Reviewerly/exHarmony huggingface dataset:
Poetry as a valuable tool for awareness creation on plastic waste management in Nigeria

The demand for plastic products is on the rise with increasing demand in different sectors of human society. This amounts to the generation of plastic waste globally at an alarming rate thereby leading to plastic pollution. This study identified that plastic pollution is one of the challenges plaguing the universe status quo with more than estimated eighty million tons of plastic-related wastes being released into the sea annually. Plastic pollution affects the health, socio-economic and agricultural sectors in Nigeria in a profound way. This study further identified the great need for proper plastic waste management strategies in order to enhance public health in Nigeria. It recommended the innovative tools of poetry, music and educational blogs among others for use in plastic pollution education for sustainable development in Nigeria. This study issued a clarion call for more intensive research on the innovative use of poetry for awareness creation on plastic waste management in Nigeria. It concluded by highlighting the need for greater international collaborations and partnerships in finding a sustainable solution to the global menace.
POLITENESS IN VERBAL COMMUNICATION AMONG MALAYSIAN SOCIETY BASED ON LEECH’S PRINCIPLE OF POLITENESS

Politeness in verbal communication is important for harmony in a country especially Malaysia which consists of a variety of races, ethnicities, and religions. However, the impoliteness in verbal communication among the members of the community is increasingly worrying until it becomes trending in nowadays communication. The use of impolite language, dialects, and cursing has destroyed the culture of politeness in verbal communication which is a very significant element in the growth and development of a society as an expresser of philosophy, knowledge, and thinking as well as a tool for human creativity in various fields of life. Thus, language should be put in an appropriate place in the context of developing and consolidating a civilized society. In the context of Malaysian society, politeness in verbal communication is emphasized as a reflection of Malaysian society. Accordingly, this study aims to identify the maxims of politeness in verbal communication among the Malaysian community as well as the relationship between Leech's Principles of Politeness and the socio-culture society in Malaysia. The research method is quantitative and involves primary data collection through a survey of 272 youths among the Malays, Chinese, and Indian communities around the Klang Valley. The findings revealed that there is politeness in verbal communication in the maxims of politeness, kindness, and polite maxims and consent in Malaysian society. Leech’s Principles of Politeness proves that all three maxims have successfully unified various ethnicities that reflect the identity of Malaysian society. Hence, this study can be used as a reference for politeness in verbal communication which is very significant in multi-ethnic society in Malaysia.
FACTORS AFFECTING USE E-LEARNING IN THE LEARNNING PROCESS AT HASANUDDIN UNIVERSITY OF MAKASSAR

The development of an increasingly rapid era, especially in the field of information and communication technologies has penetrated in every joint of human life, especially in the world of education. Information and communication technologies themselves can provide online learning facilities, one example is e-learning. This study aims to determine the effect of perceived ease of use, perceived usefulness, subjective norms, and self-efficacy on the use of e-learning. The object of this research is a lecturer at Hasanuddin University. This research was conducted by distributing questionnaires to the respondents and then the results of the research were analyzed using PLS.&#x0D; The results of this study indicate that perceived ease of use, perceived usefulness, and subjective norms have a significant effect on the use of e-learning. This study implies that lecturers feel unsure in using e learning
E-Book dengan Memanfaatkan Flipbook Maker sebagai Multimedia pada Pembelajaran Berbasis E-Newspaper Literacy dalam Mengoptimalkan Critical Thinking Skills di Perguruan Tinggi

It is necessary to provide ebooks as textbooks for the Introduction to Accounting course which is a learning medium to accommodate the diverse characteristics of students and is equipped with cases according to students' real lives in order to optimize their Critical Thinking. So that research was carried out in 2021, which produced an ebook with Flipbook Maker Based on E_Newspaper Literacy in Optimizing Critical Thinking for students in Higher Education which is valid and practical in the Introduction to Accounting course. To continue the 2021 research phase, it is necessary to carry out research in 2022 as a follow-up stage, namely the Assessment Phase, which is the stage of implementation and evaluation of the Ebook with Flipbook Maker that has been produced. Research activities in 2022 are assessing the success of using ebooks with E_Newspaper Literacy-based Flipbook Maker in improving students' critical thinking through action research. This classroom action research aims to implement an Ebook using a Flipbook Maker Based on E_Newspaper Literacy through the Case Method in an Introduction to Accounting class with 25 students. The successful use of Ebooks can be seen from the achievement of students' critical thinking skills which have exceeded the set target of ≥ 60%.
Ant Colony Optimization with Pre-exploration of Outliers for TSP

