Search results for: teaching and learning model
12617 A Conceptual Model of the Factors Affecting Saudi Citizens' Use of Social Media to Communicate with the Government
Authors: Reemiah Alotaibi, Muthu Ramachandran, Ah-Lian Kor, Amin Hosseinian-Far
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In the past decade, developers of Web 2.0 technologies have shown increasing interest in the topic of e-government. There has been a rapid growth in social media technology because of its significant role in backing up some essential social needs. Its importance and power is derived from its capacity to support two-way communication. Governments are curious to get engaged in these websites, hoping to benefit from the new forms of communication and interaction offered by such technology. Greater participation by the public can be viewed as a chief indicator of effective government communication. Yet, the level of public participation in government 2.0 is not quite satisfactory. In general, it is still at the early stage in most developing countries, including Saudi Arabia. Although it is a fact that Saudi people are among the most active in using social media, the number of people who use social media to communicate with the public institutions is not high. Furthermore, most of the governmental organisations are not using social media tools to communicate with the public. They use these platforms to disseminate information. Our study focuses on the factors affecting citizens’ adoption of social media in Saudi Arabia. Our research question is: what are the factors affecting Saudi citizens’ use of social media to communicate with the government? To answer this research question, the research aims to validate the UTAUT model for examining social media tools from the citizen perspective. An amendment will be proposed to fit the adoption of social media platforms as a communication channel in government by using a developed conceptual model which integrates constructs from the UTAUT model and others external variables based on the literature review. The set of potential factors that affect these citizens' decisions to adopt social media to communicate with their government has been identified as perceived encouragement, trust and cultural influence. The connection between the above-mentioned constructs from the basis for the research hypothesis will be examined in the light of a quantitative methodology. Data collection will be performed through a survey targeting a number of Saudi citizens who are social media users. The data collected from the primary survey will later be analysed by using statistical methods. The outcomes of this research project are argued to have potential contributions to the fields of social media and e-Government adoption, both on the theoretical and practical levels. It is believed that this research project is the first of its type that attempts to identify the factors that affect citizens’ adoption of social media to communicate with the government. The importance of identifying these factors stems from the potential use of them to enhance the government’s implementation of social media and help in making more accurate decisions and strategies based on comprehending the most important factors that affect citizens’ decisions.Keywords: social media, adoption, citizen, UTAUT model
Procedia PDF Downloads 40812616 Global Healthcare Village Based on Mobile Cloud Computing
Authors: Laleh Boroumand, Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar
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Cloud computing being the use of hardware and software that are delivered as a service over a network has its application in the area of health care. Due to the emergency cases reported in most of the medical centers, prompt for an efficient scheme to make health data available with less response time. To this end, we propose a mobile global healthcare village (MGHV) model that combines the components of three deployment model which include country, continent and global health cloud to help in solving the problem mentioned above. In the creation of continent model, two (2) data centers are created of which one is local and the other is global. The local replay the request of residence within the continent, whereas the global replay the requirements of others. With the methods adopted, there is an assurance of the availability of relevant medical data to patients, specialists, and emergency staffs regardless of locations and time. From our intensive experiment using the simulation approach, it was observed that, broker policy scheme with respect to optimized response time, yields a very good performance in terms of reduction in response time. Though, our results are comparable to others when there is an increase in the number of virtual machines (80-640 virtual machines). The proportionality in increase of response time is within 9%. The results gotten from our simulation experiments shows that utilizing MGHV leads to the reduction of health care expenditures and helps in solving the problems of unqualified medical staffs faced by both developed and developing countries.Keywords: cloud computing (MCC), e-healthcare, availability, response time, service broker policy
