Search results for: adaptive lookup tables
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1294

Search results for: adaptive lookup tables

424 The Impact of Supporting Productive Struggle in Learning Mathematics: A Quasi-Experimental Study in High School Algebra Classes

Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal

Abstract:

Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.

Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle

Procedia PDF Downloads 47
423 Gymnastics Under Special Surveillance. The Impact Of Western Sanctions On Russian Sport

Authors: Aleksandra Majewska

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The article analyses the impact of Western sanctions on Russian rhythmic gymnastics since the outbreak of war in Ukraine. The chronological presentation of events shows how international political tensions and economic sanctions have affected the organisation of competitions, training and the careers of athletes. The article outlines the key moments and decisions that have changed the landscape of Russian sport, including the decision to change the citizenship made by some gymnasts in order to continue competing in international competitions. Russia strongly opposes participation in competitions without its flag and anthem while maintaining the view that Russian gymnasts are crucial to the prestige of rhythmic gymnastics in the world. In response to the sanctions, Russia created its own rules for rhythmic gymnastics, according to which they now compete domestically. Furthermore, this sport in Russia is strongly linked to politics, which further emphasises its importance in the national and international context. The information collected derives from numerous interviews with Russian athletes, coaches and other people, which are available only in the Russian language. The findings highlight the significant difficulties Russian athletes have faced due to their isolation in the international arena and the adaptive strategies adopted by Russia in the face of these challenges. The article makes an important contribution to understanding the consequences of global politics on the world of sport and the fate of individual athletes.

Keywords: sport, gymnastics, war in Ukraine, sanctions

Procedia PDF Downloads 26
422 Conceptualising an Open Living Museum beyond Musealization in the Context of a Historic City: Study of Bhaktapur World Heritage Site, Nepal

Authors: Shyam Sunder Kawan

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Museums are enclosed buildings encompassing and displaying creative artworks, artefacts, and discoveries for people’s knowledge and observation. In the context of Nepal, museums and exhibition areas are either adaptive to small gallery spaces in residences or ‘neo-classical palatial complexes’ that evolved during the 19th century. This study accepts the sparse occurrence of a diverse range of artworks and expressions in the country's complex cultural manifestations within vivid ethnic groups. This study explores the immense potential of one such prevalence beyond the delimitation of physical boundaries. Taking Bhaktapur World Heritage Site as a case, the study perpetuates its investigation into real-time life activities that this city and its cultural landscapes ensemble. Seeking the ‘musealization’ as an urban process to induce museums into the city precinct, this study anticipates art space into urban spaces to offer a limitless experience for this contemporary world. Unveiling art as an experiential component, this study aims to conceptualize a living heritage as an infinite resource for museum interpretation beyond just educational institute purposes.

Keywords: living museum, site museum, museulization, contemporary arts, cultural heritage, historic cities

Procedia PDF Downloads 94
421 Height of Highway Embankment for Tolerable Residual Settlement of Loose Cohesionless Subsoil Overlain by Stronger Soil

Authors: Sharifullah Ahmed

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Residual settlement of cohesionless or non-plastic soil of different strength underlying highway embankment overlain by stronger soil layer highway embankment is studied. A parametric study is carried out for different height of embankment and for different ESAL factor. The sum of elastic settlements of cohesionless subsoil due to axle induced stress and due to self-weight of pavement layers is termed as the residual settlement. The values of residual settlement (Sr) for different heights of road embankment (He) are obtained and presented as design charts for different SPT Value (N60) and ESAL factor. For rigid pavement and flexible pavement in approach to bridge or culvert, the tolerable residual settlement is 0.100m. This limit is taken as 0.200m for flexible pavement in general sections of highway without approach to bridge or culvert. A simplified guideline is developed for design of highway embankment underlain by very loose to loose cohesionless subsoil overlain by a stronger soil layer for limiting value of the residual settlement. In the current research study range of ESAL factor is 1-10 and range of SPT value (N60) is 1-10. That is found that, ground improvement is not required if the overlying stronger layer is minimum 1.5m and 4.0m for general road section of flexible pavement except bridge or culvert approach and for rigid pavement or flexible pavement in bridge or culvert approach. Tables and charts are included in the prepared guideline to obtain minimum allowable height of highway embankment to limit the residual settlement with in mentioned tolerable limit. Allowable values of the embankment height (He) are obtained corresponding to tolerable or limiting level of the residual settlement of loose subsoil for different SPT value, thickness of stronger layer (d) and ESAL factor. The developed guideline is may be issued to be used in assessment of the necessity of ground improvement in case of cohesionless subsoil underlying highway embankment overlain by stronger subsoil layer for limiting residual settlement. The ground improvement is only to be required if the residual settlement of subsoil is more than tolerable limit.

