Search results for: restructuring digital factory model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19268

Search results for: restructuring digital factory model

17528 Proactive WPA/WPA2 Security Using DD-WRT Firmware

Authors: Mustafa Kamoona, Mohamed El-Sharkawy

Abstract:

Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

Procedia PDF Downloads 233
17527 Forecasting Age-Specific Mortality Rates and Life Expectancy at Births for Malaysian Sub-Populations

Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

Abstract:

In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

Procedia PDF Downloads 220
17526 Efficient Sampling of Probabilistic Program for Biological Systems

Authors: Keerthi S. Shetty, Annappa Basava

Abstract:

In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

Procedia PDF Downloads 349
17525 Machine Learning Model Applied for SCM Processes to Efficiently Determine Its Impacts on the Environment

Authors: Elena Puica

Abstract:

This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

Procedia PDF Downloads 116
17524 The Effect of Action Potential Duration and Conduction Velocity on Cardiac Pumping Efficacy: Simulation Study

Authors: Ana Rahma Yuniarti, Ki Moo Lim

Abstract:

Slowed myocardial conduction velocity (CV) and shortened action potential duration (APD) due to some reason are associated with an increased risk of re-entrant excitation, predisposing to cardiac arrhythmia. That is because both of CV reduction and APD shortening induces shortening of wavelength. In this study, we investigated quantitatively the cardiac mechanical responses under various CV and APD using multi-scale computational model of the heart. The model consisted of electrical model coupled with the mechanical contraction model together with a lumped model of the circulatory system. The electrical model consisted of 149.344 numbers of nodes and 183.993 numbers of elements of tetrahedral mesh, whereas the mechanical model consisted of 356 numbers of nodes and 172 numbers of elements of hexahedral mesh with hermite basis. We performed the electrical simulation with two scenarios: 1) by varying the CV values with constant APD and 2) by varying the APD values with constant CV. Then, we compared the electrical and mechanical responses for both scenarios. Our simulation showed that faster CV and longer APD induced largest resultants wavelength and generated better cardiac pumping efficacy by increasing the cardiac output and consuming less energy. This is due to the long wave propagation and faster conduction generated more synchronous contraction of whole ventricle.

Keywords: conduction velocity, action potential duration, mechanical contraction model, circulatory model

Procedia PDF Downloads 204
17523 Application of Computational Flow Dynamics (CFD) Analysis for Surge Inception and Propagation for Low Head Hydropower Projects

Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

Abstract:

Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

Procedia PDF Downloads 361
17522 Joint Modeling of Bottle Use, Daily Milk Intake from Bottles, and Daily Energy Intake in Toddlers

Authors: Yungtai Lo

Abstract:

The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

Procedia PDF Downloads 287
17521 Assessment of Ground Water Potential Zone: A Case Study of Paramakudi Taluk, Ramanathapuram, Tamilnadu, India

Authors: Shri Devi

Abstract:

This paper was conducted to see the ground water potential zones in Paramakudi taluk, Ramanathapuram,Tamilnadu India with a total areal extent of 745 sq. km. The various thematic map have been prepared for the study such as soil, geology, geomorphology, drainage, land use of the particular study area using the Toposheet of 1: 50000. The digital elevation model (DEM) has been generated from contour interval of 10m and also the slope was prepared. The ground water potential zone of the region was obtained using the weighted overlay analysis for which all the thematic maps were overlayed in arc gis 10.2. For the particular output the ranking has been given for all the parameters of each thematic layer with different weightage such as 25% was given to soil, 25% to geomorphology and land use land cover also 25%, slope 15%, lineament with 5% and drainage streams with 5 percentage. Using these entire potential zone maps was prepared which was overlayed with the village map to check the region which has good, moderate and low groundwater potential zone.

