Few More Results on Sum Labeling of Split Graphs
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A sum labeling is a mapping λ from the vertices of G into the positive integers such that, for any two vertices u, v ϵ V (G) with labels λ(u) and λ(v), respectively, (uv) is an edge iff λ(u) + λ(v) is the label of another vertex in V (G). Any graph supporting such a labeling is called a sum graph. It is necessary to add (as a disjoint union) a component to sum label a graph. This disconnected component is a set of isolated vertices known as isolates and the labeling scheme that requires the fewest isolates is termed optimal. The number of isolates required for a graph to support a sum labeling is known as the sum number of the graph. In this paper, we will obtain optimal sum labeling scheme for path union of split graph of star, K_(1,m)⨀Spl(P_n) and K_(1,m)⨀Spl(K_(1,n)).
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{(d(v,v1),d(v,v2 ),...,d(v,v ) / v V (G))} k Î , denoted d G and is used to study metric dimension of graphs. It
has been proved that metric dimension of any connected finite simple graph remains constant if d G
numbers of pendant edges are added to the non-basis vertices.
AN APPLICATION OF Gd -METRIC SPACES AND METRIC DIMENSION OF GRAPHS
The idea of metric dimension in graph theory was introduced by P J Slater in [2]. It has been found
applications in optimization, navigation, network theory, image processing, pattern recognition etc.
Several other authors have studied metric dimension of various standard graphs. In this paper we
introduce a real valued function called generalized metric → + Gd
: X × X × X R where X = r(v /W) =
{(d(v,v1
),d(v,v2
),...,d(v,vk
/) v∈V (G))}, denoted Gd
and is used to study metric dimension of graphs. It
has been proved that metric dimension of any connected finite simple graph remains constant if Gd
numbers of pendant edges are added to the non-basis vertices.
09_DS_MCA_Graphs.pdf
Graphs can be represented using adjacency matrices or adjacency lists. Common graph operations include traversal algorithms like depth-first search (DFS) and breadth-first search (BFS). DFS traverses a graph in a depth-wise manner similar to pre-order tree traversal, while BFS traverses in a level-wise or breadth-first manner similar to level-order tree traversal. The document also discusses graph definitions, terminologies, representations, elementary graph operations, and traversal methods like DFS and BFS.
Graph terminology and algorithm and tree.pptx
This document provides an overview of key concepts in graph theory including graph terminology, representations, traversals, spanning trees, minimum spanning trees, and shortest path algorithms. It defines graphs, directed vs undirected graphs, connectedness, degrees, adjacency, paths, cycles, trees, and graph representations using adjacency matrices and lists. It also describes breadth-first and depth-first traversals, spanning trees, minimum spanning trees, and algorithms for finding minimum spanning trees and shortest paths like Kruskal's, Prim's, Dijkstra's, Bellman-Ford and A* algorithms.
H0431038048
This document introduces and defines the concept of neighborhood triple connected domination number (ntc) of a graph. A neighborhood triple connected dominating set of a graph G is a dominating set where the induced subgraph of the open neighborhood of the set is triple connected. The ntc of G is the minimum cardinality of such a set. The document provides the ntc values for some standard graphs like complete graphs and wheels. It also gives ntc values for specific graphs like the diamond, fan, and Moser spindle graphs. Real-life applications of ntc sets are discussed. Properties of ntc sets are observed and examples are given.
Application of Graph Theory in Computer science using Data Structure.pdf
This document discusses the application of graph theory in computer science and data structures. It provides definitions of graphs, trees, and other graph theory concepts. It also describes various graph data structures like adjacency lists and matrices. Common graph algorithms like breadth-first search, depth-first search, and topological sorting are also covered. The document gives examples of how graph theory can be applied in areas like social networks, transportation, and computer networking.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
This document defines and discusses the concept of paired triple connected domination number of a graph. It begins by reviewing existing concepts like domination number, connected domination number, and triple connected domination number. It then introduces the new concept of a paired triple connected dominating set as a triple connected dominating set where the induced subgraph also has a perfect matching. The paired triple connected domination number is defined as the minimum cardinality of such a set. The document explores properties of this number and its relationship to other graph parameters. Examples are provided to illustrate the definitions.
