Reviewerly/exHarmony huggingface dataset:
Drip Irrigation Cyber-physical System with Remote Control

In today's reality, the pace of people's lives is much higher than it was 30 years ago and it is still growing. At the same time, the amount of information is also growing. This information should be processed constantly, daily, as soon as it is received. Production volumes are not also standing still. Such a lively pace of life requires process consistency and continuity and these processes must be provided by a man.&#x0D; This article describes the system of watering which should automate the process of growing plants. Also, the analysis of a new branch, that is cyber-physical systems, is carried out. The analysis of modern systems of autonomous irrigation, principles of their construction and organization of their work is conducted. A method of implementing a system that provides the possibility of constant monitoring of the growing environment and provides an opportunity to influence it is suggested. The choice of components for system construction is made. The algorithm of the system operation is described. An analysis of the relationship between system components and the user's relationship with the system is performed.
PENGARUH FLIPPED CLASSROOM BERBASIS GAMIFIKASI DAN MOTIVASI BELAJAR TERHADAP HASIL BELAJAR IPA

This study aimed to determine the effect of using a gamification-based flipped classroom on the learning outcomes of fifth-grade elementary school students in science. The method used was a quasi-experimental quantitative research method with a 2x3 factorial design. The research was conducted in two sub-districts in Bandung, namely Coblong and Cibeunying Kaler sub-districts. Samples will be taken by purposive sampling technique. The results showed: 1) the effect of the gamification-based flipped classroom model on the science learning outcomes, 2) there was an influence on student learning outcomes between the gamification-based flipped classroom model for students who had strong learning motivation, 5) there was no effect on learning outcomes students between the gamification-based flipped classroom model for students who had weak learning motivation, 6) there was no interaction between the gamification-based flipped classroom model with motivation on students learning outcomes. There is a need for other studies regarding the gamification-based flipped classroom learning model.
UPAYA PENINGKATAN HASIL BELAJAR BAHASA INDONESIA MATERI KOSAKATA BARU MELALUI MODEL PEMBELAJARAN PBL DENGAN GAMES TOURNAMENTS PADA KELAS 2 SDN JUNREJO 2 BATU

The purpose of this study was to describe the application and improvement of learning outcomes using the Problem Based Learning learning model with Games Tournaments in improving Indonesian learning outcomes for new vocabulary material in class II students at SDN Junrejo 2 Batu. This type of research is classroom action research. This type of research uses a data collection model by means of observation and also uses quantitative data analysis techniques, namely describing the results descriptively. The analysis used to analyze whether data increases students creativity through the PBL learning model with games tournaments. The results showed that there was an effect of using the PBL learning model which was shown form the results of cycle one with an average of 80% having exceeded the KKM limit. With this it can be concluded that the use of PBL model in vocabulary material for Indonesian subjects with games tournaments games in an effort to increase results learning is declared successful has passed the KKM limit.
Pectoral Muscle Removal in Digital Mammograms Using Region Based Standard Otsu Technique

Mammography is usually the first preference of imaging diagnostic modalities used for detection of breast cancer in the early stage. Two projections Cranio Caudal (CC) and Medio-Lateral Oblique (MLO) which depict different degrees for visualizing the breast are used during digital mammogram acquisition and the MLO view shows more breast tissue and Pectoral Muscle (PM) area when compared to CC view. Although, the PM is a criterion used to show proper positioning, it can result in biased results of mammographic analysis like: cancer detection and breast tissue density estimation, because the PM area has similar or even higher intensity than breast tissue and breast lesions if present. This paper proposed a Region Based Standard Otsu thresholding method for the elimination of PM area present in MLO mammograms. The proposed algorithm was implemented using 322 digital mammograms from the Mammographic Image Analysis Society (MIAS) database, and the difference between the PM detected and the manually drawn PM region by an expert was evaluated. The results showed an average: Jaccard Similarity Index, False Positive Rate (FPR) and False Negative Rate (FNR) of 93.2%, 3.54% and 5.68% respectively and also an acceptable rate of 95.65%
Neuro-Fuzzy Combination for Reactive Mobile Robot Navigation: A Survey