Keywords: axle pressure, equivalent single axle load, ground improvement, highway embankment, tolerable residual settlement

Procedia PDF Downloads 117
420 A New Obesity Index Derived from Waist Circumference and Hip Circumference Well-Matched with Other Indices in Children with Obesity

Authors: Mustafa M. Donma, Orkide Donma

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Anthropometric obesity indices such as waist circumference (WC), indices derived from anthropometric measurements such as waist-to-hip ratio (WHR), and indices created from body fat mass composition such as trunk-to-leg fat ratio (TLFR) are commonly used for the evaluation of mild or severe forms of obesity. Their clinical utilities are being compared using body mass index (BMI) percentiles to classify obesity groups. The best of them is still being investigated to make a clear-cut discrimination between healthy normal individuals (N-BMI) and overweight or obese (OB) or morbid obese patients. The aim of this study is to derive a new index, which best suits the purpose for the discrimination of children with N-BMI from OB children. A total of eighty-three children participated in the study. Two groups were constituted. The first group comprised 42 children with N-BMI, and the second group was composed of 41 OB children, whose age- and sex- adjusted BMI percentile values vary between 95 and 99. The corresponding values for the first group were between 15 and 85. This classification was based upon the tables created by World Health Organization. The institutional ethics committee approved the study protocol. Informed consent forms were filled by the parents of the participants. Anthropometric measurements were taken and recorded following a detailed physical examination. Within this context, weight, height (Ht), WC, hip C (HC), neck C (NC) values were taken. Body mass index, WHR, (WC+HC)/2, WC/Ht, (WC/HC)/Ht, WC*NC were calculated. Bioelectrical impedance analysis was performed to obtain body’s fat compartments in terms of total fat, trunk fat, leg fat, arm fat masses. Trunk-to-leg fat ratio, trunk-to-appendicular fat ratio (TAFR), (trunk fat+leg fat)/2 ((TF+LF)/2) were calculated. Fat mass index (FMI) and diagnostic obesity notation model assessment-II (D2I) index values were calculated. Statistical analysis of the data was performed. Significantly increased values of (WC+HC)/2, (TF+LF)/2, D2I, and FMI were observed in OB group in comparison with those of N-BMI group. Significant correlations were calculated between BMI and WC, (WC+HC)/2, (TF+LF)/2, TLFR, TAFR, D2I as well as FMI both in N-BMI and OB groups. The same correlations were obtained for WC. (WC+HC)/2 was correlated with TLFR, TAFR, (TF+LF)/2, D2I, and FMI in N-BMI group. In OB group, the correlations were the same except those with TLFR and TAFR. These correlations were not present with WHR. Correlations were observed between TLFR and BMI, WC, (WC+HC)/2, (TF+LF)/2, D2I as well as FMI in N-BMI group. Same correlations were observed also with TAFR. In OB group, correlations between TLFR or TAFR and BMI, WC as well as (WC+HC)/2 were missing. None was noted with WHR. From these findings, it was concluded that (WC+HC)/2, but not WHR, was much more suitable as an anthropometric obesity index. The only correlation valid in both groups was that exists between (WC+HC)/2 and (TF+LF)/2. This index was suggested as a link between anthropometric and fat-based indices.

