Reviewerly/exHarmony huggingface dataset:
An Analysis of Socio Culturally Bound Expressions In Indonesian English Translation of The English Education Department At IAIN Metro In The Academic Year Of 2020/2021

The objectives of this research are to know the students’ difficulties in translating the socio culturally-bound Expressions in Indonesian- English translation, and to analyze the cause of the students’ in translating the socio culturally-bound Expressions in Indonesian- English translation. The researcher analyzed those phenomena based on the consideration of the students’ problem in translation investigated in the process of pre-survey. Therefore, it is hoped that this research is beneficial in illustrating the phenomena of translating the socio culturally-bound expression. The method of this research was qualitative research in the form of a case study carried out at IAIN Metro. The primary source of this research is the translation assignment result of the students’ of IAIN Metro in academic year 2020/2021. The total numbers of the students’ are 20 students. The researcher uses documentation and interview in collecting the data. The documentation was conducted to know the students’ difficulties in translating the socio culturally-bound Expressions in Indonesian- English. The interview was conducted to analyze the cause of the students’ in translating the socio culturally-bound Expressions in Indonesian- English translation. The research results show the students’ translation of socio culturally-bound expression in Indonesian- English translation that consist of that consist of 85 % inappropriate use of socio cultural bound expression and 15% appropriate use of socio cultural bound expression. In addition, the second research result is about the causes of the students’ difficulties in translating the socio culturally- bound expressions in Indonesian- English translation caused by the translator's lack of knowledge in both languages in general and in the significance of the functional equivalence in particular, limited linguistic competence, their poor pragmatic competence in the target language, lack of cultural awareness and lack of cultural interaction and experience.
Digital Literacy Analysis of Elementary School Teachers on Distance Learning Instructional Process in Yogyakarta

A teacher must have digital literacy to be able to understand of information or learning resources access such as online videos, eBook’s, recordings, audio, and digital libraries from the internet and use their features in designing learning media for learning resources used during online learning. This study aimed to analyze the digital literacy of elementary school teachers. Data were collected from 153 teachers from 44 schools in the special province of Yogyakarta. The research method uses a survey method that includes seven aspects of digital literacy: information literacy, Digital scholarship, Learning skills, ICT literacy, Career and identity management, Communication and collaboration, and media literacy. The results show that all teachers use technology in the online learning process including teachers aged 40 years. It also can be used as motivation and reference for teachers to improve digital literacy/and educational institutions carrying out of training to improve digital literacy for elementary school teachers.
A Design of Blended Learning Core Curriculum based on Personalized Learning for Career Readiness

This study aims to design a core curriculum with a blended learning method based on personalized learning for students' career readiness.Career readiness is an internal aspect that needs to be prepared for since school.Seeing the current situation, it is essential for teachers, especially guidance and counselling in schools, to continue innovating and adapting in preparing students who have career readiness according to student characteristics.Core curriculum can be one of the services provided in schools.Services can be provided using a blended learning method based on personalized learning.Blended learning was chosen to adjust to the situation in COVID-19 to continue to carry out activities face to face and online.On the one hand, personalized learning was chosen to be the basis for providing services because personality learning explains the characteristics of students more profoundly.This study uses a literature review method.This research aims to produce a core curriculum blended learning design based on personalized learning that can be applied in developing students' career readiness.
Time in the Physical Picture of the World

The article is devoted to the problem of time in modern science, where in recent years there have been major changes related to the latest discoveries in the field of the foundations of quantum theory. The author refers to works of K.-F. von Weizsacker (which works are not well-known in Russian-speaking field). Weizsacker deploys a large-scale program of building modern physics, while starting (not only as a physicist, but also a professional philosopher) with questions of philosophical interpretation of postulates of modern physics, especially quantum mechanics. His key thesis is that time in physics is fundamentally distinct, which represents the whole physics as an integral scientific discipline. Weizsacker comes from physical and philosophical reflections, that give a special value to his work. Analyzing the conclusions of theoretical physics, namely the issues of substantiation of statistical mechanics, thermodynamics, and, above all, quantum mechanics, Weizsacker comes to the key idea of the structure of time in the substantiation of physical theory. The author in this conclusion disagrees with the opinion of most modern physicists that time has a subjective character, and the modus of the past, present and future reflects its essential character. The allocation of the time structure requires special logic. Such a logic is temporal and quantum. Starting from temporal logic, introducing the concept of possibility and probability, he comes to the substantiation of quantum mechanics. Being modal logic, it is based on the concept of possibility and probability. Key concept for Weizsacker is a binary alternative (Uralternative), closely related to the principle of superposition in quantum mechanics. By introducing the concept of certain alternatives, essentially actualized alternatives, Weizsacker shows how one can get the theory of relativity with its space-time structure. Further, he shows that based on its structure, you can get the theory of relativity. The space-time structure in this case is secondary, relational, as understood by Leibniz, Mach, and Einstein.
THE CONTRIBUTION OF TRADITIONAL GAMES IN ESTABLISHING SELF-CONTROL CHILDREN

