Reviewerly/exHarmony huggingface dataset:
A dual-process account for diverse reasoning strategies underlying symmetries and asymmetries between inferences between disjunctions and conditionals

How people make inferences between disjunctions and conditionals is a current important question that can test mental logic and mental model theories in propositional reasoning. We propose a dual process account that predicts and integrates diverse reasoning strategies in inferences between disjunctions and conditionals. Two experiments revealed that there were obvious individual differences in reasoning strategies, which led to individual differences in reasoning performances. In particular, the syntactic meaning contrast heuristic dominated inferences in general conditions, whereas knowledge modulation heuristics such as contradiction interpretations and prior belief biases dominated inferences in particular conditions. These heuristics trumped the compatibility heuristic and the analytic strategies of mental logic and mental model theories. Competitions among these diverse reasoning strategies led to symmetries and asymmetries between inferences between disjunctions and conditionals. The overall pattern of individual differences in reasoning strategies favors the dual process account over the other accounts. The finding of the diverse reasoning strategies suggests that there is no single reasoning mechanism that underpins all inferences between disjunctions and conditionals.
Voltage - Current Devices with Quantum Circuits

&lt;p&gt;A nonlinear parameterized voltage - current mathematical model, with quantum probabilities to modulate deterministic functions, is discussed. Different possibilities for the model and two electric circuits applications are illustrated with simulations.&lt;/p&gt;
Predictive Model for Emergency Medical Services (EMS) using Machine Learning and Data Mining

Abstract In Emergency Medical Services (EMS), we use Predictive modeling which is basically a statistical technique which anticipates and forecasts future occurrences using machine learning and data mining. Predictive modeling processes current and historical data acquired at a medical treatment using statistical methodologies, data mining, and other techniques. It allows for the formulation of most effective therapeutic regimens personalized for every patient or individual by enhancing client care depending on individual patient data. In the event of hospitalization and emergency care, where quick choices are required, prognostic models are quite useful. The overall purpose of these advanced procedures like regression modeling, parametric modeling and simulation is to improve problem solving, decision making and finding potential for healthcare. In this paper, Data Science and Machine Learning techniques and algorithms are used to create predictive model of the different obtained datasets. As first responders to life-threatening incidents, EMS plays a critical role in raising survival rates. Unbalanced EMS supply-demand distribution in the city, on the other hand, may result in a scarcity of available EMS services and postpone emergency care.
Analysis of Sentiment Analysis Research Trends using Text Mining

&lt;p&gt;Recently, sentiment analysis is actively researched in the field of natural language processing because of the expansion of computer science and social media. However, sentiment analysis has a wide range of applications and it might be challenging for individual researchers to review and comprehend the trends of the studies. Therefore, this study suggests trends in sentiment analysis research to help sentiment analysis researchers. The sources of data collection are Google Scholar and Scopus. As a result, studies using various modalities, researching the change from a particular event and based on language itself have been explored actively in recent years.&lt;/p&gt;
Scalability, Explainability and Performance of Data-Driven Algorithms in Predicting the Remaining Useful Life: A Comprehensive Review

&lt;ul&gt; &lt;li&gt;This work summarizes the state-of-the-art data-driven methods for prediction of the Remaining Useful Life&lt;br&gt; (RUL)&lt;br&gt; &lt;/li&gt; &lt;li&gt;It discusses challenges and open problems faced in PdM&lt;br&gt; &lt;/li&gt; &lt;li&gt;This study presents a discussion on the new problems that need to be considered towards the Industry 4.0 goals&lt;br&gt; &lt;/li&gt; &lt;li&gt;We propose the future direction for each challenge discussed in this article&lt;/li&gt; &lt;/ul&gt;
Attacking Distance-aware Attack: A Semi-targeted Poisoning Attack on Federated Learning

&lt;p&gt;Existing model poisoning attacks on federated learning (FL) assume that an adversary has access to the full data distribution. In reality, an adversary usually has limited prior knowledge about clients' data distributions. In such a case, a poorly chosen target class renders an attack less effective. In particular, we considered a semi-targeted situation where the source class is predetermined but the target class is not. The goal is to cause the global classifier to misclassify data of the source class. Approaches such as label flipping have been adopted to inject poisoned parameters into FL. Nevertheless, it has shown that their performances are usually class-sensitive, varying with different target classes applied. Typically, an attack can become less effective when shifting to a different target class. To overcome this challenge, we propose the Attacking Distance-aware Attack (ADA) that enhances a poisoning attack by finding the optimized target class in the feature space. ADA deduces pair-wise distances between different classes in the latent feature space based on the Fast LAyer gradient MEthod (FLAME). We performed extensive evaluations by varying the factor of attacking frequency in four benchmark image classification tasks. Furthermore, ADA's efficacy was studied under different defense strategies in FL. As a result, ADA succeeded in increasing the poisoning attack performance to 2.8 times in the most challenging case with an attacking frequency of 0.01. ADA bypassed existing defenses where differential privacy that was the most effective defense still could not reduce the attack performance to below 50%.&lt;/p&gt;
English for hospitality training at Warung Pantai Seseh

