Reviewerly/exHarmony huggingface dataset:
Writing apprehension and writing skills on English department students: A correlational design

By two different types of instruments—a questionnaire to determine students' writing apprehension and a writing test using descriptive texts to decide students' writing skills—this study investigated the correlation between writing apprehension and students' writing skills. This study used quantitative correlational research, and the English department served as the study's target population. Additionally, the researchers employed cluster sampling and correlational design, which can choose a representative sample and represent the population. To conduct the analysis, the researchers chose one class as a sample, and thirty-five students from the third semester were chosen as the sample. According to the researchers, writing apprehension and students' writing skills were shown to be negatively correlated, who concluded that the correlation between the two was r = -0.642. The inverse correlation indicates that students did not perform as good as on writing tests the more frequently they worry about writing. Additionally, it can be inferred that there is a strong correlation between students' writing skills and their level of writing apprehension.
Actor-Network Theory-based Qualitative Research Mthodology for Exploring Educational Phenomena: Meanings and Issues

The transition into posthuman era has called for the departure from humanist and representationalist approaches to qualitative research that provide specific tools to explore educational phenomena. Actor-Network Theory (ANT) has recently been gaining attention as an alternative approach to qualitative research that focuses on various socio-material phenomena emerging as effects of more-than-human entanglements. This article aims to clarify the theoretical and practical meanings of analyzing educational phenomena through ANT as one of posthumanist approaches to qualitative research methodology, and to examine the key issues of utilizing it. This article names ANT-ish approaches to analyzing (educational) heterogeneous phenomena as ‘assembling’ and discusses the ‘post-critical’ aspects and the major methodological characteristics of such approaches. Next, it examines the following issues involved in the process of ‘becoming a (educational) qualitative researcher’ utilizing ANT; researchers’ positionality, ways of data analysis and writing, and validity of ANT-based qualitative research. Finally, the directions are suggested for developing ANT-based qualitative research methodologies (working in practice) to delve into the complexities, dynamics, and ambivalences of certain educational phenomena.
Digital Sociological Review of KP2C in the Use of Whatsapp Groups for Flood Mitigation

KP2C has implemented a flood early warning system through Whatsapp groups since 2016. However, in the areas of Bojong Kulur and Jatirasa, which are the focus of KP2C information and downstream of the Cileungsi and Cikeas rivers, there are still losses for members. The interaction illustrates that achievement of KP2C’s goals has not been maximized, so the meaning of effectiveness is important to explored sociologically with variables thought to be related to it such as the digital divide, social structure’s form, and social capital’s level. This study uses a postpositivism paradigma and survey methods with data qualitative as a support. Respondents in this study were obtained by purposive technique with 40 individuals in RW 24 Bojong Kulur and RW 8 Jatirasa Village as affected areas. The results showed the majority of all variables were dominated by the medium category. Digital divide variable is strongly and positively related to social structure. Both are simultaneously also related to social capital. Therefore, it can be said that if the role of the early warning system is to be effective, then the three variables must clearly be considered.
An Adversarial Dance: Toward an Understanding of Insiders’ Responses to Organizational Information Security Measures

Despite the increased focus on organizational security policies and programs, some employees continue to engage in maladaptive responses to security measures (i.e., behaviors other than those recommended, intended, or prescribed). To help shed light on insiders’ adaptive and maladaptive responses to IS security measures, we conducted a case study of an organization at the forefront of security policy initiatives. Drawing on the beliefs-actions-outcomes (BAO) model to analyze our case data, we uncover a potentially nonvirtuous cycle consisting of security-related beliefs, actions, and outcomes, which we refer to as an “adversarial dance.” Explaining our results, we describe a novel belief framework that identifies four security belief profiles and uncovers an underexplored outcome of IS security: insiders’ lived security experiences. We find that individuals’ unfavorable lived security experiences produce counterproductive security-related beliefs that, in turn, lead to maladaptive behaviors. Maladaptive behaviors create new potential for security risk, leading to increased organizational security measures to counter them. Thus, the adversarial dance continues, as the new security measures have the potential to reinforce counterproductive security-related beliefs about the importance and risk of IS security and lead to new maladaptive behaviors. To help situate our findings within the current security literature, we integrate the results with prior research based on extant theories. While this paper is not the first to suggest that security measures can elicit maladaptive behaviors, the emergent belief framework and expanded BAO model of IS security constitute an important contribution to the behavioral IS security literature.
Combined Detection and Segmentation of Overlapping Erythrocytes in Microscopy Images Using Morphological Image Processing

