Reviewerly/exHarmony huggingface dataset:
Risk Perception and Preparedness in Flash Flood-Affected Communities: Evidence from Bahorok, Indonesia

The Bahorok River basin has a high flash-flood hazard index. This is shown by loss of lives and damage of homes due to floods in recent years, however, no research examined community preparedness on the hazard of flash-flood. This research aimed to assess the effect of disaster experience and flood-risk perception on disaster preparedness of the people of Bukit Lawang Plantation Village. A cross-sectional survey design was used to determine the relationship between disaster experience, risk perception and preparedness as the independent and dependent variables, respectively. The results showed that disaster experience and risk perception positively and significantly affect the community preparedness. Disaster risk reduction programs in the region only focus on emergency response, rehabilitation, and reconstruction. Furthermore, increasing public awareness and preparedness has not been prioritized in reducing flood risk. This is an essential aspect for consideration because mountainous areas are often marginalized and lack access to disaster risk reduction programs.&#x0D; Keywords : Flood-risk perception; preparedness; flash flood&#x0D; &#x0D; Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember&#x0D; This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
The Relationship between Indonesian Language Learning and the Environment

Environmental education aims to create a generation that is wise to the surrounding environment. The phenomenon of the environment, both in national and international news, never escapes the attention of the public and the world. The impact of damage or natural disasters that occur causes environmental education to need to be educated from an early age. Learning activities related to environmental education can be carried out directly through Natural Science-based subjects and indirectly through Indonesian language learning. Indirect learning can be done through Indonesian texts, especially factual variety texts. The factual variety text is more detailed and based on real events so that it is suitable for environmental education through Indonesian language learning. The role of the teacher is also needed to achieve optimal results because not all texts are perfect and need to be perfected. The expected result through this paper for teachers or related parties is knowledge about environmental education, especially the application through text-based Indonesian language learning.
An Empirical Analysis on Multicultural Learner’s Variables and Learning Effects in Classics Reading Classes

This study empirically analyzes the relationship between the multicultural learning variables and the learning effects of classics reading lessons regarding Korean and foreign students. The t-test, cross tabulation table, and discriminant analysis showed that Korean students improved their logical thinking power and became more interested than foreign students through the classic reading classes. The regression analysis showed that the recognition variables such as interest level, importance, necessity, and the reading of the classics did not influence the learning effects of classics reading class in regards to the necessity of the classics and the satisfaction level derived from classics reading classes. However, the improvement in presentation and the power of expression, logical thinking power, and the interest in the classic classes did affect the learning effects of classics reading class. As for the path analysis, while the recognition variable regarding the importance of the classics did not directly affect the learning effects of the classics reading classes, it appeared to indirectly influence the learning effects via the mediate variables of the enhancement of presentation and power of expression, logical thinking power, and the interest in these classic reading classes.
Research on Recommendation of Big Data for Higher Education Based on Deep Learning

To improve the recommendation accuracy of educational resources, an intelligent recommendation method based on autoencoder has been proposed by combining intelligent recommendation algorithm and autoencoder. The method uses the dimension reduction advantage of autoencoder to obtain the required feature vector. Then, the prediction score is utilized to recommend educational resources. Finally, it is verified from the algorithmic and system perspective. The results show that this recommendation method is the most efficient method. The efficiency on the dataset is 0.90, respectively. Furthermore, it can score different recommended articles, and the recommendation of different educational resources is realized.
Conversational Structure Used in Guiding Conversation on YouTube Channel

The number of followers of the account can be recovered, even it can be hundreds or thousands, the account can also be used as a model to become popular. The term for those who earn money from social networks, especially YouTube, is called as YouTuber. It becomes something interesting to study when some YouTubers uploaded their activities, one of them was the video when they went on tours or travel trips to guide the foreign tourists using English during the tours they uploaded. How the structure of the conversation they used was one of the interesting things to study. This is descriptive qualitative research which aims to describe conversational structure of tour guide in YouTube channel. The data were collected through listening, transcription, and note-taking techniques. The collected data then were analyzed using the chosen theory. The results showed that conversational structures used by tour guides in their YouTube channel include six elements which refer to opening, turn-taking, topic shift, overlapping, adjacency pair, and closing. Besides that, there are four expressions such as greeting, asking for information, giving information, and confirming. Expression of greeting consists of formal greeting. Asking for information about condition, readiness, and opinion. Giving information regarding the desire to go somewhere. Meanwhile, confirming expressions are used to ensure specific information about the guest.
Double window: definition of a new pseudo-color mapping scheme for medical imaging

