Reviewerly/exHarmony huggingface dataset:
The teaching of Thirukkural based on HOTS among the students of Tamil primary schools in the state of Perak

Order Thinking Skills (HOTS) among the teacher of Tamil Primary Schools in the state of Perak and the mastery of questioning technique based on Bloom's Taxonomy using HOTS in the teaching of Thirukkural.The approach of quantitative was employed to obtain the data of the research.80 teachers were chosen as samples from four different schools in Perak to elicit information pertaining to the mastery of HOTS among educators.Through the grading which was conducted by referring to SPSS, the results of the research revealed that the mastery of HOTS among teachers in this category is average and weak from the eight criteria which were studied.This show the efforts that are taken by the Malaysian Ministry of Education provide less impact on the teachers in understanding and mastering HOTS.Meanwhile, a quantitative method was used to understand the mastery questioning techniques of teachers for the HOTS questions.The teaching and learning method of Thirukkural for Year 5 was observed in two schools to elicit data for the mentioned purpose.Interviews were also conducted with two Year 5 Tamil teachers who were observed.The overall findings reveal that 51.3% are able to list out HOTS questions.This is a good scenario in integrating HOTS in students.In conclusion, through this research, it can be said that the teaching and learning of Thirukkural in the classroom can foster the higher order thinking among the students of Tamil Primary Schools excellently.However, it is very much dependant on the questioning techniques of teachers which encourage them towards it.The research findings will benefit educators and agencies involved in implementing the teaching and learning of Thirukkural effectively in fostering HOTS among students.
Library publisher resources: Making publishing approachable, sustainable, and values-driven

The Library Publishing Coalition (LPC) defines library publishing as the “creation, dissemination, and curation of scholarly, creative, and/or educational works” by college and university libraries. While providing a publishing platform, hosting, and services for editorial teams is key to any library publishing initiative, library publishing is also centered on furthering core library values. Thus library publishing activities are mission-driven, centered on education, and focused on finding and promoting sustainable approaches to open access publishing and building cooperative open infrastructure.
Pseudo random oracle of Merkle-Damgård hash functions revisited

Following the well-known random oracle Methodology, a cryptographic hash function is required to satisfy the property of pseudo-random oracle (PRO), that is indifferentiable from a random oracle. This paper revisits the PRO property of popular hash function modes purely from a theoretical point of view. OriginalMerkle-Damgård mode (sometimes referred to as Strengthened Merkle-Damgård) does not satisfy the PRO security due to the length-extension attack. To remedy it, a series of variants have been proposed with tweaks of either adopting a prefix-free padding or modifying the final primitive call. From these tweaks, we derive a common structural property named prefix-free computing. Indeed, all PRO-secure Merkle-Damgård variants published so far are prefix-free computing. Hence, an interesting question with respect to the nature of PRO security arises: is prefix-free computing a necessary condition for PRO-secure Merkle-Damgård hash function? This paper gives a negative answer. We investigate the difference between length-extension resistance and prefix-free computing, and find that length-extension resistance does not necessarily imply prefix-free computing. Consequently, we construct a dedicated Merkle-Damgård variant as a counterexample that is PRO-secure but not prefix-free computing.
A Generalisation of AGM Contraction and Revision to Fragments of First-Order Logic

&#x0D; &#x0D; &#x0D; AGM contraction and revision assume an underlying logic that contains propositional logic. Consequently, this assumption excludes many useful logics such as the Horn fragment of propositional logic and most description logics. Our goal in this paper is to generalise AGM contraction and revision to (near-)arbitrary fragments of classical first-order logic. To this end, we first define a very general logic that captures these fragments. In so doing, we make the modest assumptions that a logic contains conjunction and that information is expressed by closed formulas or sentences. The resulting logic is called first-order conjunctive logic or FC logic for short. We then take as the point of departure the AGM approach of constructing contraction functions through epistemic entrenchment, that is the entrenchment-based contraction. We redefine entrenchment-based contraction in ways that apply to any FC logic, which we call FC contraction. We prove a representation theorem showing its compliance with all the AGM contraction postulates except for the controversial recovery postulate. We also give methods for constructing revision functions through epistemic entrenchment which we call FC revision; which also apply to any FC logic. We show that if the underlying FC logic contains tautologies then FC revision complies with all the AGM revision postulates. Finally, in the context of FC logic, we provide three methods for generating revision functions via a variant of the Levi Identity, which we call contraction, withdrawal and cut generated revision, and explore the notion of revision equivalence. We show that withdrawal and cut generated revision coincide with FC revision and so does contraction generated revision under a finiteness condition.&#x0D; &#x0D; &#x0D;
Implementasi Metode SQ3R dalam Upaya Peningkatan Kemampuan Membaca Pemahaman Pada Mata Pelajaran Bahasa Indonesia Siswa SDN 135 Rejang Lebong

