Search results for: imbalanced data with class overlap
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25834

Search results for: imbalanced data with class overlap

25714 Flipped Classroom Instruction: Reflecting on the Experiences of Teachers and Students at Undergraduate University Level

Authors: Mubeshera Tufail

Abstract:

The purpose of the study was to explore the experiences and challenges faced by teachers and students with Flipped Classroom Instruction (FCI) for an undergraduate course at university level. The Flipped Classroom lesson plan consisted of two components: one was out-of-class component consisting of learning material for reading for students and other was within-class component involving a class quiz, class activity and the feedback/further reading task. Besides, experiences, the research study also covered the adaptations made to improve their experiences with Flipped Classroom during the study. The phenomenological research strategy was used for this research study. The data consisted of weekly reflective journals documented by class teacher and students. The reflective journals were recorded by teacher and students while working in Flipped Classroom for an undergraduate course at university level. The main challenges highlighted by teacher were related to effort and time required for planning, time management and students' guidance for shift of their role from passive to independent learner. The main challenges found in reflective journals of students were personal computers issue, electricity and internet speed issue. It is recommended to adapt to some locally useful lesson planning and classroom management techniques to enhance the effectiveness of Flipped Classroom Instruction in an undergraduate university level course.

Keywords: flipped classroom instruction, undergraduate students, independent learner, technology-integrated classroom

Procedia PDF Downloads 135
25713 Optimal Cropping Pattern in an Irrigation Project: A Hybrid Model of Artificial Neural Network and Modified Simplex Algorithm

Authors: Safayat Ali Shaikh

Abstract:

Software has been developed for optimal cropping pattern in an irrigation project considering land constraint, water availability constraint and pick up flow constraint using modified Simplex Algorithm. Artificial Neural Network Models (ANN) have been developed to predict rainfall. AR (1) model used to generate 1000 years rainfall data to train the ANN. Simulation has been done with expected rainfall data. Eight number crops and three types of soil class have been considered for optimization model. Area under each crop and each soil class have been quantified using Modified Simplex Algorithm to get optimum net return. Efficacy of the software has been tested using data of large irrigation project in India.

Keywords: artificial neural network, large irrigation project, modified simplex algorithm, optimal cropping pattern

Procedia PDF Downloads 179
25712 College Students’ Multitasking and Its Causes

Authors: Huey-Wen Chou, Shuo-Heng Liang

Abstract:

This study focuses on studying college students’ multitasking with cellphones/laptops during lectures. In-class multitasking behavior is defined as the activities students engaged that are irrelevant to learning. This study aims to understand if students' learning engagement affects students' multitasking as well as to investigate the causes or motivations that contribute to the occurrence of multitasking behavior. Survey data were collected and analyzed by PLS method and multiple regression to test the research model and hypothesis. Major results include: 1. Students' multitasking motivation positively predicts students’ in-class multitasking. 2. Factors affecting multitasking in class, including efficiency, entertainment and social needs, significantly impact on multitasking. 3. Polychronic personality traits will positively predict students’ multitasking. 4. Students' classroom learning engagement negatively predicts multitasking. 5. Course attributes negatively predict student learning engagement and positively predict student multitasking.

Keywords: engagement, monochronic personality, multitasking, learning, personality traits

Procedia PDF Downloads 115
25711 Satire of Victorian Mores in Charles Dickens’ Great Expectations

Authors: Nagwa Abouserie Soliman

Abstract:

The Victorian era, which started with the reign of Queen Victoria from June 1837 to January 1901, could be considered as one of the most significant eras that had a crucial impact which formed contemporary British life despite the fact that with the rise of the British empire many negative aspects surfaced, namelysocial inequalities such as class differences, child labor, population increase and poverty due to the industrial revolution. Charles Dickens was one of the most prominent writers of the Victorian era who perceived the hypocrisy of the Victorian mores. The appropriate researchstyle that was chosen for this literary analysis is a qualitative research method in which the researcher used the conceptual approach to analyse theDickensian characterisation andwriting style through diction, narrative voice, and images. The aim of this paper is to argue that Charles Dickens inGreat Expectations (1861) was highly satirical of the Victorian mores, as he uses a lot of sharp irony-to satirize various Victorian traditions such as class divisions, the justice system, the poor working class, and the upper-class snobbery that he thought are inhumane and unjust.