IRJET - On Strong Blast Domination of Graphs
This document introduces the concept of strong blast domination number of graphs. A strong blast dominating set S of a graph G is a connected dominating set such that the induced subgraph on S is triple connected, and each vertex in the graph but not in S is strongly dominated by a vertex in S. The document provides definitions, examples, and theorems about computing the strong blast domination number for various classes of graphs such as complete graphs, wheel graphs, and total graphs.
A NEW PARALLEL ALGORITHM FOR COMPUTING MINIMUM SPANNING TREE
Computing the minimum spanning tree of the graph is one of the fundamental computational problems. In
this paper, we present a new parallel algorithm for computing the minimum spanning tree of an undirected
weighted graph with n vertices and m edges. This algorithm uses the cluster techniques to reduce the
number of processors by fraction 1/f (n) and the parallel work by the fraction O ( 1 lo g ( f ( n )) ),where f (n) is an
arbitrary function. In the case f (n) =1, the algorithm runs in logarithmic-time and use super linear work on
EREWPRAM model. In general, the proposed algorithm is the simplest one.
Similar to Few More Results on Sum Labeling of Split Graphs (20)
FREQUENT SUBGRAPH MINING ALGORITHMS - A SURVEY AND FRAMEWORK FOR CLASSIFICATION
FREQUENT SUBGRAPH MINING ALGORITHMS - A SURVEY AND FRAMEWORK FOR CLASSIFICATION
Algorithm for Edge Antimagic Labeling for Specific Classes of Graphs
Algorithm for Edge Antimagic Labeling for Specific Classes of Graphs
International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)
Graph theory concepts complex networks presents-rouhollah nabati
Graph theory concepts complex networks presents-rouhollah nabati
ON ALGORITHMIC PROBLEMS CONCERNING GRAPHS OF HIGHER DEGREE OF SYMMETRY
ON ALGORITHMIC PROBLEMS CONCERNING GRAPHS OF HIGHER DEGREE OF SYMMETRY
On algorithmic problems concerning graphs of higher degree of symmetry
On algorithmic problems concerning graphs of higher degree of symmetry
AN APPLICATION OF Gd -METRIC SPACES AND METRIC DIMENSION OF GRAPHS
AN APPLICATION OF Gd -METRIC SPACES AND METRIC DIMENSION OF GRAPHS
Application of Graph Theory in Computer science using Data Structure.pdf
Application of Graph Theory in Computer science using Data Structure.pdf
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
A NEW PARALLEL ALGORITHM FOR COMPUTING MINIMUM SPANNING TREE
A NEW PARALLEL ALGORITHM FOR COMPUTING MINIMUM SPANNING TREE
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SPSS: An Effective Tool to Compute Learning Outcomes in Acadamics
OBJECTIVES: To determine how SPSS can be a useful tool to evaluate Course Learning Outcomes and analyze student's performance with the help of KS test, histogram and skewness of the tool. It is also contributing to facilitate Deep learning amongst students with the help of achievement of normal distribution of grades. METHODS: Comparative analysis is done using course specification, syllabus, assessment method(Final Exam Question paper is taken as tool) and result statistics for the course of STATISTICAL PROGRAMMING (217 CSM), 3rd year (level 5 course) that is part of BCS curriculum in department of Computer Science, College of computer Science in King Khalid University. Teaching strategies are compared for two years. i.e; 2013 and 2014. Moreover the research inferences the relevance of application of NCAAA standards in meeting Learning outcomes of any module for department of Computer Science, CCS, KKU. RESULTS: Comparison of question papers depict that now students are motivated to have deep learning in terms of understanding, solving, reasoning based questions as contrast to shallow learning (memorized questions) in the past. It is indeed improving Learning domains too (Knowledge, Cognitive, Interpersonal and Communication skills) more effectively than in the past. Also grade distribution is Normal with well-defined curve for 2014 as compared to 2013 having variation in Standard deviation too. Teacher centered learning lead to surface learning. After NCAA standards implementation, there is more focus on learned centered teaching. Design of learning assessments is in such a way that it should meet learning outcomes successfully. CONCLUSIONS: The research is contributing in flourishing the personality of the students to produce qualified graduates with excellence in communication, logically and technically capable enough to share their knowledge nationally and internationally with much more confidence at any platform. Also it is opening door for researchers to evaluate their performance with the help of SPSS in academics or anywhere where we want to gather.
