Search results for: generalized Douglas-Weyl (GDW) metric
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1029

Search results for: generalized Douglas-Weyl (GDW) metric

639 Measuring Entrepreneurship Intentions among Nigerian University Graduates: A Structural Equation Modeling Technique

Authors: Eunice Oluwakemi Chukwuma-Nwuba

Abstract:

Nigeria is a developing country with an increasing rate of graduate unemployment. This has triggered successive government administrations to promote the variety of programmes to address the situation. However, none of these efforts yielded the desired outcome. Accordingly, in 2006 the government included entrepreneurship module in the curriculum of universities as a compulsory general programme for all undergraduate courses. This is in the hope that the programme will help to promote entrepreneurial mind-set and new venture creation among graduates and as a result reduce the rate of graduate unemployment. The study explores the effectiveness of entrepreneurship education in promoting entrepreneurship. This study is significant in view of the endemic graduate unemployment in Nigeria and the social consequences such as youth restiveness and militancy. It is guided by the theory of planned behaviour. It employed the two-stage structural equation modelling (AMOS) to model entrepreneurial intentions as a function of innovative teaching methods, traditional teaching methods and culture Personal attitude and subjective norm are proposed to mediate the relationships between the exogenous and the endogenous variables. The first stage was tested using multi-group confirmatory factor analysis (MGCFA) framework to confirm that the two groups assign the same meaning to the scale items and to obtain goodness-of-fit indices. The multi-group confirmatory factor analysis included the tests of configural, metric and scalar invariance. With the attainment of full configural invariance and partial metric and scalar invariance, the second stage – the structural model was applied hypothesising that, the entrepreneurial intentions of graduates (respondents who have participated in the compulsory entrepreneurship programme) will be higher than those of undergraduates (respondents who are yet to participate in the programme). The study uses the quasi-experimental design. The samples comprised 409 graduates (experimental group) and 402 undergraduates (control group) from six federal universities in Nigeria. Our findings suggest that personal attitude is positively related with entrepreneurial intentions, largely confirming prior literature. However, unlike previous studies, our results indicate that subjective norm has significant direct and indirect impact on entrepreneurial intentions indicating that reference people of the participants have important roles to play in their decision to be entrepreneurial. Furthermore, unlike the assertions in prior studies, the result suggests that traditional teaching methods have indirect effect on entrepreneurial intentions supporting that since personal characteristics can change in an educational situation, an education purposively directed at entrepreneurship might achieve similar results if not better. This study has implication for practice and theory. The research extends to the theoretical understanding of the formation of entrepreneurial intentions and explains the role of the reference others in relation to how graduates perceive entrepreneurship. Further, the study adds to the body of knowledge on entrepreneurship education in Nigeria universities and provides a developing country perspective. It proposes further research in the exploration of entrepreneurship education and entrepreneurial intentions of graduates from across the country’s universities as necessary and imperative.

Keywords: entrepreneurship education, entrepreneurial intention, structural equation modeling, theory of planned behaviour

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638 Semi-Supervised Hierarchical Clustering Given a Reference Tree of Labeled Documents

Authors: Ying Zhao, Xingyan Bin

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Semi-supervised clustering algorithms have been shown effective to improve clustering process with even limited supervision. However, semi-supervised hierarchical clustering remains challenging due to the complexities of expressing constraints for agglomerative clustering algorithms. This paper proposes novel semi-supervised agglomerative clustering algorithms to build a hierarchy based on a known reference tree. We prove that by enforcing distance constraints defined by a reference tree during the process of hierarchical clustering, the resultant tree is guaranteed to be consistent with the reference tree. We also propose a framework that allows the hierarchical tree generation be aware of levels of levels of the agglomerative tree under creation, so that metric weights can be learned and adopted at each level in a recursive fashion. The experimental evaluation shows that the additional cost of our contraint-based semi-supervised hierarchical clustering algorithm (HAC) is negligible, and our combined semi-supervised HAC algorithm outperforms the state-of-the-art algorithms on real-world datasets. The experiments also show that our proposed methods can improve clustering performance even with a small number of unevenly distributed labeled data.

