Reviewerly/exHarmony huggingface dataset:
Developing English E-Vocabulary Module as Supplementary Book of Computer Learning Program

This research aims to develop an electronic English module that can be used by computer/ IT learners do deeply learn computer programming. It employes Research and Development (RnD) method by applying 4D steps namely define, design, develop and disseminate. Questionnaire is used as instrument and curriculum analysis is done to get the whole description and topic analysis. The result reveals that 83% of alumna agreed that computer learner needed the module that contain the definition of word that used in computer. While the curriculum analysis reveals that some main topics consists of 3 main subjects namely Microsoft word, Microsoft Excel, and Microsoft PowerPoint. There are two experts gave judgement and validation regarding to the product. The first expert is from English Language practitioner that validate and judges the content and language aspects. The result reveals that module got 4,7 with maximal score is 5. The second expert is from computer/ IT practitioner. He concerns on validating material, appearance, and media and technical terms on the module. The result shows that 4.4 with the maximal score is 5. It can be implied that both experts judge module is appropriate to be used as supplementary material for computer course.&#x0D;
Intralingual and Interlingual Grammatical Error Analysis on Students’ Writing

This article is intended to reveal students’ Intralingual and Interlingual Grammatical Error on their writings. The design of this research was descriptive qualitative. This research was conducted at Junior High School Level with 21 participants through purposive sampling method. Students’ writings were the main data used in this research. Based on the students' writings, the researchers pinpointed the errors' sources. Using Richards' categorization, the errors were then divided into intralingual transfer and interlingual transfer. Intralingual transfer was the first and most frequent source of errors. This type contained 66 errors, or 84%. Interlingual error was the second most common type of error, accounting for 13 or 16% of all errors. The target language itself, which led to the students' errors. Interlingual error occurred when students employed the first language system to produce language because they were unaware of the rules or grammar of the target language they were learning. It is crucial for teachers explain to students how grammatical notions function in context. Giving constructive feedback on English grammar assignments will enable teachers and students to gain a better idea of where each person sits in terms of their knowledge level.
THE STUDENTS’ PERCEPTION TOWARDS GOOGLE TRANSLATE AS A SUPPORTING MEDIA TO LEARN ENGLISH

Now, with the sophistication of smartphones, students can use Google to find out what is not known anywhere and anytime. One of the searches that students often use in learning English is Google Translate. Google Translate is a free multilingual translation service developed by Google which is used to translate text from one language to another. The students always open Google Translate many times when they don't know the meaning of a word, sentence, and text. The objective of the research was to describe the twelfth grade students' perception towards Google Translate as a supporting media to learn English at SMK Al-Hikmah Mayong. The researcher used descriptive qualitative research and the data was collected by the use of a questionnaire. In this research, the researcher used descriptive qualitative research. The participants were students of XII TAV 1 and XII TAV 2 of SMK Al-Hikmah Mayong which consist of 50 students. The result showed that the students of twelfth grade of SMK Al-Hikmah Mayong had a positive perception towards Google Translate as a supporting media to learn English with the majority of the answers they chose being “agree” that it helped them in learning English. They used Google Translate to help them such as to translate, check pronunciation, spell the word, and check synonyms. However, the results of the text translation from Google Translate are less accurate. It has a much different meaning than the original meaning.
EFFECTS OF SEGMENTATION AND SCALING ON ANOMALY DETECTION USING CONVOLUTIONAL NEURAL NETWORKS

Anomaly detection have been a successful technique in real world applications and mostly in industrial applications where precision is to be valued the most. Images are a day-to-day part of our lives, so here I have tried to present an approach for solving the issue of anomaly detection using Convolutional Neural Networks. The Neural network has been trained on diverse images of both anomalous images and Good (Normal) image. Neural Networks have been an integral and also emerged as a effective Deep Learning approach for tasks like image classification, anomaly detection and many such classification tasks. In recent years convolutional neural networks have been emerged as favorites for image classification tasks because of its various functionalities. The implications of this research are to present the effects of Scaling and Edge Preservation, Segmentation on images gives us different results of similar Neural network and to choose best of them. Thus, experimenting the Convolutional Neural Networks on different parameters yields us various results. Key Words: Convolutional Neural Networks, Image Segmentation, Edge Preservation
The Implementation of Project-Based Learning Model through ORAI in Recount Material to Enhance English Speaking Skill