Procedia PDF Downloads 37212615 An Application of Extreme Value Theory as a Risk Measurement Approach in Frontier Markets
Authors: Dany Ng Cheong Vee, Preethee Nunkoo Gonpot, Noor Sookia
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In this paper, we consider the application of Extreme Value Theory as a risk measurement tool. The Value at Risk, for a set of indices, from six Stock Exchanges of Frontier markets is calculated using the Peaks over Threshold method and the performance of the model index-wise is evaluated using coverage tests and loss functions. Our results show that 'fat-tailedness' alone of the data is not enough to justify the use of EVT as a VaR approach. The structure of the returns dynamics is also a determining factor. This approach works fine in markets which have had extremes occurring in the past thus making the model capable of coping with extremes coming up (Colombo, Tunisia and Zagreb Stock Exchanges). On the other hand, we find that indices with lower past than present volatility fail to adequately deal with future extremes (Mauritius and Kazakhstan). We also conclude that using EVT alone produces quite static VaR figures not reflecting the actual dynamics of the data.Keywords: extreme value theory, financial crisis 2008, value at risk, frontier markets
Procedia PDF Downloads 27112614 BFDD-S: Big Data Framework to Detect and Mitigate DDoS Attack in SDN Network
Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour
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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network
Procedia PDF Downloads 16412613 Mapping of Geological Structures Using Aerial Photography
Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash
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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures
Procedia PDF Downloads 68012612 Teaching Entrepreneurship in Light of the Triple Bottom Line
Authors: Sherry Robinson, Hans Anton Stubberud
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Entrepreneurship can take many forms. Traditional entrepreneurs seek profits and growth for the businesses they start themselves. Intrapreneurs act entrepreneurially within a business they do not own. Social entrepreneurs have goals other than (but not excluding) profit and growth as they seek to solve social problems or protect the environment. This type of entrepreneur often focuses on the triple bottom line, which includes a concern for people and the planet as well as profit. Ecopreneurs in particular are driven by their desire to create and promote environmentally sustainable products and processes. All of these entrepreneurs need an entrepreneurial orientation in order to survive and thrive. The three most common elements of an entrepreneurial orientation are (1) creativity and innovation, (2) the willingness to take risks and (3) the proactiveness to put ideas into action. This study describes an interdisciplinary entrepreneurship course integrating topics regarding the triple bottom line with those relevant to an entrepreneurial orientation. The results show that students significantly increased their skill levels in many areas, including soft skills such as communicating and working in teams, as well as designing innovative products and taking calculated risk.Keywords: creativity, entrepreneurship education, sustainability, triple bottom line
Procedia PDF Downloads 46412611 Designing the Maturity Model of Smart Digital Transformation through the Foundation Data Method
Authors: Mohammad Reza Fazeli
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Nowadays, the fourth industry, known as the digital transformation of industries, is seen as one of the top subjects in the history of structural revolution, which has led to the high-tech and tactical dominance of the organization. In the face of these profits, the undefined and non-transparent nature of the after-effects of investing in digital transformation has hindered many organizations from attempting this area of this industry. One of the important frameworks in the field of understanding digital transformation in all organizations is the maturity model of digital transformation. This model includes two main parts of digital transformation maturity dimensions and digital transformation maturity stages. Mediating factors of digital maturity and organizational performance at the individual (e.g., motivations, attitudes) and at the organizational level (e.g., organizational culture) should be considered. For successful technology adoption processes, organizational development and human resources must go hand in hand and be supported by a sound communication strategy. Maturity models are developed to help organizations by providing broad guidance and a roadmap for improvement. However, as a result of a systematic review of the literature and its analysis, it was observed that none of the 18 maturity models in the field of digital transformation fully meet all the criteria of appropriateness, completeness, clarity, and objectivity. A maturity assessment framework potentially helps systematize assessment processes that create opportunities for change in processes and organizations enabled by digital initiatives and long-term improvements at the project portfolio level. Cultural characteristics reflecting digital culture are not systematically integrated, and specific digital maturity models for the service sector are less clearly presented. It is also clearly evident that research on the maturity of digital transformation as a holistic concept is scarce and needs more attention in future research.Keywords: digital transformation, organizational performance, maturity models, maturity assessment
