Reviewerly/exHarmony huggingface dataset:
Improving Image Captioning with Local Attention Mechanism

Image caption generation is field of research between the fields of machine vision and natural language processing. Based on the results of evidence, it is a difficult for the machine to understand an image like a human. Most of the proposed methods in this field of automatic image description production follow the encoder-decoder framework. In these proposed methods, each word in step (n) is generated based on the characteristics or features of the image and the previously generated (pre-generated) words. Recently, the attention mechanism, which usually creates a spatial map that highlights the image areas associated with each word, is widely used in researches. In this paper also uses the encoder-decoder framework. The encoder part of our model uses ResNet101 extract the features and the decoder part of model uses three parts: Attention-LSTM, Language-LSTM, and Attention-Layer. This paper uses a attention mechanism that uses local evidence to better demonstrate image features. Our method was able to generate good captions and also improve the evaluation metrics of METEOR, ROUGH.
Learning Forward Dynamics Model and Informed Trajectory Sampler for Safe Quadruped Navigation

For autonomous quadruped robot navigation in various complex environments, a typical SOTA system is composed of four main modules -mapper, global planner, local planner, and command-tracking controller -in a hierarchical manner.In this paper, we build a robust and safe local planner which is designed to generate a velocity plan to track a coarsely planned path from the global planner.Previous works used waypointbased methods (e.g.Proportional-Differential control and pure pursuit) which simplify the path tracking problem to local pointgoal navigation.However, they suffer from frequent collisions in geometrically complex and narrow environments because of two reasons; the global planner uses a coarse and inaccurate model and the local planner is unable to track the global plan sufficiently well.Currently, deep learning methods are an appealing alternative because they can learn safety and path feasibility from experience more accurately.However, existing deep learning methods are not capable of planning for a long horizon.In this work, we propose a learning-based fully autonomous navigation framework composed of three innovative elements: a learned forward dynamics model (FDM), an online samplingbased model-predictive controller, and an informed trajectory sampler (ITS).Using our framework, a quadruped robot can autonomously navigate in various complex environments without a collision and generate a smoother command plan compared to the baseline method.Furthermore, our method can reactively handle unexpected obstacles on the planned path and avoid them.(Video 1 )
Evolutionary Exploration of Mechanical Assemblies in VR

Due to the maker movement and 3D printers, people nowadays can directly fabricate mechanical devices that meet their own objectives. However, it is not intuitive to identify the relationship between specific mechanical movements and mechanical structures that facilitate such movements. This paper presents an interactive system that can enable users to easily create and experiment with desired mechanical assemblies via direct manipulation interfaces in virtual reality, as well as to intuitively explore design space through repeated application of the crossover operation, which is used at the core of the genetic algorithm. Specifically, a mechanical assembly in our system is genetically encoded as a undirected graph structure in which each node corresponds to a mechanical part and each edge represents the connection between parts. As the user selects two different mechanical assemblies and commands the crossover operation, each of their corresponding graphs is split into two subgraphs and those subgraphs are recombined to generate the next-generation mechanical assemblies. The user can visually examine new mechanical assemblies, save assemblies that are closer to objectives, and remove the others. Based on our experiments, in which non-expert participants were asked to achieve a challenging design objective, it was verified that the proposed interface exhibited significantly effective performance.
DETECTION AND RECOGNITION OF HINDI TEXT FROM NATURAL SCENES AND ITS TRANSLITERATION TO ENGLISH

India is a country with many cultures and if you travel from one place to another, you might find yourself in totally different culture. This also means the languages change from place to place in India and it gets very difficult to read signboards, shop names and even many other common things written in local languages. This can create problems for not only the travelers travelling from other countries but also the people who move withing the country from different regions. But most of the signboards, shop names or other landmarks mostly use English or Hindi in most of the regions. Here we propose a complete text detection & recognition as well as transliteration system that will help travelers read text written in Hindi on any signboards or shops and then transliterate that detected text into English. The proposed system is capable of detecting text written in Hindi language in natural environment using Progressive Scale Expansion algorithm and then transliterating the detected text into English language. Our proposed system can detect text in tough scenarios, and it can even detect curved text from natural images. Our system after detecting text region, extracts the text from the detected area using PyTesseract OCR engine and then the extracted text is further transliterated into English text with the help of seq2seq MultiRNN LSTM model which gives us accurate transliterations without losing the actual pronunciation of the original Hindi words. We use a synthetic dataset for Hindi Text images containing approx. 100000 for Text Detection and FIRE2013 dataset for transliteration. The overall system is evaluated using BLEU score.
Decoherence: From Interpretation to Experiment