Keywords: GIS, ground water, Paramakudi, weighted overlay analysis

Procedia PDF Downloads 342
17520 Maker Education as Means for Early Entrepreneurial Education: Evaluation Results from a European Pilot Action

Authors: Elisabeth Unterfrauner, Christian Voigt

Abstract:

Since the foundation of the first Fab Lab by the Massachusetts Institute of Technology about 17 years ago, the Maker movement has spread globally with the foundation of maker spaces and Fab Labs worldwide. In these workshops, citizens have access to digital fabrication technologies such as 3D printers and laser cutters to develop and test their own ideas and prototypes, which makes it an attractive place for start-up companies. Know-How is shared not only in the physical space but also online in diverse communities. According to the Horizon report, the Maker movement, however, will also have an impact on educational settings in the following years. The European project ‘DOIT - Entrepreneurial skills for young social innovators in an open digital world’ has incorporated key elements of making to develop an early entrepreneurial education program for children between the age of six and 16. The Maker pedagogy builds on constructive learning approaches, learning by doing principles, learning in collaborative and interdisciplinary teams and learning through trial and error where mistakes are acknowledged as learning opportunities. The DOIT program consists of seven consecutive elements. It starts with a motivation phase where students get motivated by envisioning the scope of their possibilities. The second step is about Co-design: Students are asked to collect and select potential ideas for innovations. In the Co-creation phase students gather in teams and develop first prototypes of their ideas. In the iteration phase, the prototype is continuously improved and in the next step, in the reflection phase, feedback on the prototypes is exchanged between the teams. In the last two steps, scaling and reaching out, the robustness of the prototype is tested with a bigger group of users outside of the educational setting and finally students will share their projects with a wider public. The DOIT program involves 1,000 children in two pilot phases at 11 pilot sites in ten different European countries. The comprehensive evaluation design is based on a mixed method approach with a theoretical backbone on Lackeus’ model of entrepreneurship education, which distinguishes between entrepreneurial attitudes, entrepreneurial skills and entrepreneurial knowledge. A pre-post-test with quantitative measures as well as qualitative data from interviews with facilitators, students and workshop protocols will reveal the effectiveness of the program. The evaluation results will be presented at the conference.

Keywords: early entrepreneurial education, Fab Lab, maker education, Maker movement

Procedia PDF Downloads 133
17519 The Usefulness and Future of Hearing Aids Technologies and Their Impact on Hearing

Authors: Amirreza Razzaghipour Sorkhab

Abstract:

Hearing loss is one of the greatest common chronic health situations of older people. Hearing aids are the common treatment, and they recover the quality of life in older adults. Even so, comparatively few older adults with simple, mild to moderate, adult-onset, sensorineural hearing loss use hearing aids. It shouldn’t be expected that more expensive hearing aids always produce better outcomes. Given the importance of quality pledge, approaches of quantifying hearing aid fitting achievement are needed. Studies showed an important reduction in handicap following 3 weeks of hearing aid use, signifying the feasibility of using the Hearing Hindrance Inventory for the Elderly as an outcome measure for hearing aid success after a brief interval of hearing aid use. The results showed important development of the quality of life after three months of using a hearing aid in all members and improvement of their most important problems, i.e., the communication and exchange of data. Hearing loss can impair the conversation of information and so decreases the quality of life. Hearing aids have progressivemeaningfully over the past decade, chiefly due to the growing of digital technology. The next decade should see an even greater number of innovations to hearing aid technology. Development in digital hearing aids will be driven by investigate advances in the next fields such as wireless technology, hearing science, and cognitive scienceMoreover, emerging trends such as connectivity and individuation will also drive new technology. We hope that the advancement of technology will be enough to meet the needs of people with hearing aids.

