Reviewerly/exHarmony huggingface dataset:
Development Of A Computational Intelligence Course For Undergraduate And Graduate Students

This paper presents the design, implementation and experiences of a new three hour experimental course taught for a joint undergraduate and graduate class at the University of Missouri-Rolla, USA.This course is unique in the sense that it covers the four main paradigms of Computational Intelligence (CI) and their integration to develop hybrid algorithms.The paradigms covered are artificial neural networks (ANNs), evolutionary computing (EC), swarm intelligence (SI) and fuzzy systems (FS).While individual CI paradigms have been applied successfully to solve real-world problems, the current trend is to develop hybrids of paradigms, since no one paradigm is superior to the others in all situations.In doing so, we are able capitalize on the respective strengths of the components of the hybrid CI system and eliminate weakness of individual components.This course is an introductory level course and will lead students to courses focused in depth in a particular paradigm (ANNs, EC, FS, SI).The idea of an integrated course like this is to expose students to different CI paradigms at an early stage in their degree program.The paper presents the course curriculum, tools used in teaching the course and how the assessments of the students' learning were carried out in this course.
PENGARUH MOTIVASI BELAJAR DAN LINGKUNGAN KELUARGA TERHADAP DISIPLIN BELAJAR SISWA SMAN KECAMATAN AUR BIRUGO TIGO BALEH DI BUKITTINGGI

Abstract: This study aims to: 1) The Effect of Learning Motivation to the Discipline of learning of high school students in Aur Birugo Tigo Baleh District, Bukittinggi. 2) The Influence of the Family Environment on the Discipline of Learning of Senior High School students in Aur Birugo Tigo Baleh District, Bukittinggi. 3) The Influence of Learning Motivation and Family Environment jointly affects the discipline of learning of high school students in Aur Birugo Tigo Baleh District, Bukittinggi. This research is a type of associative descriptive study. The population in this study were were SMAN students in Aur Birugo Tigo Baleh sub-district in Bukittinggi. Sampling techniques using purposive sampling. Then use the Slovin formula, so that a sample of 317 people is obtained. Data collection techniques using primary data in the form of questionnaires. For data analysis used multiple regression analysis using the SPSS program. The results showed that: Variable Motivation and Family Environment Motivation had a significant and positive effect on Learning Discipline. Keywords: Learning Motivation, Family Environment, Learning Discipline
Perusing on Cloud Computing and its Security Issues

This paper examines the figuring of cloud and imposing security over information in the available cloud data by investigating information over cloud and its viewpoints that are identified with every possible security. It provides subtleties of information to impose security policies and approaches that are utilized through the world to provide assurance of extreme information by reducing dangers. Accessibility of information in the cloud is productive for a number of applications that exists and presents information over various applications that required security provisions by utilizing virtualization over distributed computing that may become hazard information when a visitor OS is implemented over a hypervisor without possessing the firm quality of visitor OS which may comprises of security provision in the cloud.
Web service replica selection analysis using a multiagent-based simulator

A distributed system always runs on top of a computer network and cannot be separated from it. In many cases this network consists of hundreds or thousands of computers and processing nodes. An effective distributed system simulator needs to simulate the underlying network. Unfortunately a great majority of existing simulation tools are pure network simulators. Even though they are very effective for designing, and evaluating computer networks, they could not be used to simulate a distributed application like a web service based application. Many components in a distributed system are complex servers and software applications running on top of all network layers. Network simulators cannot simulate them. A higher-level simulator is required to simulate their behavior. This work introduces an agent-based simulation model that integrates the simulation of a computer network and higher-level components of a distributed application. The distributed nature of agents makes them suitable to model and simulate distributed architectures including computer networks and distributed systems. To evaluate this approach the behavior of a replicated web service application will be simulated to show how effectively multi- agent-systems could be used to simulate the behavior of a distributed system.
Special issue on “Mind and Cognition in the Future of Decision Support Systems”

International Transactions in Operational ResearchVolume 27, Issue 1 p. 703-704 Call for Papers Special issue on “Mind and Cognition in the Future of Decision Support Systems” First published: 05 August 2019 https://doi.org/10.1111/itor.12709Citations: 1Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article.Citing Literature Volume27, Issue1Special Issue: Matheuristics and MetaheuristicsJanuary 2020Pages 703-704 RelatedInformation
Stemming and Lemmatization of Tweets for Sentiment Analysis using R