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining Approach
Detection of software bugs and its occurrences, repudiation and its root cause is a very difficult process in large multi threaded applications. It is a must for a software developer or software organization to identify bugs in their applications and to remove or overcome them. The application should be protected from malfunctioning. Many of the compilers and Integrated Development Environments are effectively identifying errors and bugs in applications while running or compiling, but they fail in detecting actual cause for the bugs in the running applications. The developer has to reframe or recreate the package with the new one without bugs. It is time consuming and effort is wasted in Software Development Life Cycle. There is a possibility to use graph mining techniques in detecting software bugs. But there are many problems in using graph mining techniques. Managing large graph data, processing nodes with links and processing subgraphs are the problems to be faced in graph mining approach. This paper presents a novel algorithm named BugLoc which is capable of detecting bugs from the multi threaded software application. The BugLoc uses object template to store graph data which reduces graph management complexities. It also uses substring analysis method in detecting frequent subgraphs. The BugLoc then analyses frequent subgraphs to detect exact location of the software bugs. The experimental results show that the algorithm is very efficient, accurate and scalable for large graph dataset.
Motion Object Detection Using BGS Technique
The detection of moving object is an important in many applications such as a vehicle identification in a traffic monitoring system,human detection in a crime branch.In this paper we identify a vehicle in a video sequence.This paper briefly explain the detection of moving vehicle in a video.We introduce a new algorithm BGS for idntifying vehicle in a video sequence. First, we differentiate the foreground from background in frames by learning the background. Then, the image is divided into many small nonoverlapped frames. The candidates of the vehicle part can be found from the frames if there is some change in gray level between the current image and the background. The extracted background subtraction method is used in subsequent analysis to detect a vehicle and classify moving vehicle.
Analysis of Women Harassment in Villages Using CETD Matrix Modal
It is commonly understood that misbehavior intends to upset .Law says , the repeated intentional misbehavior towards women is an offensive. The main concept of this paper can find something interesting that will make us reflect on what is done by women’s rights and gender equality. To solve such problem, in this paper we are interested to adopt CETD matrix.
Solving Assignment Problem Using L-R Fuzzy Numbers
In this paper we determine a new method to solving assignment problem using L-R fuzzy parameters. This method requires finding out the minimal cost reach optimality compared to the existing methods available in the literature. Numerical examples show that the fuzzy assignment ranking method offers an effective way for handling the fuzzy assignment problem.
Fuzzy Chroamtic Number of Line Graph using α-Cuts
In this paper, we introduce chromatic number of line graph using α-cuts. The concept of chromatic number of fuzzy graphs was introduced by Munoz et.al, later Eslahchi and onagh. They are defined by the fuzzy chromatic number of complete graphs (kn), cycle graph (cn), star graph (sn), wheel graph (wn), and line graph are found and results are summarized.
A Study on the Exposures of Rag- Pickers Using Induced Neutrosophic Cognitive...
In this paper, using a new Fuzzy bimodal called Induced Neutrosophic Cognitive Relational Maps (INCRM) we analyse the Socio-Economic problem faced by Rag-Pickers. Based on the study, conclusions and some remedial measures are stated.
Dual Trapezoidal Fuzzy Number and its Applications
In this Paper, we introduce Convergence of α-Cut. We define at Which point the α-Cut converges to the fuzzy numbers and it will be illustrated by example using dual trapezoidal fuzzy number and some mensuration problems are illustrated with approximated values.
