Search results for: deep graphical model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18459

Search results for: deep graphical model

17409 Towards A New Maturity Model for Information System

Authors: Ossama Matrane

Abstract:

Information System has become a strategic lever for enterprises. It contributes effectively to align business processes on strategies of enterprises. It is regarded as an increase in productivity and effectiveness. So, many organizations are currently involved in implementing sustainable Information System. And, a large number of studies have been conducted the last decade in order to define the success factors of information system. Thus, many studies on maturity model have been carried out. Some of this study is referred to the maturity model of Information System. In this article, we report on development of maturity models specifically designed for information system. This model is built based on three components derived from Maturity Model for Information Security Management, OPM3 for Project Management Maturity Model and processes of COBIT for IT governance. Thus, our proposed model defines three maturity stages for corporate a strong Information System to support objectives of organizations. It provides a very practical structure with which to assess and improve Information System Implementation.

Keywords: information system, maturity models, information security management, OPM3, IT governance

Procedia PDF Downloads 447
17408 Evaluation of Gesture-Based Password: User Behavioral Features Using Machine Learning Algorithms

Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

Abstract:

Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

Procedia PDF Downloads 107
17407 A Model Architecture Transformation with Approach by Modeling: From UML to Multidimensional Schemas of Data Warehouses

Authors: Ouzayr Rabhi, Ibtissam Arrassen

Abstract:

To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

Procedia PDF Downloads 160
17406 Location Choice of Firms in an Unequal Length Streets Model: Game Theory Approach as an Extension of the Spoke Model

Authors: Kiumars Shahbazi, Salah Salimian, Abdolrahim Hashemi Dizaj

Abstract:

Locating is one of the key elements in success and survival of industrial centers and has great impact on cost reduction of establishment and launching of various economic activities. In this study, streets with unequal length model have been used that is the classic extension of Spoke model; however with unlimited number of streets with uneven lengths. The results showed that the spoke model is a special case of streets with unequal length model. According to the results of this study, if the strategy of enterprises and firms is to select both price and location, there would be no balance in the game. Furthermore, increased length of streets leads to increased profit of enterprises and with increased number of streets, the enterprises choose locations that are far from center (the maximum differentiation), and the enterprises' output will decrease. Moreover, the enterprise production rate will incline toward zero when the number of streets goes to infinity, and complete competition outcome will be achieved.

Keywords: locating, Nash equilibrium, streets with unequal length model, streets with unequal length model

Procedia PDF Downloads 203
17405 Analysis of Spatial and Temporal Data Using Remote Sensing Technology

Authors: Kapil Pandey, Vishnu Goyal

Abstract:

Spatial and temporal data analysis is very well known in the field of satellite image processing. When spatial data are correlated with time, series analysis it gives the significant results in change detection studies. In this paper the GIS and Remote sensing techniques has been used to find the change detection using time series satellite imagery of Uttarakhand state during the years of 1990-2010. Natural vegetation, urban area, forest cover etc. were chosen as main landuse classes to study. Landuse/ landcover classes within several years were prepared using satellite images. Maximum likelihood supervised classification technique was adopted in this work and finally landuse change index has been generated and graphical models were used to present the changes.

Keywords: GIS, landuse/landcover, spatial and temporal data, remote sensing

Procedia PDF Downloads 433
17404 Explaining the Relationship between Religiosity and Resilience

Authors: Rita Phillips, Mark Burgess, Maga Berlinski

Abstract:

Although the positive impact of religiosity on well-being, health, and life-coping abilities is well known, up to date research has failed to provide scientific evidence for the relationship reasons. Therefore the present study took a qualitative approach by examining how religiosity interacts in coping with emotionally distressful situations, for which wedding preparations are an example. Wedding preparations, related to the experience of ambiguous emotions, can be the reason for phases of high distress. Although being per-se religious ceremonies, they are also socially-scripted and characterized by people’s striving for personally meaningful celebrations. The negotiation of these many influences can evoke conflicts. To reveal components of religiosity which contribute to stress-resolution, eight biographic-narrative interviews with recently married spouses were conducted. Participants were from different nationalities and Catholic deep-belief communities in order to determine factors independent from national-culture and social-subgroup. The audio-tape recorded, transcribed and translated interviews were analyzed by Interpretative Phenomenological Analysis. Opposing previous research on wedding-related conflicts but in-line with the quantitative account on the relation between stress-resilience and religiosity, the present study found participants reporting very low levels of distress and ambiguity. Although similar areas of potential conflicts were revealed, deep-belief Christians seemed to handle them in a different way. Participants freed themselves from own and others’ rigor mundane expectations by their spiritual preparation and the focus on a divine instance. This evoked a feeling of perceived closeness to God and of unconditional love, resulting in acceptance of oneself and others. Through relativizing mundane goods, participants perceived absolute freedom. Thus belief did not supplement coping strategies, previously defined in the literature, but substituted them. The paper implies that in explaining the connection between stress-resilience and religiosity, one’s perception and experience of unconditional love might outweigh other social or personal factors. However, further qualitative investigations are needed to fully explain the phenomenon.