The study objectives are to recognize the application of Project-based Learning (PBL) and utilization of ORAI, which can develop student’s speaking skills and immensity of the progress in recount text for tenth grade in science class 1 at MAN Sukoharjo. The students were in the second semester in Academic Year 2018/2019. More than 40 % students of tenth grade in science class 1 at MAN Sukoharjo encountered obstacles in English learning, especially in conveying recount. The data collection techniques in this research were document collection, observation, interview, and test. The data validity of this study used the triangulation method, which means that there were more techniques and observations of treatment in collecting the data. The finding reveals that the application of PBL and utilization of ORAI can improve student’s speaking skills especially in conveying recount. The average of students’ scores is found to be significantly different from each cycle. The pre-treatment average score is 69.33, the first cycle score is 72.66, and the second cycle score is 77.33. It means that almost all students can reach KKM (minimum completeness criteria). In conclusion, PBL and ORAI can be applied to enhance students’ speaking skills.
IMPLEMENTASI PROGRAM E-LEARNING MELALUI STRATEGI PENINGKATAN PERAN DAN FUNGSI KUALITAS PENDIDIKAN UNTUK MENDUKUNG S’DGS DI KOTA SURABAYA

This research in the background by education quality in Indonesia is still low, to increase education quality in Indonesia especially in Surabay city, so need to do something innovation education system by Department of education ofSurabaya city, that is by implementing education based on e-learning. E-learning is education system in learning method based on electronic.The main purpose of yhis research is (1) for knowing the role and function e-learning to support education quality in Surabaya city and (2) for analyzing policy that need to do by Surabaya government especially Department of education of Surabaya city in order to improve the role and function e-learning, in the implementation of quality education of junior high school. The location researched is SMP Negeri 23 Kedung Baruk Barat, Rungkut Surabaya.This reaserch is conducted with descriptive qualitative approach describe and interpret phenomenon results of data from field research findings. Data collection techniques used in this research is observation techniques, interview and documentation. This researc use implementing concep and theory used is Greandle theory.
Accurate Machine Learning Algorithms Based on Detection of Leukemia Disease: A Review

Abstract — Blood cell disorders are often detected in advanced stages as the number of cancer cells is much higher than the number of normal blood cells. As one of the important aspects of diagnosing leukemia and determining its progress is identifying malignant cells. This paper illustrates the discovery of leukemia and its four main types through machine learning algorithms, as it was found that Computer-Aided Diagnosis (CAD) has progressed rapidly over the past few years. To identify leukemia, multiple machines learning algorithms have been created for early detection. Leukemia is a condition synonymous with white blood cells (WBC) that affect the bone marrow and/or blood. The early, healthy, and reliable diagnosis of leukemia has a major role in treating patients and saving their lives. To define leukemia in relation to its subtypes, several methods have been developed. However, these approaches include improvements in efficiency, learning process, and performance. This research paper is explained to enhance and provide rapid and stable detection of leukemia. To facilitate real-time collaboration between patients and healthcare providers for leukemia research, early diagnosis, and treatment. Thus it can save patients and doctors time and money. While the use of machine learning algorithms has shown accurate results, it depends on the shape and size of the sample and the type of algorithm used to classify the subtypes of leukemia (leukemia).
Retracted: 3D Virtual Reality Implementation of Tourist Attractions Based on the Deep Belief Neural Network

[This retracts the article DOI: 10.1155/2021/9004797.].
Retracted: Smart Health Monitoring System with Wireless Networks to Detect Kidney Diseases

[This retracts the article DOI: 10.1155/2022/3564482.].
Retracted: Neural Network Optimal Routing Algorithm Based on Genetic Ant Colony in IPv6 Environment

[This retracts the article DOI: 10.1155/2021/3115704.].
Retracted: Intelligent Recognition Model of Business English Translation Based on Improved GLR Algorithm

[This retracts the article DOI: 10.1155/2022/4105942.].
Retracted: Dynamic Evaluation of Intensive Land Use Based on Objective Empowerment by Entropy Method and Neural Network Algorithm

[This retracts the article DOI: 10.1155/2022/2429826.].
Retracted: The Acceptability of Traditional Culture under the Background of Deep Learning

[This retracts the article DOI: 10.1155/2022/4010099.].
Retracted: Public Security Video Image Detection System Construction Platform in Cloud Computing Environment

[This retracts the article DOI: 10.1155/2022/4113803.].
Retracted: Construction of Curriculum Ideological and Political Collaborative Education Mechanism Based on Edge Computing and Neural Network Algorithm

[This retracts the article DOI: 10.1155/2022/3596665.].
Retracted: Research on Four-Dimensional Innovative Intelligent Education Platform Based on Cloud Edge-End Architecture

[This retracts the article DOI: 10.1155/2023/2263033.].
Retracted: English Teaching Quality Evaluation Based on Analytic Hierarchy Process and Fuzzy Decision Tree Algorithm