Constructing a finite set of candidates for each node has been proved that it is an effective means in ant colony optimization (ACO) for solving the travelling salesman problem (TSP). However, some neighbor nodes in the optimal routes are two nodes with large separation distance. To solve this problem, this paper proposes an ACO with pre-exploration of outliers (ACO-EO). The techniques in ACO-EO include: a) the outliers selection, b) pre-exploration adjacent nodes for outliers. To verify the effectiveness of the ACO-EO, a number of experiments are conducted using 30 benchmark instances (ranging from 101 nodes to 1784 nodes in topologies) taken from the well-known TSPLIB. From the comparison with state-of-the-art ACO-based methods, ACO-EO outperforms these competitors in terms of convergence and solution accurancy.
Benchmarking State-of-the-art DIRECT-type Methods on the BBOB Noiseless Testbed

In recent years, there has been significant progress in the development of new DIRECT-type algorithms for black-box optimization problems. In this paper, we evaluate three well-performing DIRECT-type methods from a recent extensive numerical study on the BBOB noiseless testbed in dimensions 2, 3, 5, 10, and 20. We discuss the strengths and weaknesses of these algorithms on different classes of functions and provide a comparison with the original DIRECT method, as well as with three other well-established methods: RL-SHADE, L-BFGS-B, and SLSQP.
Registration and follow-up of people with suspected COVID-19 by means of mobile applications: A mapping study

In December 2020 will be two years since the firstcase of COVID-19 was reported by the OMS. Many strategies andpolicies of isolation and social distancing have been put in placearound the world since this event to avoid contagion. At the sametime, many mobile applications started to develop to register andtrace people with suspected coronavirus in order to avoid the chainof COVID-19 infections. In this work we propose a systematicreview of mobile applications to registration and tracing of peoplewith suspected coronavirus. To develop this research, threecitation databases were used: Scopus, Web of Science and PudMed.Sixteen articles have been identified proposing the implementationof this type of applications, which were validated in differentcommunities and/or regions. The main results obtained was first-hand knowledge of the reality of how the COVID-19 diseaseexpands, evolves and is registered. On the one hand, theseapplications offer a solution that allows social contact with adultsand young people, on the other hand, they could guarantee quickand timely action for decision making. Those types of applicationscan be considered as a real-time population health surveillancesystem, with this approach would have the ability to convert datainto usable information to initiate appropriate and localized publichealth actions in a community and/or institution that are trying toavoid the chain of COVID-19 contagions.
Using the band ratio approach, FULL-PIXEL (SAM and SFF) and SUB-PIXEL (MF and SID) methodologies to discover areas with alteration using the Aster sensor: a case study in north westen Iran - Sivardaghi Area

ASTER sensor data is among the most potent satellite data accessible for doing geological investigations, with images for the whole earth's surface. In order to test the capability of this sensor to detect places with geochemical alterations, photographs of Mount Seiver Daghi in the western Iranian province of Samal were utilized in this study. This region, which comprises of magmatic and volcanic terrain, is part of the Arsbaran territory and is covered by intrusive masses with alluvial and sedimentary deposits. To conduct this study, an ASTER measuring frame was utilized, which, after performing atmospheric corrections using the internal average relative reflectance (IARR) method of false color composite images and principal component analysis (PCA), was able to differentiate between different lithological units using the Band assignment method, full-pixel methods of spectral angle mapper (SAM) and base spectrum algorithm of spectral feature fitting (SFF) as well as sub-pixel methods of matched filtering. The study demonstrates that the approach of principal component analysis and false color composition is efficient for distinguishing sedimentary rock units from igneous rock units, and its application is suggested for the designated rock units. Due to the lack of spectral characteristics of feldspars and quartz in the short infrared wavelength range, the basic spectrum methods utilized in this work are incapable of identifying such minerals. It is not advised to use these algorithms to distinguish between various magmatic units.
Mueller transform matrix neural network for underwater polarimetric dehazing imaging

Polarization dehazing imaging has been used to restore images degraded by scattering media, particularly in turbid water environments. While learning-based approaches have shown promise in improving the performance of underwater polarimetric dehazing, most current networks rely heavily on data-driven techniques without consideration of physics principles or real physical processes. This work proposes, what we believe to be, a novel Mueller transform matrix network (MTM-Net) for underwater polarimetric image recovery that considers the physical dehazing model adopting the Mueller matrix method, significantly improving the recovery performance. The network is trained with a loss function that combines content and pixel losses to facilitate detail recovery, and is sped up with the inverse residuals and channel attention structure without decreasing image recovery quality. A series of ablation experiment results and comparative tests confirm the performance of this method with a better recovery effect than other methods. These results provide deeper understanding of underwater polarimetric dehazing imaging and further expand the functionality of polarimetric dehazing method.
She is an Expert in this Research Field: The Signal of Recent Publications' Relevance