This research intended to develop a traditional game guidebook to improve self-control for children aged 9-12. This research method was R&amp;D. Research conducted involved seven validators for expert judgment, seven teachers who were certified educators for needs analysis, and six children through subjects of a limited trial of the developed traditional game guidebook. The results indicated that; 1) development of this traditional game guidebook using ADDIE, 2) traditional game guidebook belonging to the "Very good" quality strata, with an average of 3.81 (scale 1-4) and consideration "No revision needed", and 3) implementation of this traditional game guidebook affected self-control. The significance test indicated t(5) = 16.81; p = 0.00 (p &lt; 0.05) and r = 0.99 which belonged in the strata "Big effect" and equivalent to 98.26%. Thus, this traditional game guidebook could interpret 98.26% of changes in the self-control of children. The traditional game guidebook showed the effectiveness of the N-gain score of 80.39% which corresponds to the "High" strata.
An automated standalone hand wash outdoor deployment unit for infectious disease control

The recent global coronal virus pandemic raised increased awareness towards ideal hand hygiene procedures as promoted by World Health Organisation (WHO) and other related health care associations. Compliance to the prescribed procedure has been rather difficult as people gradually get accustomed to this effective hand wash habit, especially with regards the 20 s hand rub process. Traditional hand wash faucets with manual controls are prone to exposing users to recontamination or transmission of infectious deceases. Also, water wastage of 51.32% was observed from empirical studies. The designed automated standalone hand wash unit (ASHU) seeks to solve the contamination problem by running a contactless tap operation, while guiding users through the ideal hand wash procedure with the aid of visual and audio annunciators. Being a standalone unit, solar energy in used to power of the low power design system for uninterrupted outdoor operation, even in unelectrified rural regions. With the suitable level sensors and IoT infrastructure put in place, the unit maintenance operators are able to monitor the fluid levels in with the aid of a custom-built mobile app. Subsequently, the ASHU yields a water wastage potential of only a maximum of 13.31% and a user satisfaction guarantee for 93% of the refill cycle.
Python Quantitative Dynamic Panel Big Data Analysis: Starting from the Game Algorithm of Consumption Environment and Rural Consumption Growth

This paper discusses the relationship between rural consumption environment and rural economic growth within the framework of game theory. This paper argues that. The game process between government public investment and rural residents' consumption is an important way to promote rural economic growth. Using the system generalized moment estimation method, this paper conducts an empirical study on the relationship between my country's consumption environment and consumption growth. The results show that: improving the construction of infrastructure will significantly promote the growth of urban residents' consumption; perfecting the construction of my country's consumer finance market, optimizing the design of the test system for the Python quantitative investment platform, and formulating its implementation plan, which are currently many Python quantitative investments. Platform builders focus on issues.
Developing a Framework for Next Point-of-interest Recommendation from Spatiotemporal Data

Point-of-interest (POI) recommendation system is popularly used in location based social networks where the goal is to recommend interesting unvisited locations to users. The sequential nature of check-ins hindered many researchers to apply Recurrent Neural Network (RNN) based models for this task. However, most of the models consider only historical check-ins of the user for generating recommendations and fail to incorporate information about current location and time which plays an important role. For reducing data sparsity in spatial dimension, many models use hierarchical gridding of the map which can not reflect spatial distance properly between neighboring grids. Besides, most of the existing models ignored the impact of weather condition when generating recommendation. Keeping these limitations in mind, in this paper we present a framework for point-of-interest recommendation that can model sequential nature of check-ins using Long Short-Term Memory (LSTM) network. We incorporate current spatiotemporal information with weather condition that can provide better personalized recommendation. Instead of hierarchical gridding, we perform linear interpolation for smooth representation of distance between two locations. Extensive experiments on two real world dataset shows that our proposed method surpasses existing state-of-the art methods by 16-18&#x0025;.
Digital Mail: An User Demand and Verification-aware Mobile Application Featuring Parcel Delivery for the Bangladeshi Postal Services

