Reviewerly/exHarmony huggingface dataset:
An Interactive Courseware for Learning Data Warehousing on the Web

Abstract An Interactive Courseware for Learning Data Warehousing on the WebData analytics is playing a significant role in today’s science and engineering education. Datawarehouses provide online analytical processing tools for the interactive analysis ofmultidimensional data of various granularities. The objective of this project is to develop a web-based interactive courseware to help students or beginning data warehouse designers worldwidein learning data warehousing. Contributors of this project include Computer Scienceinternational graduate students from India. The end user of the courseware can be anyone whohas access to internet.In this project we have developed a courseware to reinforce learning of the key concepts of thedata warehousing using a case study approach. The courseware now contains two working sub-systems: (1) data warehousing courseware; and (2) ETL (Extraction, Transformation, and Load)courseware. We have been using this courseware in a Data Warehousing and Data Mining courseat California State University in past two years. Students had very positive feedback on theirlearning experiences with the tool. We are now in the process of expanding to include one moresub-system, OLAP (On Line Analytical Processing) cube courseware.The main advantages of using this web-based interactive courseware to supplement classroominstructions or textbook are as follows: (a) The contents of the courseware can be updated by the instructor periodically to keep up with the rapid development of the field of data warehousing and data mining. (b) The incremental developing courseware provides an ideal platform for the instructor to share latest research development results with students so that we can make the technology transfer a little faster to our students. (c) This project provides a self-paced interactive learning tool not only to the students taking a course on data warehousing but also to any engineer in the world who have to build a data warehouse from scratch and needs to learn fundamental concepts quickly. From schema design to OLAP query execution, we explain concepts step by step and illustrate implementation techniques with examples from our case study. An end user can run various demo queries interactively as he/she is making progress in his/her own pace. (d) Our digital courseware offers a low cost alternative to traditional expensive textbooks. Students usually do not want to buy additional reference books due to the high costs.In this paper, we will introduce the design and implementation of our data warehousingcourseware. Of course, we will also share the lessons that we had learned from this project. Themethod used in this project can be generalized to other engineering fields which has globeeducational needs on self-paced learning tools.
Genesis of Cu-Au mineralisation in the Cambrian Barkly River Greenstones, Victoria, Australia

Geological mapping, combined with geophysical and geochemical exploration, strongly suggest that structurally-emplaced Cambrian basement rocks exposed in the Mt Wellington Fault Zone of eastern Victoria, Australia, have significant gold and base metal potential. Although the mineralised zones identified to date in the Barkly River Greenstones display characteristics of epithermal and porphyry intrusive associations, the findings of detailed petrological and geochemical studies are consistent with the formation of the Cu-Au (±Pb-Zn) anomalies within a deep-seated, high-temperature volcanic-hosted massive sulphide (VHMS) setting. Moreover, the volcanogenic rocks identified in the Mt Wellington Fault Zone display strong petrographical and geochemical affinities to the economically significant Mt Read Volcanics in western Tasmania, which host several world-class massive sulphide deposits. These findings suggest that the Mt Wellington Fault Zone represents a new and potentially significant mineral province for VHMS and gold mineralisation in south-eastern Australia.
Curriculum of Teacher Education Programme: What Do Teacher Educators Say?

India has one of the largest systems of teacher education in the world. Besides the university departments of education and their affiliated colleges, government and government aided institutions; private and self-financing colleges and open universities are also engaged in teacher education. Though most teacher education programmes are nearly identical yet their standards vary across institutions and universities. However, teacher education curriculum across the country has been blamed for ineptitude and needs urgent reforms. Teacher educators are a pivotal point of this programme and their opinion regarding the curriculum is very important. Keeping the above in mind, the present study aimed to find out the attitude of teacher educators towards existing teacher education curriculum and the needed renewal in teacher education curriculum. Data was collected from randomly selected 107 teacher educators working in colleges of education affiliated to GGSIPU and M.D.U. A five point attitude scale was developed by the researchers for the purpose of ascertaining their attitude. The findings revealed that teacher educators are largely in disagreement with the current curriculum and hold that a new vision needs to be made for the education of teachers as per the present needs of globalisation, RTE norms, and adoption of inclusive education.
Role of Rural Agricultural Information Centre for the Sustainable Development of Floriculture Community in West Bengal

