Reviewerly/exHarmony huggingface dataset:
Machine learning for the diagnosis of malaria: a pilot study of transfer learning techniques

Despite being treatable and preventable, malaria continues to affect millions of people worldwide. A major hindrance to the disease’s eradication is difficulty with testing, and attempts have already been made to shift towards more automated testing methods rather than older testing technologies such as light microscopy and rapid diagnostic tests. Machine learning models have shown promise in diagnosing malaria, but prior machine learning algorithms have been contingent upon the availability of clean and relevant data. Furthermore, there are multiple species of malaria that may require different treatments, often resulting in fewer comparative images of individual malarial subtypes on blood slides of a given patient population. In this pilot study, we tested a machine learning technique called transfer learning to reduce the error caused by lesser amounts of available data. By training the algorithm on a known (but not necessarily related) dataset and then re-training on malaria datasets, we were able to significantly increase diagnostic accuracy. Specifically, using transfer learning to prepare the algorithm on a completely unrelated database before applying to malaria slide interpretation, our diagnostic accuracy improved from 65.5% to 80.7% in a small dataset of malaria blood slides, and from 95.5% to 98.0% in a much larger malarial dataset. Moving forward, these types of experiments will help develop a smartphone application to increase the opportunity to diagnose malaria in places where resources are too limited to permit standard diagnostic techniques.
A Statistical Comparison of the Simultaneous Attack/ Persistent Pursuit Theory Against Current Methods in Counterterrorism Using a Stochastic Model

Though current strategies in counterterrorism are somewhat effective, various counterinsurgency theorists have raised doubts about the true efficacy of current methods. Established current strategies are fundamentally flawed, with an overemphasis on eliminating leaders and highly connected agents. Colonel Derek Jones, a counterinsurgency theorist, proposed the Simultaneous Attack/Persistent Pursuit (SAPP) Theory as a superior alternative to current methods. In this strategy, attacks are conducted equally across all fronts of a clandestine intelligence network, from which connections are pursued with further attacks. To determine whether current methods are more or less effective in counterterrorism than the method proposed by the SAPP Theory, a stochastic computational model was developed to represent a traditional eastern clandestine network for an isolated sub-cell of a terrorist organization. Attacks were modeled through the loss of agents within specific components of the network. After an analysis of relevant literature discussing the efficacy of current methods in counterterrorism, we hypothesized that the SAPP model would lead to a greater reduction in the number of terrorist attacks than other methods. We simulated five attack strategies, with each strategy being simulated for thirty trials, and the resulting final number of attacks of the terrorist network was recorded. Through four two-sample t-tests comparing each of the four non SAPP strategies to the SAPP model, we concluded that the SAPP model was significantly more effective in reducing the final number of terrorist attacks. This demonstrates the comparative advantage of utilizing the SAPP model, which may prove to be critical in future efforts in counterterrorism.
Wireless Technology: Transformation from 1G to 5G and Beyond

Abstract: This research paper explores the evolution of wireless technology from 1G to 5G and provides insights into the potential of 6G technology. It discusses the historical significance of each generation, their technological features, and their impact on various aspects of our lives. Furthermore, the paper delves into the applications of 5G in fields such as IoT, healthcare, smart cities, vehicular networks, and agriculture. It concludes by offering a glimpse into the future of wireless communication with 6G, emphasizing its capacity to transform healthcare, communication, and extended reality. The research anticipates that 6G will usher in an era of limitless wireless connectivity.
Kannada to English Agricultural Cross-Lingual Retrieval: Enhancing Knowledge Access in Farming Practices

Abstract: This paper presents the development and implementation of a specialized cross-lingual information retrieval system tailored for agriculture-related queries in the Kannada language. The primary objective of the system is to facilitate accurate translation of Kannada queries into English, the target language, and to retrieve relevant documents containing vital agricultural information. The proposed system addresses key challenges including incorporating effective query preprocessing techniques, designing an efficient document retrieval mechanism, and establishing optimal data indexing strategies as well as strategies have been introduced to mitigate the challenges posed by the diversity of Kannada dialects. By overcoming the language barrier, this system enables seamless and effective knowledge dissemination in the agriculture domain.
Implementation of Holt-Winter Exponential Smoothing Method to Forecast The Spread of Covid-19