Keywords: victorian, child labour, poverty, class division, snobbery

Procedia PDF Downloads 104
25710 Application of Advanced Remote Sensing Data in Mineral Exploration in the Vicinity of Heavy Dense Forest Cover Area of Jharkhand and Odisha State Mining Area

Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

Abstract:

The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

Procedia PDF Downloads 94
25709 An Experimental Study on the Influence of Brain-Break in the Classroom on the Physical Health and Academic Performance of Fourth Grade Students

Authors: Qian Mao, Xiaozan Wang, Jiarong Zhong, Xiaolin Zou

Abstract:

Introduction: As a result of the decline of students' physical health level and the increase of study pressure, students’ academic performance is not so good. Objective: This study aims to verify whether the Brain-Break intervention in the fourth-grade classroom of primary school can improve students' physical health and academic performance. Methods: According to the principle of no difference in pre-test data, students from two classes of grade four in Fuhai Road Primary School, Fushan district, Yantai city, Shandong province, were selected as experimental subjects, including 50 students in the experimental class (25 males and 25 females) and 50 students in the control class (24 males and 26 females). The content of the experiment was that the students were asked to perform a 4-minute Brain-Berak program designed by the researcher in the second class in the morning and the afternoon, and the intervention lasted for 12 weeks. In addition, the lung capacity, 50-meter run, sitting body forward bend, one-minute jumping rope and one-minute sit-ups stipulated in the national standards for physical fitness of students (revised in 2014) were selected as the indicators of physical health. The scores of Chinese, Mathematics, and English in the unified academic test of the municipal education bureau were selected as the indicators of academic performance. The independent-sample t-test was used to compare and analyze the data of each index between the two classes. The paired-sample t-test was used to compare and analyze the data of each index in the two classes. This paper presents only results with significant differences. Results: in terms of physical health, lung capacity (P=0.002, T= -2.254), one-minute rope skipping (P=0.000, T=3.043), and one-minute sit-ups (P=0.045, T=6.153) were significantly different between the experimental class and the control class. In terms of academic performance, there is a significant difference between the Chinese performance of the experimental class and the control class (P=0.009, T=4.833). Conclusion: Adding Brain-Berak intervention in the classroom can effectively improve the cardiorespiratory endurance (lung capacity), coordination (jumping rope), and abdominal strength (sit-ups) of fourth-grade students. At the same time, it can also effectively improve their Chinese performance. Therefore, it is suggested to promote micro-sports in the classroom of primary schools throughout the country so as to help students improve their physical health and academic performance.

Keywords: academic performance, brain break, fourth grade, physical health

Procedia PDF Downloads 77
25708 Energy-Efficient Contact Selection Method for CARD in Wireless Ad-Hoc Networks

Authors: Mehdi Assefi, Keihan Hataminezhad

Abstract:

One of the efficient architectures for exploring the resources in wireless ad-hoc networks is contact-based architecture. In this architecture, each node assigns a unique zone for itself and each node keeps all information from inside the zone, as well as some from outside the zone, which is called contact. Reducing the overlap between different zones of a node and its contacts increases its performance, therefore Edge Method (EM) is designed for this purpose. Contacts selected by EM do not have any overlap with their sources, but for choosing the contact a vast amount of information must be transmitted. In this article, we will offer a new protocol for contact selection, which is called PEM. The objective would be reducing the volume of transmitted information, using Non-Uniform Dissemination Probabilistic Protocols. Consumed energy for contact selection is a function of the size of transmitted information between nodes. Therefore, by reducing the content of contact selection message using the PEM will decrease the consumed energy. For evaluation of the PEM we applied the simulation method. Results indicated that PEM consumes less energy compared to EM, and by increasing the number of nodes (level of nodes), performance of PEM will improve in comparison with EM.