Keywords: hearing loss, hearing aid, hearing aid technology, health

Procedia PDF Downloads 107
17518 Cultivating Concentration and Flow: Evaluation of a Strategy for Mitigating Digital Distractions in University Education

Authors: Vera G. Dianova, Lori P. Montross, Charles M. Burke

Abstract:

In the digital age, the widespread and frequently excessive use of mobile phones amongst university students is recognized as a significant distractor which interferes with their ability to enter a deep state of concentration during studies and diminishes their prospects of experiencing the enjoyable and instrumental state of flow, as defined and described by psychologist M. Csikszentmihalyi. This study has targeted 50 university students with the aim of teaching them to cultivate their ability to engage in deep work and to attain the state of flow, fostering more effective and enjoyable learning experiences. Prior to the start of the intervention, all participating students completed a comprehensive survey based on a variety of validated scales assessing their inclination toward lifelong learning, frequency of flow experiences during study, frustration tolerance, sense of agency, as well as their love of learning and daily time devoted to non-academic mobile phone activities. Several days after this initial assessment, students received a 90-minute lecture on the principles of flow and deep work, accompanied by a critical discourse on the detrimental effects of excessive mobile phone usage. They were encouraged to practice deep work and strive for frequent flow states throughout the semester. Subsequently, students submitted weekly surveys, including the 10-item CORE Dispositional Flow Scale, a 3-item agency scale and furthermore disclosed their average daily hours spent on non-academic mobile phone usage. As a final step, at the end of the semester students engaged in reflective report writing, sharing their experiences and evaluating the intervention's effectiveness. They considered alterations in their love of learning, reflected on the implications of their mobile phone usage, contemplated improvements in their tolerance for boredom and perseverance in complex tasks, and pondered the concept of lifelong learning. Additionally, students assessed whether they actively took steps towards managing their recreational phone usage and towards improving their commitment to becoming lifelong learners. Employing a mixed-methods approach our study offers insights into the dynamics of concentration, flow, mobile phone usage and attitudes towards learning among undergraduate and graduate university students. The findings of this study aim to promote profound contemplation, on the part of both students and instructors, on the rapidly evolving digital-age higher education environment. In an era defined by digital and AI advancements, the ability to concentrate, to experience the state of flow, and to love learning has never been more crucial. This study underscores the significance of addressing mobile phone distractions and providing strategies for cultivating deep concentration. The insights gained can guide educators in shaping effective learning strategies for the digital age. By nurturing a love for learning and encouraging lifelong learning, educational institutions can better prepare students for a rapidly changing labor market, where adaptability and continuous learning are paramount for success in a dynamic career landscape.

Keywords: deep work, flow, higher education, lifelong learning, love of learning

Procedia PDF Downloads 68
17517 Partnership Oriented Innovation Alliance Strategy Based on Market Feedback

Authors: Victor Romanov, Daria Efimenko

Abstract:

The focus on innovation in modern economy is the main factor in surviving business in a competitive environment. The innovations are based on the search and use of knowledge in a global context. Nowadays consumers and market demand are the main innovation drivers. This leads to build a business as a system with feedback, promptly restructuring production and innovation implementation in response to market demands. In modern knowledge economy, because of speed of technical progress, the product's lifecycle became much shorter, what makes more stringent requirements for innovation implementation on the enterprises of and therefore the possibility for enterprise for receiving extra income is decreasing. This circumstance imposes additional requirements for the replacement of obsolete products and the prompt release of innovative products to the market. The development of information technologies has led to the fact that only in the conditions of partnership and knowledge sharing with partners it is possible to update products quickly for innovative products. Many companies pay attention to updating innovations through the search for new partners, but the task of finding new partners presents some difficulties. The search for a suitable one includes several stages such as: determining the moment of innovation-critical, introducing a search, identifying search criteria, justifying and deciding on the choice of a partner. No less important is the question of how to manage an innovative product in response to a changing market. The article considers the problems of information support for the search for the source of innovation and partnership to decrease the time for implementation of novelty products.