Abstract The number of gray levels in medical images significantly exceeds the range of human eye recognition. In this paper, we propose a series of definitions for real-time pseudo-color enhancement based on the hue, saturation, and value (HSV) color space. First, the definitions of gray window and color window are given as follows: in the HSV color space, the gray window means mapping pixel values to value, and saturation is set to zero. Thereafter, the color window was defined by mapping pixel values to hue, with the maximum saturation and value. Moreover, pixel values greater than the upper bound of the gray window were converted to hues in the double window. The images in the double window display the details shown in the lung window, mediastinal window, and bone window for chest computed tomography and showed more details than the grayscale image in brain magnetic resonance imaging. The proposed method enhances the display effect in some cases; for example, when the image histogram has more than one peak, the information displayed white in a regular grayscale image is displayed in color.
Raw Radar data based Object Detection and Heading estimation using Cross Attention

Radar is an inevitable part of the perception sensor set for autonomous driving functions. It plays a gap-filling role to complement the shortcomings of other sensors in diverse scenarios and weather conditions. In this paper, we propose a Deep Neural Network (DNN) based end-to-end object detection and heading estimation framework using raw radar data. To this end, we approach the problem in both a Data-centric and model-centric manner. We refine the publicly available CARRADA dataset and introduce Bivariate norm annotations. Besides, the baseline model is improved by a transformer inspired cross-attention fusion and further center-offset maps are added to reduce localisation error. Our proposed model improves the detection mean Average Precision (mAP) by 5%, while reducing the model complexity by almost 23%. For comprehensive scene understanding purposes, we extend our model for heading estimation. The improved ground truth and proposed model is available at Github
IMPLEMENTATION OF SMART IRRIGATION SYSTEM ON CARROT PLANTATION USING INTERNET OF THINGS

Agriculture is one of the main sectors in Karo Regency, North Sumatra. One of the commodities produced by farmers in Karo Regency is carrot. The inability of farmers to control soil moisture may cause crop damage to a lack of productivity. This research aims to create a monitoring &amp; control system that is integrated with the website to make it easier for farmers to prevent problems that occur. The method used in the research is the design, installation, monitoring, and deactivation. The results obtained from this research are that farmers can now monitor the field conditions in real-time using a web-based monitoring &amp; control system.
A Survey Paper Based On Image Encryption and Decryption Technique

Abstract: Nowadays multimedia system knowledge protection is changing into important. The coding technique is employed to safeguard multimedia system knowledge. There are completely different techniques wont to defend confidential image knowledge from unauthorized access. during this paper, we've got an inclination to survey existing work that's used entirely completely different techniques for image coding and that we to boot give a general introduction relating to cryptography. Keywords: Encryption, Decryption, Data Encryption Standard (DES), Advanced Encryption Standard(AES), Blowfish, Modified Advanced Encryption Standard(MAES),Rubik’s Cube Algorithm
Supplemental Material for Measurement Invariance Testing Using Confirmatory Factor Analysis and Alignment Optimization: A Tutorial for Transparent Analysis Planning and Reporting

a URL, doi, or other permanent path for accessing the specified information in a public, openaccess repository, and the specified information must be provided in a format that is time-stamped, immutable, and permanent.Qualifying public, open-access repositories are committed to preserving data, materials, and/or registered analysis plans and keeping them publicly accessible via the web in perpetuity.Examples include the Open Science Framework (OSF) and the various Dataverse networks.Hundreds of other qualifying data/materials repositories are listed at http://re3data.org/.Preregistration of an analysis plan must take place via a publicly accessible registry system (e.g., OSF, ClinicalTrials.govor other trial registries in the WHO Registry Network, institutional registration systems).Personal websites and most departmental websites do not qualify as repositories.
THE ROLE AND IMPORTANCE OF DETERMINISTIC COMPUTER SIMULATIONS IN THE DEVELOPMENT OF TECHNICAL CREATIVITY

The deterministic computer simulations (abbr. DSK) are a group of simulation software most often used in the process of technical education. Innovative education based on the introduction of this group of software into the online and offline learning process creates a new work environment conducive to creativity and creativity in humans. This article presents theoretical discussions as well as the place and role of DSK among modern teaching aids.
R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning

Systematicity, i.e., the ability to recombine known parts and rules to form new sequences while reasoning over relational data, is critical to machine intelligence. A model with strong systematicity is able to train on small-scale tasks and generalize to large-scale tasks. In this paper, we propose R5, a relational reasoning framework based on reinforcement learning that reasons over relational graph data and explicitly mines underlying compositional logical rules from observations. R5 has strong systematicity and being robust to noisy data. It consists of a policy value network equipped with Monte Carlo Tree Search to perform recurrent relational prediction and a backtrack rewriting mechanism for rule mining. By alternately applying the two components, R5 progressively learns a set of explicit rules from data and performs explainable and generalizable relation prediction. We conduct extensive evaluations on multiple datasets. Experimental results show that R5 outperforms various embedding-based and rule induction baselines on relation prediction tasks while achieving a high recall rate in discovering ground truth rules.
Web security assessment and strategy optimization based on attack-defense game

Abstract Based on game theory, we analyse the attack-defence process between penetration testers and system defenders related to web vulnerabilities, and we propose a web security assessment and strategy optimisation based on attack-defence games. First, according to the actual process of the network, we build a web attack-defence game model that considers the multiple influence parameters of web vulnerabilities on the profitability of attack and defence. These parameters include the difficulty of vulnerability exploitation and detection, the influence of vulnerability hazards, and the prevalence of vulnerabilities. In addition, we quantify the decision cost and the ability of both attack and defence subjects using the Nash equilibrium principle to obtain the best attack and defence strategies corresponding to the defender. Experiments verified the effectiveness of the model proposed in this paper, focusing on the specific impact of the different capabilities of the two parties and the different decision costs of the benefits. This can not only enhance the penetration success rate of the penetration tester but also allow the system defender to make targeted defence enhancements to the system based on the defence payoff matrix.
Pelatihan English Speaking bagi Siswa dengan Model Pembelajaran Presentation Practice Produce (PPP)

This community service was aimed at improving English speaking ability using learning model of Presentation Practice Produce (PPP) for students of MA Al-Istiqomah Telaga Waru. This community service used learning model that is Presentation, Practice, Product (PPP) using cue response drill technique. Evaluation was conducted by giving speaking test to the participants to know whether or not the target of program is achieved. And to knowing whether this program has running well based on the procedure, observation rubric was also has been filled by the team when the program is in progress. The result of this training could increase students’ speaking ability. Based on the result of speaking test, students’ speaking ability have increased. The result of speaking test as the final evaluation, there are 15 out of 20 students got score ≥ 70 or (77.37%). Thus, it could be said that this program was successful because more than 75% students got target score ≥ 70. This community service could increase students’ motivation and also it became one of the learning model that could be used by English teacher. The response of the audience reveals that the program gave some good advantages for the participants as they have higher motivation in trying to speak in English. The participants also expected that the same program is conducted in the near future.
Pengaruh Media Pembelajaran Powtoon, Disiplin Belajar dan Lingkungan Belajar Terhadap Hasil Belajar Akuntansi Keuangan Dimasa Pandemi Covid-19

This study aims to analyze the effects of PowToon learning media, discipline and learning environment partially or simultaneously with learning learning results. This study uses a quantitative approach with 61 population students. The specified sample method is saturated sampling. Data was collected by a questionnaire. Data analysis with multiple linear regressions. The results of the survey conclude that: (1) The important effect of Powtoon learning media on financial accounting learning outcomes is the result of t count = 3.184&gt; ttable = 2.002. (2) In the result of t count = 2,650&gt; t table = 2,002, the learning outcome of financial accounting has an important influence of learning discipline. (3) In the result of t count = 3.136&gt; t table = 2.002, the learning outcome of financial accounting has a great influence on the learning environment. (4) Powtoon learning media, learning discipline, and learning environment have a great influence on the learning outcomes of financial accounting, as well as the results of Fcount&gt; Ftable, ie 4.908&gt; 2.76.
Intelligent Control System of Unmanned Vehicle Based on CAN Controller

In order to enable the driverless vehicle formation controller to automatically control the driving of the fleet, an intelligent driverless vehicle control system based on the CAN controller is proposed. Expansion convolution of different expansion rates is used to obtain multi-scale target information and to fuse the feature information at different scales during upsampling to enrich the semantic information. Finally, the driverless CAN bus communication platform was established, the driverless monitoring interface was developed, and the software program was written; experiments on the steering control, speed control, voltage, current, speed, and angular speed acquisition, respectively, were performed. The experimental results show that the average semantic segmentation accuracy of the obstacles in concentrated vehicles, pedestrians, and bicycles reached 84.6%, and the detection and segmentation accuracy of the models was good. Therefore, the unmanned intelligent vehicle control system designed in this paper can meet the performance requirements of the vehicle control. No matter whether the given desired path is a straight line or a curve, the unmanned car can complete the path tracking control quickly, stably, and accurately.
User Expectation and Benefits of Implementing Artificial Intelligence in the UAE Energy Sector