Developing and Porting multi-grid solver for CFD application on Intel-MIC pla...
This paper presents an implementation of one dimensional Burgers equation using implicit method with Intel Xeon Phi Coprocessor. In particular, we used MAGMA MIC library which is an open source high performance library for solving a systems of non-linear equations. Further for high performance computation we consider offload mode as the primary mode of operation for Intel Xeon phi coprocessor. The result obtained from implicit scheme is then compared with the exact values and it’s seen that the results obtained are approximate and reliable. The result table showed that the proposed scheme achieved higher performance on Intel MIC platform.
Saturation Index of π(D(r,s))
Adin and Roichman [1] introduced the concept of permutation graphs and Peter Keevash, Po-Shen Loh and Benny Sudakov [2] identified some permutation graphs with maximum number of edges. Ryuhei Uehara, Gabriel Valiente, discussed on Linear structure of Bipartite Permutation Graphs and the Longest Path Problem [3]. If i, j belongs to a permutation on p symbols {1, 2, …, p} and i is less than j then there is an edge between i and j in the permutation graph if i appears after j in the sequence of permutation. So the line of i crosses the line of j in the permutation. Hence there is a one to one correspondence between crossing of lines in the permutation and the edges of the corresponding permutation graph. In this paper we found the conditions for a permutation to realize a double star and comprehend the algorithm to determine the satuation index of the permutation. AMS Subject Classification (2010): 05C35, 05C69, 20B30.
Classification and Prediction of Heart Disease from Diabetes Patients using H...
The multi-factorial chronicle, severe disease among human is diabetes. As a result of abnormal level of glucose in body leads to heart attack, kidney disease, renal failure, Hyperglycemia and also cancer in organs like liver and pancreas. Many studies have been proved that several types of heart diseases are possible in diabetic patients having a high blood sugar. Many approaches were proposed to diagnose both Diabetes and heart diseases. Most of the diabetes people can also have heart diseases called as Diabetic Cardiomyopathy. The earliest manifestation of diabetic cardiomyopathy is needed certain processes. The objective of the study is to examine the association of heart disease and diabetes. The relationship between diabetes and cardiovascular diseases are examined by taking into account of age, sex and associated diabetic and cardiovascular risk factors. The data are collected from patients with diabetes. From these data, features are selected by ant colony optimization and those selected features are given to hybrid PSO-LIBSVM to classify abnormal and normal data. This performance is evaluated using performance metrics and proved this classifiers efficiency for detection of Diabetic Cardiomyopathy.
Format Preserving Encryption for Small Domain
Cryptography is important in communicating secured information that is vulnerable to distortion. The main goal of this paper is encrypting the small arbitrary length data without any changes in the length and data type. We propose a flexible arbitrary length small domain block cipher (FPESD). FPESD is based on AES Algorithm. The resulting cipher text is the same as input plaintext. Here, we use Galois finite field GF (28) and format preserving key to implement FPE. For decryption format preserving key is used along with cipher text and secret key.
Intuitionistic Double Layered Fuzzy Graph and its Cartesian Product Vertex De...
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Clustering and Classification in Support of Climatology to mine Weather Data ...
Knowledge of climate data of region is essential for business, society, agriculture, pollution and energy applications. Climate is not fixed, the fluctuation in the climate can be seen from year to year.The data mining application help meteorological scientists to predictaccurate weather forecast and decisions and also provide more performance and reliability than any other methods. The data mining techniques applied on weather data are efficient when compare to the mathematical models used. Various techniques of data mining are applied on climate data to support weather forecasting, climate scientists, agriculture, vegetation, water resources and tourism. The aim of this paper is to provide a review report on various data mining techniques applied on weather data set in support of weather prediction and climate analysis.