Keywords: partnership, novelty, market feedback, alliance

Procedia PDF Downloads 194
17516 A Numerical Model Simulation for an Updraft Gasifier Using High-Temperature Steam

Authors: T. M. Ismail, M. A. El-Salam

Abstract:

A mathematical model study was carried out to investigate gasification of biomass fuels using high-temperature air and steam as a gasifying agent using high-temperature air up to 1000°C. In this study, a 2D computational fluid dynamics model was developed to study the gasification process in an updraft gasifier, considering drying, pyrolysis, combustion, and gasification reactions. The gas and solid phases were resolved using a Euler−Euler multiphase approach, with exchange terms for the momentum, mass, and energy. The standard k−ε turbulence model was used in the gas phase, and the particle phase was modeled using the kinetic theory of granular flow. The results show that the present model giving a promising way in its capability and sensitivity for the parameter effects that influence the gasification process.

Keywords: computational fluid dynamics, gasification, biomass fuel, fixed bed gasifier

Procedia PDF Downloads 406
17515 Manifestation of Behavioral and Emotional Disturbances and Perceived Coping Strategies of Earthquake Survived Children

Authors: Mahwish Rabia, Najma Najam

Abstract:

The present study was conducted to identify emotional and behavioral disturbances among earthquake survived children and the perceived coping strategies of affected children. In the present study, a sample of 50 children (6-16 years) belonging to badly affected areas (earthquake) was selected from different camps in Islamabad. Child Behavioral Checklist (CBCL) and Rotter Incomplete Sentence Blank (RISB) interpretations were used to assess variety of emotional and behavioral patterns, and Child Coping Strategies Checklist (CCSC) was used to assess the perceived coping strategies of affected children. Results showed that some of the frequent emotional/behavioral reactions exhibited by children like withdrawal, anxiety\depression, aggression and attention seeking behavior. Whereas gender-based comparisons indicated that female children showed more internalizing behavioral patterns (withdrawn, somatic complaints) as compared to male children who exhibited more externalizing emotions (aggression, delinquent behavior).Coping strategies in which male children tried to adopt Positive Cognitive Restructuring and for distracting attention they used distraction strategies of coping. It is concluded that significant negative emotional and behavioral reactions are exhibited by the earthquake affected children. Male children adopt coping strategies more as compared to female children. The study identifies the negative emotional and behavioral reactions towards trauma, which can be helpful for identifying the problematic area for counseling and therapeutic interventions for these children.

Keywords: behavioural disturbances, emotional disturbances, coping strategies, earthquake, children

Procedia PDF Downloads 485
17514 Multiphase Flow Model for 3D Numerical Model Using ANSYS for Flow over Stepped Cascade with End Sill

Authors: Dheyaa Wajid Abbood, Hanan Hussien Abood

Abstract:

Stepped cascade has been utilized as a hydraulic structure for years. It has proven to be the least costly aeration system in replenishing dissolved oxygen. Numerical modeling of stepped cascade with end sill is very complicated and challenging because of the high roughness and velocity re circulation regions. Volume of fluid multiphase flow model (VOF) is used .The realizable k-ξ model is chosen to simulate turbulence. The computational results are compared with lab-scale stepped cascade data. The lab –scale model was constructed in the hydraulic laboratory, Al-Mustansiriya University, Iraq. The stepped cascade was 0.23 m wide and consisted of 3 steps each 0.2m high and 0.6 m long with variable end sill. The discharge was varied from 1 to 4 l/s. ANSYS has been employed to simulate the experimental data and their related results. This study shows that ANSYS is able to predict results almost the same as experimental findings in some regions of the structure.