Keywords: semi-supervised clustering, hierarchical agglomerative clustering, reference trees, distance constraints

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637 Ab Initio Study of Hexahalometallate Single Crystals K₂XBr₆ (X=Se, Pt)

Authors: M. Fatmi, B. Gueridi, Z. Zerrougui

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Some physical properties of hexahalometallate K₂XBr₆(X=Se, Pt) were computed in the zinc blend structure using generalized gradient approximation. The cell constant of K₂SeBr₆ and K₂PtBr₆ is consistent with the experiment value quoted in the literature, where the error is 0.95 % and 1 %. K₂SeBr₆ and K₂PtBr₆ present covalent bonding, high anisotropy and are ductile. The elastic constants of K₂SeBr₆ and K₂PtBr₆ are significantly smaller due to their larger reticular distances and lower Colombian forces, and then they are soft and damage tolerant. The interatomic separation is greater in K₂SeBr₆ than in K₂PtBr₆; hence the Colombian interaction in K₂PtBr₆ is greater than that of K2SeBr₆. The internal coordinate of the Br atom in K₂PtBr₆ is lower than that of the same atom in K2SeBr₆, and this can be explained by the fact that it is inversely proportional to the atom radius of Se and Pt. There are two major plasmonic processes, with intensities of 3.7 and 1.35, located around 53.5 nm and 72.8 nm for K₂SeBr₆ and K₂PtBr₆.

Keywords: hexahalometallate, band structure, morphology, absorption, band gap, absorber

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636 SiamMask++: More Accurate Object Tracking through Layer Wise Aggregation in Visual Object Tracking

Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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635 Reducing the Computational Overhead of Metaheuristics Parameterization with Exploratory Landscape Analysis

Authors: Iannick Gagnon, Alain April

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The performance of a metaheuristic on a given problem class depends on the class itself and the choice of parameters. Parameter tuning is the most time-consuming phase of the optimization process after the main calculations and it often nullifies the speed advantage of metaheuristics over traditional optimization algorithms. Several off-the-shelf parameter tuning algorithms are available, but when the objective function is expensive to evaluate, these can be prohibitively expensive to use. This paper presents a surrogate-like method for finding adequate parameters using fitness landscape analysis on simple benchmark functions and real-world objective functions. The result is a simple compound similarity metric based on the empirical correlation coefficient and a measure of convexity. It is then used to find the best benchmark functions to serve as surrogates. The near-optimal parameter set is then found using fractional factorial design. The real-world problem of NACA airfoil lift coefficient maximization is used as a preliminary proof of concept. The overall aim of this research is to reduce the computational overhead of metaheuristics parameterization.

Keywords: metaheuristics, stochastic optimization, particle swarm optimization, exploratory landscape analysis

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634 Task Evoked Pupillary Response for Surgical Task Difficulty Prediction via Multitask Learning

Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

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633 A General Approach to Define Adjoint of Linear and Non-linear Operators

Authors: Mehdi Jafari Matehkolaee

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In this paper, we have obtained the adjoint of an arbitrary operator (linear and nonlinear) in Hilbert space by introducing an n-dimensional Riemannian manifold. This general formalism covers every linear operator (non – differential) in Hilbert space. In fact, our approach shows that instead of using the adjoint definition of an operator directly, it can be obtained directly by relying on a suitable generalized space according to the action of the operator in question. For the case of nonlinear operators, we have to change the definition of the linear operator adjoint. But here, we have obtained an adjoint of these operators with respect to the definition of the derivative of the operator. As a matter of fact, we have shown one of the straight applications of the ''Frechet derivative'' in the algebra of the operators.