Over the years, the Post-office plays an excellent role to raise the standard of people&#x0027;s life by connecting people through the postal package delivery services along with other socio-economic services. With the progress of the digital age, nowadays peoples want more faster and reliable postal services. To cope up with people&#x0027;s expectations, Bangladeshi post-offices require user demand and verification-aware digital mobile applications for the postal services. At present, the existing work on Bangladeshi postal services do not present any intelligent digital mail mobile application by considering user demand-aware postal package delivery, login/signup system for users and officials, package tracking and receiver verification by using QR code, different bill payment option, nearby post-office suggestion, complaint regarding service delivery, help, and customer notification regarding the package delivery at the same time. To overcome the existing issues, this paper presents a user demand and verification-aware &#x0027;digital mail&#x2019; mobile application featuring flexible parcel delivery for the Bangladeshi post offices. The proposed mobile application offers several facilities for postal services like user verification, login, demand-aware package submission, payment, package notification, and delivery, parcel tracking, user feedback, and help features. The user feedback results with almost 85&#x0025; users satisfaction indicate the necessity of the proposed system.
A Study of Contextual Theology and Ethics in Asian-American Theology

This study initiates its question about the idea of the orthodoxy theology with criticism of Stephen Bevans' contextual theology, as such theology is contextual. To develop this thesis, this study delves in the theological meaning of Asian-American theology. To begin with, this research studies the emerging identities of Asian-Americans such as suffering(han), marginality, hybridity and mimicry as the foundation of Asian-American theology. The theology of the healing and forgiveness of the suffering is established by the theology of Tao (the way). Second, women's diasporic and historical memories formulates Asian postcolonial feminist theology, like the experience of jeong, as related to Korean and Korean American women's memories of love, related to a postcolonial feminist theology. Furthermore, this study also demonstrates a theological ethics based on Jung Young Lee and Paul Tillich, since theological ethics is also based on experiences of marginality. The awareness of marginality drives people to go to the place of morality based on the notion of human-relatedness and acknowledgement of difference. Finally, theological ethics reaches to the ultimate place of love, agape, the final goal of theological ethics. Theological ethics formulates a new center through the divine love, agape, in order not to have a new ruling power, but in order to build a new community of love. Thus, this study argues that Asian-American theology and ethics contribute to this new possibility of ethics.
A Hybrid Recommendation Approach for Medical Services That Incorporates Knowledge Graphs

At present, there are a large number of growing medical applications in the application market. It is difficult for users to find satisfactory medical services conveniently and efficiently. The classical collaborative filtering algorithm has some problems, such as cold start, unsatisfactory recommendation results, and so on. This paper proposes a hybrid medical service recommendation approach based on knowledge graph to solve the above problems. This approach introduces the open knowledge graph and establishes the semantic link relationship between the mobile application and the knowledge graph entity. It not only enhances the semantic feature of single application for improving the accuracy of recommendation results, but also realizes the in-depth analysis of the semantic relationship among multiple application entities in the knowledge graph through the TransHR model which can alleviate the cold start problem. Then we design a hybrid recommendation algorithm based on multi-dimensional similarity fusion. This algorithm uses the entropy method to organically integrate the calculation results of multi-dimensional semantic similarity, such as feature vector similarity, entity relation similarity, and user rating similarity. It is convenient and efficient to recommend satisfactory medical application services to target users. Finally, we test and analyze the accuracy and effectiveness of our proposed approach by experiment.
Analysis on Skew Detection and Rectification Techniques for Offline Handwritten Scripts

Multilingual recognition framework is trustworthy to be advantageous to a bunch of community that desires automatic sorting of multilingual documents. This analysis will furthermore be enlarged to document forensic zone or mediation agency to differentiate obscure native document. In this paper, we tend to conceive to arise to common problems with manually written records like nonparallel content lines within the midst of a page, slanted, and connected characters. This framework comprises of taking after modules such as skew angle discovery and skew correction. The skew point is obtained with the aid of finding out a peak within the histogram of the gradient orientation of the input gray-level image. The asymmetry of the document is adjusted by means of a flip at an associate degree angle. The techniques can be utilized as a preprocessing stage to any handwriting character recognition system.
Knowledge mining from scientific literature for acute aquatic toxicity: classification for hybrid predictive modelling

This work proposes a systematic method consisting of state-of-the-art text processing approaches and human-machine interaction for the extraction of useful sentences and data in tabular, graphical, and numerical form, containing information particularly relevant for hybrid modelling. It is applied to the domain of acute aquatic toxicity of chemicals, which is particularly relevant for the safety, health, and environmental hazard assessment of chemicals. Nearly 400 papers from 2000-2021 were identified and processed with the proposed method. The results indicate that the vast amount of knowledge can be efficiently processed in orders of magnitude faster than conventional methods without loss of detail and interpretation depth. The information is in a form that can be useful in hybrid modelling with respect to model and predictor selection, prioritization, and constraints, addressing data gaps, and validating and interpreting model performance.
Cross-modal representation learning based on contrast learning

