysis technique used was qualitative description method. The results showed that the inventory accounting system and procedure applied at PT. Bumi Sarana Beton was Enterprise Resource Planning (ERP) system, where this system can assist in controlling the inventory activity. The improvement of inventory will be recorded directly according to the transaction date, and when a stock mutation accurs it will be recorded directly in the Report Movement Inventory (Mutation Movement) and Inventory On Hand Report (Stock Inventory Card), if there is a movement inventory, the value and quantity of inventory will be directly displayed by the system. This ERP system can improve the company’s internal inventory control, because this system shows the value of inventory stock in real time according to what we need.
Design of Blockchain Based Smart Contract for Tendering

Information technology is the backbone for all 21st century organizations that are looking forward to offer better customer service and gain competitive advantage. Today, blockchain technology is being adopted by a number of organizations such as financial services, healthcare, agriculture and even government. . However, the tendering sector have not been able to take advantage of the new blockchain technology, owing to the absence of blockchain based frameworks and a model for secure tendering. This study focuses on block-chain with its BYOE (Bring Your Own Encryption) concept in the procurement sector. The research comes up with a design of a blockchain based smart contract model for organizations in Kenya following ASD approach. In addition a discussion of challenges and opportunities of Blockchain based tendering is also presented.
Simulation of The Application of Intelligence in Vernam Cipher Cryptography (One Time Pad)

Technological advances in the field of computers allow thousands of people and computers around the world to be connected in one virtual world known as cyberspace or the Internet. But these technological advances are always accompanied by the downside of the technology itself. One of them is the vulnerability of data security, giving rise to challenges and demands for the availability of a data security system that is as sophisticated as the advancement of computer technology itself. In this study, an algorithm that can secure data will be used which the authors discuss is the Vernam Cipher Algorithm. Vernam Cipher Algorithm is one of the key algorithms. Until now, the Vernam Cipher algorithm is still trusted as an encryption method, Vernam Cipher cryptography uses the same key for encryption and decryption.
LibGuides: O’Reilly for Higher Education: O'Reilly for Mobile Devices

This guide includes information on how to log in to O'Reilly, tips for searching O'Reilly and details on how to contact the Library.
Authority Management System Design in Forestry Information System Based on Asp.net Three Layer Network Architecture

The authority management system of network structure in forestry information system is one ofthe core security measures of industrial intelligent manufacturing network. In order to deal witha large amount of information, it often takes a lot of time, manpower and material resources toupdate and maintain the permission information. This paper discusses the three-tier networkarchitecture of professional website authority management system in forestry informationsystem based on asp.net technology. This paper elaborates the functions of user interface layer,business logic layer and data access layer, and their roles in authority management. This papercompares and analyzes the advantages and disadvantages of ASP and ASP. Net technology inprofessional website design. The experimental data show that the professional website authoritymanagement system based on asp.net technology improves the security, scalability andmaintainability of the website, and achieves good results.
Implementation Comic Life Learning Media for Class VII to Improve Studentsâ€™ Mathematical Communication and Mathematical Disposition Ability

The purpose of this research is to see how effective the learning media that have been designed are. The method used in this research stage is development research, in which learning media based on the Comic Life assisted set materials are developed.Â Â This Study included 54 students from Bandung and 114 students from Ngamprah Subdistrict from the Junior High School association VII grade level. In the development of media, there are four stages of research namely define; design; develop; disseminate. The stage result in an average data validation of the material expert of 76.3% for the first stage and 80.8%% for the second stage. Stage I validation findings were 53.3%, stage II validation was 74%, and stage III validation was 81%. Student replies of 76% and instructor responses of 78% revealed the findings of the validation in limited trials and broad trials. Meanwhile, 79.5% of student responded positively during product testing. The level of efficacy of learning media utilizing Comic Life is attained with an N-Gain of 0.34, implying that the level of effectiveness of Comic Life assisted learning is quite effective. According to the findings of the mathematical communication and disposition exam, students who study using the Problem Based Learning approach with Comic Life have a better-mathematical abilities than those who learn conventional learning. In terms of mathematical disposition, it can be determined that students who utilize the Comic Life assisted Problem Based Learning technique have a better mathematical disposition than those use conventional learning. This development research is based on the learning design produced and the characteristics of students.
Classifying Twitter Data using Deep Learning Technique

Online social networks have a lot of information. But often people do not provide personal information, such as age, gender and other demographic data, although the confidence analysis uses such information to develop useful applications in people's daily lives. But there is still a failure in this type of analysis, whether by the limited number of words contained in the word dictionary or because they do not consider the most diverse parameters Can influence feelings in sentences; Therefore, more reliable results will be obtained if considering user profile data and user writing style. This research shows that one of the most relevant parameters contained in the user profile is the age group, which shows that there is normal behavior among users of the same age group, especially when these users write about. With the same topic Detailed analysis with 7000 sentences has been conducted to determine which features are relevant, such as the use of punctuation, number of characters, sharing of media, other topics, and which ones can ignore the age group classification. Different learning machine algorithms have been tested for the classification of adolescent and adult groups and the Deep Convolutional Neural Network (DCNN) has the best performance with accuracy up to 0.95 in the validation test. must In addition, in order to verify the usefulness of the proposed model for age group classification, it is implemented in the Sentiment Metric (eSM) that has been improved. In performance audits, subjective tests are performed and eSM with the proposed model arrives. Mean Square root error and Pearson's correlation coefficient of 0.25 and 0.94, respectively, are more efficient than the eSM indicators when no age group information is specified.
A probable effect of the development of internet technology on insurance &amp; banking sectors, decision processes and service structures