Keywords: deep-belief, religiosity, resilience, wedding

Procedia PDF Downloads 245
17403 Static Analysis Deployment Model for Code Quality on Research and Development Projects of Software Development

Authors: Jeong-Hyun Park, Young-Sik Park, Hyo-Teag Jung

Abstract:

This paper presents static analysis deployment model for code quality on R&D Projects of SW Development. The proposed model includes the scope of R&D projects and index for static analysis of source code, operation model and execution process, environments and infrastructure system for R&D projects of SW development. There is the static analysis result of pilot project as case study based on the proposed deployment model and environment, and strategic considerations for success operation of the proposed static analysis deployment model for R&D Projects of SW Development. The proposed static analysis deployment model in this paper will be adapted and improved continuously for quality upgrade of R&D projects, and customer satisfaction of developed source codes and products.

Keywords: static analysis, code quality, coding rules, automation tool

Procedia PDF Downloads 520
17402 Visualizing Class Metrics and Object Calls for Software Systems

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

Abstract:

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

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

Procedia PDF Downloads 205
17401 Geology, Geomorphology and Genesis of Andarokh Karstic Cave, North-East Iran

Authors: Mojtaba Heydarizad

Abstract:

Andarokh basin is one of the main karstic regions in Khorasan Razavi province NE Iran. This basin is part of Kopeh-Dagh mega zone extending from Caspian Sea in the east to northern Afghanistan in the west. This basin is covered by Mozdooran Formation, Ngr evaporative formation and quaternary alluvium deposits in descending order of age. Mozdooran carbonate formation is notably karstified. The main surface karstic features in Mozdooran formation are Groove karren, Cleft karren, Rain pit, Rill karren, Tritt karren, Kamintza, Domes, and Table karren. In addition to surface features, deep karstic feature Andarokh Cave also exists in the region. Studying Ca, Mg, Mn, Sr, Fe concentration and Sr/Mn ratio in Mozdooran formation samples with distance to main faults and joints system using PCA analyses demonstrates intense meteoric digenesis role in controlling carbonate rock geochemistry. The karst evaluation in Andarokh basin varies from early stages 'deep seated karst' in Mesozoic to mature karstic system 'Exhumed karst' in quaternary period. Andarokh cave (the main cave in Andarokh basin) is rudimentary branch work consists of three passages of A, B and C and two entrances Andarokh and Sky.

Keywords: Andarokh basin, Andarokh cave, geochemical analyses, karst evaluation

Procedia PDF Downloads 154
17400 The Spherical Geometric Model of Absorbed Particles: Application to the Electron Transport Study

Authors: A. Bentabet, A. Aydin, N. Fenineche

Abstract:

The mean penetration depth has a most important in the absorption transport phenomena. Analytical model of light ion backscattering coefficients from solid targets have been made by Vicanek and Urbassek. In the present work, we showed a mathematical expression (deterministic model) for Z1/2. In advantage, in the best of our knowledge, relatively only one analytical model exit for electron or positron mean penetration depth in solid targets. In this work, we have presented a simple geometric spherical model of absorbed particles based on CSDA scheme. In advantage, we have showed an analytical expression of the mean penetration depth by combination between our model and the Vicanek and Urbassek theory. For this, we have used the Relativistic Partial Wave Expansion Method (RPWEM) and the optical dielectric model to calculate the elastic cross sections and the ranges respectively. Good agreement was found with the experimental and theoretical data.