Is Very Important For The Development Of The Floriculture Community. In This Aspect,
Big Data meets Big Fridge (a frolic)

This article offers a possibly optimistic view of the influence of the new anti-terror laws on the profitability of the telecommunications industry.
Using the RFP Process to Select a Serials Vendor: A Work in Progress

In this workshop, two librarians and a vendor described, and discussed the Request for Proposal (RFP) process to serials acquisitions librarians and vendor representatives. The format of the workshop followed the process of an actual RFP, beginning with the planning stage, the drafting of the request document, the submission to sources, the receipt by the solicited vendors, the preparation of a response, the evaluation, and the actual award. The central theme of the workshop was the contrast between the formal Request for Proposal (RFP) and the informal RFP. The formal RFP is usually mandated by law of by institutional regulations and always involves a Purchasing Department or Contracting Office outside the library. The informal RFP is not required by institutional or governmental regulations and is administered totally within the library.
Using Software Engineering Concepts And Techniques To Leverage Learning: A Novel Approach

This paper describes an approach to integrating software engineering concepts and principles into the Electrical and Computer Engineering (ECE) and Computer Science (CS) curricula.Our philosophy is to apply software engineering techniques throughout the ECE/CS curricula to leverage learning in non-software engineering courses.Our technique is to seek out faculty interested in innovative teaching techniques, consult with them to identify some way that they and we feel a course they are teaching could benefit pedagogically from some application of software engineering, and work with them to make that happen.The chief intended result is to leverage learning in diverse courses, thereby benefiting pedagogy of non-software engineering topics.An auxiliary important result is to increase awareness among both students and faculty of the software engineering body of knowledge.Many software engineering approaches to understanding and solving problems in the software life cycle can also address a variety of learning needs across disciplines in ECE and CS.For example, there are software engineering techniques that can emphasize visualization (benefiting students who respond to the visual modality), logical sequences (benefiting sequential learners), summarizations (benefiting global learners), and others.Additionally, general issues of teamwork and the engineering life cycle can be addressed.We have applied our approach to a diverse set of electrical engineering and computing courses at four universities in the US and Canada, and based on those experiences we believe we have identified a win-win paradigm that can be a model for integration of software engineering concepts into electrical engineering and computing curricula.
Shopper: A System for Executing and Simulating Expressive Plans

We present Shopper, a plan execution engine that facilitates experimental evaluation of plans and makes it easier for planning researchers to incorporate replanning. Shopper interprets the LTML plan language, which extends PDDL in two major ways: with more expressive control structures, and with support for semantic web services modeled on OWL-S. LTML's command structures include not only conventional ones such as branching, iteration, and procedure calls, but also features needed to handle HTN plans, such as precondition-filtered method choice. Unlike conventional programming languages, LTML supports interaction with the agent's belief store, so that its execution semantics line up with those assumed by planners. LTML actions extend PDDL actions in having outputs as well as effects, which means that they can support actions that sense the world; an important special case of this is semantic web services, which reveal information about a state hidden from the agent. To support experimentation as well as action in the real world, Shopper accommodates multiple, swappable implementations of its primitive action API. For example, one may interact with real web services through SOAP and WSDL, or with simulated web services through local procedure calls. We describe novel features of LTML, the interpretation strategy, swappable back-ends, and the implementation.
Ontology Adaptation for Opinion Mining in French Corpora

This paper presents the development of an ontology for opinion mining in French corpora. Since ontology construction from scratch is expensive and time consuming, the model is built by adapting an existing ontology modeling appraisal categories in English. The construction method consists of two main steps: first, the ontology of appraisals is translated in French by using a concept-to-concept approach; then different adaptation strategies are implemented to improve the result of this translation. Adaptation strategies are based on text mining, weakly supervised methods and the use of WordNet to refine the model. The goal of the adaptation phase is to cope with limitations of concept-to-concept translation, to integrate concepts and relations from external corpora and resources, and to build a model that captures various features of opinions. The ontology was designed and build to incorporate linguistic and extra linguistic information on the description of opinions in French. The model was validated by using both expert insights to validate the relevance of concepts and relations and formal criteria to describe the ontology qualities for practical use.
Reading Teachers: Reading Strategies Employed in Teaching Reading in Grade School