Segmentation of clusters of erythrocytes into their constituent single cells is a procedure needed in various biomedical applications related to microscopy images. This task is part of the general problem of splitting clumps of objects in images which continues being an open research topic in the Image Processing field. This work presents a unified morphological method to detect and segment clusters of erythrocytes in microscopy images, and proposes two main contributions. The first one is to formulate and evaluate a method to detect clusters as connected components in binary images, obtained from a previous coarse segmentation, which is not capable of further dividing a cluster into its constituent cells. Secondly, to propose the best alternative to split the clusters into their constituent individual cells after evaluating three algorithms based in the combination of the transforms: H-maxima, weighted external distance and marker-controlled watershed. Evaluation of the proposed cluster detection methods was made in terms of standard measures of effectiveness. Segmentation accuracy was evaluated comparing the segmented objects obtained to a manually segmented ground truth, by means of the Jaccard index. Then the Friedman test allowed validating the advantages of the proposed method in comparison to the other alternatives studied here.
Ship Detection and Classification Using Hybrid Optimization Enabled Deep Learning Approach by Remote Sensing Images

The recognition and categorization of ships is very significant for maritime security and defense board. The existing SAR image-oriented ship recognition techniques are not capable of real-time applications since the count of SAR sensors is sparse and the contrast of images is minimum. To cope up with certain issues, this article designs an efficient technique for ship detection and classification by introducing hybrid optimization-based deep learning technique. Here, segmentation is done using bounding box segmentation. The ships on the ocean surface are effectively detected using deep convolutional neural network, where the network is trained utilizing devised exponential mayfly optimization algorithm (EMO). The newly designed EMO is derived by the combination of the exponential weighted moving average (EWMA) and mayfly optimization algorithm (MA). The type of ships is classified effectively utilizing deep residual neural network (DRN) and the network is trained by introducing the proposed political exponential mayfly optimization algorithm (PoEMO).
Searchable Encryption Semantics

After acquiring adequate background knowledge, we are now about to advance to the world of searchable encryption, which has made prosperous progress since its first construction in the early 2000s. Since mainstream designs in searchable encryption focus on symmetric key-based primitives, we will focus on them in this chapter and only briefly discuss other designs when necessary.
Mummy Labels: A Witness to the Use and Processing of Wood in Roman Egypt

Abstract Mummy labels are relics found in large quantities in Egypt, often in an excellent state of preservation (like most woods preserved in arid environments). As a result, they are widespread in Roman Egyptian collections of many museums. These labels reflect funerary practices that possess Egyptian and Roman influences and are an important source of historical and archaeological information. These corpora of mummy labels offer several possibilities for investigation. The inscriptions on these labels have been the subject of an international project (Death on the Nile) in which all accessible objects were recorded in a database. However, the potential of these funerary objects extend beyond the inscriptions to the methods of manufacturing and cutting, the choice of species used, and their dendrochronological potential to better define their chronology and possibly their provenance. The study of mummy labels allows us to propose a new typology, some forms of which seem to be limited to certain necropolises. Mummy labels, whether made by the family of the deceased or by specific workshops, show that their realizations vary greatly, ranging from coarse specimens to others with beautiful detailing. They are made from endemic as well as imported species, which are symbolic of long-distance trade, especially for conifer trees, which are well represented. Their dendrochronological potential has also been demonstrated in numerous studies, some of which have allowed the identification of labels from the same tree, supported by inscriptions attesting to the same family relationship.
Introduction to Freedom of Expression in an Age of Social Media, Misinformation, and Political Polarization

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Effectiveness of Self-Evaluation, Peer Evaluation and 2nd-Step Self-Evaluation- Covering Anchoring Training in Maritime Education and Training