Test Suite Reduction Based on Fault Detection with Cost Optimization
Test Suite Reduction is an optimization technique to identify the minimally sized subset of test cases with enforced constraints involved. The main purpose of test suite reduction is to deduce increased number of test cases that in turn increase the time and cost involved in execution. Fault Detection is the method of identifying the faults that affect the outcome of the system either logically or syntactically. This paper focuses on the reduction of the test suite that has high fault identification rates and also incurs low cost of execution of test cases. The proposed approach includes a new parameter Fault Detection Effectiveness to identify fault rates of test suite; an algorithm for test suite reduction based on priority of requirements; a low cost framework to identify the execution of test cases with minimum budget. Thus, the proposed work defines a test suite that has high fault detection effectiveness providing maximum coverage to requirements at minimum cost of execution.
Artifact Facet Ranking and It’s Applications
As the e-commerce is gaining popularity various customer surveys of objects are currently accessible on the Internet. These surveys are frequently disordered, prompting challenges in knowledge discovery and object assessment. This article proposes an object feature positioning skeleton, which consequently recognizes the critical features of an object from online customer surveys. The critical object features are recognized focused around two perceptions: 1) they are normally commented extensively by customers and 2) customer suppositions on the critical feature significantly impact their general assessments on the object. Specifically, given the customer surveys of an item, we first extract the object feature by a shallow reliance parser and focus customer suppositions on these features through an opinion characterizer. We then create a probabilistic object feature positioning calculation to identify the criticalness of perspectives by at the same time considering feature recurrence and the impact of customer opinion given to every feature over their general opinion. The experimental results on 3 popular products demonstrate the effectiveness of our approach.
Effectual Data Integrity Checking Technique Based on Number Theory
Cloud Computing makes data really mobile and a client can simply access a chosen cloud with any internet accessible device. The espousal and dispersion of Cloud computing are threatened by unresolved security issues that affect both the cloud provider and the cloud user. The integrity of data stored in the cloud is one of the challenges to be addressed before the novel storage model is applied widely. This paper analyses the efficiency issues and security dodge of an existing scheme and proposes an amended data integrity scheme using improved RSA and number theory based concept for cloud archive. This scheme of protecting the integrity of guest virtual machines can be agreed upon by both the cloud and the customer and can be incorporated in the service level agreement (SLA).Based onhypothetical analysis, we demonstrate that the proposedscheme has a provably safe and highly adroit dataintegrity inspection measure.
Micro-Neuro-Sensor Recording of STN Neurons of the Human Brain
What cause to the neurons of the human brain cells when they are damaged. They become inactive. So damage to subthalamiuc nucleus (STN) neurons of the human brain causing larger involuntary movements and thereby attacking the Parkinson’s disease (PD). Deep brain stimulation (DBS) of bilateral sub thalamic nuclei (STN) is an efficient method of rehabilitation technique in subjects with advanced idiopathic Parkinson’s (or Parkinson) disease. Accurate targeting of STN neurons and placement of microelectrodes/ (neurosensors) are paramount importance for optimal results after STN-DBS method.In this paper, microminiaturized electrode recordings (MER) of STN neurons were detected in a mean of 3.5 ±1.1 channels on right hemisphere and 3.6 ±1.04 on left hemisphere.Final channel selected were most commonly central seen in 42.3% followed by anterior in 33.7%. When a high current is delivered to STN or GPi neurons of basal ganglia (a component of human brain), causing their inhibition and improved indication of symptoms. It is now known that there is a significant change in the firing pattern and a reorganization of the entire basal ganglia circuit with DBS. The MER of STN neurons has identified a specific high frequency irregular larger amplitude firing patterns seen only in disease states and hence used to detect the neurons of ST nucleus during functional surgery. Microelectrode recording is so useful to confirm the right path but has to be taken in consideration with effects on macro stimulation.
EDM: Finding Answers to Reduce Dropout Rates in Schools
The focus of this paper is to get a bird's eye view of the various factors that could be analyzed to present schools and governments timely indicators of school dropouts. With the help of EDM, one could have access to enormous amounts of data. The crux of the matter would be to identify the data in line with plans and ideas that would eventually lead to the formulation of policies that enhance the teaching and learning process.
Analysis of Effort Estimation Model in Traditional and Agile (USING METRICS ...