The purpose of the study. The aims of this research are to determine the teachers' reading style, determine their reading speed, and determine which reading methods are the teachers' strengths and weaknesses utilizing a thorough evaluation of reading techniques from Hawker Brownlow Education. This study utilized the comprehensive assessment of reading strategies from Hawker Brownlow Education. This material is composed of four series of tests namely, Reading Comprehension 1- Historical Fiction, Reading Comprehension 2- History Article, Reading Comprehension 3- Kate Wrote About a Special Zoo, and Reading Comprehension 4- Email written by Carl with different reading passages using the same 12 reading strategies. It is found that readers can effectively comprehend when they use the following strategies namely, finding word meaning in context, understanding sequence, and making predictions. Therefore, the four series of assessments, show that there are varied ways of comprehending a material that might directly influence the duration and time limit allocated in reading and answering the material, the recurring events of the same material used, and the scheduling of reading comprehension tests.
Cryptanalysis of Draco

Draco is a lightweight stream cipher designed by Hamann et al. in IACR ToSC 2022. It has a Grain-like structure with two state registers of size 95 and 33 bits. In addition, the cipher uses a 128-bit secret key and a 96-bit IV. The first 32 bits of the key and the IV forms a non-volatile internal state that does not change during the time that the cipher produces keystream bits.The authors claim that the cipher is provably secure against Time-Memory-Data (TMD) Tradeoff attacks. However in this paper, we first present two TMD tradeoff attacks against Draco. Both attacks leverage the fact that for certain judiciously chosen IVs the state update function of the cipher depend on only a small fraction of the non-volatile internal state. This makes the state update function in Draco essentially a one way function over a much smaller domain and range. The first attack requires around 2114.2 Draco iterations and requires that the adversary has access to 232 chosen IVs. The second attack is such that the attack parameters can be tuned as per the requirements of the attacker. If the attacker prioritizes that the number of different chosen IVs is limited to 220 say, then the attack can be done in around time proportional to 2126 Draco rounds. However if the total attack complexity is to be optimized, then the attack can be performed in 2107 time using around 240 chosen IVs.
Teachers’ Perspectives on Innovative and Interactive Teaching Methods: Perspective of Mobile Learning

This study aims to reflect teachers' perspectives on the use of innovative and interactive teaching methods (mobile learning and others) and to present the importance of the application of modern teaching methods by first-level teachers (grades 1-5) and second-level teachers (grades 6-9), in the development of student competencies. The research includes the Anamorava Region in Kosovo which covers an area of ​​650 km2 and has about 200,000 inhabitants. Quantitative methods were used to research this issue, while Likert scale questionnaires were used as a tool for measuring teachers' thoughts and attitudes. The research sample consists of 97 teachers working with first and second-level students. The results show that teachers do not use a variety of methods while a number of them state that teaching methods are always in coherence with the age and skills of students. A small number of teachers pay special attention to students' prior knowledge. Based on the general data from the research, I have noticed that teachers do not practice enough modern teaching methods to develop students' competencies and promote their activity and creativity.
Laboratory performance prediction using virtual reality behaviometrics

In this study, we show that virtual reality (VR) behaviometrics can be used for the assessment of compliance and physical laboratory skills. Drawing on approaches from machine learning and classical statistics, significant behavioral predictors were deduced from a logistic regression model that classified students and biopharma company employees as experts or novices on pH meter handling with 77% accuracy. Specifically, the game score and number of interactions in VR tasks requiring practical skills were found to be performance predictors. The study provides biopharma companies and academic institutions the possibility of assessing performance using an automatic, reliable, and simple alternative to traditional in-person assessment methods. Integrating the assessment into the training tool renders such laborious post-training assessments unnecessary.
Personalizing Hybrid-Based Dialogue Agents

In this paper, we present a continuation of our work on the personification of dialogue agents. We expand upon the previously demonstrated models—the ranking and generative models—and propose new hybrid models. Because there is no single definitive way to build a hybrid model, we explore various architectures where the components adopt different roles, sequentially and in parallel. Applying the perplexity and BLEU performance metrics, we discover that the Retrieve and Refine and KG model—a modification of the Retrieve and Refine model where the ranking and generative components work in parallel and compete based on the proximity of the candidate found by the ranking model with a knowledge-grounded generation block—achieves the best performance, with values of 1.64 for perplexity and 0.231 for BLEU scores.
A Multi-Disturbance Marine Predator Algorithm Based on Oppositional Learning and Compound Mutation