Abstract Energy is one of the most fundamental elements to drive economic development. Therefore, it is a significant element of the economic development of UAE. United Arab Emirates (UAE) is keen to exploit the benefits of AI to deliver clean, secure, affordable energy. Thus this paper studied the benefits and user expectations if AI is adopted in the energy sector. This was achieved through a questionnaire amongst the personnel working in the energy sector. From the analysis of 350 completed questionnaire form, this was found that “AI able to increase employees’ job performance”; “AI able to improve the customer retention” and “AI bring positive impact to the organization” are three significant benefits of AI implementation in energy sector. Similarly, “Using AI Technology fits well with the way I work”, “Interacting with AI Technology is often frustrating” and “Assistance is available if facing difficulty using AI Technology” are three major expectations of the users. Further, the difference of the opinions amongst the respondent groups with different level of working experience and working positions was presented based on comparing means. The findings of this study will encourage the practitioners to implement AI in energy sector. This will also enhance the performance of the energy sector.
Pelatihan Penulisan Artikel Ilmiah untuk Meningkatkan Kompetensi Profesional Guru SMA Negeri 2 Merauke Provinsi Papua

The aims of this community service is to improve teachers’ professional competence through training for writing scientific article and classroom action research. The method used was training method with online and offline form. This training was done on September until November 2021. The target was the teachers of Senior High School 2 Merauke province Papua. There were some steps of this community service namely observation, giving material, and monitoring to know the progress of the program. After that training was done, the participants were give the questionnaires that consisted of ten statements. Based on the result of questionnaires, the teachers of Senior High School 2 Merauke gave positive responses namely the responses on very good, good, and neutral category. The result showed that the training can help the teachers in doing classroom action research and scientific research, improving the motivation in writing, helping the job, and improving the professional competency of the teacher.
The Relationship between Indonesia Language Learning and the Environment

The environment is one component that is very influential as a supporter of student success in the teaching and learning process at school. Schools with a clean environment will make students learn comfortably and vice versa. However, our level of awareness of the importance of the environment is still very minimal. Teachers as educators play an important role in teaching environmental education and raise awareness of students about the environment.
Semantics Convolutional Neural Network for Medical Images Analysis

Big Data Analysis is a solution that makes it possible to extract valuable information from the mass of data by using deep learning algorithms and especially the Convolutional Neural Network algorithm. In this article, we have proposed an approach that allows the addition of the semantic aspect in the classification layer of the Convolutional Neural Network algorithm. The proposed approach helps medical professionals to develop an automatic system for identifying various classes of lung cancers. First, the input data are processed to reduce the search space, and the image noise, and normalize data. Then, the preprocessed data are analyzed to reduce image space by preserving all important features. After that, the semantic memory method converts the feature vectors from the analysis layer into semantic feature vectors. Finally, the last layer classifies the input image into two classes. We evaluate our approach using the LUNA16 dataset. Our study led to better results and predictions by reducing false negatives and positives using the Semantic Convolutional Neural Network algorithm. In our approach, cancer tissues can be identified with a maximum of 97.27% for accuracy and 99.46% for AUC. This model has increased efficiency compared with state-of-the-art approaches.
Testing Learning Media for English Learning Applications Using BlackBox Testing Based on Equivalence Partitions

Some testings or testings of an application are very important. So that an application can appear to be running properly or there are still errors in its use. Which later can be improved optimally. In this test, the black box testing technique was used as a test. Black box testing is a system for testing an application by looking at the menu whether it is following what is desired or still needs improvement. The application that will be tested is the Duolingo application which on the play store gets a high rating and is used by more than 12 million smartphone users. The type of testing of the method used, namely the black box, varies, but one of the methods used here is Equivalence Partitions. The Equivalence Partitions technique is a test based on entering data on each form of the system or application used. In each menu, input data on each form will be tested and carried out based on its function, whether it is valid or not. So that by doing this testing the application is getting better and the application must be of good quality according to their respective functions. So that many smartphone users who want to use the application make it easy to use it&lt;p&gt; &lt;/p&gt;