Evaluation is an essential part of education and training, and it can be used in maritime education and training to help learners organize their knowledge and improve their skills, as well as to improve education and training methods. In this study, self-evaluation and mutual evaluation were conducted during anchoring training on the training ship Shioji Maru belonging to the Tokyo University of Marine Science and Technology. In a survey of students trained in 2020 and 2021 regarding the acquisition of knowledge and skills, 94.5% of students rated themselves as “very effective” or “effective” in their self-evaluation and 92.0% of students rated themselves as “very effective” or “effective” in their mutual evaluation. Comparing the self-evaluation scores with the mutual evaluation scores, it was found that the mutual evaluation scores tended to rank higher than the self-evaluation scores. This is thought to be due to a lack of confidence in one’s own ship handling skills, which leads to harsh evaluations of oneself and more lenient evaluations of others. It was also found that the higher the instructor’s evaluation score, the smaller the difference between the self-evaluation score and the instructor’s evaluation score. Students with higher scores in the instructor’s evaluation were more confident in their ship handling skills, which is thought to indicate that they can evaluate themselves more accurately. On the other hand, self-evaluation was conducted at an early stage immediately after the training, and the bridge operation team and the entire team also conducted the self-evaluation again after the debriefing. In other words, a 2nd-step self-evaluation was conducted through two evaluations conducted at different times. We show the results of a qualitative analysis of the students’ impressions and opinions of these self-evaluations and peer evaluation using the steps for coding and theorization (SCAT) method.
REAL TIME SIGN LANGUAGE RECOGNITION USING COMPUTER VISION

A disability that hinders a person's capacity for verbal communication is linguistic impediment.Among the most structured languages is sign language, which would be designed to address this issue.There seems to be undeniably a requirement for a system or software program which can detect sign language gestures, allowing for communication even with individuals who do not understand sign language.A real-time system was developed with the aid of machine learning and image processing.Pre-processing images and eradicating multiple hands from the background are both done via image processing.These images, which were taken after the background was removed, were used to create data that contained the 26 English alphabets.Indeed a customized dataset and spontaneous hand gestures performed by individuals of varied complexion have been employed to evaluate the convolutional neural network that has been proposed here.
Cryptic crossword #100

We have totally misunderstood what causes depression. But, surprisingly, the search for treatments is making good progress, finds Clare Wilson
Alchemical Symbols and Motifs in the Novel by E.T.A. Hoffmann The Golden Pot

The present observations are an attempt at the study of the novel “The Golden Pot” by E. T. A. Hoffmann. The purpose of the article is to propose a possible way of interpreting Hoffmann's work full of symbolism through the prism of alchemical art. Through the juxtaposition of the “Golden Pot” and alchemical symbolism, parallels are sought between the fusion of Anselmus and the Serpentine and the alchemical fusion of the White Queen and the Red King that creates the Philosopher's Stone. The observations are directed, on the one hand, to the overall structure of the novella, as a kind of alchemical opus. Individual elements and symbols that could also be interpreted as alchemical are also sought.
Application of the Literary Concept of “Chronotope” in the Sociological Analyses

The article presents an interdisciplinary theoretical attempt to transfer the concept of chronotope from science of literature into the methodological coordinate of sociological analysis
Are You Ready for the Latest Data Integrity Guidance? Part 1: Scope, Data Governance, and Paper Records

The new PIC/S data guidance document was published in July 2021. The guidance will be reviewed in two parts, starting with the scope, data governance, and paper records.
Arabic Machine Translation: A Panoramic Survey

In a world where linguistic and logical barriers are dissolving and communication must be possible on demand and in a language one is familiar with, Machine Translation (MT) has become essential. This natural language processing sub-field is now the most exciting but also the most difficult topic to solve, as it automates the translation process and decreases the reliance on human translators. Researchers are attempting to translate English into their native language and vice versa, but achieving perfect MT has proven to be a difficult task for researchers all over the world. This paper provides a high-level overview of this subject, reviewing the accomplishments and findings of various MT studies in the context of Arabic language, which is known by its richness and complexity. At the end of the survey, open challenges and issues are discussed. Therefore, this study might be useful for future research and for selecting the best method for a certain purpose
Online Resource Allocation with Noisy Predictions

Brief Biography: Jessica Maghakian is a final-year PhD candidate in Operations Research at Stony Brook University. She has collaborated with several industry partners and interned at Microsoft Research NYC. Jessica's research combines data-driven decision making with traditional online algorithms approaches to solve challenging resource allocation problems that arise in IT infrastructure systems. Her work has been awarded an NSF Graduate Research Fellowship, a Stony Brook University STRIDE Fellowship for excellence in visualization, science communication and decision-support, and a Best Paper Nomination at ACM e-Energy. She received her Bachelors of Science from the Massachusetts Institute of Technology (MIT) with a double major in Mathematics and Brain and Cognitive Sciences.
A Bibliometric Analysis of Research Output from Indian Institutes of Management