Keywords: children, hip circumference, obesity, waist circumference

Procedia PDF Downloads 158
419 An Adaptive Dimensionality Reduction Approach for Hyperspectral Imagery Semantic Interpretation

Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation

Procedia PDF Downloads 340
418 Channel Sounding and PAPR Reduction in OFDM for WiMAX Using Software Defined Radio

Authors: B. Siva Kumar Reddy, B. Lakshmi

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WiMAX is a high speed broadband wireless access technology that adopted OFDM/OFDMA techniques to supply higher data rates with high spectral efficiency. However, OFDM suffers in view of high Peak to Average Power Ratio (PAPR) and high affect to synchronization errors. In this paper, the high PAPR problem is solved by using phase modulation to get Constant Envelop Orthogonal Frequency Division Multiplexing (CE-OFDM). The synchronization failures are brought down by employing a frequency lock loop, Poly phase clock synchronizer, Costas loop and blind equalizers such as Constant Modulus Algorithm (CMA) equalizer and Sign Kurtosis Maximization Adaptive Algorithm (SKMAA) equalizers. The WiMAX physical layer is executed on Software Defined Radio (SDR) prototype by utilizing USRP N210 as hardware and GNU Radio as software plat-forms. A SNR estimation is performed on the signal received through USRP N210. To empathize wireless propagation in specific environments, a sliding correlator wireless channel sounding system is designed by using SDR testbed.

Keywords: BER, CMA equalizer, Kurtosis equalizer, GNU Radio, OFDM/OFDMA, USRP N210

Procedia PDF Downloads 340
417 Comparative Analysis of Photosynthetic and Antioxidative Responses of Two Species of Anabaena under Ni and As(III) Stress

Authors: Shivam Yadav, Neelam Atri

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Cyanobacteria, the photosynthetic prokaryotes are indispensable components of paddy soil contribute substantially to the nitrogen economy however often appended with metal load. They are well known to play crucial roles in maintenance of soil fertility and rice productivity. Nickel is one such metal that plays a vital role in the cellular physiology, however at higher concentrations it exerts adverse effects. Arsenic is another toxic metalloid that negatively affects the cyanobacterial proliferation. However species-specific comparative responses under As and Ni is largely unknown. The present study focuses on the comparative effects of nickel (Ni2+) and arsenite (As(III)) on two diazotrophic cyanobacterial species (Anabaena doliolum and Anabaena sp. PCC7120) in terms of antioxidative aspects. Oxidative damage measured in terms of lipid peroxidation and peroxide content was significantly higher after As(III) than Ni treatment as compared to control. Similarly, all the studied enzymatic and non-enzymatic parameters of antioxidative defense system except glutathione reductase (GR) showed greater induction against As(III) than Ni. Moreover, integrating comparative analysis of all studied parameters also demonstrated interspecies variation in terms of stress adaptive strategies reflected through higher sensitivity of Anabaena doliolum over Anabaena PCC7120.

Keywords: antioxidative system, arsenic, cyanobacteria, nickel

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416 The Influence of Positive and Negative Affect on Perception and Judgement

Authors: Annamarija Paula

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Modern psychology is divided into three distinct domains: cognition, affect, and conation. Historically, psychology devalued the importance of studying the effect in order to explain human behavior as it supposedly lacked both rational thought and a scientific foundation. As a result, affect remained the least studied domain for years to come. However, the last 30 years have marked a significant change in perspective, claiming that not only is affect highly adaptive, but it also plays a crucial role in cognitive processes. Affective states have a crucial impact on human behavior, which led to fundamental advances in the study of affective states on perception and judgment. Positive affect and negative affect are distinct entities and have different effects on social information processing. In addition, emotions of the same valence are manifested in distinct and unique physiological reactions indicating that not all forms of positive or negative affect are the same or serve the same purpose. The effect plays a vital role in perception and judgments, which impacts the validity and reliability of memory retrieval. The research paper analyzes key findings from the past three decades of observational and empirical research on affective states and cognition. The paper also addresses the limitations connected to the findings and proposes suggestions for possible future research.