Procedia PDF Downloads 8312610 A Novel Rapid Well Control Technique Modelled in Computational Fluid Dynamics Software
Authors: Michael Williams
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The ability to control a flowing well is of the utmost important. During the kill phase, heavy weight kill mud is circulated around the well. While increasing bottom hole pressure near wellbore formation, the damage is increased. The addition of high density spherical objects has the potential to minimise this near wellbore damage, increase bottom hole pressure and reduce operational time to kill the well. This operational time saving is seen in the rapid deployment of high density spherical objects instead of building high density drilling fluid. The research aims to model the well kill process using a Computational Fluid Dynamics software. A model has been created as a proof of concept to analyse the flow of micron sized spherical objects in the drilling fluid. Initial results show that this new methodology of spherical objects in drilling fluid agrees with traditional stream lines seen in non-particle flow. Additional models have been created to demonstrate that areas of higher flow rate around the bit can lead to increased probability of wash out of formations but do not affect the flow of micron sized spherical objects. Interestingly, areas that experience dimensional changes such as tool joints and various BHA components do not appear at this initial stage to experience increased velocity or create areas of turbulent flow, which could lead to further borehole stability. In conclusion, the initial models of this novel well control methodology have not demonstrated any adverse flow patterns, which would conclude that this model may be viable under field conditions.Keywords: well control, fluid mechanics, safety, environment
Procedia PDF Downloads 16512609 Series Network-Structured Inverse Models of Data Envelopment Analysis: Pitfalls and Solutions
Authors: Zohreh Moghaddas, Morteza Yazdani, Farhad Hosseinzadeh
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Nowadays, data envelopment analysis (DEA) models featuring network structures have gained widespread usage for evaluating the performance of production systems and activities (Decision-Making Units (DMUs)) across diverse fields. By examining the relationships between the internal stages of the network, these models offer valuable insights to managers and decision-makers regarding the performance of each stage and its impact on the overall network. To further empower system decision-makers, the inverse data envelopment analysis (IDEA) model has been introduced. This model allows the estimation of crucial information for estimating parameters while keeping the efficiency score unchanged or improved, enabling analysis of the sensitivity of system inputs or outputs according to managers' preferences. This empowers managers to apply their preferences and policies on resources, such as inputs and outputs, and analyze various aspects like production, resource allocation processes, and resource efficiency enhancement within the system. The results obtained can be instrumental in making informed decisions in the future. The top result of this study is an analysis of infeasibility and incorrect estimation that may arise in the theory and application of the inverse model of data envelopment analysis with network structures. By addressing these pitfalls, novel protocols are proposed to circumvent these shortcomings effectively. Subsequently, several theoretical and applied problems are examined and resolved through insightful case studies.Keywords: inverse models of data envelopment analysis, series network, estimation of inputs and outputs, efficiency, resource allocation, sensitivity analysis, infeasibility
Procedia PDF Downloads 3912608 The Effects of an Exercise Program Integrated with the Transtheoretical Model on Pain and Trunk Muscle Endurance of Rice Farmers with Chronic Low Back Pain
Authors: Thanakorn Thanawat, Nomjit Nualnetr