Keywords: wireless ad-hoc networks, contact selection, method for CARD, energy-efficient

Procedia PDF Downloads 263
25707 Theoretical Study of the Structural and Elastic Properties of Semiconducting Rare Earth Chalcogenide Sm1-XEuXS under Pressure

Authors: R. Dubey, M. Sarwan, S. Singh

Abstract:

We have investigated the phase transition pressure and associated volume collapse in Sm1– X EuX S alloy (0≤x≤1) which shows transition from discontinuous to continuous as x is reduced. The calculated results from present approach are in good agreement with experimental data available for the end point members (x=0 and x=1). The results for the alloy counter parts are also in fair agreement with experimental data generated from the vegard’s law. An improved interaction potential model has been developed which includes coulomb, three body interaction, polarizability effect and overlap repulsive interaction operative up to second neighbor ions. It is found that the inclusion of polarizability effect has improved our results.

Keywords: elastic constants, high pressure, phase transition, rare earth compound

Procedia PDF Downloads 396
25706 The Mechanisms of Peer-Effects in Education: A Frame-Factor Analysis of Instruction

Authors: Pontus Backstrom

Abstract:

In the educational literature on peer effects, attention has been brought to the fact that the mechanisms creating peer effects are still to a large extent hidden in obscurity. The hypothesis in this study is that the Frame Factor Theory can be used to explain these mechanisms. At heart of the theory is the concept of “time needed” for students to learn a certain curricula unit. The relations between class-aggregated time needed and the actual time available, steers and hinders the actions possible for the teacher. Further, the theory predicts that the timing and pacing of the teachers’ instruction is governed by a “criterion steering group” (CSG), namely the pupils in the 10th-25th percentile of the aptitude distribution in class. The class composition hereby set the possibilities and limitations for instruction, creating peer effects on individual outcomes. To test if the theory can be applied to the issue of peer effects, the study employs multilevel structural equation modelling (M-SEM) on Swedish TIMSS 2015-data (Trends in International Mathematics and Science Study; students N=4090, teachers N=200). Using confirmatory factor analysis (CFA) in the SEM-framework in MPLUS, latent variables are specified according to the theory, such as “limitations of instruction” from TIMSS survey items. The results indicate a good model fit to data of the measurement model. Research is still in progress, but preliminary results from initial M-SEM-models verify a strong relation between the mean level of the CSG and the latent variable of limitations on instruction, a variable which in turn have a great impact on individual students’ test results. Further analysis is required, but so far the analysis indicates a confirmation of the predictions derived from the frame factor theory and reveals that one of the important mechanisms creating peer effects in student outcomes is the effect the class composition has upon the teachers’ instruction in class.

Keywords: compositional effects, frame factor theory, peer effects, structural equation modelling

Procedia PDF Downloads 108
25705 Identity Crisis and Class Difference in Charles Dickens' 'Great Expectations'

Authors: Ramin Barati, Atefeh Salemi

Abstract:

In Victorian era, the society had been surrounded by extreme class ranking in order to identify the people of the classes and to intensify power relationships due to the growth of industry in Charles Dickens's (1812-1870) Great Expectations (2003) in which he illustrates the clash and dichotomy in the 19th century London. The classes in Victorian period have socially divided the population into two parts, the lower and the upper class of the community. In such a panopticon society, the major character Pip was the best example of the working class who was under the domination of violence, malice, and abuse of Miss Havisham as a member of the ruling class in order to take revenge on her failures. The conflict and disunity represented in vindictiveness and the sense of revenge applied by Miss Havisham against his victim Pip, made him experience alienation and eventually suffer from identity crisis. This paper considers New Historicism based on the theories of the French critic Michel Foucault (1926-1984). The social concept, panopticism, was called after the panopticon society, basically elaborated by Foucault in his book Discipline and Punish (1975) and he considers the panopticon as a sign of punitive community of surveillance. This paper evaluates the problems of a dual society to show that the people of the lower class are under the domination of capitalist society.