Keywords: stepped cascade weir, aeration, multiphase flow model, ansys

Procedia PDF Downloads 336
17513 Developing an Integrated Seismic Risk Model for Existing Buildings in Northern Algeria

Authors: R. Monteiro, A. Abarca

Abstract:

Large scale seismic risk assessment has become increasingly popular to evaluate the physical vulnerability of a given region to seismic events, by putting together hazard, exposure and vulnerability components. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), explains the steps and expected results for the development of an integrated seismic risk model for assessment of the vulnerability of residential buildings in Northern Algeria. For this purpose, the model foresees the consideration of an updated seismic hazard model, as well as ad-hoc exposure and physical vulnerability models for local residential buildings. The first results of this endeavor, such as the hazard model and a specific taxonomy to be used for the exposure and fragility components of the model are presented, using as starting point the province of Blida, in Algeria. Specific remarks and conclusions regarding the characteristics of the Northern Algerian in-built are then made based on these results.

Keywords: Northern Algeria, risk, seismic hazard, vulnerability

Procedia PDF Downloads 201
17512 Modelling of Atomic Force Microscopic Nano Robot's Friction Force on Rough Surfaces

Authors: M. Kharazmi, M. Zakeri, M. Packirisamy, J. Faraji

Abstract:

Micro/Nanorobotics or manipulation of nanoparticles by Atomic Force Microscopic (AFM) is one of the most important solutions for controlling the movement of atoms, particles and micro/nano metrics components and assembling of them to design micro/nano-meter tools. Accurate modelling of manipulation requires identification of forces and mechanical knowledge in the Nanoscale which are different from macro world. Due to the importance of the adhesion forces and the interaction of surfaces at the nanoscale several friction models were presented. In this research, friction and normal forces that are applied on the AFM by using of the dynamic bending-torsion model of AFM are obtained based on Hurtado-Kim friction model (HK), Johnson-Kendall-Robert contact model (JKR) and Greenwood-Williamson roughness model (GW). Finally, the effect of standard deviation of asperities height on the normal load, friction force and friction coefficient are studied.

Keywords: atomic force microscopy, contact model, friction coefficient, Greenwood-Williamson model

Procedia PDF Downloads 199
17511 Wind Wave Modeling Using MIKE 21 SW Spectral Model

Authors: Pouya Molana, Zeinab Alimohammadi

Abstract:

Determining wind wave characteristics is essential for implementing projects related to Coastal and Marine engineering such as designing coastal and marine structures, estimating sediment transport rates and coastal erosion rates in order to predict significant wave height (H_s), this study applies the third generation spectral wave model, Mike 21 SW, along with CEM model. For SW model calibration and verification, two data sets of meteorology and wave spectroscopy are used. The model was exposed to time-varying wind power and the results showed that difference ratio mean, standard deviation of difference ratio and correlation coefficient in SW model for H_s parameter are 1.102, 0.279 and 0.983, respectively. Whereas, the difference ratio mean, standard deviation and correlation coefficient in The Choice Experiment Method (CEM) for the same parameter are 0.869, 1.317 and 0.8359, respectively. Comparing these expected results it is revealed that the Choice Experiment Method CEM has more errors in comparison to MIKE 21 SW third generation spectral wave model and higher correlation coefficient does not necessarily mean higher accuracy.

Keywords: MIKE 21 SW, CEM method, significant wave height, difference ratio

Procedia PDF Downloads 402
17510 The Clarification of Palm Oil Wastewater Treatment by Coagulant Composite from Palm Oil Ash

Authors: Rewadee Anuwattana, Narumol Soparatana, Pattamaphorn Phuangngamphan, Worapong Pattayawan, Atiporn Jinprayoon, Saroj Klangkongsap, Supinya Sutthima

Abstract:

In this work focus on clarification in palm oil wastewater treatment by using coagulant composite from palm oil ash. The design of this study was carried out by two steps; first, synthesis of new coagulant composite from palm oil ash which was fused by using Al source combined with Fe source and form to the crystal by the hydrothermal crystallization process. The characterization of coagulant composite from palm oil ash was analyzed by advanced instruments, and The pattern was analyzed by X-ray Diffraction (XRD), chemical composition by X-Ray Fluorescence (XRFS) and morphology characterized by SEM. The second step, the clarification wastewater treatment efficiency of synthetic coagulant composite, was evaluated by coagulation/flocculation process based on the COD, turbidity, phosphate and color removal of wastewater from palm oil factory by varying the coagulant dosage (1-8 %w/v) with no adjusted pH and commercial coagulants (Alum, Ferric Chloride and poly aluminum chloride) which adjusted the pH (6). The results found that the maximum removal of 6% w/v of synthetic coagulant from palm oil ash can remove COD, turbidity, phosphate and color was 88.44%, 93.32%, 93.32% and 93.32%, respectively. The experiments were compared using 6% w/v of commercial coagulants (Alum, Ferric Chloride and Polyaluminum Chloride) can remove COD of 74.29%, 71.43% and 57.14%, respectively.

Keywords: coagulation, coagulant, wastewater treatment, waste utilization, palm oil ash

Procedia PDF Downloads 191
17509 Superiority of High Frequency Based Volatility Models: Empirical Evidence from an Emerging Market

Authors: Sibel Celik, Hüseyin Ergin

Abstract:

The paper aims to find the best volatility forecasting model for stock markets in Turkey. For this purpose, we compare performance of different volatility models-both traditional GARCH model and high frequency based volatility models- and conclude that both in pre-crisis and crisis period, the performance of high frequency based volatility models are better than traditional GARCH model. The findings of paper are important for policy makers, financial institutions and investors.

Keywords: volatility, GARCH model, realized volatility, high frequency data

Procedia PDF Downloads 486
17508 Application of the Tripartite Model to the Link between Non-Suicidal Self-Injury and Suicidal Risk

Authors: Ashley Wei-Ting Wang, Wen-Yau Hsu

Abstract:

Objectives: The current study applies and expands the Tripartite Model to elaborate the link between non-suicidal self-injury (NSSI) and suicidal behavior. We propose a structural model of NSSI and suicidal risk, in which negative affect (NA) predicts both anxiety and depression, positive affect (PA) predicts depression only, anxiety is linked to NSSI, and depression is linked to suicidal risk. Method: Four hundreds and eighty seven undergraduates participated. Data were collected by administering self-report questionnaires. We performed hierarchical regression and structural equation modeling to test the proposed structural model. Results: The results largely support the proposed structural model, with one exception: anxiety was strongly associated with NSSI and to a lesser extent with suicidal risk. Conclusions: We conclude that the co-occurrence of NSSI and suicidal risk is due to NA and anxiety, and suicidal risk can be differentiated by depression. Further theoretical and practical implications are discussed.

Keywords: non-suicidal self-injury, suicidal risk, anxiety, depression, the tripartite model, hierarchical relationship

Procedia PDF Downloads 470
17507 Enacting Educational Technology Affordances as Mechanisms Responsible for Gaining Epistemological Access: A Case of Underprivileged Students at Higher Institutions in Northern Nigeria

Authors: Bukhari Badamasi, Chidi G. Ononiwu

Abstract:

Globally, educational technology (EdTech) has become a known catalyst for gaining access to education, job creation, and national development of a nation. Howbeit, it is common understanding that higher institutions continue to deploy digital technologies, to help provide access to education, but in most case, it is somehow institutional access not epistemological access especially in sub Saharan African higher institutions. Some scholars, however, lament the fact that studies on educational technology affordances are mostly fragmented because they focus on specific theme or sub aspect of access (i.e., institutional access). Thus, drawing from the Archer Morphogenetic approach, and Gibson Affordance theory, and applying critical realist based Danermark model for explanatory research, the study seeks to conduct a realist case study on underprivileged students in Higher institutions on how they gain epistemological access by enacting educational technology (EdTech) affordances.