This research is motivated by problems in learning Indonesian. The view of reading is difficult to be embedded in students. The learning process carried out does not provide opportunities for students to develop ideas in developing the potential of reading skills. Classroom Action Research (CAR) consists of 2 cycles, each of which consists of two meetings. The stages in each cycle consist of the stages of planning, implementation, observation or observation, and reflection. The research subjects were fifth grade students of SDN 135 RejangLebong consisting of 23 people in the 2016/2017 school year. In the first cycle student learning outcomes obtained an average of 73.19 and the percentage of classical learning completeness was 69.56%. In cycle II there were no more weaknesses that occurred in cycle I. Learning outcomes in the second cycle obtained an average of 81.69 with a percentage of classical learning completeness 91.30%. This fulfills the completeness criteria, ie 85% of students get a value of ,07.0 and the learning process is said to be completed individually if students get a value of ≥7.
Dynamic cuckoo search algorithm based on Taguchi opposition-based search

The cuckoo search (CS) algorithm is a relatively new, nature-inspired intelligent algorithm that uses a whole updating and evaluation strategy to find solutions for continuous global optimisation problems. Despite its efficiency and wide use, CS suffers from premature convergence and poor balance between exploitation and exploration. These issues result from interference phenomena among dimensions that arise when solving multi-dimension function optimisation problems. To overcome these issues, we proposed an enhanced CS algorithm called dynamic CS with Taguchi opposition-based search (TOB-DCS) that employed two new strategies: Taguchi opposition-based search and dynamic evaluation. The Taguchi search strategy provided random generalised learning based on opposing relationships to enhance the exploration ability of the algorithm. The dynamic evaluation strategy reduced the number of function evaluations, and accelerated the convergence property. For this research, we conducted experiments on 22 classic benchmark functions, including unimodal, multi-modal and shifted test functions. Statistical comparisons of our experimental results showed that the proposed TOB-DCS algorithm made an appropriate trade-off between exploration and exploitation.
Limits and Possibilities of Forgetting in Abstract Argumentation

The topic of forgetting has been extensively studied in the field of knowledge representation and reasoning for many major formalisms. Quite recently it has been introduced to abstract argumentation. However, many already known as well as essential aspects about forgetting like strong persistence or strong invariance have been left unconsidered. We show that forgetting in abstract argumentation cannot be reduced to forgetting in logic programming. In addition, we deal with the more general problem of forgetting whole sets of arguments and show that iterative application of existing operators for single arguments does not necessarily yield a desirable result as it may not produce an informationally economic argumentation framework. As a consequence we provide a systematic and exhaustive study of forgetting desiderata and associated operations adapted to the intrinsics of abstract argumentation. We show the limits and shed light on the possibilities.
Data Sharing Policy for Balkan Medical Journal

In 2004, the International Committee of Medical Journal Editors (ICMJE) announced a statement on clinical trial registration (1).According to the statement, a clinical trial is defined as any research project that prospectively assigns human subjects to intervention or comparison groups to study the cause-and-effect relationship between a medical intervention and a health outcome.Thereafter,
Challenges and Prospects of Commercial Bank Loan Extended to Farmers in Lagelu Local Government of Oyo State, Nigeria

The study investigated the challenges and prospects of commercial bank loan extended to farmers in Lagelu Local Government of Oyo state, Nigeria. The methods used include descriptive statistics, binomial logistic regression analysis with multinomial logit regression. The result of the binomial logistic regression revealed that the variables that determine farm output are age, household size, hired labour, marital status, number of loan applications, amount of loan collected, off-farm income and interest rate on loan. Also, the multinomial logit regression analysis revealed that the variables that determine cassava crop production are hired labour, number of loan application and amount of loan collected, amount of loan collect and off-farm income determine rice production in the study area, interest rate on loan was the only variable that determine potatoes production, household size, and farming experience are the only variables that determine the production of maize in the study area, while farm size determine the output of groundnut production in the study area. The study recommended that since loan is one of the avenues that farmers can increase their farming output which will product the growth of gross domestic product, government agency should instruct commercial banks to direct more loans to agricultural activities. Farmers should not give up in applying for loan because at the end of the day, they will be surely granted and interest rate on loans given to farmers by commercial banks should be lower in other to encourage them to borrow more.
Testing the robustness of final strictness in verse lines