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Background and Purpose: In Thailand, rice farmers have the most prevalence of low back pain when compared with other manual workers. Exercises have been suggested to be a principal part of treatment programs for low back pain. However, the programs should be tailored to an individual’s readiness to change categorized by a behavioral approach. This study aimed to evaluate a difference between the responses of rice farmers with chronic low back pain who received an exercise program integrated with the transtheoretical model of behavior change (TTM) and those of the comparison group regarding severity of pain and trunk muscle endurance. Materials and Methods: An 8-week exercise program was conducted to rice farmers with chronic low back pain who were randomized to either the TTM (n=62, 52 woman and 10 men, mean age ± SD 45.0±5.4 years) or non-TTM (n=64, 53 woman and 11 men, mean age ± SD 44.7±5.4 years) groups. All participants were tested for their severity of pain and trunk (abdominal and back) muscle endurance at baseline (week 0) and immediately after termination of the program (week 8). Data were analysed by using descriptive statistics and student’s t-tests. The results revealed that both TTM and non-TTM groups could decrease their severity of pain and improve trunk muscle endurance after participating in the 8-week exercise program. When compared with the non-TTM group, however, the TTM showed a significantly greater increase in abdominal muscle endurance than did the non-TTM (P=0.004, 95% CI -12.4 to -2.3). Conclusions and Clinical Relevance: An exercise program integrated with the TTM could provide benefits to rice farmers with chronic low back pain. Future studies with a longitudinal design and more outcome measures such as physical performance and quality of life are suggested to reveal further benefits of the program.Keywords: chronic low back pain, transtheoretical model, rice farmers, exercise program
Procedia PDF Downloads 37712607 Shield Tunnel Excavation Simulation of a Case Study Using a So-Called 'Stress Relaxation' Method
Authors: Shengwei Zhu, Alireza Afshani, Hirokazu Akagi
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Ground surface settlement induced by shield tunneling is addressing increasing attention as shield tunneling becomes a popular construction technique for tunnels in urban areas. This paper discusses a 2D longitudinal FEM simulation of a tunneling case study in Japan (Tokyo Metro Yurakucho Line). Tunneling-induced field data was already collected and is used here for comparison and evaluating purposes. In this model, earth pressure, face pressure, backfilling grouting, elastic tunnel lining, and Mohr-Coulomb failure criterion for soil elements are considered. A method called ‘stress relaxation’ is also exploited to simulate the gradual tunneling excavation. Ground surface settlements obtained from numerical results using the introduced method are then compared with the measurement data.Keywords: 2D longitudinal FEM model, tunneling case study, stress relaxation, shield tunneling excavation
Procedia PDF Downloads 32312606 Modelling and Simulating CO2 Electro-Reduction to Formic Acid Using Microfluidic Electrolytic Cells: The Influence of Bi-Sn Catalyst and 1-Ethyl-3-Methyl Imidazolium Tetra-Fluoroborate Electrolyte on Cell Performance
Authors: Akan C. Offong, E. J. Anthony, Vasilije Manovic
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A modified steady-state numerical model is developed for the electrochemical reduction of CO2 to formic acid. The numerical model achieves a CD (current density) (~60 mA/cm2), FE-faradaic efficiency (~98%) and conversion (~80%) for CO2 electro-reduction to formic acid in a microfluidic cell. The model integrates charge and species transport, mass conservation, and momentum with electrochemistry. Specifically, the influences of Bi-Sn based nanoparticle catalyst (on the cathode surface) at different mole fractions and 1-ethyl-3-methyl imidazolium tetra-fluoroborate ([EMIM][BF4]) electrolyte, on CD, FE and CO2 conversion to formic acid is studied. The reaction is carried out at a constant concentration of electrolyte (85% v/v., [EMIM][BF4]). Based on the mass transfer characteristics analysis (concentration contours), mole ratio 0.5:0.5 Bi-Sn catalyst displays the highest CO2 mole consumption in the cathode gas channel. After validating with experimental data (polarisation curves) from literature, extensive simulations reveal performance measure: CD, FE and CO2 conversion. Increasing the negative cathode potential increases the current densities for both formic acid and H2 formations. However, H2 formations are minimal as a result of insufficient hydrogen ions in the ionic liquid electrolyte. Moreover, the limited hydrogen ions have a negative effect on formic acid CD. As CO2 flow rate increases, CD, FE and CO2 conversion increases.Keywords: carbon dioxide, electro-chemical reduction, ionic liquids, microfluidics, modelling
Procedia PDF Downloads 13812605 Dynamic Construction Site Layout Using Ant Colony Optimization
Authors: Yassir AbdelRazig
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Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model.Keywords: ant colony, construction site layout, optimization, genetic algorithms
Procedia PDF Downloads 37312604 Advanced Real-Time Fluorescence Imaging System for Rat's Femoral Vein Thrombosis Monitoring
Authors: Sang Hun Park, Chul Gyu Song