Agile software development has been gaining popularity and replacing the traditional methods of developing software. However, estimating the size and effort in Agile software development still remains a challenge. Measurement practices in agile methods are more important than traditional methods, because lack of appropriate an effective measurement practices will increase the risk of project. This paper discuss about traditional and agile effort estimation model, and analysis done on how the metrics are used in estimation process. The paper also suggeststo use object point and use case point to improve accuracy of effort in agile software development.
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Signatures of wave erosion in Titan’s coasts
The shorelines of Titan’s hydrocarbon seas trace flooded erosional landforms such as river valleys; however, it isunclear whether coastal erosion has subsequently altered these shorelines. Spacecraft observations and theo-retical models suggest that wind may cause waves to form on Titan’s seas, potentially driving coastal erosion,but the observational evidence of waves is indirect, and the processes affecting shoreline evolution on Titanremain unknown. No widely accepted framework exists for using shoreline morphology to quantitatively dis-cern coastal erosion mechanisms, even on Earth, where the dominant mechanisms are known. We combinelandscape evolution models with measurements of shoreline shape on Earth to characterize how differentcoastal erosion mechanisms affect shoreline morphology. Applying this framework to Titan, we find that theshorelines of Titan’s seas are most consistent with flooded landscapes that subsequently have been eroded bywaves, rather than a uniform erosional process or no coastal erosion, particularly if wave growth saturates atfetch lengths of tens of kilometers.
Immersive Learning That Works: Research Grounding and Paths Forward
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
Anti-Universe And Emergent Gravity and the Dark Universe
Recent theoretical progress indicates that spacetime and gravity emerge together from the entanglement structure of an underlying microscopic theory. These ideas are best understood in Anti-de Sitter space, where they rely on the area law for entanglement entropy. The extension to de Sitter space requires taking into account the entropy and temperature associated with the cosmological horizon. Using insights from string theory, black hole physics and quantum information theory we argue that the positive dark energy leads to a thermal volume law contribution to the entropy that overtakes the area law precisely at the cosmological horizon. Due to the competition between area and volume law entanglement the microscopic de Sitter states do not thermalise at sub-Hubble scales: they exhibit memory effects in the form of an entropy displacement caused by matter. The emergent laws of gravity contain an additional ‘dark’ gravitational force describing the ‘elastic’ response due to the entropy displacement. We derive an estimate of the strength of this extra force in terms of the baryonic mass, Newton’s constant and the Hubble acceleration scale a0 = cH0, and provide evidence for the fact that this additional ‘dark gravity force’ explains the observed phenomena in galaxies and clusters currently attributed to dark matter.
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...Advanced-Concepts-Team
Presentation in the Science Coffee of the Advanced Concepts Team of the European Space Agency on the 07.06.2024.
Speaker: Diego Blas (IFAE/ICREA)
Title: Gravitational wave detection with orbital motion of Moon and artificial
Abstract:
In this talk I will describe some recent ideas to find gravitational waves from supermassive black holes or of primordial origin by studying their secular effect on the orbital motion of the Moon or satellites that are laser ranged.11.1 Role of physical biological in deterioration of grains.pdf
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Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Wereport the study of a huge optical intraday flare on 2021 November 12 at 2 a.m. UT in the blazar OJ287. In the binary black hole model, it is associated with an impact of the secondary black hole on the accretion disk of the primary. Our multifrequency observing campaign was set up to search for such a signature of the impact based on a prediction made 8 yr earlier. The first I-band results of the flare have already been reported by Kishore et al. (2024). Here we combine these data with our monitoring in the R-band. There is a big change in the R–I spectral index by 1.0 ±0.1 between the normal background and the flare, suggesting a new component of radiation. The polarization variation during the rise of the flare suggests the same. The limits on the source size place it most reasonably in the jet of the secondary BH. We then ask why we have not seen this phenomenon before. We show that OJ287 was never before observed with sufficient sensitivity on the night when the flare should have happened according to the binary model. We also study the probability that this flare is just an oversized example of intraday variability using the Krakow data set of intense monitoring between 2015 and 2023. We find that the occurrence of a flare of this size and rapidity is unlikely. In machine-readable Tables 1 and 2, we give the full orbit-linked historical light curve of OJ287 as well as the dense monitoring sample of Krakow.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
Compexometric titration/Chelatorphy titration/chelating titration
Classification
Metal ion ion indicators
Masking and demasking reagents
Estimation of Magnisium sulphate
Calcium gluconate
Complexometric Titration/ chelatometry titration/chelating titration, introduction, Types-
1.Direct Titration
2.Back Titration
3.Replacement Titration
4.Indirect Titration
Masking agent, Demasking agents
formation of complex
comparition between masking and demasking agents,
Indicators/Metal ion indicators/ Metallochromic indicators/pM indicators,
Visual Technique,PM indicators (metallochromic), Indicators of pH, Redox Indicators
Instrumental Techniques-Photometry
Potentiometry
Miscellaneous methods.