Keywords: memory, affect, perception, judgement, mood congruency effect

Procedia PDF Downloads 116
415 Examining Geometric Thinking Behaviours of Undergraduates in Online Geometry Course

Authors: Peter Akayuure

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Geometry is considered an important strand in mathematics due to its wide-ranging utilitarian value and because it serves as a building block for understanding other aspects of undergraduate mathematics, including algebra and calculus. Matters regarding students’ geometric thinking have therefore long been pursued by mathematics researchers and educators globally via different theoretical lenses, curriculum reform efforts, and innovative instructional practices. However, so far, studies remain inconclusive about the instructional platforms that effectively promote geometric thinking. At the University of Education, Winneba, an undergraduate geometry course was designed and delivered on UEW Learning Management System (LMS) using Moodle platform. This study utilizes van Hiele’s theoretical lens to examine the entry and exit’s geometric thinking behaviours of prospective teachers who took the undergraduate geometry course in the LMS platform. The study was a descriptive survey that involved an intact class of 280 first-year students enrolled to pursue a bachelor's in mathematics education at the university. The van Hiele’s Geometric thinking test was used to assess participants’ entry and exit behaviours, while semi-structured interviews were used to obtain data for triangulation. Data were analysed descriptively and displayed in tables and charts. An Independent t-test was used to test for significant differences in geometric thinking behaviours between those who entered the university with a diploma certificate and with senior high certificate. The results show that on entry, more than 70% of the prospective teachers operated within the visualization level of van Hiele’s geometric thinking. Less than 20% reached analysis and abstraction levels, and no participant reached deduction and rigor levels. On exit, participants’ geometric thinking levels increased markedly across levels, but the difference from entry was not significant and might have occurred by chance. The geometric thinking behaviours of those enrolled with diploma certificates did not differ significant from those enrolled directly from senior high school. The study recommends that the design principles and delivery of undergraduate geometry course via LMS should be structured and tackled using van Hiele’s geometric thinking levels to serve as means of bridging the existing learning gaps of undergraduate students.

Keywords: geometric thinking, van Hiele’s, UEW learning management system, undergraduate geometry

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414 English Title Adaptive Comparison of Outdoor and Indoor Social Security in Damaged Area and New Residential Complex with Two-Way Anova Case Study: Qasr-Al-Dasht and Moalem District in Shiraz

Authors: Homa Parmoon, Narges Hamzeh

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Since today's urban spaces are disposed towards behavioral disorders and lack of security, both qualitative and quantitative aspects of security especially social and physical security are considered as basic necessities in urban planning. This research focused on the variable of place of living, examined social security in the old and new textures, and investigated the amount of residents’ social security in Shiraz including safety, financial, emotional and moral security. To this end, two neighborhoods in region 1 of Shiraz- Qasr-Al-Dasht (old texture) and Moalem (new texture)- were examined through a comparative study of 60 samples lived in two neighborhoods. Data were gathered through two-way ANOVA between the variables of residential context and internal and external security. This analysis represents the significance or insignificance of the model as well as the individual effects of each independent variable on the dependent variable. It was tested by ANCOVA and F-test. Research findings indicated place of living has a significant effect on families’ social security. The safety, financial, emotional, and moral security also represented a great impact on social security. As a result, it can be concluded that social security changes with the changing in place of living.

Keywords: social security, damaged area, two-way ANOVA, Shiraz

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413 Deep Routing Strategy: Deep Learning based Intelligent Routing in Software Defined Internet of Things.

Authors: Zabeehullah, Fahim Arif, Yawar Abbas

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Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

Procedia PDF Downloads 100
412 Relevance Feedback within CBIR Systems

Authors: Mawloud Mosbah, Bachir Boucheham

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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN

Procedia PDF Downloads 270
411 The Determinant Factors of Technology Adoption for Improving Firm’s Performance; Toward a Conceptual Model

Authors: Zainal Arifin, Avanti Fontana

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Considering that TOE framework is the most useful instrument for studying technology adoption in firm context, this paper will analyze the influence of technological, organizational and environmental (TOE) factors to the Dynamic capabilities (DCs) associated with technology adoption strategy for improving the firm’s performance. Focusing on the determinant factors of technology adoption at the firm level, the study will contribute to the broader study of resource base view (RBV) and dynamic capability (DC). There is no study connecting directly the TOE factors to the DCs, this paper proposes technology adoption as a functional competence/capability which mediates a relationship between technology adoptions with firm’s performance. The study wants to show a conceptual model of the indirect effects of DCs at the firm level, which can be key predictors of firm performance in dynamic business environment. The results of this research is mostly relevant to top corporate executives (BOD) or top management team (TMT) who seek to provide some supporting ‘hardware’ content and condition such as technological factors, organizational factors, environmental factors, and to improve firm's ‘software ‘ ability such as adaptive capability, absorptive capability and innovative capability, in order to achieve a successful technology adoption in organization. There are also mediating factors which are elaborated at this paper; timing and external network. A further research for showing its empirical results is highly recommended.