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Artery and vein occlusion changes observed in patients and experimental animals are unexplainable symptoms. As the fat accumulated in cardiovascular ruptures, it causes vascular blocking. Likewise, early detection of cardiovascular disease can be useful for treatment. In this study, we used the mouse femoral occlusion model to observe the arterial and venous occlusion changes without darkroom. We observed the femoral arterial flow pattern changes by proposed fluorescent imaging system using an animal model of thrombosis. We adjusted the near-infrared light source current in order to control the intensity of the fluorescent substance light. We got the clear fluorescent images and femoral artery flow pattern were measured by a 5-minute interval. The result showed that the fluorescent substance flowing in the femoral arteries were accumulated in thrombus as time passed, and the fluorescence of other vessels gradually decreased.Keywords: thrombus, fluorescence, femoral, arteries
Procedia PDF Downloads 33312603 A Guide for Using Viscoelasticity in ANSYS
Authors: A. Fettahoglu
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Theory of viscoelasticity is used by many researchers to represent the behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell model and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Afterwards, a guide is illustrated to ease using of viscoelasticity tool in ANSYS.Keywords: ANSYS, generalized Maxwell model, finite element method, Prony series, viscoelasticity, viscoelastic material curve fitting
Procedia PDF Downloads 56812602 Multilevel Regression Model - Evaluate Relationship Between Early Years’ Activities of Daily Living and Alzheimer’s Disease Onset Accounting for Influence of Key Sociodemographic Factors Using a Longitudinal Household Survey Data
Authors: Linyi Fan, C.J. Schumaker
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Background: Biomedical efforts to treat Alzheimer’s disease (AD) have typically produced mixed to poor results, while more lifestyle-focused treatments such as exercise may fare better than existing biomedical treatments. A few promising studies have indicated that activities of daily life (ADL) may be a useful way of predicting AD. However, the existing cross-sectional studies fail to show how functional-related issues such as ADL in early years predict AD and how social factors influence health either in addition to or in interaction with individual risk factors. This study would helpbetterscreening and early treatments for the elderly population and healthcare practice. The findings have significance academically and practically in terms of creating positive social change. Methodology: The purpose of this quantitative historical, correlational study was to examine the relationship between early years’ ADL and the development of AD in later years. The studyincluded 4,526participantsderived fromRAND HRS dataset. The Health and Retirement Study (HRS) is a longitudinal household survey data set that is available forresearchof retirement and health among the elderly in the United States. The sample was selected by the completion of survey questionnaire about AD and dementia. The variablethat indicates whether the participant has been diagnosed with AD was the dependent variable. The ADL indices and changes in ADL were the independent variables. A four-step multilevel regression model approach was utilized to address the research questions. Results: Amongst 4,526 patients who completed the AD and dementia questionnaire, 144 (3.1%) were diagnosed with AD. Of the 4,526 participants, 3,465 (76.6%) have high school and upper education degrees,4,074 (90.0%) were above poverty threshold. The model evaluatedthe effect of ADL and change in ADL on onset of AD in late years while allowing the intercept of the model to vary by level of education. The results suggested that the only significant predictor of the onset of AD was changes in early years’ ADL (b = 20.253, z = 2.761, p < .05). However, the result of the sensitivity analysis (b = 7.562, z = 1.900, p =.058), which included more control variables and increased the observation period of ADL, are not supported this finding. The model also estimated whether the variances of random effect vary by Level-2 variables. The results suggested that the variances associated with random slopes were approximately zero, suggesting that the relationship between early years’ ADL were not influenced bysociodemographic factors. Conclusion: The finding indicated that an increase in changes in ADL leads to an increase in the probability of onset AD in the future. However, this finding is not support in a broad observation period model. The study also failed to reject the hypothesis that the sociodemographic factors explained significant amounts of variance in random effect. Recommendations were then made for future research and practice based on these limitations and the significance of the findings.Keywords: alzheimer’s disease, epidemiology, moderation, multilevel modeling
Procedia PDF Downloads 12512601 Three Issues for Integrating Artificial Intelligence into Legal Reasoning