Marine Predator Algorithm (MPA) is a meta-heuristic algorithm based on the foraging behavior of marine animals. It has the advantages of few parameters, simple setup, easy implementation, accurate calculation, and easy application. However, compared with other meta-heuristic algorithms, this algorithm has some problems, such as a lack of transition between exploitation and exploration and unsatisfactory global optimization performance. Aiming at the shortage of MPA, this paper proposes a multi-disturbance Marine Predator Algorithm based on oppositional learning and compound mutation (mMPA-OC). Firstly, the optimal value selection process is improved by using Opposition-Based Learning mechanism and enhance MPA’s exploration ability. Secondly, the combined mutation strategy was used to improve the predator position updating mechanism and improve the MPA’s global search ability. Finally, the disturbances factors are improved to multiple disturbances factors, so that the MPA could maintain the population diversity. In order to verify the performance of the mMPA-OC, experiments are conducted to compare mMPA-OC with seven meta-heuristic algorithms, including MPA on different dimensions of the CEC-2017 benchmark function, complex CEC-2019 benchmark function, and engineering optimization problems. Experiments have shown that the mMPA-OC is more efficient than other meta-heuristic algorithms.
Perceptions and Attitudes of BA and MA Graduating Students in Philology Towards the Writing of Their Final Research Papers. A Survey-Based Case Study

Abstract This paper discusses the results of a survey on university students’ perceptions and attitudes towards the writing-up process of their final graduation paper. The google form questionnaire was addressed to all the BA and MA graduating philology students, covering four study programmes in English, in a university in western part of Romania. The findings indicate a possible re-thinking of the curricula aiming at the inclusion of mandatory courses in academic writing and research skills at the incipient phases of the study programmes.
Prolog-based agnostic explanation module for structured pattern classification

This paper presents a Prolog-based reasoning module to generate counterfactual explanations given the predictions computed by a black-box classifier. Our approach comprises four well-defined stages that can be applied to any structured pattern classification problem. Firstly, we pre-process the given dataset by imputing missing values and normalizing the numerical features. Secondly, we transform numerical features into symbolic ones using fuzzy clustering such that extracted fuzzy clusters are mapped to an ordered set of predefined symbols. Thirdly, we encode instances as a Prolog rule using the nominal values, the predefined symbols, the decision classes, and the confidence values. Fourthly, we compute the overall confidence of each Prolog rule using fuzzy-rough set theory to handle the uncertainty caused by transforming numerical quantities into symbols. This step comes with an additional theoretical contribution to a new similarity function to compare the previously defined Prolog rules involving confidence values. Finally, we implement a chatbot as a proxy between humans and the Prolog-based reasoning module to resolve natural language queries and generate counterfactual explanations. During the numerical simulations using synthetic datasets, we study the performance of our system when using different fuzzy operators and similarity functions.
Signal Source Localization with Long-Term Observations in Distributed Angle-Only Sensors

Angle-only sensors cannot provide range information of targets and in order to determine accurate position of a signal source, one can connect distributed passive sensors with communication links and implement a fusion algorithm to estimate target position. To measure moving targets with sensors on moving platforms, most of existing algorithms resort to the filtering method. In this paper, we present two fusion algorithms to estimate both the position and velocity of moving target with distributed angle-only sensors in motion. The first algorithm is termed as the gross least square (LS) algorithm, which takes all observations from distributed sensors together to form an estimate of the position and velocity and thus needs a huge communication cost and a huge computation cost. The second algorithm is termed as the linear LS algorithm, which approximates locations of sensors, locations of targets, and angle-only measures for each sensor by linear models and thus does not need each local sensors to transmit raw data of angle-only observations, resulting in a lower communication cost between sensors and then a lower computation cost at the fusion center. Based on the second algorithm, a truncated LS algorithm, which estimates the target velocity through an average operation, is also presented. Numerical results indicate that the gross LS algorithm, without linear approximation operation, often benefits from more observations, whereas the linear LS algorithm and the truncated LS algorithm, both bear lower communication and computation costs, may endure performance loss if the observations are collected in a long period such that the linear approximation model becomes mismatch.