Keywords: adjoint operator, non-linear operator, differentiable operator, manifold

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632 [Keynote Talk]: Production Flow Coordination on Supply Chains: Brazilian Case Studies

Authors: Maico R. Severino, Laura G. Caixeta, Nadine M. Costa, Raísa L. T. Napoleão, Éverton F. V. Valle, Diego D. Calixto, Danielle Oliveira

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One of the biggest barriers that companies find nowadays is the coordination of production flow in their Supply Chains (SC). In this study, coordination is understood as a mechanism for incorporating the entire production channel, with everyone involved focused on achieving the same goals. Sometimes, this coordination is attempted by the use of logistics practices or production plan and control methods. No papers were found in the literature that presented the combined use of logistics practices and production plan and control methods. The main objective of this paper is to propose solutions for six case studies combining logistics practices and Ordering Systems (OS). The methodology used in this study was a conceptual model of decision making. This model contains six phases: a) the analysis the types and characteristics of relationships in the SC; b) the choice of the OS; c) the choice of the logistics practices; d) the development of alternative proposals of combined use; e) the analysis of the consistency of the chosen alternative; f) the qualitative and quantitative assessment of the impact on the coordination of the production flow and the verification of applicability of the proposal in the real case. This study was conducted on six Brazilian SC of different sectors: footwear, food and beverages, garment, sugarcane, mineral and metal mechanical. The results from this study showed that there was improvement in the coordination of the production flow through the following proposals: a) for the footwear industry the use of Period Bath Control (PBC), Quick Response (QR) and Enterprise Resource Planning (ERP); b) for the food and beverage sector firstly the use of Electronic Data Interchange (EDI), ERP, Continuous Replenishment (CR) and Drum-Buffer-Rope Order (DBR) (for situations in which the plants of both companies are distant), and secondly EDI, ERP, Milk-Run and Review System Continues (for situations in which the plants of both companies are close); c) for the garment industry the use of Collaborative Planning, Forecasting, and Replenishment (CPFR) and Constant Work-In-Process (CONWIP) System; d) for the sugarcane sector the use of EDI, ERP and CONWIP System; e) for the mineral processes industry the use of Vendor Managed Inventory (VMI), EDI and MaxMin Control System; f) for the metal mechanical sector the use of CONWIP System and Continuous Replenishment (CR). It should be emphasized that the proposals are exclusively recommended for the relationship between client and supplier studied. Therefore, it cannot be generalized to other cases. However, what can be generalized is the methodology used to choose the best practices for each case. Based on the study, it can be concluded that the combined use of OS and logistics practices enable a better coordination of flow production on SC.

Keywords: supply chain management, production flow coordination, logistics practices, ordering systems

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631 I, Me and the Bot: Forming a theory of symbolic interactivity with a Chatbot

Authors: Felix Liedel

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The rise of artificial intelligence has numerous and far-reaching consequences. In addition to the obvious consequences for entire professions, the increasing interaction with chatbots also has a wide range of social consequences and implications. We are already increasingly used to interacting with digital chatbots, be it in virtual consulting situations, creative development processes or even in building personal or intimate virtual relationships. A media-theoretical classification of these phenomena has so far been difficult, partly because the interactive element in the exchange with artificial intelligence has undeniable similarities to human-to-human communication but is not identical to it. The proposed study, therefore, aims to reformulate the concept of symbolic interaction in the tradition of George Herbert Mead as symbolic interactivity in communication with chatbots. In particular, Mead's socio-psychological considerations will be brought into dialog with the specific conditions of digital media, the special dispositive situation of chatbots and the characteristics of artificial intelligence. One example that illustrates this particular communication situation with chatbots is so-called consensus fiction: In face-to-face communication, we use symbols on the assumption that they will be interpreted in the same or a similar way by the other person. When briefing a chatbot, it quickly becomes clear that this is by no means the case: only the bot's response shows whether the initial request corresponds to the sender's actual intention. This makes it clear that chatbots do not just respond to requests. Rather, they function equally as projection surfaces for their communication partners but also as distillations of generalized social attitudes. The personalities of the chatbot avatars result, on the one hand, from the way we behave towards them and, on the other, from the content we have learned in advance. Similarly, we interpret the response behavior of the chatbots and make it the subject of our own actions with them. In conversation with the virtual chatbot, we enter into a dialog with ourselves but also with the content that the chatbot has previously learned. In our exchanges with chatbots, we, therefore, interpret socially influenced signs and behave towards them in an individual way according to the conditions that the medium deems acceptable. This leads to the emergence of situationally determined digital identities that are in exchange with the real self but are not identical to it: In conversation with digital chatbots, we bring our own impulses, which are brought into permanent negotiation with a generalized social attitude by the chatbot. This also leads to numerous media-ethical follow-up questions. The proposed approach is a continuation of my dissertation on moral decision-making in so-called interactive films. In this dissertation, I attempted to develop a concept of symbolic interactivity based on Mead. Current developments in artificial intelligence are now opening up new areas of application.