Keywords: class, identity crisis, violence, panoptic society, domination

Procedia PDF Downloads 190
25704 Capacitive Coupling Wireless Power Transfer System with 6.78 MHz Class D Inverter

Authors: Kang Hyun Yi

Abstract:

Wireless power transfer technologies are inductive coupling, magnetic resonance, and capacitive coupling methods, typically. Among them, the capacitive coupling wireless power transfer, also named Capacitive Coupling Wireless Power Transfer (CCWPT), has been researched to overcome the drawbacks of other approaches. The CCWPT has many advantages such as a simple structure, low standing power loss, reduced Electromagnetic Interference (EMI) and the ability to transfer power through metal barriers. In this paper, the CCWPT system with 6.78MHz class D inverter is proposed and analyzed. The proposed system is consisted of the 6.78MHz class D inverter with the LC low pass filter, the capacitor between a transmitter and a receiver and impedance transformers. The system is verified with a prototype for charging mobile devices.

Keywords: wireless power transfer, capacitive coupling power transfer, class D inverter, 6.78MHz

Procedia PDF Downloads 624
25703 Description of Geotechnical Properties of Jabal Omar

Authors: Ibrahim Abdel Gadir Malik, Dafalla Siddig Dafalla, Osama Abdelgadir El-Bushra

Abstract:

Geological and engineering characteristics of intact rock and the discontinuity surfaces was used to describe and classify rock mass into zones based on mechanical and physical properties. Many conditions terms that affect the rock mas; such as Rock strength, Rock Quality Designation (RQD) value, joint spacing, and condition of joint, water condition with block size, joint roughness, separation, joint hardness, friction angle and weathering were used to classify the rock mass into: Good quality (class II) (RMR values range between 75% and 56%), Good to fair quality (class II to III) (RMR values range between 70% and 55%), Fair quality (class III) (RMR values range between 60% and 50%) and Fair to poor quality (Class III to IV) (RMR values, range between (50% and 35%).

Keywords: rock strength, RQD, joints, weathering

Procedia PDF Downloads 385
25702 Data Mining Spatial: Unsupervised Classification of Geographic Data

Authors: Chahrazed Zouaoui

Abstract:

In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

Procedia PDF Downloads 358
25701 Second Representation of Modules over Commutative Rings

Authors: Jawad Abuhlail, Hamza Hroub

Abstract:

Let R be a commutative ring. Representation theory studies the representation of R-modules as (possibly finite) sums of special types of R-submodules. Here we are interested in a class of R-modules between the class of semisimple R-modules and the class of R-modules that can be written as (possibly finite) sums of secondary R-submodules (we know that every simple R-submodule is secondary). We investigate R-modules which can be written as (possibly finite) sums of second R-submodules (we call those modules second representable). Moreover, we investigate the class of (main) second attached prime ideals related to a module with such representation. We provide sufficient conditions for an R-module M to get a (minimal) second representation. We also found the collection of second attached prime ideals for some types of second representable R-modules, in particular within the class of injective R-modules. As we know that every simple R-submodule is second and every second R-submodule is secondary, we can see the importance of the second representable R-module.

Keywords: lifting modules, second attached prime ideals, second representations, secondary representations, semisimple modules, second submodules

Procedia PDF Downloads 160
25700 Visualizing Class Metrics and Object Calls for Software Systems

Authors: Mohammad Alnabhan, Awni Hammouri, Mustafa Hammad, Anas Al-Badareen, Omamah Al-Thnebat

Abstract:

Software visualization is one of the main techniques used to simplify the presentation of software systems and enhance their understandability. It is used to present the software system in a visual manner using simple, clear and meaningful symbols. This study proposes a new 2D software visualization approach. In this approach, each class is represented by rectangle, the name of the class placed above the rectangle, the size of class (Line of Code) represented by the height of the rectangle. The methods and the attributes are represented by circles and triangles respectively. The relationships among classes correspond to arrows. The proposed visualization approach was evaluated in terms of applicability and efficiency. Results have confirmed successful implementation of the proposed approach, and its ability to provide a simple and effective graphical presentation of extracted software components and properties.