In the field of metrics, it has long been observed that verse lines tend to be more regular or restricted towards the end (Arnold 1905). This has led to the Strict End Hypothesis [SEH], which proposes a general versification principle of universal scope (Hayes 1983). This paper argues that two main challenges hinder the substantiation of the SEH in a broad typological sample of unrelated verse corpora. First, the concept of strictness is too coarse and needs to be narrowed down to testable features or subcomponents. Second, explicit measures need to be developed which enable the systematic comparison of corpora, particularly when trying to capture potentially gradient features such as the relative faithfulness to a metrical template. This study showcases how to overcome these issues by analysing the entropy at different positions in the line for corpora in five languages (English, Dutch, Sanskrit, Estonian, Berber). Finally, I argue that, if the SEH is shown to be typologically robust, shared human cognitive features may provide a partial explanation for this puzzling asymmetry in verse lines.
EXAMINING PEDAGOGICAL CONTENT KNOWLEDGE OF ESP TEACHERS

A prerequisite for successful knowledge transfer is for a teacher to have sound pedagogical content knowledge, i.e. to have understanding of students’ learning abilities, educational context, content and to employ appropriate instructional techniques. The aim of this paper was to study English for Specific Purposes (ESP) teachers’ teaching experience. For that purpose, 47 ESP teachers working at 7 Croatian universities voluntarily participated in an anonymous survey whose results were processed in SPSS. The results indicated that the teachers compile their teaching materials consulting various available resources, but rarely cooperate with their specialized course colleagues despite recognizing the importance and fruitfulness of such cooperation. In spite of feeling less confident about content knowledge, the teachers prepare thoroughly and present content in an appealing and interesting way. Finally, the teachers carry out course evaluations implementing students’ suggestions into their courses, all of which point to the teachers’ carefully considering all elements of the teaching process constantly aiming to improve both their own and students’ performance.
Introduction to Deep Density Models with Latent Variables

This chapter introduces deep density models with latent variables which are based on a greedy layer-wise unsupervised learning algorithm. Each layer of the deep models employs a model that has only one layer of latent variables, such as the Mixtures of Factor Analyzers (MFAs) and the Mixtures of Factor Analyzers with Common Loadings (MCFAs). As the background, MFAs and MCFAs approaches are reviewed. By the comparison between these two approaches, sharing the common loading is more physically meaningful since the common loading is regarded as a kind of feature selection or reduction matrix. Importantly, MCFAs can remarkably reduce the number of free parameters than MFAs. Then the deep models (deep MFAs and deep MCFAs) and their inferences are described, which show that the greedy layer-wise algorithm is an efficient way to learn deep density models and the deep architectures can be much more efficient (sometimes exponentially) than shallow architectures. The performance is evaluated between two shallow models, and two deep models separately on both density estimation and clustering. Furthermore, the deep models are also compared with their shallow counterparts.
Kyrix: Interactive Visual Data Exploration at Scale.

Scalable interactive visual data exploration is crucial in many domains due to increasingly large datasets generated at rapid rates. Details-on-demand provides a useful interaction paradigm for exploring large datasets, where users start at an overview, find regions of interest, zoom in to see detailed views, zoom out and then repeat. This paradigm is the primary user interaction mode of widely-used systems such as Google Maps, Aperture Tiles and ForeCache. These earlier systems, however, are highly customized with hardcoded visual representations and optimizations. A more general framework is needed to facilitate the development of visual data exploration systems at scale. In this paper, we present Kyrix, an end-to-end system for developing scalable details-on-demand data exploration applications. Kyrix provides developers with a declarative model for easy specification of general visualizations. Behind the scenes, Kyrix utilizes a suite of performance optimization techniques to achieve a response time within 500ms for various user interactions. We also report results from a performance study which shows that a novel dynamic fetching scheme adopted by Kyrix outperforms tile-based fetching used in earlier systems.
Extracting Data from Comparable Corpora

Comparable corpora may comprise different types of single-word and multi-word phrases that can be considered as reciprocal translations, which may be beneficial for many different natural language processing tasks. This chapter describes methods and tools developed within the ACCURAT project that allow utilising comparable corpora in order to (1) identify terms, named entities (NEs), and other lexical units in comparable corpora, and (2) to cross-lingually map the identified single-word and multi-word phrases in order to create automatically extracted bilingual dictionaries that can be further utilised in machine translation, question answering, indexing, and other areas where bilingual dictionaries can be useful.
Dental hygiene students and faculty attitudes and utilization of a single source electronic textbook platform