I offer a few selected reflections on the decoherence program, with an emphasis on Zeh's role and views. First, I discuss Zeh's commitment to a realistic interpretation of the quantum state, which he saw as necessary for a consistent understanding of the decoherence process. I suggest that this commitment has been more fundamental than, and prior to, his support of an Everett-style interpretation of quantum mechanics. Seen through this lens, both his defense of Everett and the genesis of his ideas on decoherence emerge as consequences of his realistic view of the quantum state. Second, I give an overview of experiments on decoherence and describe, using the study of collisional decoherence as an example, the close interplay between experimental advances and theoretical modeling in decoherence research.
SECRS TEMPLATE TO AID NOVICE DEVELOPERS IN SECURITY REQUIREMENTS IDENTIFICATION AND DOCUMENTATION

The security requirements are one of the non-functional requirements (NFR) which acts as a constraint on the functions of the system to be built. Security requirements are important and may affect the entire quality of the system. Unfortunately, many organizations do not pay much attention to it. The security problems should be focused on the early phases of the development process i.e. in the requirements phase to stop the problems spreading down in the later phases and in turn to avoid the rework. Subsequently, when security requirements are to be focused, proper guidance should be provided which should assist requirements engineers. Many security requirements engineering methods were developed in the past which require different level of expertise such as SQUARE process which requires requirements engineer to have a certain level of security expertise. Moreover, it lacks proper guidance especially for novice developers in applying the existing security requirements engineering (SecRE) methods to identify security requirements. Hence, this study intends to address the gap by developing a guided template to assist novice developers in the security requirements identification and documentation. The main objectives of the research are: 1) to study and investigate the existing security requirements engineering (SecRE) methods. 2) To develop a template to aid novice developers in identifying and documenting security requirements. The developed template is applied to two case studies of software projects to determine its usability and applicability. The results of the case studies evaluation show that both the usability and applicability of the template is good. The template is also evaluated by several experts and software practitioners. The evaluation results show that the SecRS template is found to be satisfying the usability and applicability factors; thereby confirming that the proposed template achieves its desired objective of aiding the novice developers to identify and document security requirements correctly.
English-Indonesian crisis translation: accuracy and adequacy of Covid-19 terms translated by three MT tools

This study focuses on one basic question: how accurate and adequate are the three MT tools, namely Google Translate, Bing and Systran, in generating Covid-19 terms?It measures mainly the accuracy and adequacy of Covid-19 terms translated by three popular MT tools between English and Indonesian.Data analysis is conducted manually through human evaluation toward translation products by using a translation rubric.The assessment includes several samples covering the level of words, sentences and paragraphs.All samples are purposively retrieved from the Coronavirus Corpus and are translated by using the three MT tools.Two raters are involved to analyze texts at sentence and paragraph levels.The raters are used to provide the credibility of translation texts analysis.Results showed that the three MT tools produce different language accuracy and adequacy in revealing COVID-19 terms.Translating noun and pronoun in particular context from English into Indonesian language still remains unclear.This may affect paragraph cohesion.Furthermore, even though these MT tools successfully translate a number of English words into Indonesian, several of the words cited are officially absent in the Great Indonesian Dictionary.This gap raises confusion for Indonesian readers whose English is not sufficient to understand the lexical meaning.In this case, the study highlights the importance of updating the words data base.As this article implements an evaluation translation method, the goal is to produce some recommendations that may be useful for several parties: reader of target language, MT's developer, linguist and government.
Optimised Shop-Floor Operator Support on an Integrated AR and PLM Framework for Remanufacturing

Product disassembly and inspection are essential operations in a sustainable product life cycle, particularly in end-of-life strategies such as remanufacturing. This study identifies critical aspects of usability of a framework that supports the remanufacturing process and its operators. Two of the challenges faced by operators in remanufacturing are the number of product variants and quality decisions. As a result of these, the performance time and the number of errors committed increase. The integration of Augmented Reality (AR), product lifecycle management and expert systems increase the efficiency of managing stored data and supports the remanufacturing process and its operators. A head-mounted display has been used to run the application, allowing the operator to take it right to the working area. The information displayed during the manufacturing processes includes CAD models or images of the industrial equipment and its components and dynamic information, providing clear instructions easy to follow during the remanufacturing process. The proposed methodologic approach uses the concept of rule-based Expert Systems to determine the information content that is dynamically displayed on the AR device and to optimise the route that should be followed in remanufacturing operations. A pilot testing was done to assess the functional suitability of the final AR application to support the delivery of dynamic information in its final industrial environment. The evaluation was done in a real-working environment selecting the assembly, disassembly and inspection operations as a base. A questionnaire to measure the usability of the system was provided to the test subjects after the testing. The results from the questionnaire show a positive perception of the usability of the framework. According to the result analysis, the framework has high usability and can reduce errors and impaired decision-making.
Visualization as a Means of Influence (on the Example of Student Periodicals)