Keywords: affordance, epistemological access, educational technology, underprivileged students

Procedia PDF Downloads 84
17506 Valuation of Caps and Floors in a LIBOR Market Model with Markov Jump Risks

Authors: Shih-Kuei Lin

Abstract:

The characterization of the arbitrage-free dynamics of interest rates is developed in this study under the presence of Markov jump risks, when the term structure of the interest rates is modeled through simple forward rates. We consider Markov jump risks by allowing randomness in jump sizes, independence between jump sizes and jump times. The Markov jump diffusion model is used to capture empirical phenomena and to accurately describe interest jump risks in a financial market. We derive the arbitrage-free model of simple forward rates under the spot measure. Moreover, the analytical pricing formulas for a cap and a floor are derived under the forward measure when the jump size follows a lognormal distribution. In our empirical analysis, we find that the LIBOR market model with Markov jump risk better accounts for changes from/to different states and different rates.

Keywords: arbitrage-free, cap and floor, Markov jump diffusion model, simple forward rate model, volatility smile, EM algorithm

Procedia PDF Downloads 421
17505 Integrated Gas Turbine Performance Diagnostics and Condition Monitoring Using Adaptive GPA

Authors: Yi-Guang Li, Suresh Sampath

Abstract:

Gas turbine performance degrades over time, and the degradation is greatly affected by environmental, ambient, and operating conditions. The engines may degrade slowly under favorable conditions and result in a waste of engine life if a scheduled maintenance scheme is followed. They may also degrade fast and fail before a scheduled overhaul if the conditions are unfavorable, resulting in serious secondary damage, loss of engine availability, and increased maintenance costs. To overcome these problems, gas turbine owners are gradually moving from scheduled maintenance to condition-based maintenance, where condition monitoring is one of the key supporting technologies. This paper presents an integrated adaptive GPA diagnostics and performance monitoring system developed at Cranfield University for gas turbine gas path condition monitoring. It has the capability to predict the performance degradation of major gas path components of gas turbine engines, such as compressors, combustors, and turbines, using gas path measurement data. It is also able to predict engine key performance parameters for condition monitoring, such as turbine entry temperature that cannot be directly measured. The developed technology has been implemented into digital twin computer Software, Pythia, to support the condition monitoring of gas turbine engines. The capabilities of the integrated GPA condition monitoring system are demonstrated in three test cases using a model gas turbine engine similar to the GE aero-derivative LM2500 engine widely used in power generation and marine propulsion. It shows that when the compressor of the model engine degrades, the Adaptive GPA is able to predict the degradation and the changing engine performance accurately using gas path measurements. Such a presented technology and software are generic, can be applied to different types of gas turbine engines, and provide crucial engine health and performance parameters to support condition monitoring and condition-based maintenance.

Keywords: gas turbine, adaptive GPA, performance, diagnostics, condition monitoring

Procedia PDF Downloads 88
17504 An Investigation of Cyber Financial Crimes After the Enactment of PECA: A Case Study of Pakistan’s Banking Sector During 2016 to 2022

Authors: Zain Khalid

Abstract:

The paper outlines the trends of cyber financial crimes and frauds – approximating upto – in Pakistan after the enactment of The Prevention of Electronic Crimes Act in 2016. The paper elaborates on the newer methods that fraudsters have adopted after tighter preventive and counter measures were employed in Pakistan partly as a result of following the international finance related commitments, particularly the FATF regulations. The paper adopts case studies methods to highlight various aspects of the financial frauds and crimes committed and later investigated jointly by Pakistan’s one of the federal law enforcement agencies, the Federal Investigation Agency, and Mobilink Microfinance Bank , Pakistan’s premier microfinance bank. It additionally enriches the data through expert interviews – with crime investigators and the experts to carry out an in-depth analysis of the various factors involving the crime. This paper emphasizes the structural and situational factors that shape up the cyber financial crimes in Pakistan vis-à-vis digital illiteracy and lack of awareness among the users of financial services. This paper, thus, on the basis of findings and expert interviews, suggests policy reforms to reduce the instances of the financial crimes, especially in the remotest areas of the country.