Keywords: software visualization, software metrics, calling relationships, 2D graphs

Procedia PDF Downloads 172
25699 The Effectiveness of Synthesizing A-Pillar Structures in Passenger Cars

Authors: Chris Phan, Yong Seok Park

Abstract:

The Toyota Camry is one of the best-selling cars in America. It is economical, reliable, and most importantly, safe. These attributes allowed the Camry to be the trustworthy choice when choosing dependable vehicle. However, a new finding brought question to the Camry’s safety. Since 1997, the Camry received a “good” rating on its moderate overlap front crash test through the Insurance Institute of Highway Safety. In 2012, the Insurance Institute of Highway Safety introduced a frontal small overlap crash test into the overall evaluation of vehicle occupant safety test. The 2012 Camry received a “poor” rating on this new test, while the 2015 Camry redeemed itself with a “good” rating once again. This study aims to find a possible solution that Toyota implemented to reduce the severity of a frontal small overlap crash in the Camry during a mid-cycle update. The purpose of this study is to analyze and evaluate the performance of various A-pillar shapes as energy absorbing structures in improving passenger safety in a frontal crash. First, A-pillar structures of the 2012 and 2015 Camry were modeled using CAD software, namely SolidWorks. Then, a crash test simulation using ANSYS software, was applied to the A-pillars to analyze the behavior of the structures in similar conditions. Finally, the results were compared to safety values of cabin intrusion to determine the crashworthy behaviors of both A-pillar structures by measuring total deformation. This study highlights that it is possible that Toyota improved the shape of the A-pillar in the 2015 Camry in order to receive a “good” rating from the IIHS safety evaluation once again. These findings can possibly be used to increase safety performance in future vehicles to decrease passenger injury or fatality.

Keywords: A-pillar, Crashworthiness, Design Synthesis, Finite Element Analysis

Procedia PDF Downloads 93
25698 Heterogeneity of Thinking: Religious Beliefs and Logical Concepts

Authors: Alisa Rekunova

Abstract:

According to the theory of word meaning structure developed by Lev Vygotsky (and later modified by Aaro Toomela), there are several levels of thought: sensory-based concepts, situation concepts, logical concepts, and structural-systemic concepts. There are differences between people who have relatively easy access to logical thought compared to those who mostly tend to think in everyday concepts. Religious beliefs are connected with unprovable concepts (Christian Jesus’s ascension or Pagan energy) that cannot be non-controversially related to scientific concepts. However, many scientists in the research are believers of some kinds. Religious views can be different: there are believers, non-believers (atheists), and undecided (we can call them agnostics). Some of the respondents say that scientific or professional and religious spheres do not overlap. Therefore, we can assume they do not see any conflict. Some of them, on the contrary, hesitate to answer and we can conclude they see the conflicts, but they do not want (or do not believe they are able to) to solve it. Finally, the third category of respondents says that religious beliefs and scientific concepts cannot coexist in the human mind. It can be expected that the third category of respondents should have higher education (or even work in the scientific field) but many scientists in the research answer that religious and scientific spheres do not overlap. Therefore, there are other things besides the level of education that is connected with resolving conflicts.

Keywords: conflicts in thinking, cultural-historical psychology, heterogeneity of thinking, religious thinking

Procedia PDF Downloads 121
25697 Constructing the Cult of the Self: On White, Working-Class Males and the Neoliberalisation of Identities: An Autoethnographic Study

Authors: Dane B. Norris

Abstract:

This paper offers a reflective and reflexive examination of the lived reality of a group of young white, working-class males engaging in secondary education in England at a time when this population is widely recognised as the lowest attaining ethnic group within British schools. The focus of the paper is an exploration of the development of identities and aspirations alongside contemporary demographic shifts in the British population within the intersection of neoliberal education policies and the emerging ideological conflict between identity conservatism and liberalism. The construction and performance of intersecting social-class, gender, ethnic and national identities are considered, as well as the process through which socially constructed narratives inform identities and aspirations. Evocative autoethnography is then employed to offer reflections on working-class habitus and, in particular, classed and gendered codes that underpin expectations of manhood in post-industrial culture within an education system which seemingly requires the abandonment of aspects of a working-class background, affiliation, and identity. Findings from the study identify the emergence of a culture of hyper-individualisation amongst white, working-class males in schools and a belief in the meritocratic ideologies of the New Right. In particular, the breakdown of the social contract, including notions of political and civic responsibility, coupled with the symbolic violence perpetrated against working-class culture and solidarity in British schools, have all informed the construction of working-class masculinity which values the individual entrepreneur over the collective and depoliticizes students to an extent where a focus on the spectacle and performance of success has replaced individual and collective investment in community.