Keywords: Bentabet spherical geometric model, continuous slowing down approximation, stopping powers, ranges, mean penetration depth

Procedia PDF Downloads 642
17399 Expert Review on Conceptual Design Model of iTV Advertising towards Impulse Purchase

Authors: Azizah Che Omar

Abstract:

Various studies have proposed factors of impulse purchase in different advertising mediums like website, mobile, traditional retail store and traditional television. However, to the best of researchers’ knowledge, none of the impulse purchase model is dedicated towards impulse purchase tendency for interactive TV (iTV) advertising. Therefore, the proposed model conceptual design model of interactive television advertising toward impulse purchase (iTVAdIP) was developed. The focus of this study is to evaluate the conceptual design model of iTVAdIP through expert review. As a result, the finding showed that majority of expert reviews agreed that the conceptual design model iTVAdIP is applicable to the development of interactive television advertising and it will increase the effectiveness of advertising. This study also shows the conceptual design model of iTVAdIP that has been reviewed.

Keywords: impulse purchase, interactive television advertising, persuasive

Procedia PDF Downloads 355
17398 The Estimation of Human Vital Signs Complexity

Authors: L. Bikulciene, E. Venskaityte, G. Jarusevicius

Abstract:

Non-stationary and nonlinear signals generated by living complex systems defy traditional mechanistic approaches, which are based on homeostasis. Previous our studies have shown that the evaluation of the interactions of physiological signals by using special analysis methods is suitable for observation of physiological processes. It is demonstrated the possibility of using deep physiological model, based interpretation of the changes of the human body’s functional states combined with an application of the analytical method based on matrix theory for the physiological signals analysis, which was applied on high risk cardiac patients. It is shown that evaluation of cardiac signals interactions show peculiar for each individual functional changes at the onset of hemodynamic restoration procedure. Therefore we suggest that the alterations of functional state of the body, after patients overcome surgery can be complemented by the data received from the suggested approach of the evaluation of functional variables interactions.

Keywords: cardiac diseases, complex systems theory, ECG analysis, matrix analysis

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17397 Presenting the Mathematical Model to Determine Retention in the Watersheds

Authors: S. Shamohammadi, L. Razavi

Abstract:

This paper based on the principle concepts of SCS-CN model, a new mathematical model for computation of retention potential (S) presented. In the mathematical model, not only precipitation-runoff concepts in SCS-CN model are precisely represented in a mathematical form, but also new concepts, called “maximum retention” and “total retention” is introduced, and concepts of potential retention capacity, maximum retention, and total retention have been separated from each other. In the proposed model, actual retention (F), maximum actual retention (Fmax), total retention (S), maximum retention (Smax), and potential retention (Sp), for the first time clearly defined, so that Sp is not variable, but a function of morphological characteristics of the watershed. Indeed, based on the mathematical relation of the conceptual curve of SCS-CN model, the proposed model provides a new method for the computation of actual retention in watershed and it simply determined runoff based on. In the corresponding relations, in addition to Precipitation (P), Initial retention (Ia), cumulative values of actual retention capacity (F), total retention (S), runoff (Q), antecedent moisture (M), potential retention (Sp), total retention (S), we introduced Fmax and Fmin referring to maximum and minimum actual retention, respectively. As well as, ksh is a coefficient which depends on morphological characteristics of the watershed. Advantages of the modified version versus the original model include a better precision, higher performance, easier calibration and speed computing.

Keywords: model, mathematical, retention, watershed, SCS

Procedia PDF Downloads 458
17396 Freshwater Pinch Analysis for Optimal Design of the Photovoltaic Powered-Pumping System

Authors: Iman Janghorban Esfahani

Abstract:

Due to the increased use of irrigation in agriculture, the importance and need for highly reliable water pumping systems have significantly increased. The pumping of the groundwater is essential to provide water for both drip and furrow irrigation to increase the agricultural yield, especially in arid regions that suffer from scarcities of surface water. The most common irrigation pumping systems (IPS) consume conventional energies through the use of electric motors and generators or connecting to the electricity grid. Due to the shortage and transportation difficulties of fossil fuels, and unreliable access to the electricity grid, especially in the rural areas, and the adverse environmental impacts of fossil fuel usage, such as greenhouse gas (GHG) emissions, the need for renewable energy sources such as photovoltaic systems (PVS) as an alternative way of powering irrigation pumping systems is urgent. Integration of the photovoltaic systems with irrigation pumping systems as the Photovoltaic Powered-Irrigation Pumping System (PVP-IPS) can avoid fossil fuel dependency and the subsequent greenhouse gas emissions, as well as ultimately lower energy costs and improve efficiency, which made PVP-IPS systems as an environmentally and economically efficient solution for agriculture irrigation in every region. The greatest problem faced by integration of PVP with IPS systems is matching the intermittence of the energy supply with the dynamic water demand. The best solution to overcome the intermittence is to incorporate a storage system into the PVP-IPS to provide water-on-demand as a highly reliable stand-alone irrigation pumping system. The water storage tank (WST) is the most common storage device for PVP-IPS systems. In the integrated PVP-IPS with a water storage tank (PVP-IPS-WST), a water storage tank stores the water pumped by the IPS in excess of the water demand and then delivers it when demands are high. The Freshwater pinch analysis (FWaPA) as an alternative to mathematical modeling was used by other researchers for retrofitting the off-grid battery less photovoltaic-powered reverse osmosis system. However, the Freshwater pinch analysis has not been used to integrate the photovoltaic systems with irrigation pumping system with water storage tanks. In this study, FWaPA graphical and numerical tools were used for retrofitting an existing PVP-IPS system located in Salahadin, Republic of Iraq. The plant includes a 5 kW submersible water pump and 7.5 kW solar PV system. The Freshwater Composite Curve as the graphical tool and Freashwater Storage Cascade Table as the numerical tool were constructed to determine the minimum required outsourced water during operation, optimal amount of delivered electricity to the water pump, and optimal size of the water storage tank for one-year operation data. The results of implementing the FWaPA on the case study show that the PVP-IPS system with a WST as the reliable system can reduce outsourced water by 95.41% compare to the PVP-IPS system without storage tank.

Keywords: irrigation, photovoltaic, pinch analysis, pumping, solar energy

Procedia PDF Downloads 138
17395 On Parameter Estimation of Simultaneous Linear Functional Relationship Model for Circular Variables

Authors: N. A. Mokhtar, A. G. Hussin, Y. Z. Zubairi

Abstract:

This paper proposes a new simultaneous simple linear functional relationship model by assuming equal error variances. We derive the maximum likelihood estimate of the parameters in the simultaneous model and the covariance. We show by simulation study the small bias values of the parameters suggest the suitability of the estimation method. As an illustration, the proposed simultaneous model is applied to real data of the wind direction and wave direction measured by two different instruments.

Keywords: simultaneous linear functional relationship model, Fisher information matrix, parameter estimation, circular variables

Procedia PDF Downloads 367
17394 A Study of Population Growth Models and Future Population of India

Authors: Sheena K. J., Jyoti Badge, Sayed Mohammed Zeeshan

Abstract:

A Comparative Study of Exponential and Logistic Population Growth Models in India India is the second most populous city in the world, just behind China, and is going to be in the first place by next year. The Indian population has remarkably at higher rate than the other countries from the past 20 years. There were many scientists and demographers who has formulated various models of population growth in order to study and predict the future population. Some of the models are Fibonacci population growth model, Exponential growth model, Logistic growth model, Lotka-Volterra model, etc. These models have been effective in the past to an extent in predicting the population. However, it is essential to have a detailed comparative study between the population models to come out with a more accurate one. Having said that, this research study helps to analyze and compare the two population models under consideration - exponential and logistic growth models, thereby identifying the most effective one. Using the census data of 2011, the approximate population for 2016 to 2031 are calculated for 20 Indian states using both the models, compared and recorded the data with the actual population. On comparing the results of both models, it is found that logistic population model is more accurate than the exponential model, and using this model, we can predict the future population in a more effective way. This will give an insight to the researchers about the effective models of population and how effective these population models are in predicting the future population.

Keywords: population growth, population models, exponential model, logistic model, fibonacci model, lotka-volterra model, future population prediction, demographers

Procedia PDF Downloads 124
17393 Extended Arithmetic Precision in Meshfree Calculations

Authors: Edward J. Kansa, Pavel Holoborodko

Abstract:

Continuously differentiable radial basis functions (RBFs) are meshfree, converge faster as the dimensionality increases, and is theoretically spectrally convergent. When implemented on current single and double precision computers, such RBFs can suffer from ill-conditioning because the systems of equations needed to be solved to find the expansion coefficients are full. However, the Advanpix extended precision software package allows computer mathematics to resemble asymptotically ideal Platonic mathematics. Additionally, full systems with extended precision execute faster graphical processors units and field-programmable gate arrays because no branching is needed. Sparse equation systems are fast for iterative solvers in a very limited number of cases.

Keywords: partial differential equations, Meshfree radial basis functions, , no restrictions on spatial dimensions, Extended arithmetic precision.