Assessing the expertise of researchers has garnered increased interest recently. This heightened focus arises from the growing emphasis on interdisciplinary science and the subsequent need to form expert teams. When forming these teams, the coordinators need to assess expertise in fields that are often very different from theirs. The conventional reliance on signals of success, prestige, and academic impact can unintentionally perpetuate biases within the assessment process. This traditional approach favors senior researchers and those affiliated with prestigious institutions, potentially overlooking talented individuals from underrepresented backgrounds or institutions. This paper addresses the challenge of determining expertise by proposing a methodology that leverages the relevance of a researcher's recent publication track to the proposed research as a "sensemaking" signal. We introduce a novel {\em $\alpha-$relevance} metric between the trained embedding over the titles and abstracts of a researcher's recent publications and the embedding of a call and show that high values of {\em $\alpha-$relevance} indicate expertise in the field of the call. By evaluating the {\em $\alpha-$relevance} threshold, we establish a robust framework for the assessment process. For the evaluation process, we use (1) NIH grant-winning records and researchers' publications obtained from Scopus and (2) grant submissions dataset from a research university and the corresponding researchers' publications. Additionally, we investigate the optimal time window required to capture the researcher's expertise based on their publication timeline. Considering the temporal relationship between grant winnings and publications, we identify the most informative time window reflecting the researcher's relevant contributions. The data-driven methodology transcends traditional signals of success, promoting a fair evaluation process of the researcher's relevance to the proposed research. By leveraging objective indicators, we aim to facilitate the formation of expert teams across disciplines while mitigating biases in assessing expertise.
Development of Flipbook Maker-Based E-Module in Economics Subjects to Improve Students’ Interest in Learning

The background of this research is the lack of student interest in learning in economics subjects. This study aimed to develop a flipbook maker-based e-module in economics subjects tested from the level of validity, practicality, and effectiveness in improving students’ interest in learning. This research method was research and development (RD). The data used in this study consisted of quantitative data (question scores of material experts, media experts, linguists, educators, and students) and qualitative data (validators’ comments on the product developed). The instruments used in data collection consisted of validation sheets, teacher and student response questionnaires, as well as learning interest questionnaires. The results showed that: the development of a flipbook maker based e-module on economics subject which refers to the Borg and Gall model modified by Sugiyono consisted of ten steps; the validity level of flipbook maker-based e-modules in economics subjects was categorized as valid; the practicality level of flipbook maker-based e-modules in economics subjects was categorized as practical; and the level of effectiveness of flipbook maker based e-modules in economics subjects was categorized as effective in improving student interest in learning.
The Alienation Experienced by Bruno &amp; Shmuel in The Boy in the Striped Pajamas by John Boyne

Alienation is described as encompassing individual psychological states and types of social relationships. In the context of this study, individuals experience profound feelings of disconnection and estrangement (Kalekin-Fishman, 1998). The objective of this research was to elucidate the diverse causes of alienation depicted in the novel "The Boy in the Striped Pajamas." Analyzing the reasons for alienation in this literary work could provide deeper insights into how war and human atrocities impact an individual's mental well-being. It also contributed to a more comprehensive understanding of the theme of alienation in literary research. The research employed a literature study approach with a psychological perspective, drawing on Erich Fromm's concept of alienation. The primary data source for this study was the novel "The Boy in the Striped Pajamas" by John Boyne, focusing on character dialogues and the author's narration within the story units. The novel, published on 5 January 2006, consists of 216 pages. To analyze the data, the researcher collected, reviewed, identified, organized, and drew conclusions from the gathered information. The findings of this research reveal various causes of alienation present in the characters of Bruno and Shmuel in the novel. These causes included alienation arising from interactions with other people, alienation resulting from societal factors, and alienation stemming from internal struggles within themselves. The exploration of these aspects shed light on the complex psychological impacts of alienation amidst the backdrop of war and its atrocities in the narrative of "The Boy in the Striped Pajamas.
The development of cultural integrated Indonesian speaking e-module for higher education students in Indonesia

The importance of language proficiency, particularly speaking skill competence, has been acknowledged in the field of education for many years. However, despite numerous efforts to improve it, the achievement of student speaking skill competence is still far from the expected target. One of the main reasons behind this problem is the availability, accessibility, and validity of the teaching materials used. This study aimed to address the issue of unsatisfactory Indonesian students’ speaking abilities, which are partly attributed to the lack of available teaching media, particularly those that integrate cultural values. Therefore, this research used research and development study of a speaking skill e-module that is integrated with cultural values that was developed in an Android-based device. The module was designed for university students in South Sulawesi, Indonesia. The results of the study indicated that the use of the speaking e-module helped improve students' speaking abilities, as well as their understanding of cultural values. Therefore, this research is also expected to reach the potential to be beneficial to a wider audience in Indonesia, beyond the scope of South Sulawesi universities.
Implementation of The Direct Reading Thinking Activity Model on The Short Story Reading Skills of Fourth Grade Students at Elementary School