Keywords: technology adoption, TOE framework, dynamic capability, resources based view

Procedia PDF Downloads 318
410 Development of Fuzzy Logic and Neuro-Fuzzy Surface Roughness Prediction Systems Coupled with Cutting Current in Milling Operation

Authors: Joseph C. Chen, Venkata Mohan Kudapa

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Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

Procedia PDF Downloads 128
409 Innovative Entrepreneurship in Tourism Business: An International Comparative Study of Key Drivers

Authors: Mohammed Gamil Montasser, Angelo Battaglia

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Entrepreneurship is mostly related to the beginning of organization. In growing business organizations, entrepreneurship expands its conceptualization. It reveals itself through new business creation in the active organization, through renewal, change, innovation, creation and development of current organization, through breaking and changing of established rules inside or outside the organization and becomes more flexible, adaptive and competitive, also improving effectiveness of organization activity. Therefore, the topic of entrepreneurship, relates the creation of firms to personal / individual characteristics of the entrepreneurs and their social context. This paper is an empirical study, which aims to address these two gaps in the literature. For this endeavor, we use the latest available data from the Global Entrepreneurship Monitor (GEM) project. This data set is widely regarded as a unique source of information about entrepreneurial activity, as well as the aspirations and attitudes of individuals across a wide number of countries and territories worldwide. This paper tries to contribute to fill this gap, by exploring the key drivers of innovative entrepreneurship in the tourism sector. Our findings are consistent with the existing literature in terms of the individual characteristics of entrepreneurs, but quite surprisingly we find an inverted U-shape relation between human development and innovative entrepreneurship in tourism sector. It has been revealed that tourism entrepreneurs are less likely to have innovative products, compared with entrepreneurs in medium developed countries.

Keywords: GEM, human development, innovative entrepreneurship, occupational choice, tourism

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408 Analysis of Hard Turning Process of AISI D3-Thermal Aspects

Authors: B. Varaprasad, C. Srinivasa Rao

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In the manufacturing sector, hard turning has emerged as vital machining process for cutting hardened steels. Besides many advantages of hard turning operation, one has to implement to achieve close tolerances in terms of surface finish, high product quality, reduced machining time, low operating cost and environmentally friendly characteristics. In the present study, three-dimensional CAE (Computer Aided Engineering) based simulation of  hard turning by using commercial software DEFORM 3D has been compared to experimental results of  stresses, temperatures and tool forces in machining of AISI D3 steel using mixed Ceramic inserts (CC6050). In the present analysis, orthogonal cutting models are proposed, considering several processing parameters such as cutting speed, feed, and depth of cut. An exhaustive friction modeling at the tool-work interfaces is carried out. Work material flow around the cutting edge is carefully modeled with adaptive re-meshing simulation capability. In process simulations, feed rate and cutting speed are constant (i.e.,. 0.075 mm/rev and 155 m/min), and analysis is focused on stresses, forces, and temperatures during machining. Close agreement is observed between CAE simulation and experimental values.

Keywords: hard turning, computer aided engineering, computational machining, finite element method

Procedia PDF Downloads 444
407 On the Use of Machine Learning for Tamper Detection

Authors: Basel Halak, Christian Hall, Syed Abdul Father, Nelson Chow Wai Kit, Ruwaydah Widaad Raymode

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The attack surface on computing devices is becoming very sophisticated, driven by the sheer increase of interconnected devices, reaching 50B in 2025, which makes it easier for adversaries to have direct access and perform well-known physical attacks. The impact of increased security vulnerability of electronic systems is exacerbated for devices that are part of the critical infrastructure or those used in military applications, where the likelihood of being targeted is very high. This continuously evolving landscape of security threats calls for a new generation of defense methods that are equally effective and adaptive. This paper proposes an intelligent defense mechanism to protect from physical tampering, it consists of a tamper detection system enhanced with machine learning capabilities, which allows it to recognize normal operating conditions, classify known physical attacks and identify new types of malicious behaviors. A prototype of the proposed system has been implemented, and its functionality has been successfully verified for two types of normal operating conditions and further four forms of physical attacks. In addition, a systematic threat modeling analysis and security validation was carried out, which indicated the proposed solution provides better protection against including information leakage, loss of data, and disruption of operation.