This research examines the Holt winters exponential smoothing method to solve forecasting problems using case studies of the spread of Covid-19. The data source uses the transmission of Covid-19 in Indonesia. MAPE is used to measure errors in data forecasting. The results are structured to serve as a recommendation for other researchers in choosing a method for predicting the spread of the disease. Based on the results, forecasting with the Holt-Winters model in positive cases produces a MAPE value of 9.21% using the Multiplicative model and the best parameter values of alpha, beta and gamma (0.4, 0.05, 0.25). Whereas in the case of human recovery, the MAPE value was 11.86% using the Multiplicative model and the best values for the parameters alpha, beta and gamma (0.4, 0.03, 0.1). And in the case of death it produces a MAPE of 17.97% using the Multiplicative model and the parameter values alpha, beta and gamma (0.4, 0.01, 0.1). So, it can be concluded that the Holt-Winters method on human positive case data shows a good outcome performance while recovered and deceased cases produce a well-being analysis performance.
COBIT 2019 Implementation for Enhancing IT Governance in Educational Institutions

This study explores the application of COBIT 2019 in assessing IT governance at Yayasan Bunda Hati Kudus, a prominent educational institution. The research uses the Planning, Field Work, Reporting, and Follow-Up stages to leverage the Gallegos' framework. Findings reveal that Yayasan Bunda Hati Kudus operates at IT governance level two, employing COBIT 2019 domains BAI04, BAI05, and BAI11. Notably, the organization faces challenges in implementing IT across campuses, requiring remedies for decentralized systems, operational disruptions, and unmet needs. The study underscores COBIT's efficacy in addressing IT-related challenges and governance implementation. The novelty lies in adapting COBIT 2019 to assess IT governance within an educational context, offering tailored insights for enhancing capability levels and aligning IT strategies with organizational priorities.
The Examination of SQL Queries Efficiency in Chosen IT System

Optimization of SQL queries is an important part of any system using a database. Several different optimization methods have been selected and presented in this article, The research was conducted on the MS SQL database engine. The execution times of SQL queries were carefully examined according to defined criteria, then performance optimization was done, followed by repeated tests to obtain results after the optimization. Finally, the results were compared through which conclusions were drawn.
Comparative analysis of Angular and React development frameworks

This thesis aimed to examine the Angular framework and React library in terms of performance on three popular web browsers. To achieve this, two similar test applications were implemented to create user interfaces, along with a server application for database communication and the aforementioned programming frameworks. Subsequently, tests were conducted to assess the time required for downloading and displaying images, records, and their deletion. In addition to performance results, a literature review was conducted to provide a better understanding of the current state of knowledge in the field, and individual features distinguishing the respective framework or library were described. Furthermore, the obtained data was analyzed for statistical differences using statistical tests.
Pemodelan Proses Bisnis Kuliah Online MOOCs menggunakan BPMN (Studi Kasus alison.com)

Online lectures have been recognized for their existence in independent learning. However, many still don't know the scope of the business process, from the account registration process to taking exams. This article discusses business process modeling using Business Process Modeling Notation (BPMN) in online lectures on the international standard ALISON MOOC models. This research aims to overview the process and business model of MOOC online lectures with ALISON. This type of research is descriptive qualitative, which describes objective conditions based on facts the researcher found in the field. Data is collected through literature study, problem analysis, and business process modeling. This research results in modeling the online college business process at ALISON. The business process elements, from course registration to the exam implementation, are mapped in detail using the BPMN standard. Through modeling using BPMN, the process of creating an account, participant profile, course selection, course registration, learning media, completing assignments and exams, and obtaining a certificate can be described. This article provides helpful information for users interested in business process modeling and its notation in the ALISON online course.
Flood Mitigation Strategy in Banjar City, West Java

The flood disaster that occurred in Banjar City was caused by the high intensity of rainfall in each rainy season. The disaster resulted in considerable material and non-material losses. As a result of these impacts, a flood disaster mitigation strategy is needed in Banjar City. Flood disaster mitigation strategies are needed as a form of effort to reduce and manage the risks posed by floods to human health, economic activities, the environment, and cultural heritage. Therefore, this study aims to create a flood disaster mitigation strategy that can be done in Banjar City. This study uses the Analytic Hierarchy Process (AHP) method which aims to obtain weights and determine the priority scale of flood disaster mitigation strategies used. In using this method there are several principles that must be understood in solving problems with AHP, namely decomposition, comparative judgment, synthsesis of priority and logical consistency.The results of the AHP analysis show that regional regulation policy strategies and their implementation (weight 0.195), policy strategies related to coordination between stakeholders (weight 0.185), policy strategies related to disaster risk assessment (weight 0.129), policy strategies related to disaster management funding (weight 0.170), policy strategies related to increasing stakeholder capacity (weight 0.089), strategies for disaster-resilient communities and facilities and infrastructure (weight 0.089), strategies for improving the quality and quantity of human resources (weight 0.085), and strategies for post-disaster recovery (weight 0.059). Based on the results of the AHP analysis, an inconsistensy ratio of 0.014 &lt; 0.1 was obtained, which means that the results of the analysis can be accepted.
Upper and Lower Bounds for the Height of Proofs in Sequent Calculus for Intuitionistic Logic