Beachside restaurant is one of Bali's popular tourism industries right now. One of them is Warung Pantai Seseh, a restaurant and MSME that is located in Seseh Beach, Badung Regency. The primary problem is a lack of English communications skills in the hospitality. To enhance excellent service to tourists, steps to increase English proficiency also are required. Implementation methods used include a pre-test, training, and a post-test which was attended by 11 Warung Pantai Seseh employees. The employees of Warung Pantai Seseh have improved their knowledge and skill in English for hospitality as a result of the community service. Results from the post-test indicate that 81.8% of employees have good English for hospitality skills, with a minimum score of 80.
Training on the use of digital media for implementation digital pharmacy for pharmacist at Salatiga in supporting the industrial revolution 4.0

Today, the health sector has begun to adopt digital information technology, one of which is telemedicine. Utilization of digital media can be used for business interests and support pharmaceutical care activities. However, pharmacists in Salatiga city have not been able to make optimal use of digital media. This activity was carried out in the form of training on the use of digital media for the implementation of digital pharmacy for IAI PC Pharmacists in Salatiga City in facing the era of the industrial revolution 4.0. Activities carried out are training and providing information about digital pharmacy and medication therapy management. This program has proven successful in increasing pharmacist knowledge regarding digital pharmacy and medication therapy management with a p-value of 0.0000. Furthermore, 69 pharmacists experienced an increase in knowledge, 5 pharmacists experienced a decrease, and 7 pharmacists did not experience an increase in knowledge.
Sistem Informasi Berbasis Web Untuk Pemetaan Geografis Lahan Pertanian (Studi Kasus : Desa Darmasari Kecamatan Sikur Lombok Timur)

The potential of agricultural land in Indonesia is still extensive, so the agricultural sector is still one of the incomes for most Indonesians. The agricultural land sector is widespread in various regions in Indonesia, one of which is in Darmasari Village, Sikur District. As an agricultural area, most of the population in Darmasari Village chooses livelihood as farmers. However, the distribution of agricultural land has not been mapped, which can provide information about the location of agricultural land, especially those in Darmasari Village. In this study, a web-based Agricultural Land Geographic Information System was constructed in Darmasari village. The geographic information system that is built can display information in the form of spatial and non-spatial data that describes an object based on the state of the earth. The method used in creating this system is to use the object-oriented method. With the construction of this Geographic Information System, it is hoped that it will be able to provide information for the community about the distribution of the location and area of agricultural land, especially in the Darmasari Village area
Prediction Distribution for Simultaneous Auto-Regressive Model with Multivariate Student-T Error under the Bayesian Approach

Prediction distribution is a basis for predictive inferences applied in many real world situations. The Bayesian approach under uniform prior is employed in this paper to derive the prediction distribution for Simultaneous Auto-regressive model with multivariate Student-t error distribution. Conditional on a set of realized responses, a single and a set of future responses have a univariate and multivariate Student-t distributions respectively, whose degrees of freedom depend on the size of the realized sample and the dimension of the auto-regression parameters' vector but do not depend on the degrees of freedom of the error distribution. Results are identical to those obtained under normal error distribution by a range of statistical approaches such as the normal distribution, autocorrelations and classical methods. This indicates not only the inference robustness with respect to departures from normal error to multivariate Student-t error distributions, but also indicates that the Bayesian approach with uniform prior is competitive with other statistical methods in the derivation of prediction distribution.
Groundwater Vulnerability Assessment Using Modified DRASTIC Index, the Case of Doornfontein Area (Johannesburg)

Groundwater is an essential resource for the domestic, agricultural, and industrial sectors.Nevertheless, groundwater quality has declined due to the increased use of pesticides and industrial effluent being discharged into water systems.This study aims to assess groundwater vulnerability by using the modified DRASTIC model around Doornfontein, Central Business District (CBD) of Johannesburg.Land use types are considered as a model parameter to produce a modified DRASTIC model, where the result varies between 103 and 219 (low to very high, vulnerable zones).Approximately 5.6% of the study area is covered by very high vulnerable zones and distributed in southern region.High, moderate and low vulnerability zone covers the area of 55.3%, 28.8% and 10.3%, respectively.The study uses a nitrate concentration level to validate the accuracy of the model.The correlation analysis between nitrate level and DRASTIC model shows R 2 = 0.548 and significant correlation with the modified DRASTIC model R 2 = 0.56.The single parameter sensitivity analysis reveal that land use, aquifer media, soil media, and topography have a prominent role in assessing vulnerability.The study output shows the area is highly vulnerable to contamination, necessitating the relevant authorities' careful attention and protection of the area's groundwater resources.
A COMPARATIVE STUDY BETWEEN EXTROVERT AND INTROVERT PERSONALITY OF STUDENTS SPEAKING PERFORMANCE OF UNIVERSITAS MUHAMMADIYAH BULUKUMBA