Keywords: artificial intelligence, chatbot, media theory, symbolic interactivity

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630 First Principle Calculations of Magnetic and Electronic Properties of Double Perovskite Ba2MnMoO6

Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Souidi, A. Abbad, T. Lantri, Z. Aziz, A. Zitouni

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The electronic and magnetic structures of double perovskite Ba2MnMoO6 are systematically investigated using the first principle method of the Full Potential Linear Augmented Plane Waves Plus the Local Orbitals (FP-LAPW+LO) within the Local Spin Density Approximation (LSDA) and the Generalized Gradient Approximation (GGA). In order to take into account the strong on-site Coulomb interaction, we included the Hubbard correlation terms: LSDA+U and GGA+U approaches. Whereas half-metallic ferromagnetic character is observed due to dominant Mn spin-up and Mo spin-down contributions insulating ground state is obtained. The LSDA+U and GGA+U calculations yield better agreement with the theoretical and the experimental results than LSDA and GGA do.

Keywords: electronic structure, double perovskite, first principles, Ba2MnMoO6, half-metallic

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629 Mathematical Properties of the Viscous Rotating Stratified Fluid Counting with Salinity and Heat Transfer in a Layer

Authors: A. Giniatoulline

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A model of the mathematical fluid dynamics which describes the motion of a three-dimensional viscous rotating fluid in a homogeneous gravitational field with the consideration of the salinity and heat transfer is considered in a vertical finite layer. The model is a generalization of the linearized Navier-Stokes system with the addition of the Coriolis parameter and the equations for changeable density, salinity, and heat transfer. An explicit solution is constructed and the proof of the existence and uniqueness theorems is given. The localization and the structure of the spectrum of inner waves is also investigated. The results may be used, in particular, for constructing stable numerical algorithms for solutions of the considered models of fluid dynamics of the Atmosphere and the Ocean.

Keywords: Fourier transform, generalized solutions, Navier-Stokes equations, stratified fluid

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628 On the Effect of Immigration on Destination: Country Corruption

Authors: Eugen Dimant, Tim Krieger, Margarete Redlin

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This paper analyzes the impact of migration on destination-country corruption levels. Capitalizing on a comprehensive dataset consisting of annual immigration stocks of OECD coun-tries from 207 countries of origin for the period 1984-2008, we explore different channels through which corruption might migrate. We employ different estimation methods using fixed effects and Tobit regressions in order to validate our findings. What is more, we also address the issue of endogeneity by using the Difference-Generalized Method of Moments (GMM) estimator. Independent of the econometric methodology we consistently find that while general migration has an insignificant effect on the destination country’s corruption level, immigration from corruption-ridden origin countries boosts corruption in the destination country. Our findings provide a more profound understanding of the economic implications associated with migration flows.

Keywords: corruption, migration, impact of migration, destination-country corruption

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627 An Innovative Auditory Impulsed EEG and Neural Network Based Biometric Identification System

Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

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The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

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626 Effect of Outliers in Assessing Significant Wave Heights Through a Time-Dependent GEV Model

Authors: F. Calderón-Vega, A. D. García-Soto, C. Mösso

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Recorded significant wave heights sometimes exhibit large uncommon values (outliers) that can be associated with extreme phenomena such as hurricanes and cold fronts. In this study, some extremely large wave heights recorded in NOAA buoys (National Data Buoy Center, noaa.gov) are used to investigate their effect in the prediction of future wave heights associated with given return periods. Extreme waves are predicted through a time-dependent model based on the so-called generalized extreme value distribution. It is found that the outliers do affect the estimated wave heights. It is concluded that a detailed inspection of outliers is envisaged to determine whether they are real recorded values since this will impact defining design wave heights for coastal protection purposes.