In our digital India, the use of social media like twitter, blogs and various forums is growing with the rapid rate. Thus the size of the data is becoming big day by day and in the span of this type of high varied and volume data, manual analysis would be a clumsy job. So, there is an alarming rate to analyze that large amount of data to make it suitable for analysis purpose. As a most elaborate open source platform, R has immeasurable user communities that thrives and perpetuate a huge amount of text analysis packages. So, in this paper we are analyzing movie related tweets using machine learning in R.
Association analysis of online learning behaviour in interactive education based on an intelligent concept machine

Aiming at the problem that the existing association analysis of online learning behaviour in interactive education has poor practical application effect, this paper proposes an association analysis method of online learning behaviour in interactive education based on intelligent concept machine. Association rules are used to obtain association information between data. Based on the characteristics of online learning, a data classification index system was constructed by RFM analysis method. K-means method is adopted to cluster user behaviours. PageRank algorithm was used to obtain the most representative learning users, recommend the best courses for users, and analyse the learning behaviour and effect through association rules. Finally, through simulation experiment, it is found that the average learning score of learners increases by 15 points after using this method, and the application effect is good, which verifies the effectiveness of this method.
Software Security Requirement Engineering for Risk and Compliance Management

The objective of the research work is to propose a software based security requirement engineering model using categorical and morphisms theory. The earlier security requirement engineering models focus different viewpoints on parallel processing and develop rewrite based knowledge centred models but does not include different functional mappings between the security objects to select the best strategy. The security models have not considered the needed security functions that are to be implemented in different environments with different levels of executions. The proposed requirement engineering model is based on the formal theory of category of objects and the morphisms between them in addition to n categories and multiple morphisms that were used to organize the security requirement functional objects of different categories. The on demand security requirement objects, morphisms and the uncertain events in any one of the subsystems are considered to manage this security requirement category as an algebraic data types. The collection of security requirement objects using classification and clustering techniques are implicitly applied by the formation of category and morphism. The risk and compliances both in the form of direct and indirect categories are mapped so as to provide a security assurance functors with minimum risk on the requirements to the next design state. An ‘n’ category and ‘n’ morphic model for software security requirement model is proposed towards for minimum security risks through efficient compliance management techniques.
An Optimization based Algorithm for Association Rule Mining in Large Databases

In recent trends, the information and science technology has been developed which makes most of the research in Association Rule Mining (ARM) to be focused on enhancing the computational efficiency.But the searching for most appropriate data in large databases become more difficult.The major difficulties in this is determining the threshold values for confidence and support which causes effect on the quality of the association rule mining. Thus a novel optimization based algorithm for association rule mining is proposed in this work for the purpose of enhancing the computational efficiency and also to determine the appropriate threshold values automatically. Initially the input raw data is taken from the large transactional database.Then this input raw data is preprocessed and converted into binary type data.After this, the Modified Binary Particle Swarm Optimization (MBPSO) algorithm is used which involves five phases namely 1) Encoding – where a string based encoding is followed that encodes every single item into respective string chromosome, 2) Fitness Evaluation – where the ‘maximization’ has been determined using association rule type parameters, 3) Population generation – where an initial population has been generated using particles with best fitness values, 4) Searching – where best particles are searched in order to prevent it from falling apart from search space whenever the position is updated, 5) Stopping circumstance – as it is essential to complete the particle evaluation, by finding respective confidence and support as the minimal threshold values. This would be helpful in deriving valuable information in ARM. The performance of this proposed methodology is validated and compared with the tradition association rule mining algorithms. This proposed methodology offers better results with increased efficiency and proves its superiority.
"Story-making: Re-imagining possible futures through collaborative world-building approaches"

This paper discusses insights from a collection of workshops where participants were invited to engage in active imagination and play with world-building and collaborative story-making through activities inspired by improvisation and tabletop role-playing games (TRPGs).The purpose is to explore ways of dismantling the ingrained habits of current design methodologies; unlearn normalized ways of thinking and re-construct shared approaches for designing, making, rethinking and reframing problems.To achieve this, the authors interrogate three of the workshops seeking patterns and characteristics that might offer opportunities for tools that are less encumbered by the legacies of their western modernist colonialist roots.We believe that speculative tools such as these can provide a point of departure for discussing 'alternatives to alternatives' and make spaces for emergence.Exploring the potentials of such tools is not so much about radical change but about creating spaces for shared active-imagination and moments of re-creation and re-framing that leads to hopeful pluriversal futures.
UDL Ontology