The purpose of this research was to find out the significant difference on speaking performance between extrovert and introvert students at the sixth semester English Department of Universitas Muhammadiyah Bulukumba. The population of this study is one class in sixth semester consisting 26 students at English Department of Universitas Muhammadiyah Bulukumba. And the sample of this research were consist 5 students extrovert and 5 students introvert in 19.A class This research used quantitative approach and the type of this research was a causalcomparative. In collecting the data, the researcher distributed the questionnaire to the respondents in order to determine extrovert and introvert students, which consisted of 30 questions developed from indicators of extrovert and introvert and the questions adopted from Eysenck Personality Inventory. Then, the researcher used oral test to know students speaking performance. The researcher used analysis statistically to analyze the mean score. Then, the result of analysis statistically found that, the mean score of extrovert student is 8,2. And the mean score of introvert students is 4,8. it means that there is a significant difference on students speaking performance between extrovert and introvert students. The result showed that extrovert students outperformed than introvert students in speaking performance. Based on the finding above, it is concluded that speaking performance of extrovert students better than speaking performance of introvert students, in the sixth semseter of English Department of Universitas Muhammadiyah Bulukumba
Scientific, technological and other bases of production processes digitalization

Relevance. “Digital transformation”, “digital twin” and similar terms are media phenomena. However, these and related terms hide meanings, goals, objectives, technologies, prospects and dangers inevitable at the present stage of an industrial society development and transformation into post-industrial and beyond. In literature, digital transformation is usually applied to business management and is not concerned with material production. Research objective is to consider "digitalization" in relation to technical and technological objects of industrial production by the example of a coal mine. Methods of research. In the context of industrial civilization and industrial production, using the methods of system analysis and mathematical modeling, the article considers the development and connection between the processes of automation, digitalization, informatization, and intellectualization. It has been shown that it is possible to preserve and develop industrial production based on its digital transformation, which is based on digital twins that transform the concept of automation. The digital twin, which operates in real time and is synchronized with the simulated production process, is considered as a simulation model of matter and energy transformation processes. The descriptions of a coal mine and its digital twin are considered in a general form. The objectives have been formulated for the optimal production control and its digital twin synchronization. Results. The necessary and critical technologies and possibilities for implementing a digital twin have been identified. The relationship has been shown between the digital transformation of the industry, the objectives of large-scale planning, and the emergence of social problems.
IMPLEMENTASI MEDIA PEMBELAJARAN OPOS UNTUK MENINGKATKAN HASIL BELAJAR TEKNOLOGI INFORMASI DAN KOMUNIKASI KELAS X IIS SMA NEGERI 7 BULUKUMBA

Abstract: Classroom action research is caused by the low quality of information and communication technology guidance results. This is due to the absence of ICT subjects in the structure of the school curriculum that causes students' treatment of ICT subjects to be considered unimportant. The method used is Class Action Research, Kemmis and McTaggart model A cycle-shaped procedure that will take place through two cycles, each cycle consisting of four stages: planning, execution, observation and reflection. The data collection technique used is a test in the form of questionnaires and non-tests in the form of observation of student activities. The study was conducted in class X IIS Sma Negeri 7 Bulukumba from June to December 2021. Research aims to improve the learning outcomes of ICT guidance. The results of the study is implementing OPOS learning media on ICT guidance increased, the average grade of first cycle student learning outcomes by 53.49 percent to 70.30 percent in second cycle. OPOS learning media also increased learning activity, in fist cycle student activity 65.33 percentincreased to 73.33 percent second cycle.
Posyandu cadre training in utilizing information systems to manage elderly medical record data

Posyandu activities for the elderly are carried out regularly in RW 29 and RW 30 Padukuhan Tegalwaras, Sariharjo, Kapanewon Ngaglik, Sleman, Yogyakarta. Bougenvile Posyandu cadres carry out the process of recording medical record data on paper and books. Data that is difficult to read and unsustainable needs to be changed. The aim of this program is to train all posyandu cadres in managing elderly data through a web browser. The implementation method is an analysis of information system needs, counseling related to health information systems, technical training of equipment used, assistance in the use of information systems, monitoring and evaluating the results of all activities by analyzing the ability to use posyandu information systems every month. As a result, on the system there are main menus, namely registration, inspection, print reports, graphics, restore data, user data, my profile, materials, and activities. The existence of an information system for the elderly posyandu is able to increase the knowledge and skills of cadres in managing data using a web-based information system.
Review of Sentiment Analysis: An Hybrid Approach