The history of the development of the Internet of Things (IoT) covers the last twenty years. Despite the short of time, the concept and implementation of the Internet of Things have widely spread all over the world. The impetus of the dissemination of the concept has exponential speed. In the near future, billions of smart sensors and devices will interact with one another without human intervention. The early impact of the Internet of Things has been observed and discussed in the areas of technology, transportation, production, and marketing. The prospective effect of the Internet of Things on the finance sector has been discussed recently. In this study, the development of the concept of the Internet of Things and it is effect on the finance sector and specifically the insurance and banking sectors and future expectations have been evaluated.
Bitcoin and the First Wave of COVID-19

Extending the time period of Goodell and Goutte (2020), we apply wavelet methods to daily data of COVID-19 world deaths and daily Bitcoin prices from December 31, 2019 to August 31, 2020. We confirm Goodell and Goutte (2020) for an extended period by evidencing a positive correlation between levels of COVID-19 and Bitcoin prices, suggesting Bitcoin as a safe haven investment. Investigations such as this are important to both scholars and policy-makers, as well as investment professionals interested in the financial implications of both COVID-19 and cryptocurrencies.
A RWSM based Efficient CBIR system in JPEG Domain with GMCO Algorithm

Content-Based Image Retrieval (CBIR) is an efficient system for searching the desired image from a large database with the help of the various statistical features extracted from the image. The existing methods developed for image retrieval have failed to meet the user requirements, mainly due to the inability of retrieving accurate images and consumes more time for retrieving. To overcome these issues, this paper proposes an RWSM similarity calculation measure and global and local features for retrieving the images. Firstly, the JPEG images are used as the input images and are decomposed by using the RDTCWT algorithm. After that, color and texture features are extracted from the images by using the coefficient of sub bands of RDTCWT. The same processes are done for the query image too. For retrieving very similar images, the similarity is calculated in between the obtained class of database image and the query image features by using the RWSM method, and then, the higher score image is retrieved as the output. At last, the user is satisfied with the images that are retrieved using the GMCO method as relevance feedback. The experimental evaluation of the proposed method demonstrates that the proposed image retrieval system achieves better results than the existing methods.
Effect of Central Bank of Nigeria (CBN)’s empowerment schemes on development of entrepreneurship in Maiduguri Borno State Nigeria.

Most of the policies of governments and other agencies on economic development in developing countries like Nigeria are entrepreneurship development policies. Entrepreneurship programs are observed to be most reliable policy for employment creation in the country. The present study was to examine the Effect of Central Bank of Nigeria (CBN)’s empowerment schemes on development of entrepreneurship in Maiduguri Metropolitan Council of Borno State ad in Nigeria. Descriptive survey was adopted. Structured Questionnaire was used to collect data from the entrepreneurs within the Maiduguri metropolitan council of Borno state through survey and available data methods of data collection. Responses collected were analyzed with aid of simple percentage. Hypothesis was tested with the aid of chi-square test. The study found out that Central Bank of Nigeria Maiduguri Branch has significance relationship with the entrepreneurship skills development in Maiduguri Borno state. Despite the contribution of Central Bank of Nigeria through Maiduguri Branch in several areas toward entrepreneurship skills development in Maiduguri Nigeria, there are still much to be done in order to feel the desired effect. The Central Bank of Nigeria (CBN) through Maiduguri Branch and other government and non-governmental agencies that are geared toward entrepreneurship development in Maiduguri Borno state and in Nigeria at large should continue with the numerous roles played and this will go a long way in reducing the level of unemployment, expansion of existing businesses and creation of new once. This actually boosts the economy of Maiduguri and the state at large. There should be increased in fund mobilization by the Central Bank of Nigeria (CBN) and other organizations to promote entrepreneurship skills development in Maiduguri Borno state and in Nigeria at large.
Philipp Hacker, Ioannis Lianos, Georgios Dimitropoulos, and Stefan Eich (eds.), <i>Regulating Blockchain: Techno-Social and Legal Challenges</i>

1. In their book Regulating Blockchain: Techno-Social and Legal Challenges, the editors declare “it is more timely than ever to reflect on the broader social and legal challenges of the underlying technology” (Preface). The book thus probes the intersections and frictions between the law and blockchain, offering a well-rounded presentation of novel research and theory. 2. In Chapter 1, Paolo Tasca and Riccardo Piselli fill the gaps in previous studies involving Lessig’s Four Modalities of Regulation by examining all modality interactions with blockchain architecture, not just law (pp. 28–29). They observe that blockchain, among all other technologies and code architectures, is uniquely capable of modifying the other regulatory tools while remaining especially resistant itself (p. 35). Understanding these interactions is essential to attempting direct or indirect regulation. 3. Jonathan Rohr and Aaron Wright explore how smart contracts enable privately ordered governance in Chapter 2. Blockchain removes “many of the...