Cross-modal retrieval refers to accurate retrieval between data from different modes. Its core task is how to measure the similarity between different modal data across semantic divides. In this paper, a novel cross-modal retrieval model CLCMR is proposed, which makes the identification of similar samples of different images more inclusive and the identification of different samples more discriminative. Specifically, the comparative learning method is introduced into the model, the pretraining dataset is processed by the data enhancement method, and the image Encode is pre-trained to make the image features extracted by the same sample closer The difference in image characteristics of similar samples improves their recognition accuracy and accuracy. In the downstream task, in order to ensure the effect of Encode, three loss functions are selected to ensure the nativeity of the data mapping of each mode into the common space, that is, to reduce the modal loss caused by the transformation space. Finally, in order to semantically align images and text, the content of Fast-RCNN was added to the CLCMR network framework for cross-modal retrieval. In this paper, several experiments are conducted on the Pascal Sentence dataset and the XmediaNet dataset, and the results show that the CLCMR cross-modal retrieval framework proposed in this paper is used The mAP value is better than some of the methods commonly used at present, which verifies the feasibility and perfection of the method.
Quadrotor attitude controller based on super-twisting algorithm

Actuator saturation has an important influence on the stability of the quadrotor UAV (Unmanned Aerial Vehicle) control system. The characteristic of the control structure of the quadrotor UAV is that the inner loop control commanddirectlyaffects the actuator. Aiming at the problem of actuator saturation of quadrotor UAV attitude control, an attitudecontroller based on Conditioned Super-Twisting Algorithm (CSTA) is designed. The two sign functions in CSTAarereplaced by the hyperbolic tangent function, and the input of the hyperbolic tangent function is adjusted byagainparameter, thereby suppressing the chattering of controller. The experimental results show that the designed controllercan track the attitude command better than PID when the actuator is saturated. Compared with the CSTAalgorithm, thedesigned controller output chattering is significantly reduced.
An Analysis of Convergence in Speaking Skills among the Eleventh-Graders

Communication’s objective is to deliver information from one person to another. People adapt their communication in everyday life in order to attain the purpose of communication. It can be shown which features of convergence mostly appeal appear communication-related to the reason for it. The aim of this study is to analyze the English convergence in speaking skills among the eleventh-grade students at senior high school in Lampung Tengah, Indonesia. It is especially interested in analyzing the most dominant feature of convergence and why the students have it when speaking English. In this study, a qualitative method using a case study approach was applied. The participants were chosen from a group of sixteen eleventh graders. A classroom observations sheet and interview session were used to collect the data. The result of the study shows that the most dominant feature of convergence in speaking skills among the eleventh graders at senior high school in Lampung Tengah, Indonesia is Utterance Length. Utterance length involves Listening and Clarifying. All students certainly listen to the interlocutor and are speechless while clarifying. Secondly, the reason for the eleventh graders at senior high school in Lampung Tengah, Indonesia apply convergence is to be attracted by others and evoke social status.&#x0D;
(Retracted) Support vector machine parallelized remote sensing image classification algorithm based on big data

With the development of big data technology, machine learning classification methods have been widely used in the classification and recognition of remote sensing images. For remote sensing big data, how to quickly and efficiently use machine learning classification algorithms to classify remote sensing images is an urgent problem. It is a general term for the theory, method, technology, and activities of obtaining valuable information based on massive remote sensing data sets, synthesizing auxiliary data from other sources, and using big data thinking and means. The purpose of this paper is to study the support vector machine (SVM) parallelized remote sensing image classification algorithm based on big data. We propose a parallel nesting of GPU in MPI multiprocesses based on the big data framework, which can more effectively improve the calculation processing speed and build a high-performance SVM parallel computing framework based on the big data framework. The optimization problem of SVM considers both empirical risk and structural risk minimization and requires maximum edge distance when constructing hyperplane decision boundaries, so there is ample space between the interval boundaries to accommodate the test samples. Based on this framework, we improve the machine learning SVM algorithm and realize the high-performance parallel computing of SVM classification algorithm on this platform. It is an efficient hybrid parallel mode to nest GPU in MPI multiprocess in parallel. When the number of nodes is 2, 4, and 6, the speedup of the SVM classification algorithm is 1.52, 2.24, and 2.55.