This study aimed to analyze the implementation of the direct reading thinking activity (DRTA) in the short story reading skills of fourth grade elementary school students. This research uses a qualitative approach with a descriptive research type. Data collected by interview, observation, and documentation. The results showed that the implementation of the direct reading thinking activity (DRTA) model was carried out through three stages, namely pre-reading activities, reading activities and post-reading activities. In pre-reading activities, the teacher provides a stimulus by showing pictures and giving clues to the title of short story, so that students can be directly oriented in predicting. In reading activities, the teacher gives freedom to students to read the text and begins to equate with the results of student predictions. In post-reading activities the teacher gives freedom to students to convey the results of predictions about the contents of short story that have been made orally.
Magnetic Resonance Image Super-Resolution via Multi-Resolution Learning

High-resolution magnetic resonance images are of great significance for medical diagnosis.A convolutional neural network with multi-resolution learning is proposed for magnetic resonance image (MR) superresolution.The network is an improved deep residual network, which involves residual units for feature extraction, a deconvolution layer for multi-resolution up-sampling, and a multi-resolution learning layer.The proposed network performs the super-resolution task in the low-resolution space, which can accelerate the network.Multiresolution upsampling is put forward to integrate multiple residual unit information and to accelerate the network.Multi-resolution learning can adaptively determine the contributions of these upsampled high-dimensional feature maps to highresolution MR image reconstruction.Experiment results indicate that the proposed method can achieve a good super-resolution reconstruction performance for magnetic resonance images, which is superior to the state-of-the-art deep learning methods.
TEACHING SPEAKING USING VOICE NOTE TO SECOND SEMESTER STUDENTS-2021A OF STKIP PGRI SIDOARJO

The aims of the study were to describe the implementation of teaching speaking by using Voice Notes; and to describe the student’s perceptions in teaching speaking using Voice Notes for second semester students at STKIP PGRI Sidoarjo. The method used descriptive qualitative. The subjects of this study were the lecturer and the 25 students second semester. The instruments were used Observation Check List, Handphone and Questionnaires. The findings of the implementation of teaching speaking by using Voice Notes for second semester students at STKIP PGRI Sidoarjo were first, Lecturer, distributed text and Voice Note to students thru Voice Note in WhatsApp, then explained to students about text of “A Tour Guide in the Everglades National Park”. Lecturer asked to translate all the text on the home work book, then asked the students to shadow and to follow the native speaker’s voice from Voice Note many times, until comprehended. Lecturer evaluated students’ speaking ability, the results were 32% students who got excellent scores, 52% students who got good scores, one student got average score 8% and students who got poor score 12%. While, the students’ perception results were 78,8% liked the implementation of teaching using Voice Note on the other hand 21,2% didn’t like the implementation of teaching using voice note.
Laser triangular spot positioning combined with cross-correlation and B-spline interpolation

Abstract： Laser triangulation spot location is usually affected by the skewness of the image spot.To im • prove the measurement accuracy and surface adaptability of the laser triangulation displacement sensor by analyzing the skewness characteristics of the laser triangulation spot， this paper proposes a novel spot loca• tion algorithm based on cross-correlation and non-uniform rational B-spline interpolation.First， a filtering method combining time and space domain is adopted for the spot signal to reduce external noise interfer• ence.Subsequently， the calibration spot is matched to perform the cross-correlation operation， and the pix• el-level correlation coefficient distribution is determined by maximizing the grayscale and position similarity
Imprinting or Learning? Charting the Organizational Evolution of Scientific Laboratories

How do scientific laboratories vary in how they operate, and do they change over time? While the study of scientific productivity typically focuses on individual investigators, science and technology studies organizational scholars have pushed us to peer into the operation of scientific labs. To understand how lab models vary among scientific labs across organizations and over time, we compare two competing sets of propositions. Research on organizational imprinting suggests that scientific labs express an organizational model established at time of founding that persists over time. In contrast, research on organizational learning suggests that scientific labs express an organizational model that changes and adapts over time that increasingly differs from its time of founding. Evaluating these competing propositions in the field of academic scientific labs across over 33 American universities, we use a combination of statistical models and machine learning to identify a six-model typology for how labs organize and carry out scientific activity. While we find that while a majority of faculty maintain the same lab model throughout their recorded career, many faculty switch lab models at least once in ways that are patterned across time, by faculty gender, and by initial recorded lab model.