Complex titration with EDTA.
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Randomised Optimisation Algorithms in DAPHNE
Slides from talk:
Aleš Zamuda: Randomised Optimisation Algorithms in DAPHNE .
Austrian-Slovenian HPC Meeting 2024 – ASHPC24, Seeblickhotel Grundlsee in Austria, 10–13 June 2024
https://ashpc.eu/
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
Description:
Dive into the fascinating realm of solid-state physics with our meticulously crafted online PowerPoint presentation. This immersive educational resource offers a comprehensive exploration of the fundamental concepts, theories, and applications within the realm of solid-state physics.
From crystalline structures to semiconductor devices, this presentation delves into the intricate principles governing the behavior of solids, providing clear explanations and illustrative examples to enhance understanding. Whether you're a student delving into the subject for the first time or a seasoned researcher seeking to deepen your knowledge, our presentation offers valuable insights and in-depth analyses to cater to various levels of expertise.
Key topics covered include:
Crystal Structures: Unravel the mysteries of crystalline arrangements and their significance in determining material properties.
Band Theory: Explore the electronic band structure of solids and understand how it influences their conductive properties.
Semiconductor Physics: Delve into the behavior of semiconductors, including doping, carrier transport, and device applications.
Magnetic Properties: Investigate the magnetic behavior of solids, including ferromagnetism, antiferromagnetism, and ferrimagnetism.
Optical Properties: Examine the interaction of light with solids, including absorption, reflection, and transmission phenomena.
With visually engaging slides, informative content, and interactive elements, our online PowerPoint presentation serves as a valuable resource for students, educators, and enthusiasts alike, facilitating a deeper understanding of the captivating world of solid-state physics. Explore the intricacies of solid-state materials and unlock the secrets behind their remarkable properties with our comprehensive presentation.
Authoring a personal GPT for your research and practice: How we created the Q...
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
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Few More Results on Sum Labeling of Split Graphs
- 1. International Journal of Computing Algorithm, Vol 3(3), June 2014 ISSN(Print):2278-2397 Website: www.ijcoa.com Few More Results on Sum Labeling of Split Graphs J. Gerard Rozario Department of Mathematics, IFET College of Engineering, Villupuram, Tamil Nadu, India E-mail: rozario.gerard@yahoo.com Abstract A sum labeling is a mapping λ from the vertices of G into the positive integers such that, for any two vertices u, v ϵ V (G) with labels λ(u) and λ(v), respectively, (uv) is an edge iff λ(u) + λ(v) is the label of another vertex in V (G). Any graph supporting such a labeling is called a sum graph. It is necessary to add (as a disjoint union) a component to sum label a graph. This disconnected component is a set of isolated vertices known as isolates and the labeling scheme that requires the fewest isolates is termed optimal. The number of isolates required for a graph to support a sum labeling is known as the sum number of the graph. In this paper, we will obtain optimal sum labeling scheme for path union of split graph of star, K , ⨀Spl(P ) and K , ⨀Spl(K , ).