Keywords: financial crimes, cyber crimes, digital literacy, terrorism financing, banking sector

Procedia PDF Downloads 88
17503 An Adjusted Network Information Criterion for Model Selection in Statistical Neural Network Models

Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

Abstract:

In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

Procedia PDF Downloads 567
17502 Training Undergraduate Engineering Students in Robotics and Automation through Model-Based Design Training: A Case Study at Assumption University of Thailand

Authors: Sajed A. Habib

Abstract:

Problem-based learning (PBL) is a student-centered pedagogy that originated in the medical field and has also been used extensively in other knowledge disciplines with recognized advantages and limitations. PBL has been used in various undergraduate engineering programs with mixed outcomes. The current fourth industrial revolution (digital era or Industry 4.0) has made it essential for many science and engineering students to receive effective training in advanced courses such as industrial automation and robotics. This paper presents a case study at Assumption University of Thailand, where a PBL-like approach was used to teach some aspects of automation and robotics to selected groups of undergraduate engineering students. These students were given some basic level training in automation prior to participating in a subsequent training session in order to solve technical problems with increased complexity. The participating students’ evaluation of the training sessions in terms of learning effectiveness, skills enhancement, and incremental knowledge following the problem-solving session was captured through a follow-up survey consisting of 14 questions and a 5-point scoring system. From the most recent training event, an overall 70% of the respondents indicated that their skill levels were enhanced to a much greater level than they had had before the training, whereas 60.4% of the respondents from the same event indicated that their incremental knowledge following the session was much greater than what they had prior to the training. The instructor-facilitator involved in the training events suggested that this method of learning was more suitable for senior/advanced level students than those at the freshmen level as certain skills to effectively participate in such problem-solving sessions are acquired over a period of time, and not instantly.

Keywords: automation, industry 4.0, model-based design training, problem-based learning

Procedia PDF Downloads 134
17501 Causal Modeling of the Glucose-Insulin System in Type-I Diabetic Patients

Authors: J. Fernandez, N. Aguilar, R. Fernandez de Canete, J. C. Ramos-Diaz

Abstract:

In this paper, a simulation model of the glucose-insulin system for a patient undergoing diabetes Type 1 is developed by using a causal modeling approach under system dynamics. The OpenModelica simulation environment has been employed to build the so called causal model, while the glucose-insulin model parameters were adjusted to fit recorded mean data of a diabetic patient database. Model results under different conditions of a three-meal glucose and exogenous insulin ingestion patterns have been obtained. This simulation model can be useful to evaluate glucose-insulin performance in several circumstances, including insulin infusion algorithms in open-loop and decision support systems in closed-loop.

Keywords: causal modeling, diabetes, glucose-insulin system, diabetes, causal modeling, OpenModelica software

Procedia PDF Downloads 330
17500 A Mathematical Optimization Model for Locating and Fortifying Capacitated Warehouses under Risk of Failure

Authors: Tareq Oshan

Abstract:

Facility location and size decisions are important to any company because they affect profitability and success. However, warehouses are exposed to various risks of failure that affect their activity. This paper presents a mixed-integer non-linear mathematical model that can be used to determine optimal warehouse locations and sizes, which warehouses to fortify, and which branches should be assigned to specific warehouses when there is a risk of warehouse failure. Every branch is assigned to a fortified primary warehouse or a nonfortified primary warehouse and a fortified backup warehouse. The standard method and an introduced method, based on the average probabilities, for linearizing this mathematical model were used. A Canadian case study was used to demonstrate the developed mathematical model, followed by some sensitivity analysis.

Keywords: supply chain network design, fortified warehouse, mixed-integer mathematical model, warehouse failure risk

Procedia PDF Downloads 243
17499 Optimization for Autonomous Robotic Construction by Visual Guidance through Machine Learning

Authors: Yangzhi Li

Abstract:

Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 86