Upper and lower bounds for the height of proofs in sequent calculus for intuitionistic logic are proved for the case when cut formulas may only contain essentially positive occurrences of the existential quantifier. The considered cases include both proofs with and proofs without function symbols.
PUBLIC SIGNS IN KOMODO NATIONAL PARK, FLORES-NTT: A LINGUISTIC LANDSCAPE STUDY

This article aims at investigating language/s used in public signs in Taman Nasional Komodo (TNK), Labuan Bajo, Flores-NTT. It was designed as a qualitative study as the data are pictures, words, and sentences found in the public signs in TNK. The data were collected by doing an observation where every single sign found in TNK was photographed by using a Vivo y17 camera. After collecting the data, the data were analyzed by the following steps: data reduction, data display and data verification and conclusion. The result mentions that public signs in TNK divided into two types; they are monolingual and bilingual signs. The monolingual signs confirm that the public signs in TNK just use one language either Indonesian or English. However, bilingual refers to the public signs in TNK using both Indonesian and English for the same public sign. There are nine types of signs applied in TNK public signs. They are signs of place name, place manager, place description, map, history, notice, warning, appeal, and esthetic. Also, the signs have served purposes related to conveying information, representing symbols, and aiding in education.
CLASSIFICATION OF TODDLER’S NUTRITIONAL STATUS USING THE ROUGH SET ALGORITHM

The health and nutrition of children at the age of five are very important aspects in the children’s growth and development. An assessment of the nutritional status of toddlers that is commonly used is anthropometry. This study aims to obtain the decision rules used to classify toddlers into nutritional status groups using the rough set algorithm and determine the level of classification accuracy of the resulting decision rules. The index used in this study is the weight-for-age index. Attributes used in this study were the mother’s education level, mother’s level of knowledge, the status of exclusive breastfeeding, history of illness in the last month, and nutritional status of toddlers. The results of the analysis show that there are 21 decision rules. In this study, the resulting decision rules experience inconsistencies. The selection of decision rules that experience inconsistencies is based on each decision rule’s highest strength value. The rough set algorithm can be used for the classification process with an accuracy rate of 86.36%.
JCI MODELING IN INDONESIA BASED ON INDUSTRIAL PRODUCTION INDEX WITH LOCAL POLYNOMIAL ESTIMATOR APPROACH

The industrial sector is the leading sector that contributes the most to Indonesia's economic growth. Industry can be caused by various factors, one of which is the Jakarta Composite Index (JCI). Indonesian stock prices have a high variance that requires proper modeling. Therefore, this study uses a local polynomial nonparametric regression approach. This study aims to estimate and obtain the best JCI model based on the production index of large and medium industries using a local polynomial estimator and also knowing the accuracy of the JCI model based on the production index of large and medium industries. The data used in this study is secondary data using production index data for medium-large industries and data on the composite stock index in Indonesia in the form of Time series which were obtained through the Central Statistics Agency Publication website on the page www.bps.go.id. JCI modeling in Indonesia based on the production index of large and medium industries is most effective on local polynomials with polynomial degree two which obtains an optimal bandwidth of 7,8795 with a minimum Cross-Validation (CV) value of 163170,3 and a Mean Absolute Percentage Error (MAPE) value of 9,1%. From the MAPE value it is said that the model is good for making future predictions.
Analysis of Radiation Barrier Design in Peat Soil Using NCRP Method No.147 at Murjani Regional Hospital