Sentiment analysis is acknowledged as detecting thoughts used from field content features additionally it's recognized while one linked to the main parts of standpoint extraction. Through this type of process, we will be able to discover if a movie script is positive, negative, or natural. Using this research, a feeling examination is executed along with calvados data. The text message sensation analyzer combines organic and natural language processing (NLP) and even machine studying techniques to provide measured assessment rankings to be able to entities, subjects, themes, and groups in a term or key phrase. Inside expressing feelings, the particular polarity of calvados written content reviews can always be graded for the damaging to good range utilizing the education algorithm. The certain current decade presents seen substantial improvements in artificial brains; along with the device mastering revolution offers converted the complete AI sector. In the end, unit learning techniques include grown to always be an important aspect of any design and style in today's absorbing world. However, this ensemble of researching techniques promises for anyone who is part of motorization using the removal of common regulations for textual written content message and sentiment category activities. This kind of particular thesis has to style and carry out a good superior functionality matrix employing ensemble studying intended for sentiment category while well as software. With this paper, we possess analyzed the well-known techniques adopted within the classical Emotion Analysis problem associated with analyzing Elections evaluations like; Support Vector Machine (SVM) and Linear Regression (LR) for the effective detection of sentiments from the dataset obtained from the Kaggle machine learning repository.
Petrological, Geochemical and Mechanical Characteristics of Kooz Kunarr Khewa Calcite Marble.

This methodical investigation's primary goal is to ascertain the geological, geochemical, mineralogical, and mechanical characteristics of the calcite marble found in Khewa. The article includes all important information about Khewa calcite marble, including its quality, constituent minerals, related elements, and other data. The procedures employed for the precise investigation and evaluation of the mine's characteristics include manipulative field observation, laboratory examination of Khewa calcite marble, and preliminary library studies concerning the research location. The calcite marble library research provided exact and accurate information about the location of the examined area's geology, as well as information about its tectonics and magmatism. In order for the laboratory analysis to determine the true geology of the area under study, including adjacent rocks, and the chemical makeup of the calcite marble, laboratory examination is required. Mica schist is the neighboring rock to calcite marble (a metamorphic rocks).
Study of agricultural finance policy information extraction based on ELECTRA-BiLSTM-CRF

Abstract As China’s agriculture has developed towards modern agriculture, agricultural finance has played a crucial role in promoting China’s rapid agricultural development. Due to the ineffective interpretation of policy support of agricultural finance, poor agricultural areas cannot benefit from the current policy. The purpose of this paper is to propose a model that combines the ELECTRA model with a bi-directional long- and short-term memory network, BiLSTM and conditional random field (CRF) for identifying agricultural finance policy information. The first step is to convert the plain text of agricultural finance policy into word vectors using ELECTRA’s pre-trained language model. By incorporating zigzag character substitution in the generator, the adaptability of the pre-training target to the annotation task on agricultural finance policy is improved. Next, the BiLSTM neural network is used to obtain the contextual abstract features of the serialised text. Finally, the global optimisation sequence decoding annotation is combined with the CRF to extract the structured agricultural finance policy information. The results indicate that the agricultural finance policy information extraction model is more effective than other models in capturing agricultural finance policy information and has excellent information extraction capabilities.
Implementasi Algoritma Naive Bayes Untuk Klasifikasi Penerima Beasiswa (Studi Kasus Universitas Hamzanwadi)

Every year the University offers various types of scholarships to its students, including Hamzanwadi Selong University, East Lombok. One type of scholarship offered is the Bidikmisi scholarship (KIP/K) which is intended for students who have middle to lower economic levels but have good academic achievement or potential. Every year the number of applicants for this scholarship continues to increase, but the number received each year is limited. The large number of piles of files applying for scholarships and the manual selection process tends to be ineffective and efficient and the results of the selection are inaccurate, so a system is needed that is able to assist in the selection process quickly, easily and on target. The method used is CRIS-DM with the Naive Bayes Classifier algorithm modeling, this method is an approach that refers to the Bayes theorem which combines previous knowledge with new knowledge. The variables consist of 7 attributes, namely: Name, DTKS status, achievement, parents' occupation, total income of parents, home ownership, and number of family dependents[1]. Testing was carried out using k-fold cross validation, and the highest accuracy results were obtained from k-fold 4 of 91.43%, while the AUC was 0.996% with a very good diagnostic classification. Thus it can be interpreted that the Naive Bayes algorithm is very well used in the selection of scholarships for bidikmisi scholarships at Hamzanwadi University