Keywords: anti-tamper, hardware, machine learning, physical security, embedded devices, ioT

Procedia PDF Downloads 142
406 Motion Performance Analyses and Trajectory Planning of the Movable Leg-Foot Lander

Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

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In response to the functional limitations of the fixed landers, those are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability in deep space exploration currently, a movable lander based on the leg-foot walking mechanism is presented. Firstly, a quadruped landing mechanism based on pushrod-damping is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and the multi-function main/auxiliary buffers based on the crumple-energy absorption and screw-nut mechanism. Secondly, the workspace of the end of the leg-foot mechanism is solved by Monte Carlo method, and the key points on the desired trajectory of the end of the leg-foot mechanism are fitted by cubic spline curve. Finally, an optimal time-jerk trajectory based on weight coefficient is planned and analyzed by an adaptive genetic algorithm (AGA). The simulation results prove the rationality and stability of walking motion of the movable leg-foot lander in the star catalogue. In addition, this research can also provide a technical solution integrating of soft-landing, large-scale inspection and material transfer for future star catalogue exploration, and can even serve as the technical basis for developing the reusable landers.

Keywords: motion performance, trajectory planning, movable, leg-foot lander

Procedia PDF Downloads 127
405 A Cross-Sectional Study on Clinical Self-Efficacy of Final Year School of Nursing Students among Universities of Tigray Region, Northern Ethiopia

Authors: Awole Seid, Yosef Zenebe, Hadgu Gerensea, Kebede Haile Misgina

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Background: Clinical competence is one of the ultimate goals of nursing education. Clinical skills are more than successfully performing tasks; it incorporates client assessment, identification of deficits and the ability to critically think to provide solutions. Assessment of clinical competence, particularly identifying gaps that need improvement and determining the educational needs of nursing students have great importance in nursing education. Thus this study aims determining clinical self-efficacy of final year school of nursing students in three universities of Tigray Region. Methods: A cross-sectional study was conducted on 224 final year school of nursing students from department of nursing, psychiatric nursing, and midwifery on three universities of Tigray region. Anonymous self-administered questionnaire was administered to generate data collected on June, 2017. The data were analyzed using SPSS version 20. The result is described using tables and charts as required. Logistic regression was employed to test associations. Result: The mean age of students was 22.94 + 1.44. Generally, 21% of students have been graduated in the department in which they are not interested. The study demonstrated 28.6% had poor and 71.4% had good perceived clinical self-efficacy. Beside this, 43.8% of psychiatric nursing and 32.6% of comprehensive nursing students have poor clinical self-efficacy. Among the four domains, 39.3% and 37.9% have poor clinical self- efficacy with regard to ‘Professional development’ and ‘Management of care’. Place of the institution [AOR=3.480 (1.333 - 9.088), p=0.011], interest during department selection [AOR=2.202 (1.045 - 4.642), p=.038], and theory-practice gap [AOR=0.224 (0.110 - 0.457), p=0.000] were significantly associated with perceived clinical self-efficacy. Conclusion: The magnitude of students with poor clinically self efficacy was high. Place of institution, theory-practice gap, students interest to the discipline were the significant predictors of clinical self-efficacy. Students from youngest universities have good clinical self-efficacy. During department selection, student’s interest should be respected. The universities and other stakeholders should improve the capacity of surrounding affiliate teaching hospitals to set and improve care standards in order to narrow the theory-practice gap. School faculties should provide trainings to hospital staffs and monitor standards of clinical procedures.