The use of X-ray aircraft can hurt workers and the community, so they must pay attention to radiation protection aspects such as the design of radiation retaining walls which function to absorb and attenuate the resulting radiation exposure. This research was conducted to analyze the value of radiation exposure from radiology buildings on peat soil using the NCRP method No. 147. In this analysis, the rate of radiation exposure was measured using a Gamma Surveymeter, and the Pb thickness was calculated using the fitting and algebraic methods recommended by NCRP No. 147. Measurement and calculation of Pb are divided into 2 areas, namely controlled areas (Point B, Point C, and Point F) and uncontrolled areas (Point A, Point D, Point E, Point G, and Point H). The results of measurements and calculations from these eight protection points obtained radiation exposure rates in controlled areas at Point B (0.09 ?Sv/hour), Point C (0.04 ?Sv/hour), and Point F (0.03 (?Sv/hour ), and the results of calculating Pb thickness at Point B (0.07 mm), Point C (0.03 mm), and Point F (0.18 mm). Meanwhile, the rate of radiation exposure in uncontrolled areas at Point A (0.480 ?Sv /hour), Point D (0.068 ?Sv/hour), Point E (0.075 ?Sv/hour), Point G (0.41 ?Sv/hour), and Point H (0.45 ?Sv/hour), and the results of Pb thickness calculations at Point A (0.46 mm), Point D (0.08 mm), Point E (0.071 mm), Point G (0.038 mm), and Point H (0.005 mm). Based on these results, the radiation exposure rate value in controlled areas is still within safe limits, and in uncontrolled areas, the rate of radiation exposure that occurs is above the threshold of the dose-limiting value set by NCRP No. 147.
Applications of the SUM integral transform in science and technology

In this paper, the application of the new integral “SUM transfoin the research fields of science and technology is study such as nuclear physics, population growth, electric circuits, pharmacokinetic, beam deflection, Newton’s law of cooling and other fields of mechanics.
Use of English Textism: A Study of the Impact of Text Messaging on the Academic Writing Abilities of University Students

This study aimed to investigate the ramifications of excessive text messaging on the written proficiency of students in their acquisition of a second language. It investigated WhatsApp and other text messaging portals had an influence on students’ written English Language. The popularity of Mobile Instant Messaging (MIM), has given rise to the fabrication of more simplified language terms called “textisms”, which in turn, have impacted their “textiquettes'. A reasonable number of language students from a private university were taken under consideration for conducting the study. The data was collected from each student in three forms: one in the form of students’ rough or during lecture note jotting, other their internal and summative assessments like quizzes and exam papers, third their daily emails. This data was compared against another form of data that was actually the collection of text messages of each student. It provided the researcher with the evidence of recurrent short forms and contractions used by the sample students during texting. The technique of content analysis was employed. The results indicated that text messaging impacted their language usage in informal situations. But, when students were brought to their formal register, they did not deviate from the normal pattern of writing. Mistakes pertaining to spellings and punctuations were plethoric in both the registers. It was also found that they generally got affected by automatic keyboard responses which caused them to forget the actual spellings of words. The text messages assisted students to impart knowledge and information concisely.
Aligning (In)Congruent Chatbot–Employee Empathic Responses with Service-Recovery Contexts for Customer Retention

The use of artificial intelligence (AI) technologies in service recovery is transforming the frontline interfaces across the tourism industry, as AI chatbots are now being designed to show empathy. Using a multi-method approach combining survey, experimental, and field data obtained from hotel guests, this study explores the effects of chatbot–employee collaborative empathic responses on customer retention under various service-recovery contexts. It finds that congruence (vs. incongruence) and higher (vs. lower) levels of congruence in chatbot–employee empathic responses more effectively retain customers. Further, the effects of incongruence and congruence on customer retention diminish when the chatbot’s identity is disclosed but are strengthened when employees’ acceptance of a chatbot increases. Only the negative effects of empathic response incongruence correspondingly increase when chatbot efficiency and flexibility (ambidexterity) increase. These findings suggest that tourism practitioners can rely on chatbot–employee collaboration to accomplish service-recovery tasks but should pay attention to chatbot-side and employee-side uncertainties in a service triad, especially chatbot ambidexterity.
A deep learning-based approach for identifying unresolved questions on Stack Exchange Q &amp;A communities through graph-based communication modelling

Abstract In recent years, online question–answer (Q &amp;A) platforms, such as Stack Exchange (SE), have become increasingly popular for information and knowledge sharing. Despite the vast amount of information available on these platforms, many questions remain unresolved. In this work, we aim to address this issue by proposing a novel approach to identify unresolved questions in SE Q &amp;A communities. Our approach utilises the graph structure of communication formed around a question by users to model the communication network surrounding it. We employ a property graph model and graph neural networks (GNNs), which can effectively capture both the structure of communication and the content of messages exchanged among users. By leveraging the power of graph representation and GNNs, our approach can effectively identify unresolved questions in SE communities. Experimental results on the complete historical data from three distinct Q &amp;A communities demonstrate the superiority of our proposed approach over baseline methods that only consider the content of questions. Finally, our work represents a first but important step towards better understanding the factors that can affect questions becoming and remaining unresolved in SE communities.