Keywords: education, identity, masculinity, neoliberalism, working-class

Procedia PDF Downloads 81
25696 A Hybrid Feature Selection and Deep Learning Algorithm for Cancer Disease Classification

Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

Abstract:

Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

Procedia PDF Downloads 90
25695 Automatic API Regression Analyzer and Executor

Authors: Praveena Sridhar, Nihar Devathi, Parikshit Chakraborty

Abstract:

As the software product changes versions across releases, there are changes to the API’s and features and the upgrades become necessary. Hence, it becomes imperative to get the impact of upgrading the dependent components. This tool finds out API changes across two versions and their impact on other API’s followed by execution of the automated regression suites relevant to updates and their impacted areas. This tool has 4 layer architecture, each layer with its own unique pre-assigned capability which it does and sends the required information to next layer. This are the 4 layers. 1) Comparator: Compares the two versions of API. 2) Analyzer: Analyses the API doc and gives the modified class and its dependencies along with implemented interface details. 3) Impact Filter: Find the impact of the modified class on the other API methods. 4) Auto Executer: Based on the output given by Impact Filter, Executor will run the API regression Suite. Tool reads the java doc and extracts the required information of classes, interfaces and enumerations. The extracted information is saved into a data structure which shows the class details and its dependencies along with interfaces and enumerations that are listed in the java doc.

Keywords: automation impact regression, java doc, executor, analyzer, layers

Procedia PDF Downloads 463
25694 Assessing Student Collaboration in Music Ensemble Class: From the Formulation of Grading Rubrics to Their Effective Implementation

Authors: Jason Sah

Abstract:

Music ensemble class is a non-traditional classroom in the sense that it is always a group effort during rehearsal. When measuring student performance ability in class, it is imperative that the grading rubric includes a collaborative skill component. Assessments that stop short of testing students' ability to make music with others undermine the group mentality by elevating individual prowess. Applying empirical and evidence-based methodology, this research develops a grading rubric that defines the criteria for assessing collaborative skill, and then explores different strategies for implementing this rubric in a timely and effective manner. Findings show that when collaborative skill is regularly tested, students gradually shift their attention from playing their own part well to sharing their part with others.

Keywords: assessment, ensemble class, grading rubric, student collaboration

Procedia PDF Downloads 111
25693 Towards Efficient Reasoning about Families of Class Diagrams Using Union Models

Authors: Tejush Badal, Sanaa Alwidian

Abstract:

Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

Procedia PDF Downloads 48
25692 Feature Extraction and Classification Based on the Bayes Test for Minimum Error

Authors: Nasar Aldian Ambark Shashoa

Abstract:

Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

Procedia PDF Downloads 503
25691 Dynamic Distribution Calibration for Improved Few-Shot Image Classification

Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

Abstract:

Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

Procedia PDF Downloads 36
25690 Secure Multiparty Computations for Privacy Preserving Classifiers

Authors: M. Sumana, K. S. Hareesha

Abstract:

Secure computations are essential while performing privacy preserving data mining. Distributed privacy preserving data mining involve two to more sites that cannot pool in their data to a third party due to the violation of law regarding the individual. Hence in order to model the private data without compromising privacy and information loss, secure multiparty computations are used. Secure computations of product, mean, variance, dot product, sigmoid function using the additive and multiplicative homomorphic property is discussed. The computations are performed on vertically partitioned data with a single site holding the class value.