Autonomous navigation of mobile robots is a fruitful research area because of the diversity of methods adopted by artificial intelligence. Recently, several works have generally surveyed the methods adopted to solve the path-planning problem of mobile robots. But in this paper, we focus on methods that combine neuro-fuzzy techniques to solve the reactive navigation problem of mobile robots in a previously unknown environment. Based on information sensed locally by an onboard system, these methods aim to design controllers capable of leading a robot to a target and avoiding obstacles encountered in a workspace. Thus, this study explores the neuro-fuzzy methods that have shown their effectiveness in reactive mobile robot navigation to analyze their architectures and discuss the algorithms and metaheuristics adopted in the learning phase.
E-governance and teachers recruitment in Anambra state schools system: The Soludo experience

The study investigated the effectiveness and appropriateness of e-governance practices for public service delivery in Anambra state using the 2022/23 teachers' recruitment exercise conducted by His Excellency, Professor Charles Soludo.It examined whether the e-governance administration of Anambra state teachers' recruitment exercise was adequate and effective; and if e-governance advanced transparency, fairness, and equity during the recruitment exercise.Online survey method, a researcher-structured questionnaire, and a sample of 306 participants derived from a population of 6,120 using Ejifugha (1998) sampling technique were adopted.A systematic sampling method was adopted to collect data from participants while tables and SPSS tool were used to analyse the data.Results of analyses reveal that e-governance practices were adequate and effective for the teachers' recruitment, and that poor network connection together with network crash hindered the process.It further observed that e-governance did not enhance transparency, fairness, and equity due to political, nepotism, and parochial issues.The research among others recommends government intervention and investment in ICTs and e-governance management frameworks, and the re-visitation of the employment exercise using the e-governance generated results for purposes of transparency, fairness, and equity.
Advancements and Challenges in Breast Cancer: A Comprehensive Review

Introduction: Breast cancer is a global health concern, accounting for significant morbidity and mortality among women. The fragile ill prepared healthcare systems in low- &amp; middle-income countries need to address these challenges find solutions with their limited resources. Objectives: Through a critical examination of the literature, this article aims to contribute to a better understanding of breast cancer and to stimulate further research in this field. Methods &amp; Analysis: This review article provides an in-depth analysis of the current state of breast cancer research, focusing on advancements in diagnosis, treatment, and prevention, as well as the challenges and future directions. Conclusion: Emerging technologies, such as AI, 3D bioprinting, and nanotechnology, hold promise for addressing the challenges like management of metastatic disease, global disparities in outcomes, and the need for a better understanding of breast cancer etiology and revolutionizing breast cancer care.
Analisis Kepuasan Driver Terhadap Aplikasi Maxim Menggunakan Metode End User Computing Satisfaction (EUCS)

Maxim is here as a new innovation and as a competitor in the world of online transportation. However, this application has not fully provided service satisfaction to driver partners. This study aims to analyze driver satisfaction with the Maxim application using the End User Computing Satisfaction (EUCS) method. The problem faced is the high level of driver complaints against the Maxim application which has the potential to reduce the quality of online transportation services. This indicates that there is user dissatisfaction with the features available in the Maxim application. Therefore, it is necessary to analyze driver satisfaction with the Maxim application to find out the factors that influence user satisfaction. The EUCS method is used to measure driver satisfaction with the Maxim application using 5 variables, namely content(X1), Accuracy(X2), Format(X3), Ease of use(X4) and Timelines(X5). So that the level of satisfaction (Y) from maxim application users is more measurable, so as to generate input for system developers and developers. This research was conducted by taking a sample of 100 drivers in the city of Palembang by random sampling. The results of the research conducted show that driver satisfaction with the Maxim application is at a fairly good level, with an average satisfaction score of 3.67 out of a scale of 5. With this value, the company needs to improve the development of features related to Maxim application users. The results of this study can be input for the company in improving the quality of the Maxim application service, so that it can meet the needs and satisfaction of its users. So that in the future the Maxim company itself wants to compete with fellow online transportation service entrepreneurs in serving the service users offered.
Raw eye tracking data of healthy adults reading aloud words, pseudowords and numerals

This paper describes data from de Chambrier et al.[1] The dataset [2] contains raw eye tracking data of 36 healthy adults, collected using an EyeLink 1000 (SR Research Ltd., ON, Canada) during an on-screen reading task. Participants read 96 items including words, pseudowords and numerals. Each item was presented at the center of the screen until the participant produced an oral response and pressed the keyboard's space bar. Part of the data were analyzed to extract key metrics such as fixation number, fixation duration, saccade number, and saccade amplitude identified by the EyeLink 1000[1]. Reuse potential includes (but is not limited to) pupil diameter data analysis, identification of fixations and saccades using custom algorithms, and secondary analyses using participant demographics (age, gender) as independent variables.
Modality in News Reports on Public Health Events from the Perspective of Political Discourse Analysis