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17392 Vision-Based Collision Avoidance for Unmanned Aerial Vehicles by Recurrent Neural Networks

Authors: Yao-Hong Tsai

Abstract:

Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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17391 Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction

Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova

Abstract:

A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Keywords: analogy-making, categorization, learning of categories, abstraction, hierarchical structure

Procedia PDF Downloads 191
17390 The Gasoil Hydrofining Kinetics Constants Identification

Authors: C. Patrascioiu, V. Matei, N. Nicolae

Abstract:

The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Keywords: hydrofining, kinetic, modeling, optimization

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17389 From Mathematics Project-Based Learning to Commercial Product Using Geometer’s Sketchpad (GSP)

Authors: Krongthong Khairiree

Abstract:

The purpose of this research study is to explore mathematics project-based learning approach and the use of technology in the context of school mathematics in Thailand. Data of the study were collected from 6 sample secondary schools and the students were 6-14 years old. Research findings show that through mathematics project-based learning approach and the use of GSP, students were able to make mathematics learning fun and challenging. Based on the students’ interviews they revealed that, with GSP, they were able to visualize and create graphical representations, which will enable them to develop their mathematical thinking skills, concepts and understanding. The students had fun in creating variety of graphs of functions which they can not do by drawing on graph paper. In addition, there are evidences to show the students’ abilities in connecting mathematics to real life outside the classroom and commercial products, such as weaving, patterning of broomstick, and ceramics design.

Keywords: mathematics, project-based learning, Geometer’s Sketchpad (GSP), commercial products

Procedia PDF Downloads 336
17388 A Mean–Variance–Skewness Portfolio Optimization Model

Authors: Kostas Metaxiotis

Abstract:

Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: evolutionary algorithms, portfolio optimization, skewness, stock selection

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17387 Low Power Glitch Free Dual Output Coarse Digitally Controlled Delay Lines

Authors: K. Shaji Mon, P. R. John Sreenidhi

Abstract:

In deep-submicrometer CMOS processes, time-domain resolution of a digital signal is becoming higher than voltage resolution of analog signals. This claim is nowadays pushing toward a new circuit design paradigm in which the traditional analog signal processing is expected to be progressively substituted by the processing of times in the digital domain. Within this novel paradigm, digitally controlled delay lines (DCDL) should play the role of digital-to-analog converters in traditional, analog-intensive, circuits. Digital delay locked loops are highly prevalent in integrated systems.The proposed paper addresses the glitches present in delay circuits along with area,power dissipation and signal integrity.The digitally controlled delay lines(DCDL) under study have been designed in a 90 nm CMOS technology 6 layer metal Copper Strained SiGe Low K Dielectric. Simulation and synthesis results show that the novel circuits exhibit no glitches for dual output coarse DCDL with less power dissipation and consumes less area compared to the glitch free NAND based DCDL.

Keywords: glitch free, NAND-based DCDL, CMOS, deep-submicrometer

Procedia PDF Downloads 245
17386 Developing a Total Quality Management Model Using Structural Equation Modeling for Indonesian Healthcare Industry

Authors: Jonny, T. Yuri M. Zagloel

Abstract:

This paper is made to present an Indonesian Healthcare model. Currently, there are nine TQM (Total Quality Management) practices in healthcare industry. However, these practices are not integrated yet. Therefore, this paper aims to integrate these practices as a model by using Structural Equation Modeling (SEM). After administering about 210 questionnaires to various stakeholders of this industry, a LISREL program was used to evaluate the model's fitness. The result confirmed that the model is fit because the p-value was about 0.45 or above required 0.05. This has signified that previously mentioned of nine TQM practices are able to be integrated as an Indonesian healthcare model.

Keywords: healthcare, total quality management (TQM), structural equation modeling (SEM), linear structural relations (LISREL)

Procedia PDF Downloads 292
17385 A Research on Flipped-Classroom Teaching Model in English for Academic Purpose Teaching

Authors: Li Shuang

Abstract:

With rigid teaching procedures and limited academic performance assessment methods, traditional teaching model stands in the way of college English reform in China, which features EAP (English for Academic Purpose) teaching. Flipped-classroom teaching, which has been extensively applied to science subjects teaching, however, covers the shortage of traditional teaching model in EAP teaching, via creatively inverting traditional teaching procedures. Besides, the application of flipped-classroom teaching model in EAP teaching also proves that this new teaching philosophy is not confined to science subjects teaching; it goes perfectly well with liberal-arts subjects teaching. Data analysis, desk research survey, and comparative study are referred to in the essay so as to prove its feasibility and advantages in EAP teaching.