Keywords: GEV model, non-stationary, seasonality, outliers

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625 A Novel Approach towards Test Case Prioritization Technique

Authors: Kamna Solanki, Yudhvir Singh, Sandeep Dalal

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Software testing is a time and cost intensive process. A scrutiny of the code and rigorous testing is required to identify and rectify the putative bugs. The process of bug identification and its consequent correction is continuous in nature and often some of the bugs are removed after the software has been launched in the market. This process of code validation of the altered software during the maintenance phase is termed as Regression testing. Regression testing ubiquitously considers resource constraints; therefore, the deduction of an appropriate set of test cases, from the ensemble of the entire gamut of test cases, is a critical issue for regression test planning. This paper presents a novel method for designing a suitable prioritization process to optimize fault detection rate and performance of regression test on predefined constraints. The proposed method for test case prioritization m-ACO alters the food source selection criteria of natural ants and is basically a modified version of Ant Colony Optimization (ACO). The proposed m-ACO approach has been coded in 'Perl' language and results are validated using three examples by computation of Average Percentage of Faults Detected (APFD) metric.

Keywords: regression testing, software testing, test case prioritization, test suite optimization

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624 Electron-Ion Recombination of N^{2+} and O^{3+} Ions

Authors: Shahin A. Abdel-Naby, Asad T. Hassan, Stuart Loch, Michael Fogle, Negil R. Badnell, Michael S. Pindzola

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Accurate and reliable laboratory astrophysical data for electron-ion recombination are needed for plasma modeling. Dielectronic recombination (DR) rate coefficients are calculated for boron-like nitrogen and oxygen ions using state-of-the-art multi-configuration Breit-Pauli atomic structure AUTOSTRUCTURE collisional package within the generalized collisional-radiative framework. The calculations are performed in intermediate coupling scheme associated with n = 0 (2  2) and n = 1 (2  3) core-excitations. Good agreements are found between the theoretically convoluted rate coefficients and the experimental measurements performed at CRYRING heavy-ion storage ring for both ions. Fitting coefficients for the rate coefficients are produced for these ions in the temperature range q2(102-107) K, where q is the ion charge before recombination.

Keywords: Atomic data, atomic processes, electron-ion collision, plasma

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623 The Impact of Government Subsidies to Keep Residents Studying at Home

Authors: Melissa James Maceachern

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This study examines a financial aid program that is designed to “keep residents at home” to attend higher education by providing financial aid as an incentive or discount in their first year of university following high school graduation. This study offers insight into financial matters for higher education students that can assist in providing policy direction for student financing. In particular, this study found that students appeared to value the bursary but none of the key metrics related to participation or conversion to the home institution indicated that the bursary impacted enrolment or participation. One key metric, student loans received by direct entry high school students did indicate a decline in the number of recipients. This study also identified accessibility issues to higher education that are of importance when considering the declining youth populations, future labour market needs and the need to sustain higher education institutions. This is undoubtedly a challenging period of time given the changing social and demographic forces within Canada. A comprehensive examination of the policy and programs to address these forces needs to be undertaken. This study highlights the importance of utilizing financial aid in combination with other policy to assist students in accessing higher education.

Keywords: accessibility, participation, financing, government

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622 The Board Structure of Public and Private Sector Companies and Its Impact on Firm Performance: A Study of Fortune 500 Indian Companies from 2006 to 2015

Authors: Gayathri P. Nair

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The focus of this study is to identify whether the board structure has any significant impact on the firm performance and finding out any evidence of being listed in the Fortune 500 list compiled and published by the American business magazine, Fortune and published globally by Time Inc., as the world’s wealthiest companies. The list has been released based on the ranking obtained for the total revenues for the respective fiscal year which has ended on or before March 31st. The study has been conducted on the Indian companies that were listed in the Fortune 500 list for the past 10 years. This study employs a logical regression between the variables, firm performance and board composition as mentioned in the clause 49 of companies act 1956 and 2013. For getting the firm performance, ROA has selected as the key performance metric, as it focuses the management attention on the assets required to run the business. The highlight of the study is that the tools had been applied between public and private sector firms so that, it reveals whether the board composition is helping out to maintain the position in the list. In addition, the findings reveal that apart from independent directors, all other variables have significant impact on firm performance.