[This retracts the article DOI: 10.1155/2022/5398085.].
Retracted: Feature Extraction of Ancient Chinese Characters Based on Deep Convolution Neural Network and Big Data Analysis

[This retracts the article DOI: 10.1155/2021/2491116.].
Retracted: Construction and Computation of the College English Teaching Path in the Artificial Intelligence Teaching Environment

[This retracts the article DOI: 10.1155/2022/3415999.].
A Digital Dial Recognition Method Based on Lightweight ResNet

Abstract The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Retracted: An Enhancement on Convolutional Artificial Intelligent Based Diagnosis for Skin Disease Using Nanotechnology Sensors

[This retracts the article DOI: 10.1155/2022/9539503.].
Retracted: Cloud Statistics of Accounting Informatization Based on Statistics Mining

[This retracts the article DOI: 10.1155/2022/3493678.].
THE IMPLEMENTATION OF ENGLISH BRIDGING PROGRAM ADAPTING CAMBRIDGE CURRICULUM FOR PRIMARY SCHOOL

This study aims to explore and describe English bridging program adapting Cambridge curriculum for grade one of primary school at Afkaaruna Islamic School (AIS), Yogyakarta. The bridging program was a program to facilitate new students to improve their English language skills before joining real class. This study used qualitative approach with the case study research design. To collect the data, the researcher used interview, observation, and documentation. The researchers interviewed three English teachers. Then, data were analysed using the theory of Miles and Huberman including data collection, data reduction, data display and conclution/verifying. The results included the implementation of the Bridging Program was carried out for 2 to 3 months with the three focused subjects: Indonesian literacy, English literacy, attitude and character. Activities done included a pre-test conducted to determine students' abilities. The obstacles during the learning process were during online learning and the gap in students' abilities. The solution given was to provide additional classes for students who had not reached the learning target. The benefit of implementing English Bridging Program was to help students prepare themselves in the learning process and improve students' English ability to communicate and interact with others.
IMPLEMENTASI PEMANTAUAN SUHU, KELEMBABAN DAN KADAR GAS AMONIA BERBASIS ANDROID PADA PETERNAKAN KAMBING SAPERA MITRA AGRO ABADI FARM

The partner of this program is a dairy goat breeder Mitra Agro Abadi Farm which is located in Barukan Village, Semarang Regency. The fundamental problem of dairy goat farmers in Barukan Village is related to continuous real time monitoring of temperature, humidity and ammonia gas levels in goat cages. Breeders still use the manual method by estimating changes in temperature and humidity and changes in ammonia gas making the goat cage susceptible to disease in goats so that it affects the production of goat milk produced. Therefore, the PKM team offers a solution to create a system that can monitor temperature, humidity and ammonia gas levels in an Android-based goat pen that can be monitored via the farmer's cellphone, then the monitoring data is sent via the internet and then provides notifications to farmers remotely in real time. via mobile phones so that farmers can provide immediate handling or action if the cage conditions are not in accordance with ideal conditions. The goal to be achieved from this activity is that the Barukan Village goat breeders are IT literate and it is easier to control the condition of the goat cages in a measurable manner. Thus, the quality of goat's milk production also increases
Phonological Analysis in Delivering Stories through Video Recording

Postulating the language as means of communication playing crucial role in our daily lives is truly indisputable. A lot of problems occurred in the field of phonology by the students in delivering their speaking performance. This research is intended to analyze the phonological error in the second semester students in performing stories in the form of speaking. The kind of this research is classified as qualitative research which focuses on analyzing students’ utterances, particularly in terms of English phonology. In this study, the data were collected in the form of video-recorded speaking performance and written transcription by the subjects of the research. Furthermore, after a careful and detailed analyzing process by the researcher, it is concluded that most students made several phonological errors in pronouncing some English words. The result of the study showed that diversity of language skills and components particularly pronunciation, fluency, and accuracy is dominantly due to the previous educational background, students’ motivation in learning, the intensity of students’ exercise, students’ current efforts in learning English, and having a grit. By having a grit, the students have passion and perseverance to train themselves in learning English and practicing the English skills for long-term.
Gender Difference and Errors in Writing Narrative Texts among Indonesian EFL College Students