Abstract Objective Transitioning to interactive e‐textbooks has been considered revolutionary for enhancing student learning. However, adopting this technology has been met with hesitation. This study investigates student and faculty attitudes and utilization of mandatory e‐textbooks in a dental hygiene program. Methods In 2017, an online questionnaire was distributed to students and a focus group was conducted with faculty to examine their perspectives about using VitalSource™. Using a 5‐point Likert scale with five indicating strongly agree, the questionnaire examined convenience; compatibility with learning style; perceived enjoyment; and usefulness. Open‐ended questions captured benefits and challenges. The focus group gathered faculty perspectives. Questionnaire data were analysed using descriptive statistics. Data from the open‐ended questionnaire questions and focus group transcript followed a narrative analysis process. Results Survey response was 48% (n = 105). Students scored all factors below neutral. Results from four categories showed convenience (M = 2.75, SD = 0.92); compatibility (M = 1.93, SD = 0.83); perceived effectiveness (M = 2.15, SD = 0.90); and perceived usefulness (M = 2.36, SD = 1.04). A high correlation between all factors suggests they were uniformly rated by students. Majority of students (71%) did not use a textbook greater than once a month. Narrative analysis revealed few benefits; challenges included technical glitches, eyestrain, cost and inability to choose books as desired. Faculty's perspectives aligned with the students, but they appreciated portability of texts and quality of clinical images. Conclusions Students strongly disliked the platform and the online medium and do not frequently access e‐textbooks but rely on PowerPoint handouts for studying. Faculty felt e‐textbooks do not align with positive learning experiences.
Using Miniature Visualizations of Descriptive Statistics to Investigate the Quality of Electronic Health Records

Descriptive statistics are typically presented as text, but that quickly becomes overwhelming when datasets contain many variables or analysts need to compare multiple datasets. Visualization offers a solution, but is rarely used apart from to show cardinalities (e.g., the % missing values) or distributions of a small set of variables. This paper describes dataset- and variable-centric designs for visualizing three categories of descriptive statistic (cardinalities, distributions and patterns), which scale to more than 100 variables, and use multiple channels to encode important semantic differences (e.g., zero vs. 1+ missing values). We evaluated our approach using large (multi-million record) primary and secondary care datasets. The miniature visualizations provided our users with a variety of important insights, including differences in character patterns that indicate data validation issues, missing values for a variable that should always be complete, and inconsistent encryption of patient identifiers. Finally, we highlight the need for research into methods of identifying anomalies in the distributions of dates in health data.
Classification of the Fire Station Requirement with Using Machine Learning Algorithms

In crowded cities, selection of the suitable location for fire stations within the town is a vital issue in terms of rapid response to fires and minimizing loss of life and property.For the selection of the suitable fire station location, at first it is necessary to divide the whole city into certain zones and the need for a fire station service should be questioned for each zone.In this study, based on existing fire stations service area, classification of fire station requirement by zones was carried out using machine learning classification algorithms.In order to estimate fire station requirement according to the zones, a classification study was conducted by using some data such as the travel time of the fire engines to zone from closed fire stations, population density of the zone, the mean number of main and assistant vehicles travelling to the zone from closed fire stations, and the fire station existence data in the zone.The purpose of this study was to determine the most successful classification algorithm for the classification of the fire station requirement of 808 zones determined by Izmir Metropolitan Municipality.As a result of the analysis of fire records between 2015 and 2017, it was found that for the classification of the zones, the most successful algorithm was Random Forest algorithm with 93.84% accuracy rate.Experimental evaluation of the study; according to the 5-minute access distance of the existing fire stations, the fire station requirements of the regions and the fire station needs of the regions covered by the machine learning algorithm classification results were found to be 85.43% similar.
Conceptual Design of a Water-air Amphibious Unmanned Vehicle

Aiming at the inefficiency of the current maritime search and rescue system, this paper aims to provide a conceptual design scheme for an amphibious unmanned surface vehicle that can realize the integration of air and water. In this design, detailed mechanical and structural analysis were performed for each part. The amphibious unmanned vehicles can independently choose the air flight and surface navigation conditions in harsh sea conditions, to cruise and rescue work. At the same time, the amphibious unmanned vehicle can realize the rapidly transfer between water and air modes through the water-air dual-purpose propulsion module, thus improving the efficiency of cruise and rescue.
DEVONIAN CONODONTS FROM SPITI HIMALAYA, INDIA

The present paper describes the lower Upper Devonian conodont fauna from the upper units of Muth Formation, Spiti Valley, Himalaya.