Authors: Fausto Morais
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Artificial intelligence has been widely used in law. Programs are able to classify suits, to identify decision-making patterns, to predict outcomes, and to formalize legal arguments as well. In Brazil, the artificial intelligence victor has been classifying cases to supreme court’s standards. When those programs act doing those tasks, they simulate some kind of legal decision and legal arguments, raising doubts about how artificial intelligence can be integrated into legal reasoning. Taking this into account, the following three issues are identified; the problem of hypernormatization, the argument of legal anthropocentrism, and the artificial legal principles. Hypernormatization can be seen in the Brazilian legal context in the Supreme Court’s usage of the Victor program. This program generated efficiency and consistency. On the other hand, there is a feasible risk of over standardizing factual and normative legal features. Then legal clerks and programmers should work together to develop an adequate way to model legal language into computational code. If this is possible, intelligent programs may enact legal decisions in easy cases automatically cases, and, in this picture, the legal anthropocentrism argument takes place. Such an argument argues that just humans beings should enact legal decisions. This is so because human beings have a conscience, free will, and self unity. In spite of that, it is possible to argue against the anthropocentrism argument and to show how intelligent programs may work overcoming human beings' problems like misleading cognition, emotions, and lack of memory. In this way, intelligent machines could be able to pass legal decisions automatically by classification, as Victor in Brazil does, because they are binding by legal patterns and should not deviate from them. Notwithstanding, artificial intelligent programs can be helpful beyond easy cases. In hard cases, they are able to identify legal standards and legal arguments by using machine learning. For that, a dataset of legal decisions regarding a particular matter must be available, which is a reality in Brazilian Judiciary. Doing such procedure, artificial intelligent programs can support a human decision in hard cases, providing legal standards and arguments based on empirical evidence. Those legal features claim an argumentative weight in legal reasoning and should serve as references for judges when they must decide to maintain or overcome a legal standard.Keywords: artificial intelligence, artificial legal principles, hypernormatization, legal anthropocentrism argument, legal reasoning
Procedia PDF Downloads 13812600 Tuned Mass Damper Effects of Stationary People on Structural Damping of Footbridge Due to Dynamic Interaction in Vertical Motion
Authors: M. Yoneda
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It is known that stationary human occupants act as dynamic mass-spring-damper systems and can change the modal properties of civil engineering structures. This paper describes the full scale measurement to explain the tuned mass damper effects of stationary people on structural damping of footbridge with center span length of 33 m. A human body can be represented by a lumped system consisting of masses, springs, and dashpots. Complex eigenvalue calculation is also conducted by using ISO5982:1981 human model (two degree of freedom system). Based on experimental and analytical results for the footbridge with the stationary people in the standing position, it is demonstrated that stationary people behave as a tuned mass damper and that ISO5982:1981 human model can explain the structural damping characteristics measured in the field.Keywords: dynamic interaction, footbridge, stationary people, structural damping
Procedia PDF Downloads 26612599 A Framework for Defining Innovation Districts: A Case Study of 22@ Barcelona
Authors: Arnault Morisson
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Innovation districts are being implemented as urban regeneration strategies in cities as diverse as Barcelona (Spain), Boston (Massachusetts), Chattanooga (Tennessee), Detroit (Michigan), Medellin (Colombia), and Montréal (Canada). Little, however, is known about the concept. This paper aims to provide a framework to define innovation districts. The research methodology is based on a qualitative approach using 22@ Barcelona as a case study. 22@ Barcelona was the first innovation district ever created and has been a model for the innovation districts of Medellin (Colombia) and Boston (Massachusetts) among others. Innovation districts based on the 22@ Barcelona’s model can be defined as top-down urban innovation ecosystems designed around four multilayered and multidimensional models of innovation: urban planning, productive, collaborative, and creative, all coordinated under strong leadership, with the ultimate objectives to accelerate the innovation process and competitiveness of a locality. Innovation districts aim to respond to a new economic paradigm in which economic production flows back to cities.Keywords: innovation ecosystem, governance, technology park, urban planning, urban policy, urban regeneration