Visualization is a modern tool of communication with media perceptive readers. Visual means allow to influence the emotional sphere of the reader, replace certain information and the number of characters, diversify the compositional design of publications and create their aesthetics, which affects the image and reputation of periodicals. Visualization is a tool that is actively used in student periodicals, the target audience of which is modern youth with clip thinking. In order to attract the attention of such readers, to intensify their attention, the editors of student publications diversify the content with the help of a set of visual aids. In particular, typical forms of visualization in publications are photographs, drawings, pictures, symbols, comics, puzzles, tables, graphics, variation of page space with fonts, colors, decorative lines. The article analyzes the content of student magazines in Ukraine and Poland on the means of visualization and states the effectiveness of visual communication for these publications. As a result of research it is established that visualization has specificity of the influence (complexity and systematics). Determining criteria for the effectiveness of visual communication of student periodicals are visual activity, the degree of cognitive perception, compositional organization, supragraphemics, topographemics, non-pictographic elements, text positioning.
Effect of Online Learning Using Quizizz Application to Improve English Reading Skills of Higher Education Students

In this current era of technology, the use of online-based learning media that suits the needs of students can improve their learning skills, so teachers need to know the media criteria that must be applied to attract students' learning interests and those materials can be well received by students. Quizizz is one of those quiz-shaped and 4.0-based apps which is already popular among higher education. Quizizz can be used to train reading skills, especially students in English because in the application many features allow students to enhance their reading interest. The purpose of this study is that researchers will identify the influence of the Quizizz application on students' reading ability. The method used in this study was experimental. The instrument used is a test sheet. For data collection techniques conducted is to conduct a pre-test at the beginning of learning and a post-test at the end of learning, so that it can be seen the influence of the application of Quizizz application, in this case, improve students' English reading skills.
A Pose-based Image Searching using Computer Vision and Post-Estimate

As the cost of human forces increases, people in some careers, like the artists, may find some difficulties when models are needed in the processes of making art. Obviously, one alternative solution is to find pictures online, however, when some specific poses are needed, they may also find some difficulties to describe them. This paper develops an application to search for pictures with the target pose described by the user's graphical input. In this project, one hundred images describing distinct actions and activities with various poses and view-angles are collected. Mediapipe is then used to analyze those images in a quantitative way. We also embedded a User Interface that allows the user to imitate the intended pose as well as the viewing angles by simply dragging around body joints of the figure. Different sets of feature points and matching algorithms are also tested to find out the best solution.
Effect of Coping Strategies Education regarding Bullying on Knowledge and Behavioral Change among Secondary School Students

Bullying in schools is a widespread problem that, if not managed properly, can lead to a population that is psychologically, emotionally, physically, and socially dysfunctional for an extended length of time. The aim was to evaluate the effect of coping strategies education regarding bullying on knowledge and behavioral change among secondary school students. Subjects and method: Design: A quasi-experimental research design was utilized to fulfill the aim of this study. Setting: the research was conducted at four secondary schools in Port Said city. Subjects: A multi-stages technique of a purposive sample of 300 secondary school students was enrolled. Tools for data collection: The first tool was a structured interview questionnaire which consisted of two parts; part (I) demographic characteristics of the secondary school students; part (II) secondary school students' knowledge regarding bullying (pre/post) and the second tool was a coping behavior checklist for bullying. Results: The study result revealed that 56.0% of the secondary school students aged between 16-18 years with a mean of 16.38+1.23. There were highly significant improvements in secondary school students' knowledge post coping strategies education regarding bullying after two months of intervention (P<0.001). Three-fifths of the studied secondary school students reported suffering from all health effects, followed by absenteeism then depression, and suffering decreased self-esteem. The results also showed a highly statistically significant improvement in the secondary school students' behaviors regarding bullying between pre and post-intervention phases. Conclusion: The present study concluded that coping strategies education had a positive effect on improving knowledge and behavioral change among secondary school students. Recommendations: The study recommended that training programs should be provided among secondary school students to fight against bullying and should be aware of the harms of bullying and focus on its prevention in their organizations. Replication of the current study with a larger sample of secondary school students in different settings is required for generalizing the results.
IPMA ANALYSIS OF ACCEPTANCE OF USE OF LEARNING MANAGEMENT SYSTEM (LMS)