Since 2020, the Covid-19 epidemic has become a hot issue in the world. Based on the theory of modality combined with political discourse analysis, this study aims to analyze the situation of the prevention and control of the Covid-19 epidemic, to dissect American people’s attitudes towards the epidemic and to discuss the influence of American political system with 30 news reports from the New York Times by the combination of quantitative analysis and qualitative analysis. The findings are as follows. In terms of Modality, modal operators clearly reflect interviewers’ opinions and interviewees’ attitudes. In terms of political institutions, federalism, differences between two parties, and conflicts between them make it a challenge for the United States to surmount Covid-19.
Teaching English in Nepal and its Space in Secondary Level Curriculum

This paper analyzes Nepali Secondary Level Curriculum to identify the spaces of English from 1990 BS to 2079 using descriptive approach. The information was collected using observation check list with the weekly/annual weight age, full marks and credit hours of English. The findings reveal that there ions systematic way of inclusion of English with its weight age and full marks which is found gradually decreasing as compared to the past. The study also shows the space of English was strong at the beginning of the curriculum (1990 BS) till 2028BS in which 200 marks for compulsory English papers were included in the SLC (Secondary) curriculum. The weight age of English is being reduced from 12, 7, 5, 4 period weight age weekly. Currently, the secondary curriculum incorporates agrading system and credit hours since 2016 in SEE. In grade 9-10, students are required to complete 160 annual hours of compulsory English, which carries a weight of 5 credit hours. Additionally, students have the option to take 128 annual working hours of optional English, which carries a weight of 4 credit hours. In grades 11 and 12, compulsory English carries a weight of four credit hours and requires 128 annual working hours, which is comparatively lower than other subjects. However, general subjects such as Shanskrit, Gonpa, and Madarsha offer optional English, which consists of five credit hours and 160 annual working hours.
Analyzing Character Networks in Portuguese-language Literary Works

Literary works are complex narratives with multifaceted character relationships. Studying these relationships can reveal important insights into the story’s structure and each character’s contribution to the plot development. This research investigates character networks in Portuguese-language literature using two main analytical approaches: structural network analysis and character importance metrics. Our analyses emphasize the significance of character networks in understanding the narrative structure of literary works and reveal the intricate interplay between characters in Portuguese-language literature. These findings deepen our comprehension of literary works’ fundamental structure and the characters’ pivotal role in shaping the story.
Optimality Certificates for Classical Planning

Algorithms are usually shown to be correct on paper, but bugs in their implementations can still lead to incorrect results. In the case of classical planning, it is fortunately straightforward to check whether a computed plan is correct. For optimal planning however, plans are additionally required to have minimal cost, which is significantly more difficult to verify. While some domain-specific approaches exists, we lack a general tool to verify optimality for arbitrary problems. We bridge this gap and introduce two approaches based on the principle of certifying algorithms, which provide a computer-verifiable certificate of correctness alongside their answer. We show that both approaches are sound and complete, analyze whether they can be generated and verified efficiently, and show how to apply them to concrete planning algorithms. The experimental evaluation shows that verifying optimality comes with a cost but is still practically feasible. Furthermore it confirms that the tested planner configurations provide optimal plans on the given instances, as all certificates were verified successfully.
Planning with Multiple Action-Cost Estimates

AI Planning require computing the costs of ground actions. While often assumed to be negligible, the run-time of this computation can become a major component in the overall planning run-time. To address this, we introduce planning with multiple action cost estimates, a generalization of classical planning, where action cost can be incrementally determined using multiple estimation procedures, which trade computational effort for increasingly tightening bounds on the exact cost. We then present ACE, a generalized A*, to solve such problems. We provide theoretical guarantees, and extensive experiments that show considerable run-time savings compared to alternatives.
Reducing Redundant Work in Jump Point Search

JPS (Jump Point Search) is a state-of-the-art optimal algorithm for online grid-based pathfinding. Widely used in games and other navigation scenarios, JPS nevertheless can exhibit pathological behaviours which are not well studied: (i) it may repeatedly scan the same area of the map to find successors; (ii) it may generate and expand suboptimal search nodes. In this work, we examine the source of these pathological behaviours, show how they can occur in practice, and propose a purely online approach, called Constrained JPS (CJPS), to tackle them efficiently. Experimental results show that CJPS has low overheads and is often faster than JPS in dynamically changing grid environments: by up to 7x in large game maps and up to 14x in pathological scenarios.
Tracking Progress in Multi-Agent Path Finding (Student Abstract)