Keywords: EAP, traditional teaching method, flipped-classroom teaching model, teaching model design

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17384 Interactive Effects of Challenge-Hindrance Stressors and Core Self-Evaluations on In-Role and Extra-Role Performance

Authors: Khansa Hayat

Abstract:

Organizational stress is one of the vital phenomena which is having its roots deep down in has deep roots in management, psychology, and organizational behavior research. In the meanwhile, keeping its focus on the positive strength of humans rather than the traditional negativity oriented research, positive psychology has emerged as a separate branch of organizational behavior. The current study investigates the interactive effects of Challenge and hindrance stressors and core Self Evaluations (CSE’s) of the individual on job performances including the in-role performance and extra role performances. The study also aims to investigate the supporting/buffering role of the human dispositions (i.e., self esteem, self efficacy, locus of control and emotional stability). The results show that Challenge stressors have a significant positive effect on in role performance and extra role performance of the individual. The findings of the study indicate that Core Self evaluations strengthen the relationship between challenge stressors and in role performance of the individual. In case of Hindrance Stressors the Core self Evaluations lessen the negative impact of Hindrance stressors and they let the individual perform at a better and normal position even when the Hindrance stressors are high. The relationship and implication of conservation of resource theory are also discussed. The limitations, future research directions and implications of the study are also discussed.

Keywords: challenge-hindrance stressors, core self evaluations, in-role performance, extra-role performance

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17383 Analytical Model to Predict the Shear Capacity of Reinforced Concrete Beams Externally Strengthened with CFRP Composites Conditions

Authors: Rajai Al-Rousan

Abstract:

This paper presents a proposed analytical model for predicting the shear strength of reinforced concrete beams strengthened with CFRP composites as external reinforcement. The proposed analytical model can predict the shear contribution of CFRP composites of RC beams with an acceptable coefficient of correlation with the tested results. Based on the comparison of the proposed model with the published well-known models (ACI model, Triantafillou model, and Colotti model), the ACI model had a wider range of 0.16 to 10.08 for the ratio between tested and predicted ultimate shears at failure. Also, an acceptable range of 0.27 to 2.78 for the ratio between tested and predicted ultimate shears by the Triantafillou model. Finally, the best prediction (the ratio between the tested and predicted ones) of the ultimate shear capacity is observed by using Colotti model with a range of 0.20 to 1.78. Thus, the contribution of the CFRP composites as external reinforcement can be predicted with high accuracy by using the proposed analytical model.

Keywords: predicting, shear capacity, reinforced concrete, beams, strengthened, externally, CFRP composites

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17382 Effect of Drying on the Concrete Structures

Authors: A. Brahma

Abstract:

The drying of hydraulics materials is unavoidable and conducted to important spontaneous deformations. In this study, we show that it is possible to describe the drying shrinkage of the high-performance concrete by a simple expression. A multiple regression model was developed for the prediction of the drying shrinkage of the high-performance concrete. The assessment of the proposed model has been done by a set of statistical tests. The model developed takes in consideration the main parameters of confection and conservation. There was a very good agreement between drying shrinkage predicted by the multiple regression model and experimental results. The developed model adjusts easily to all hydraulic concrete types.

Keywords: hydraulic concretes, drying, shrinkage, prediction, modeling

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17381 Parametric Study of Vertical Diffusion Stills for Water Desalination

Authors: A. Seleem, M. Mortada, M. El-Morsi, M. Younan

Abstract:

Diffusion stills have been effective in water desalination. The present work represents a model of the distillation process by using vertical single-effect diffusion stills. A semi-analytical model has been developed to model the process. A software computer code using Engineering Equation Solver EES software has been developed to solve the equations of the developed model. An experimental setup has been constructed, and used for the validation of the model. The model is also validated against former literature results. The results obtained from the present experimental test rig, and the data from the literature, have been compared with the results of the code to find its best range of validity. In addition, a parametric analysis of the system has been developed using the model to determine the effect of operating conditions on the system's performance. The dominant parameters that affect the productivity of the still are the hot plate temperature that ranges from (55-90 °C) and feed flow rate in range of (0.00694-0.0211 kg/m2-s).

Keywords: analytical model, solar distillation, sustainable water systems, vertical diffusion still

Procedia PDF Downloads 405
17380 Towards End-To-End Disease Prediction from Raw Metagenomic Data

Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

Abstract:

Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

Procedia PDF Downloads 125