Procedia PDF Downloads 36312598 Effect of Dual-Oligo Saccharide on Loperamide-Induced Constipation in Rat Model
Authors: So Hyun Ahn, Geu Rim Seo, Byungsoo Shin, Kwang-Won Yu, Hyung Joo Suh, Sung Hee Han
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We investigated the effects of GOS, lactulose and DuOligo in loperamide-induced constipation rat model. Dual-Oligo saccharide (DuOligo) was composed with galacto-oligosaccharide (GOS) and lactulose. GOS is an important dietary prebiotics that affects intestinal microbiota and barrier functions to have beneficial effect and lactulose is used as a laxative to treat constipation. To study the DuOligo, after adaptation period of four weeks of Spraque-Dawley rats, loperamide (5 mg/kg, twice per day) was injected to induce constipation for 1 week. DuOligo increased the fecal pellet amount, fecal weight, and water content of feces in rats with loperamide-induced constipation. DuOligo groups tended to produce more total fatty acid than that of observed for the control group. Gastrointestinal transit ratio and length and area of intestinal mucosa increased after treatment with DuOligo in loperamide-induced rats. These results showed that oral administration of DuOligo significantly modulated intestinal peristalsis.Keywords: constipation, DuOligo, GOS, lactulose
Procedia PDF Downloads 40712597 The Effects of Wood Ash on Ignition Point of Wood
Authors: K. A. Ibe, J. I. Mbonu, G. K. Umukoro
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The effects of wood ash on the ignition point of five common tropical woods in Nigeria were investigated. The ash and moisture contents of the wood saw dust from Mahogany (Khaya ivorensis), Opepe (Sarcocephalus latifolius), Abura (Hallealedermannii verdc), Rubber (Heavea brasilensis) and Poroporo (Sorghum bicolour) were determined using a furnace (Vecstar furnaces, model ECF2, serial no. f3077) and oven (Genlab laboratory oven, model MINO/040) respectively. The metal contents of the five wood sawdust ash samples were determined using a Perkin Elmer optima 3000 dv atomic absorption spectrometer while the ignition points were determined using Vecstar furnaces model ECF2. Poroporo had the highest ash content, 2.263 g while rubber had the least, 0.710 g. The results for the moisture content range from 2.971 g to 0.903 g. Magnesium metal had the highest concentration of all the metals, in all the wood ash samples; with mahogany ash having the highest concentration, 9.196 ppm while rubber ash had the least concentration of magnesium metal, 2.196 ppm. The ignition point results showed that the wood ashes from mahogany and opepe increased the ignition points of the test wood samples when coated on them while the ashes from poroporo, rubber and abura decreased the ignition points of the test wood samples when coated on them. However, Opepe saw dust ash decreased the ignition point in one of the test wood samples, suggesting that the metal content of the test wood sample was more than that of the Opepe saw dust ash. Therefore, Mahogany and Opepe saw dust ashes could be used in the surface treatment of wood to enhance their fire resistance or retardancy. However, the caution to be exercised in this application is that the metal content of the test wood samples should be evaluated as well.Keywords: ash, fire, ignition point, retardant, wood saw dust
Procedia PDF Downloads 37812596 Seismic Perimeter Surveillance System (Virtual Fence) for Threat Detection and Characterization Using Multiple ML Based Trained Models in Weighted Ensemble Voting
Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey
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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method
Procedia PDF Downloads 7212595 Production and Distribution Network Planning Optimization: A Case Study of Large Cement Company
Authors: Lokendra Kumar Devangan, Ajay Mishra
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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.Keywords: production planning, mixed integer optimization, network model, network optimization
Procedia PDF Downloads 5812594 Numerical Prediction of Bearing Strength on Composite Bolted Joint Using Three Dimensional Puck Failure Criteria
Authors: M. S. Meon, M. N. Rao, K-U. Schröder
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Mechanical fasteners especially bolting is commonly used in joining carbon-fiber reinforced polymer (CFRP) composite structures due to their good joinability and easy for maintenance characteristics. Since this approach involves with notching, a proper progressive damage model (PDM) need to be implemented and verified to capture existence of damages in the structure. A three dimensional (3D) failure criteria of Puck is established to predict the ultimate bearing failure of such joint. The failure criteria incorporated with degradation scheme are coded based on user subroutine executed in Abaqus. Single lap joint (SLJ) of composite bolted joint is used as target configuration. The results revealed that the PDM adopted here could sufficiently predict the behaviour of composite bolted joint up to ultimate bearing failure. In addition, mesh refinement near holes increased the accuracy of predicted strength as well as computational effort.Keywords: bearing strength, bolted joint, degradation scheme, progressive damage model