Indian Institutes of Management (IIMs) are among the most prestigious business schools in India, mainly offering postgraduate, doctoral and executive education programmes in the fields of Management and Business Education. They also contribute significantly to research in the area. This article attempts to analyse the bibliometric patterns in research output of IIMs. The data for research publications indexed in Scopus during 2010-19 is downloaded and analysed to identify important patterns and trends of research output, citations, international collaboration, open access, gender distribution and social media visibility. The results are also compared with three top internationally renowned business schools (Harvard Business School, MIT Sloan School of Management and NUS Business School). Results indicate that the older IIMs like Ahmedabad and Bangalore are placed at the top in terms of publication counts and citations. Newer IIMs like Rohtak and Raipur are found to be doing well in publications as compared to other IIMs of their generation. IIM Udaipur has more than 40 % of its research output internationally collaborated and also highest citations per paper value amongst all the IIMs. However, when the IIMs are compared with three well-known international schools (two of which have mentored the initial two IIMs), there appears a large gap in several indicators, such as h-index. The paper, thus, indicates that IIMs need to improve their research output and quality to be at par with the top business schools of the world. Research themes like ‘sustainability’, ‘emerging markets’ and ‘supply chain management’ are the most prominent thematic areas observed in the research output from IIMs, which indicates that IIMs are working on research topics of contemporary relevance.
Coastal Batik Motifs Identification Using K-Nearest Neighbor Based on The Grey Level Co-occurrence Method

Indonesia is a country rich in natural, cultural, and tourism resources. One of the famous human cultural heritage in Indonesia is batik. Batik has unique motifs that are very diverse so it is difficult to recognize the in certain classes. This research was conducted to classify coastal batik, especially Tegal batik, Pekalongan batik, and Cirebon batik so that it can help facilitate the introduction and understanding of coastal batik when compared to another batik, such as Yogyakarta batik. The method used is Grey Level Co-occurrence Matrices to extract texture features, while, to determine the proximity of the test image to the training data using the K-Nearest Neighbor method, the calculation of the distance to be used is the Euclidean Distance and Manhattan Distance based on the texture characteristics of the batik image obtained. In this study, the highest score was obtained at 64% for Euclidean Distance and 66% for Manhattan Distance at k=15
H-Classic Papers in Atomic Spectroscopy: An Integrative Literature Review

In this study, we present a methodical qualitative and quantitative analysis of H-Classic publications that have made key contributions and identify intensive mainstream research areas in atomic spectroscopy. The main objective of this study is to determine which publications are cited the most and who contributed to those publications. This study also provides an insight into recent historical developments in atomic spectroscopy, which can be valuable to academic organizations and editorial staff in determining areas and fields of research. This study also creates awareness about the research trends in atomic spectroscopy among research communities, government organizations, and funding bodies.
A distributed and transparent food supply chain management system using blockchain and IoT technologies

The food supply chain is the most crucial supply chain on our planet. Existing food supply chain systems do not investigate features like food origin traceability, timestamps of food processing, a proper money distribution facility among the parties, and a customer feedback evaluation system at the same time. To make the food supply chain more effective, this paper proposes an immutable, distributed, and transparent food supply chain using IoT and blockchain technologies. This paper develops a blockchain system using Raspberry Pi, in which the transaction data is created from the sensors and database data. Three different blockchains are developed for customers, warehouses, and farmers. Customer blockchain is public and anyone can participate in this. Other blockchains are private and require registration for participation. Our experimental results based on sensors and blockchain data show that our proposed scheme improves 96.83% of the existing scheme's time.
RANCANG BANGUN SISTEM MANAJEMEN LAPAK PASAR BERBASIS WEB MOBILE

&lt;p&gt;&lt;em&gt;&lt;span&gt;Wameo Market is one of the traditional markets in Baubau City which plays an important role in promoting economic growth in the Buton Islands region. The existence of the Wameo market is very helpful, not only for the local government but also for the people who depend on trading activities. The management of the tax levy for the use of stalls is often delayed in reporting to the Trade and Industry Office of Baubau City due to the unavailability of a system that manages users of the Wameo market stalls. Therefore we need a system that can overcome these problems. This study aims to create a payment management system for market stall retribution payments electronically. The system development method used in this study is the Waterfall method. This research resulted in a user management application for the Wameo market shanties and the payment of lapak fees. Merchants can make payments with the application provided, so that field officers can easily make reports.&lt;/span&gt;&lt;/em&gt;&lt;/p&gt;