Keywords: homomorphic property, secure product, secure mean and variance, secure dot product, vertically partitioned data

Procedia PDF Downloads 392
25689 Constructing the Cult of the Self: on White, Working-class Males And The Neoliberalisation Of Identities – An Autoethnographic Study

Authors: Dane Morace-Court

Abstract:

This paper offers a reflective and reflexive examination of the lived experience of a group of young, white, working-class males engaging in secondary-education in England at a time when this population is widely recognised as the lowest attaining ethnic group within British schools. The focus of the paper is an exploration of the development of identities and aspirations, alongside contemporary demographic and ideological shifts in the British population, in their intersection with neoliberal education policies and the emerging ideological conflict between identity conservatism and liberalism. The construction and performance of intersecting social-class, gender, ethnic and national identities is considered as well as the process through which socially constructed narratives inform identities, values, and aspirations. Evocative autoethnography is then employed to offer reflections on working-class habitus and, in particular, classed and gendered codes that underpin expectations of manhood in post-industrial culture within an education system which seemingly requires the abandonment of aspects of a working-class background. Findings from the study identify the emergence of a culture of hyper-individualisation amongst white, working-class males in schools and a belief in the meritocratic ideologies of the New Right. In particular, the breakdown of the social contract, including notions of political and civic responsibility, coupled with the symbolic violence perpetrated against working-class culture and solidarity in British schools, have all informed the construction of a working-class masculinity which values the individual entrepreneur over the collective, and depoliticizes students to an extent where a focus on the spectacle and performance of success has replaced individual and collective investment in community.

Keywords: education, identity, masculinity, neoliberalism, working-class, intersectionality, autoethnography

Procedia PDF Downloads 79
25688 Flipped Learning in the Delivery of Structural Analysis

Authors: Ali Amin

Abstract:

This paper describes a flipped learning initiative which was trialed in the delivery of the course: structural analysis and modelling. A short series of interactive videos were developed, which introduced the key concepts of each topic. The purpose of the videos was to introduce concepts and give the students more time to develop their thoughts prior to the lecture. This allowed more time for face to face engagement during the lecture. As part of the initial study, videos were developed for half the topics covered. The videos included a short summary of the key concepts ( < 10 mins each) as well as fully worked-out examples (~30mins each). Qualitative feedback was attained from the students. On a scale from strongly disagree to strongly agree, students were rate statements such as 'The pre-class videos assisted your learning experience', 'I felt I could appreciate the content of the lecture more by watching the videos prior to class'. As a result of the pre-class engagement, the students formed more specific and targeted questions during class, and this generated greater comprehension of the material. The students also scored, on average, higher marks in questions pertaining to topics which had videos assigned to them.

Keywords: flipped learning, structural analysis, pre-class videos, engineering education

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25687 Survival Data with Incomplete Missing Categorical Covariates

Authors: Madaki Umar Yusuf, Mohd Rizam B. Abubakar

Abstract:

The survival censored data with incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. With model when the missing covariates are categorical, a useful technique for obtaining parameter estimates is the EM by the method of weights. The survival outcome for the class of generalized linear model is applied and this method requires the estimation of the parameters of the distribution of the covariates. In this paper, we propose some clinical trials with ve covariates, four of which have some missing values which clearly show that they were fully censored data.

Keywords: EM algorithm, incomplete categorical covariates, ignorable missing data, missing at random (MAR), Weibull Distribution

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25686 Unseen Classes: The Paradigm Shift in Machine Learning

Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

Abstract:

Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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25685 Influence of Instructors in Engaging Online Graduate Students in Active Learning in the United States

Authors: Ehi E. Aimiuwu

Abstract:

As of 2017, many online learning professionals, institutions, and journals are still wondering how instructors can keep student engaged in the online learning environment to facilitate active learning effectively. The purpose of this qualitative single-case and narrative research is to explore whether online professors understand their role as mentors and facilitators of students’ academic success by keeping students engaged in active learning based on personalized experience in the field. Data collection tools that were used in the study included an NVivo 12 Plus qualitative software, an interview protocol, a digital audiotape, an observation sheet, and a transcription. Seven online professors in the United States from LinkedIn and residencies were interviewed for this study. Eleven online teaching techniques from previous research were used as the study framework. Data analysis process, member checking, and key themes were used to achieve saturation. About 85.7% of professors agreed on rubric as the preferred online grading technique. About 57.1% agreed on professors logging in daily, students logging in about 2-5 times weekly, knowing students to increase accountability, email as preferred communication tool, and computer access for adequate online learning. About 42.9% agreed on syllabus for clear class expectations, participation to show what has been learned, and energizing students for creativity.

Keywords: class facilitation, class management, online teaching, online education, pedagogy

Procedia PDF Downloads 95