Keywords: clinical self-efficacy, nursing students, Tigray, northern Ethiopia

Procedia PDF Downloads 160
404 Stress and Coping Strategies: A Correlational Analysis to Profiling Maladaptive Behaviors at Work

Authors: Silvia Riva, Ezekiel Chinyio

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Introduction: Workers in different sectors are prone to stress at varying levels. They also respond to stress in different ways. An inspiration was to study stress development amongst workers in a work dangerous setting (Construction Industry) as well as how they cope with specific stress incidences. Objective: The overarching objective of the study was to study and correlate between stress and coping strategies. The research was conducted in an organizational industrial setting, and its findings on the coping actions of construction workers are reported in this article. Methods: An online cross-sectional survey was conducted with 80 participants aged 18-62. These were working for three different construction organizations in the West Midland region of the UK. Their coping actions were assessed using the COPE Inventory (Carver, 2013) instrument while the level of stress was assessed by the Perceived Stress Scale (Cohen, 1994). Results: Out of 80 workers (20 female, 25%, mean age 40.66), positive reinterpretation (M=4.15, SD=2.60) and active coping (M=4.18, SD=2.55) were the two most adaptive strategies reported by the workers while the most frequent maladaptive behavior was mental disengagement (M=3.62, SD=2.25). Among the maladaptive tactics, alcohol and drug abuse was a significant moderator in stress reactions (t=6.12, p=.000). Conclusion: Some maladaptive strategies are adopted by construction workers to cope with stress. So, it could be argued that programs of stress prevention and control in the construction industry have a basis to develop solutions that can improve and strengthen effective interventions when workers are stressed or getting stressed.

Keywords: coping, organization, strategies, stress

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403 The Experience of Applying Multi-Sensory Stimulation ICU for Arousing a Patient with Traumatic Brain Injury in Intensive Care

Authors: Hsiao-Wen Tsai

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Motor vehicle accident is the first cause of head injury in the world; severe head injury cases may cause conscious disturbance and death. This is a report about a case of a young adult patient suffering from motor vehicle accident leading to severe head injury who passed through three time surgical procedures, and his mother (who is the informal caregiver). This case was followed from 28th January to 15th February 2011 by using Gordon’s 11 functional health patterns. Patient’s cognitive-perceptual and self-perception-self-concept patterns were altered. Anxiety was also noted on his informal caregiver due to patients’ condition. During the intensive care period, maintaining patient’s vital signs and cerebral perfusion pressure were essential to avoid secondary neuronal injury. Multi-sensory stimulation, caring accompanying, supporting, listening and encouraging patient’s family involved in patient care were very important to reduce informal caregiver anxiety. Finally, the patient consciousness improved from GCS 4 to GCS 11 before discharging from ICU. Patient’s primary informal caregiver, his mother, also showed anxiety improvement. This is was successful case with traumatic brain injury recovered from coma.

Keywords: anxiety, multi-sensory stimulation, reduce intracranial adaptive capacity, traumatic brain injury

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402 The Data-Driven Localized Wave Solution of the Fokas-Lenells Equation Using Physics-Informed Neural Network

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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401 Diagnosis and Analysis of Automated Liver and Tumor Segmentation on CT

Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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400 Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning

Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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399 Touristification of Industrial Waterfronts: The Rocks and Darling Harbour

Authors: Ece Kaya

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Industrial heritage reflects the traces of an industrial past that have contributed to the economic development of a country. This heritage should be included within the scope of preservation to remind of and to connect the city and its inhabitants to the past. Through adaptive conservation, industrial heritage can be reintroduced into contemporary urban life, with suitable functions and unique identities sustained. The conservation of industrial heritage should protect the material fabric of such heritage and maintain its cultural significance. Emphasising the historical and cultural significance of industrial areas, this research argues that industrial heritage is primarily impacted by political and economic thinking rather than by informed heritage and conservation issues. Waterfront redevelopment projects create similar landscapes around the world, transforming industrial identities and cultural significances. In the case of The Rocks and Darling Harbour, the goal of redevelopment was the creation of employment opportunities, and the provision of places to work, live and shop, through tourism promoted by the NSW State Government. The two case study areas were pivotal to the European industrial development of Sydney. Sydney Cove was one of the largest commercial wharves used to handle cargo in Australia. This paper argues, together with many historians, planners and heritage experts, that these areas have not received the due diligence deserved in regards to their significance to the industrial history of Sydney and modern Australia.