An education that values and enhances the skills and strengths of each student incorporates important advantages for learners and educators. However, the teacher is not always prepared to create educational resources that consider such a diversity of skills, especially when including disabled learners. In this context, this paper presents UDLOntology, an ontology in the domain of Education based on Universal Design for Learning principles. Its goal is to infer recommendations of educational materials that best facilitate and stimulate student learning according to their individual learning skills and strengths. UDLOntology together with the SELI course authoring platform (Smart Ecosystem for Learning and Inclusion) will guide and assist teachers and educators in building didactic resources to support and empower people with disabilities. In order to verify the adequacy of the ontology, still under development, in the inference of specific educational materials for each skill, some properties necessary for attending students with Down syndrome were specified. The main UDLOntology goal is to highlight learning skills and strengths rather than disabilities.
Ontology (<i>Ontologie</i>)

Ontology, for the Heidegger of Being and Time, is the study of being (Sein), where being is necessarily the being of entities (Seiendes), but not itself an entity.
Kernel and regression spline smoothing techniques to estimate coefficient in rates model and its application in psoriasis

Kernel and regression spline smoothing techniques to estimate coefficient in rates model and its application in psoriasis
WIP: Decoding a Discipline – Toward Identifying Threshold Concepts in Geomatics Engineering

Abstract This is a work-in-progress paper on a descriptive or a ‘what is’ type of teaching and learning project related to deep learning of fundamental knowledge in geomatics engineering. On the hard-soft and pure-applied spectrums the discipline of geomatics engineering can be classified as hard and applied. This makes sustaining an environment for deep learning, as opposed to superficial learning, of core geomatics engineering knowledge a challenging task. This environment sometimes comes at the cost of instructors of higher level courses having to repeatedly review concepts taught in lower level courses. As a result, little time is left for tackling advanced learning outcomes. This problem can be mitigated by assessing the current learning environments in core geomatics engineering courses and, more specifically, identifying threshold concepts or areas of troublesome knowledge in these courses; developing and implementing a collection of learning resources and teaching activities to address these matters; and observing and analyzing the effect of using these resources and activities on geomatics engineering students. This paper will focus on the first part of the problem, namely, what methods to use in order to assess the learning environment and detect the threshold concepts in select geomatics engineering courses. The authors propose a series of questionnaires, observation sessions, and reflection meetings where students in their second and third year of geomatics engineering will be invited to participate. The questionnaires will be formative minute papers on muddy concepts throughout the semester, and summative end-of-term surveys asking the students to describe their learning experience during the semester. The observation sessions will be in-class (teacher-student interactions) and think-aloud (individual or in groups). The reflection meetings will be conducted after certain exams, tutorials or labs, where the students will be given the opportunity to express their opinions on the learning objectives involved. In addition, grades from midterm and final exams will be analyzed for any alignment between the concepts in question and the respective student performance. This part of the project will be run for two years, so the authors will be seeking input from the engineering education community in order to improve the study in its second iteration.
Autonomic resource management framework for virtualised environments

Virtualisation enables multiples virtual machines (VMs) to co-locate on a same physical machine with total isolation. Hence using VMs to launch web services or applications is the common trend nowadays in enterprise information technology (IT). Data centre provides infrastructure to create, configure and manage VMs. It has seen as a utility that clients can pay for only as needed. The growing complexity of modern networked computer systems with virtualisation technology necessitates the needs efficient resource management. We have proposed an intelligent resource manager to control the resource allocation in Xen virtualised environment for dynamically allocating resources to individual VM. Our resource management architecture comprises of fuzzy logic based controller. Experimental results shows that with the proposed system data centre can efficiently allocate CPU resources to VMs that have been produced by customers. The scaling of CPU resources is automatically done in accordance with dynamically changing workload at a minimum granularity of 2 seconds. It improves the resource utilisation by 30% as compared to the ideal method while maintaining throughput as equivalent to the ideal workload allocation.
Exploring the Future of Engineering Education: Perspectives from a Workshop on Artificial Intelligence and the Future of STEM and Societies