Keywords: board structure, Fortune 500 company, firm performance, India

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621 A Weighted Group EI Incorporating Role Information for More Representative Group EI Measurement

Authors: Siyu Wang, Anthony Ward

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Emotional intelligence (EI) is a well-established personal characteristic. It has been viewed as a critical factor which can influence an individual's academic achievement, ability to work and potential to succeed. When working in a group, EI is fundamentally connected to the group members' interaction and ability to work as a team. The ability of a group member to intelligently perceive and understand own emotions (Intrapersonal EI), to intelligently perceive and understand other members' emotions (Interpersonal EI), and to intelligently perceive and understand emotions between different groups (Cross-boundary EI) can be considered as Group emotional intelligence (Group EI). In this research, a more representative Group EI measurement approach, which incorporates the information of the composition of a group and an individual’s role in that group, is proposed. To demonstrate the claim of being more representative Group EI measurement approach, this study adopts a multi-method research design, involving a combination of both qualitative and quantitative techniques to establish a metric of Group EI. From the results, it can be concluded that by introducing the weight coefficient of each group member on group work into the measurement of Group EI, Group EI will be more representative and more capable of understanding what happens during teamwork than previous approaches.

Keywords: case study, emotional intelligence, group EI, multi-method research

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620 Mechanism of Formation, Mineralogy and Geochemistry of Iron Mineralization in M'Taguinarou North Tebessa, Algeria

Authors: Fakher Eddine Messaoudi

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The M'Taguinarou North iron occurrence contains Iron and polymetallic mineralization (Fe-Zn-Cu), hosted in Turonian limestone. It manifests in metric clusters of goethite and hematite and in centimetre veins of smithsonite, malachite, and azurite. The genesis of this mineralization is clearly polyphased and results from the supergene processes superposed on hydrothermal phases where the Triassic diapirs probably generated the circulation of hydrothermal fluids through the sedimentary series, and the alteration of the Turonian limestone gave the formation of the hydrothermal primary ore composed of iron carbonates (siderite). Several uplift episodes affected the mineralization and the host rocks, generating the genesis of a polymetallic supergene assembly (goethite, malachite, azurite, quartz, and calcite). In M’taguinarou North, iron oxy-hydroxides are mainly observed in the form of fibrous stalactites, stalagmites, and Botroydale structures, where hematite precipitated first, followed immediately by goethite, limonite, and smithsonite. Siderite is completely absent. Subsequently, malachite, azurite, and calcite formed in the form of small veins intersecting the surrounding limestone.

Keywords: mineralization, genetic model, hydrothermal iron, supergene, Tebessa, Algeria

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619 Geometric Contrast of a 3D Model Obtained by Means of Digital Photogrametry with a Quasimetric Camera on UAV Classical Methods

Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Cristina Diego Soroa

Abstract:

Nowadays, the use of drones has been extended to practically any human activity. One of the main applications is focused on the surveying field. In this regard, software programs that process the images captured by the sensor from the drone in an almost automatic way have been developed and commercialized, but they only allow contrasting the results through control points. This work proposes the contrast of a 3D model obtained from a flight developed by a drone and a non-metric camera (due to its low cost), with a second model that is obtained by means of the historically-endorsed classical methods. In addition to this, the contrast is developed over a certain territory with a significant unevenness, so as to test the model generated with photogrammetry, and considering that photogrammetry with drones finds more difficulties in terms of accuracy in this kind of situations. Distances, heights, surfaces and volumes are measured on the basis of the 3D models generated, and the results are contrasted. The differences are about 0.2% for the measurement of distances and heights, 0.3% for surfaces and 0.6% when measuring volumes. Although they are not important, they do not meet the order of magnitude that is presented by salespeople.