This study aims at identifying and analyzing linguistic and textual errors in writing narrative texts committed by male and female students of the fourth-semester English department students. The focus is on finding the significant differences between male and female students in terms of the frequencies of linguistic and textual errors in their narrative texts and the factors contributing to the errors. Data were collected through writing tests. Data were analyzed and interpreted by quantitative descriptive analysis and multivariate analysis using Two Ways ANOVA (F-Test) to investigate the significant differences linguistic and textual errors. Then the types of linguistic and textual errors in the two groups of male and female students were compared using descriptive analysis and statistical analysis. The results show that 57.93% of linguistic errors occurred in female’s narrative writing, with 42.07% occurred in male’s. Meanwhile, 46.29% of textual errors occurred in female’s narrative writing, with 53.71% found in the male’s. Statistically, there was no significantly different interaction between male and female students in terms of textual error frequency in writing narrative text, with p = 0.975 (p &gt; 0.05) at the level of significance a = 5 %. And there was a significantly different interaction between male and female students in terms of linguistic error frequency in writing narrative texts, with p = 0.029 (p &lt; 0.05) at the level of significance a = 5%. Several factors that affect female and male students’ errors in their narrative text are intralingual interference, language transfer, lack of knowledge about the narrative text, and gender difference.
Teaching English Based-Realia for Young Learners in MBS (Muhammadiyah Boarding School) Mataram NTB

Essentially, language professionals have offered a plenty of fascinating and enjoyable language education approaches and ideas. Media realia is one of the alternative strategies presented in this study. The purpose of this research is to investigate the impact of using realia media to teach English to young children. The study was conducted at the Sang Surya Muhammadiyah Boarding School Kindergarten in Mataram with 11 children as the sample. The pre-experimental approach, namely pre-test and post-test group design was applied in this research. The instruments to gather the data were observation, a vocabulary test and recording, while the data collection procedure was done through pre-test, treatment and post test. Finally, the data were analyzed using a pre-experimental formula in the form of statistical computation. The result shows that the comparison of the t-test and t-table is 3.21 ≥ 2.60, or the test results exceed the minimal accomplishment levels. It revealed that the use of the "realia" technique has a significant impact on the development of children's vocabulary learning. In another words, the use of "Realia" technique in teaching English to young children at MBS Batu Ringgit is "effective" when used in the teaching and learning process.
Global Path Planning Method for Parks based on Complete Coverage Cleaning Task

In this paper, based on a small driving sanitation platform of an enterprise, the global path planning method in the unmanned decision system is studied and designed for the characteristics of the park environment and the task requirements. The operation space of the sanitation platform is divided into rectangular square cleaning area and lane cleaning area based on the task demand of full coverage of the park. For the sweeping task of the lane area, multiple parallel sweeping reference paths are generated by raster erosion of the lane map; for the sweeping task of the rectangular square, this paper proposes an improved bow-shaped full coverage algorithm combining forward and reverse based on the steering capacity constraint of the sanitation vehicle. Finally, the path articulation algorithm is used to connect the sweeping paths of suboperating areas to form a global reference path for the sweeping operation of the park.
Interpretability for Conditional Coordinated Behavior in Multi-Agent Reinforcement Learning

We propose a model-free reinforcement learning architecture, called distributed attentional actor architecture after conditional attention (DA6-X), to provide better interpretability of conditional coordinated behaviors. The underlying principle involves reusing the saliency vector, which represents the conditional states of the environment, such as the global position of agents. Hence, agents with DA6-X flexibility built into their policy exhibit superior performance by considering the additional information in the conditional states during the decision-making process. The effectiveness of the proposed method was experimentally evaluated by comparing it with conventional methods in an objects collection game. By visualizing the attention weights from DA6-X, we confirmed that agents successfully learn situation-dependent coordinated behaviors by correctly identifying various conditional states, leading to improved interpretability of agents along with superior performance.
Autonomous Recognition of Collective Motion Behaviours in Robotic Swarms from Video using a Deep Neural Network

Recognition of swarm behavior is important for two reasons. First, it permits the early detection of adversarial collective motion behaviours such that counter-collective motion can be activated. Second, it permits the monitoring and assessment of own swarms to enable detecting any disruptions to the required behavior. Existing work in this area requires feature-based data provided by an external observer that has access to all the swarm states that could not be available all the time. However, the need for pre-processing swarm data to calculate its features can lead to inefficient behavior recognition. This paper addresses this limitation by using raw video data for swarm behavior recognition. This paper proposes a new framework to autonomously recognize structured collective behavior in swarm robots from camera data First, we present a dataset of both collective motion and random behaviors of Pioneer 3DX robots. Then we formulate the recognition problem as a spatiotemporal learning problem. A recurrent neural network is used as the main building block to evaluate each video representation—Our experimental results showed that this video-based recognition without any data pre-processing results in high accuracy that is comparative to feature-based recognition techniques. The proposed model is able to efficiently recognise robots’ behaviour with 99.8% accuracy. Also, our methodology can distinguish behaviours of real robots with 79% accuracy even with different numbers of agents.