There is four interrelated
Creating a TRNSYS Model of Spiral Flow Flat Plate Solar Water Heater (SFSWH) and Comparing Unique Results with Parallel Flow Flat Plate Collector

A unique SFSWH system is proposed for domestic hot water in Kovilpatti, TamilNadu, 9° 10′N 77°52′E. This SFSWH system is successfully simulated in TRNSYS Software and the results are clarified with the similarities of parallel flow solar water heater. Firstly, a complete model of spiral flow flat plate collector is formulated in TRNSYS software and taking into an account of heat transfer, outlet temperature and efficiency which are theoretically compared with parallel flow flat plate collector by means of TRNSYS simulation program. The SFSWH system performs a function with the assist of NASA surface Meteorology and solar energy year readings and with the assist of ISRO’s solar calculator application relative to Kovilpatti, Tamilnadu, India. To prove the accuracy of TRNSYS model of the SFSWH, an experimental setup is done at kovilpatti and required results were obtained under kovilpatti weather conditions. The validation of this SFSWH TRNSYS model simulation program is completed by checking the similarities between the predicted results from software with original results. This SFSWH TRNSYS model result shows the SFSWH is functioned more effectively compared with conventional parallel flow water heater. Thus TRNSYS model is reliable and which alternates the experimentation.
PENDEKATAN PEMBELAJARAN MEMBACA PADA BUKU TEKS PELAJARAN TEMATIK KELAS III SD/MI DI KECAMATAN PURBALINGGA

Text book used at Indonesian elementary school particularly the reading sections play significant role for 1st – 3rd grade students as it prepares them to master their reading skill at 4th – 6th grade. Reading strategies which appropriate to students needs should be implemented to give rooms for student to exercise their reading skills. Occurred from April to June 2021, this study aimed to determine whether or not the five text books used at Purbalingga regency are suitable for students, and to find out what kind of reading strategy used in those textbooks. As a library research, the prime source of this study is five textbooks for 3rd grade students from which Miles and Huberman model was used to analyzed the data. The findings showed that the five textbooks are all suitable, they fitted the criteria to be categorized as good and proper for teaching reading. Three out of the five textbooks utilized whole language reading strategy, the other two textbooks, brought into play both contextual and whole language reading strategies. These two reading strategies encourage students to be active participants and all the five textbooks make this possible through various independent reading activities.
INFORMATION LITERACIES AND DIGITAL LITERACIES

This paper intents to promote a study about how the market demand on digital and informational skills boosted the professionals’ training in this field and influenced the research over digital and information literacies since the first years of schooling until undergraduate and professional courses. The qualitative and quantitative research was structured over data base search engines and offers as a result a holistic overview about the information professional market demand and the educational process since the early ages for building citizens as democratic pillars in the information age’s knowledge society.
MDA Transformation Process from predictive project management methodologies to agile project management methodologies

Project management models are constantly evolving over time, among the most widely answered models we find Agile models or else called "Adaptive" and "Predictive" models.A study by the Standish group confirms that Agile projects achieve the desired result three times more than projects that are carried out by conventional (predictive) Methodologies.Thus, many organizations tend to apply the new project management model or migrate from the standard model to the agile one.In this article, building on previous research, we'll build on the principles of MDA to define a metamodel of Agile and Predictive Methodologies, and then we'll effect a transformation that will help organizations transform project management.
Sentiment Analysis of Healthcare Quality

In this work, concentrate on Hospital Service quality provided to patients through hospitals and hospital staff. Services are similar as the Doctor's reaction to the patients, instrument feature in hospital, area of expertise of Doctors, Compounder and Nurse. The patient expects good services from employees of hospital similar as from Doctor, ward boys, nurses, etc. These employees must take care of the patient’s health, give needful medicine to the patient; the environment of the Hospital must be clean and comfortable for a patient. This paper concentrates on the patient’s feedback about a hospital. We have taken patient’s feedbacks from online website, social websites like Twitter, blogs, and Government healthcare-related website. These feedbacks are the form of comments available on websites. Then we need to analyze the comments, classify these comments as positive, negative and neutral by making use of sentiment analysis technique. Finally, based on results, we can decide which facility is in lower in quality, and recognize hospital which is better for patient’s health improvement.