Keywords: industrial heritage, post-industrial city, transformation of waterfronts, tourism, consumption

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398 Form of Social Quality Moving Process of Suburb Communities in a Changing World

Authors: Supannee Chaiumporn

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This article is to introduce the meaning and form of social quality moving process as indicated by members of two suburb communities with different social and cultural contexts. The form of social quality moving process is very significant for the community and social development, because it will make the people living together with sustainable happiness. This is a qualitative study involving 30 key-informants from two suburb communities. Data were collected though key-informant interviews, and analyzed using logical content description and descriptive statistics. This research found that on the social quality component, the people in both communities stressed the procedure for social quality-making. This includes the generousness, sharing and assisting among people in the communities. These practices helped making people to live together with sustainable happiness. Living as a family or appear to be a family is the major social characteristic of these two communities. This research also found that form of social quality’s moving process of both communities stress relation of human and nature; “nature overpower humans” paradigm and influence of religious doctrine that emphasizes relations among humans. Both criteria make the form of social’s moving process simple, adaptive to nature and caring for opinion sharing and understanding among each other before action. This form of social quality’s moving process is composed of 4 steps; (1) awareness building, (2) motivation to change, (3) participation from every party concerned (4) self-reliance.

Keywords: social quality, form of social quality moving process, happiness, different social and cultural context

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397 Hybrid Learning and Testing at times of Corona: A Case Study at an English Department

Authors: Mimoun Melliti

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In the wake of the global pandemic, educational systems worldwide faced unprecedented challenges and had to swiftly adapt to new conditions. This necessitated a fundamental shift in assessment processes, as traditional in-person exams became impractical. The present paper aims to investigate how educational systems have adapted to the new conditions imposed by the outbreak of the pandemic. This paper serves as a case study documenting the various decisions, conditions, experiments, and outcomes associated with transitioning the assessment processes of a higher education institution to a fully online format. The participants of this study consisted of 4666 students from health, engineering, science, and humanities disciplines, who were enrolled in general English (Eng101/104) and English for specific purposes (Eng102/113) courses at a preparatory year institution in Saudi Arabia. The findings of this study indicate that online assessment can be effectively implemented given the fulfillment of specific requirements. These prerequisites encompass the presence of competent staff, administrative flexibility, and the availability of necessary infrastructure and technological support. The significance of this case study lies in its comprehensive description of the various steps and measures undertaken to adapt to the "new normal" situation. Furthermore, it evaluates the impact of these measures and offers detailed recommendations for potential similar future scenarios.

Keywords: hybrid learning, testing, adaptive teaching, EFL

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396 Soft Computing Approach for Diagnosis of Lassa Fever

Authors: Roseline Oghogho Osaseri, Osaseri E. I.

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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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395 Adaptive Architecture and Urbanism - A Study of Coastal Cities, Climate Change Problems, Effects, Risks And Opportunities for Making Sustainable Habitat

Authors: Santosh Kumar Ketham

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Climate change creating most dramatic and destructive consequences, the result is global warming and sea-level rise, flooding coastal cities around the world forming vulnerable situations affecting in multiple ways: environment, economy, social and political. The aim and goal of the research is to develop cities on water. Taking the problem as an opportunity to bring science, engineering, policies and design together to make a resilient and sustainable floating community on water considering existing/new technologies of floating. The quest is to make sustainable habitat on water to live, work, learn and play.  To make sustainable energy generation and storage alongside maintaining balance of land and marine to conserve Ecosystem. The research would serve as a model for sustainable neighbourhoods designed in a modular way and thus can easily extend or re-arranged, to adapt for future socioeconomic realities.  This research paper studies primarily on climate change problems, effects, risks and opportunities. It does so, through analysing existing case studies, books and writings published on coastal cities and understanding its various aspects for making sustainable habitat.

Keywords: floating cities, flexible modular typologies, rising sea levels, sustainable architecture and urbanism

Procedia PDF Downloads 121