The current COVID-19 pandemic is causing big problems around the world, including in the world of education, which is experiencing changes in its learning system. Distance learning is now used by all universities in Indonesia due to the impact of the pandemic. Telkom University makes e-learning technology called CeLOE Learning Management System (LMS) as a distance learning platform for all lecturers and students. The purpose of this study is to determine the importance rating by using IPMA of the factors that influence the acceptance of CeLOE LMS technology using the General Extended Technology Acceptance Model for E-Learning (GETAMEL). The minimum sample in this study amounted to a minimum of 379 samples of respondents conducted by CeLOE LMS users. This study uses a non-probability sampling technique and the analysis technique used in this study is PLS-SEM using Smart PLS 3.2.9 software.
NFT METAVERSE STARTUPS AND A POSSIBILITY OF FUNDRAISING THROUGH TOKEN ISSUANCE

Blockchain has been one of the leading technology breakthroughs in recent years. It has enabled the creation of multiple cryptocurrencies and tokens which, amongst others, financed the activities of various startup projects. The last few years have seen the emergence of another blockchain-enabled product – Non Fungible Tokens (NFT) which are a digital certificate of ownership. Both NFTs and tokens are wider part of the creation of a metaverse – a new digital, online environment. This article analyses theoretical aspects of cryptocurrencies, tokens, NFTs and metaverse. The fundraising and token issuance aspects are analysed here based on examples of startups Metahero, Ultiarena and Bloktopia.
Fake Job Detection Using Machine Learning

Abstract: The research proposes an automated solution based on machine learning-based classification approaches to prevent fraudulent job postings on the internet. Many organizations these days like to list their job openings online so that job seekers may access them quickly and simply. However, this could be a form of scam perpetrated by con artists who offer job seekers work in exchange for money. Many people are duped by this fraud and lose a lot of money as a result. We can determine which job postings are fraudulent and which are not by conducting an exploratory data analysis on the data and using the insights gained. In order to detect bogus posts, a machine learning approach is used, which employs numerous categorization algorithms. The system would train the model to classify jobs as authentic or false based on previous data of bogus and legitimate job postings. To start, supervised learning algorithms as classification techniques can be considered to handle the challenge of recognizing scammers on job postings. It will employ two or more machine learning algorithms, selecting the one that yields the highest accuracy score in the prediction of whether a job advertising headline is genuine or not. Keywords: Fake Job, Online Recruitment, Machine Learning, Ensemble Approach.
Membangun Ketahanan Lingkungan Perpustakaan di Masa Pandemi COVID-19 dengan Penerapan SNI ISO/PAS 45005:2020

Libraries signify one of the service businesses impacted by the COVID-19 pandemic.Since the beginning of the pandemic, information about library closure or restriction almost happened in all parts of the world, including Indonesia.Then, during the reopening of library services, management needs to consider aspects related to occupational health and safety (OHS) as an effort to build a library environment that is safe from COVID-19, both for librarians and users.This study aims to describe an international standard that can be used by library management as guidance in managing a safe work environment during a pandemic, namely ISO/PAS 45005:2020.This study uses a qualitative descriptive research design.The data collection method used literature studies, interviews, and online observations.Descriptive data analysis using qualitative data analysis techniques with a narrative research analysis approach.SWOT analysis is used to analyze data related to the strategy of implementing ISO/PAS 45005 in libraries.The trustworthiness of this research uses credibility criteria, with respondent validation and triangulation techniques.Results of this study show that ISO/PAS 45005:2020 provides specific and comprehensive guidance for managing a safe library environment during a pandemic.For optimal implementation, management should identify strategic steps based on a SWOT analysis of internal and external issues to produce the right formulation of the implementation strategy.The implementation of this standard can be integrated with standards related to the occupational health and safety management system based on ISO 45001, and for risk management, it can be integrated with ISO 31000.In general, this standard complements the guidelines and regulations set by the government regarding efforts to prevent the spread of COVID-19 at workplaces.