Keywords: accuracy, classical topographic, model tridimensional, photogrammetry, Uav.

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618 Habitat Model Review and a Proposed Methodology to Value Economic Trade-Off between Cage Culture and Habitat of an Endemic Species in Lake Maninjau, Indonesia

Authors: Ivana Yuniarti, Iwan Ridwansyah

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This paper delivers a review of various methodologies for habitat assessment and a proposed methodology to assess an endemic fish species habitat in Lake Maninjau, Indonesia as a part of a Ph.D. project. This application is mainly aimed to assess the trade-off between the economic value of aquaculture and the fisheries. The proposed methodology is a generalized linear model (GLM) combined with GIS to assess presence-absence data or habitat suitability index (HSI) combined with the analytical hierarchy process (AHP). Further, a cost of habitat replacement approach is planned to be used to calculate the habitat value as well as its trade-off with the economic value of aquaculture. The result of the study is expected to be a scientific consideration in local decision making and to provide a reference for other areas in the country.

Keywords: AHP, habitat, GLM, HSI, Maninjau

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617 Structural, Electronic and Optical Properties of LiₓNa1-ₓH for Hydrogen Storage

Authors: B. Bahloul

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This study investigates the structural, electronic, and optical properties of LiH and NaH compounds, as well as their ternary mixed crystals LiₓNa1-ₓH, adopting a face-centered cubic structure with space group Fm-3m (number 225). The structural and electronic characteristics are examined using density functional theory (DFT), while empirical methods, specifically the modified Moss relation, are employed for analyzing optical properties. The exchange-correlation potential is determined through the generalized gradient approximation (PBEsol-GGA) within the density functional theory (DFT) framework, utilizing the projected augmented wave pseudopotentials (PAW) approach. The Quantum Espresso code is employed for conducting these calculations. The calculated lattice parameters at equilibrium volume and the bulk modulus for x=0 and x=1 exhibit good agreement with existing literature data. Additionally, the LiₓNa1-ₓH alloys are identified as having a direct band gap.

Keywords: DFT, structural, electronic, optical properties

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616 Optimization of FGM Sandwich Beams Using Imperialist Competitive Algorithm

Authors: Saeed Kamarian, Mahmoud Shakeri

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Sandwich structures are used in a variety of engineering applications including aircraft, construction and transportation where strong, stiff and light structures are required. In this paper, frequency maximization of Functionally Graded Sandwich (FGS) beams resting on Pasternak foundations is investigated. A generalized power-law distribution with four parameters is considered for material distribution through the thicknesses of face layers. Since the search space is large, the optimization processes becomes so complicated and too much time consuming. Thus a novel meta–heuristic called Imperialist Competitive Algorithm (ICA) which is a socio-politically motivated global search strategy is implemented to improve the speed of optimization process. Results show the success of applying ICA for engineering problems especially for design optimization of FGM sandwich beams.

Keywords: sandwich beam, functionally graded materials, optimization, imperialist competitive algorithm

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615 Half Metallic Antiferromagnetic of Doped TiO2 Rutile with Doubles Impurities (Os, Mo) from Ab Initio Calculations

Authors: M. Fakhim Lamrani, M. Ouchri, M. Belaiche, El Kenz, M. Loulidi, A. Benyoussef

Abstract:

Electronic and magnetic calculations based on density functional theory within the generalized gradient approximation for II-VI compound semiconductor TiO2 doped with single impurity Os and Mo; these compounds are a half metallic ferromagnet in their ground state with a total magnetic moment of 2 μB for both systems. Then, TiO2 doped with double impurities Os and Mo have been performed. As result, Ti1-2xOsxMoxO2 with x=0.065 is half-metallic antiferromagnets with 100% spin polarization of the conduction electrons crossing the Fermi level, without showing a net magnetization. Moreover, Ti14OsMoO32 compound is stable energetically than Ti1-xMoxO2 and Ti1-xOsxO2. The antiferromagnetic interaction in Ti1-2xOsxMoxO2 system is attributed to the double exchange mechanism, and the latter could also be the origin of their half metallic.