In this work, we introduce a set of methodological and visualisation tools to track progress and state-of-the-art performance in the area of Multi-Agent Path Finding (MAPF). Our objectives are to lower the barriers of entry for new researchers and to further promote the study of MAPF.
Multi-Agent Pathfinding with Predefined Paths: To Wait, or Not to Wait, That Is the Question [Extended Abstract]

Multi-agent pathfinding is the task of navigating a set of agents in a shared environment without collisions. Finding an optimal plan is a computationally hard problem, therefore, one may want to sacrifice optimality for faster computation time. In this paper, we present our preliminary work on finding a valid solution using only a predefined path for each agent with the possibility of adding wait actions. This restriction makes some instances unsolvable, however, we show instances where this approach is guaranteed to find a solution.
Multi-Agent Open Framework: Developing a Holistic System to Solve MAPF (Student Abstract)

Automation in industries is becoming an ever-increasing necessity, especially in the sector of logistics. In many cases, this means having many different automated guided vehicles (AGVs) moving at the same time, hence needing coordination to avoid conflicts between different agents. The problem of organizing a fleet of autonomous robots is known as the Multi-Agent Path Finding (MAPF) problem in the literature for which several optimal and sub-optimal algorithms have been proposed. When faced with real-life scenarios, these algorithms must provide the best feasible solution in the shortest time possible, therefore they must scale for large scenarios and be efficient. In this work, we briefly describe our open-source framework we are working on and we lay down the research paths we are going to focus on. The goal is to develop a holistic system that allows to control different aspects of the MAPF problem, from graph topology to goal scheduling.
Analysis Of Peer Group Support and the Learning Environment with Learning Motivation for Nursing Students

Learning motivation is a driving force from within a person to carry out activities including learning in achieving achievement. Motivation to learn can be seen from the results of exams and even from everyday phenomena such as studying only during exams, being sleepy while studying, working together during exams. If that motivation is not increased and instilled in oneself, it can lead to a degradation of enthusiasm, it can even lead to a loss of enthusiasm for learning. The purpose of this study was to analyze the relationship between peer group support and the learning environment with the learning motivation nursing students. The research design used correlation with cross sectional approach. The population and research sample were 93 people using total sampling technique. Data collection is done directly using a questionnaire. Based on the results of the study, the average peer group support is found to be 60.67, standard deviation 6.611, min-max value 37-77, estimate interval 59.31-62.03. Learning environment with a mean of 42.04, standard deviation of 4.147, min-max value of 31-35, estimates interval of 41.18-42.90. Motivation to learn with an average of 67.55, standard deviation 6.470, min-max value 52-80, estimates interval 66.22-68.88. The results of the Pearson product moment statistical test between peer group support and a learning environment with learning motivation found p-values ​​of 0.001 and 0.007, respectively. The correlation value of peer group support and learning environment with positive learning motivation is 0.346 and 0.279, respectively. This means that there is a significant relationship between peer group support and the learning environment with learning motivation and the higher the value of the peer group and learning environment, the greater the score of learning motivation. It is hoped that STIKes Santa Elisabeth Medan will continue to improve peer groups and comfortable infrastructure, away from noise in increasing student motivation to learn.
Predicting and determining antecedent factors of tourist village development using naive bayes and tree algorithm

This study aims to predict the progress status of tourism villages in the Kedung Ombo area, Java, Indonesia, and find the antecedent factors of the progress of tourism villages in Indonesia. This study uses a modern approach, namely data mining. Data sources for tourist villages use the data available on the Google link and the observation method. The prediction technique uses the Naïve Bayes machine learning algorithm and Tree Decision on Orange 3.3.0 software. The number of tourist villages analyzed was 126. The results showed that all tourist villages in the Kedung Ombo area were at the development level of the four tourist village classifications of the Ministry of Tourism and Creative Economy. The antecedent factors for the progress of tourism villages are the completeness of ICT facilities, multi-stakeholder partnerships, strong government support, community involvement, and various attractions. Another finding is that the Tree Decision algorithm provides better predictions than the Naïve Bayes method. The results of this study can be used to design policies for developing tourist villages throughout Indonesia.