Keywords: diluted magnetic semiconductor, half-metallic antiferromagnetic, augmented spherical wave method

Procedia PDF Downloads 403
614 A Survey on Fixed Point Iterations in Modular Function Spaces and an Application to Ode

Authors: Hudson Akewe

Abstract:

This research presents complementary results with wider applications on convergence and rate of convergence of classical fixed point theory in Banach spaces to the world of the theory of fixed points of mappings defined in classes of spaces of measurable functions, known in the literature as modular function spaces. The study gives a comprehensive survey of various iterative fixed point results for the classes of multivalued ρ-contractive-like, ρ-quasi-contractive-like, ρ-quasi-contractive, ρ-Zamfirescu and ρ-contraction mappings in the framework of modular function spaces. An example is presented to demonstrate the applicability of the implicit-type iterative schemes to the system of ordinary differential equations. Furthermore, numerical examples are given to show the rate of convergence of the various explicit Kirk-type and implicit Kirk-type iterative schemes under consideration. Our results complement the results obtained on normed and metric spaces in the literature. Also, our methods of proof serve as a guide to obtain several similar improved results for nonexpansive, pseudo-contractive, and accretive type mappings.

Keywords: implicit Kirk-type iterative schemes, multivalued mappings, convergence results, fixed point

Procedia PDF Downloads 101
613 Using Lagrange Equations to Study the Relative Motion of a Mechanism

Authors: R. A. Petre, S. E. Nichifor, A. Craifaleanu, I. Stroe

Abstract:

The relative motion of a robotic arm formed by homogeneous bars of different lengths and masses, hinged to each other is investigated. The first bar of the mechanism is articulated on a platform, considered initially fixed on the surface of the Earth, while for the second case the platform is considered to be in rotation with respect to the Earth. For both analyzed cases the motion equations are determined using the Lagrangian formalism, applied in its traditional form, valid with respect to an inertial reference system, conventionally considered as fixed. However, in the second case, a generalized form of the formalism valid with respect to a non-inertial reference frame will also be applied. The numerical calculations were performed using a MATLAB program.

Keywords: Lagrange equations, relative motion, inertial reference frame, non-inertial reference frame

Procedia PDF Downloads 100
612 Signal Processing Approach to Study Multifractality and Singularity of Solar Wind Speed Time Series

Authors: Tushnik Sarkar, Mofazzal H. Khondekar, Subrata Banerjee

Abstract:

This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1st January, 1997 to 28th October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal.

Keywords: detrended fluctuation analysis, generalized hurst exponent, holder exponents, multifractal exponent, multifractal spectrum, singularity spectrum, time series analysis

Procedia PDF Downloads 372
611 Supervised/Unsupervised Mahalanobis Algorithm for Improving Performance for Cyberattack Detection over Communications Networks

Authors: Radhika Ranjan Roy

Abstract:

Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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610 An Ab Initio Study of Delafossite Transparent Conductive Oxides Cu(In, Ga)O2 and Absorbers Films Cu(In, Ga)S2 in Solar-Cell

Authors: Mokdad Sakhri, Youcef Bouhadda

Abstract:

Thin film chalcopyrite technology is thus nowadays a solid candidate for photovoltaic cells. The currently used window layer for the solar cell Cu(In,Ga)S2 is our interest point in this work. For this purpose, we have performed a first-principles study of structural, electronic and optical properties for both delafossite transparent conductive oxides Cu (In, Ga)O2 and absorbers films Cu(In,Ga)S2. The calculations have been carried out within the local density functional (LDA) and generalized gradient approximations (GGA) combined with the hubbard potential using norm-conserving pseudopotentials and a plane-wave basis with ABINIT code. We have found the energy gap is :1.6, 2.53, 3.6, 3.8 eV for CuInS2, CuGaS2, CuInO2 and CuGaO2 respectively. The results are in good agreement with experimental results.

Keywords: ABINIT code, DFT, electronic and optical properties, solar-cell absorbers, delafossite transparent conductive oxides

Procedia PDF Downloads 542