Procedia PDF Downloads 49812593 Performance Complexity Measurement of Tightening Equipment Based on Kolmogorov Entropy
Authors: Guoliang Fan, Aiping Li, Xuemei Liu, Liyun Xu
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The performance of the tightening equipment will decline with the working process in manufacturing system. The main manifestations are the randomness and discretization degree increasing of the tightening performance. To evaluate the degradation tendency of the tightening performance accurately, a complexity measurement approach based on Kolmogorov entropy is presented. At first, the states of performance index are divided for calibrating the discrete degree. Then the complexity measurement model based on Kolmogorov entropy is built. The model describes the performance degradation tendency of tightening equipment quantitatively. At last, a study case is applied for verifying the efficiency and validity of the approach. The research achievement shows that the presented complexity measurement can effectively evaluate the degradation tendency of the tightening equipment. It can provide theoretical basis for preventive maintenance and life prediction of equipment.Keywords: complexity measurement, Kolmogorov entropy, manufacturing system, performance evaluation, tightening equipment
Procedia PDF Downloads 25812592 A Review of Critical Thinking Formative Assessment Framework: Coping with Teachers Resistance to Critical Pedagogy
Authors: Chenhui Wang, Chwee Beng Lee
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The practice of critical pedagogy is challenged by resistance from teachers. This study presents a discussion on teachers' resistance to critical pedagogy and previous practical frameworks for assessing critical thinking in formative assessment in the classroom through a critical review of the related literature. The authors found out that the main issue of teachers' resistance is not whether teachers should possess theoretical knowledge of critical thinking but how they apply that knowledge in their classroom teaching. In addition, critical thinking in formative assessment may provide teachers with a comprehensive understanding of critical pedagogical planning, implementing, and reflecting. Therefore, this paper intends to discuss a practical step-by-step framework for critical thinking formative assessment to address this resistance. Such discussion is based on a thorough examination of the related theories and frameworks. This review paper will benefit teachers in understanding and reducing their resistance to critical pedagogy as well as in implementing critical pedagogy.Keywords: critical thinking, critical pedagogy, critical thinking formative assessment framework, teachers resistance
Procedia PDF Downloads 10512591 A Semi-Implicit Phase Field Model for Droplet Evolution
Authors: M. H. Kazemi, D. Salac
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A semi-implicit phase field method for droplet evolution is proposed. Using the phase field Cahn-Hilliard equation, we are able to track the interface in multiphase flow. The idea of a semi-implicit finite difference scheme is reviewed and employed to solve two nonlinear equations, including the Navier-Stokes and the Cahn-Hilliard equations. The use of a semi-implicit method allows us to have larger time steps compared to explicit schemes. The governing equations are coupled and then solved by a GMRES solver (generalized minimal residual method) using modified Gram-Schmidt orthogonalization. To show the validity of the method, we apply the method to the simulation of a rising droplet, a leaky dielectric drop and the coalescence of drops. The numerical solutions to the phase field model match well with existing solutions over a defined range of variables.Keywords: coalescence, leaky dielectric, numerical method, phase field, rising droplet, semi-implicit method
Procedia PDF Downloads 46612590 Estimation Model for Concrete Slump Recovery by Using Superplasticizer
Authors: Chaiyakrit Raoupatham, Ram Hari Dhakal, Chalermchai Wanichlamlert
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This paper is aimed to introduce the solution of concrete slump recovery using chemical admixture type-F (superplasticizer, naphthalene base) to the practice, in order to solve unusable concrete problem due to concrete loss its slump, especially for those tropical countries that have faster slump loss rate. In the other hand, randomly adding superplasticizer into concrete can cause concrete to segregate. Therefore, this paper also develops the estimation model used to calculate amount of second dose of superplasticizer need for concrete slump recovery. Fresh properties of ordinary Portland cement concrete with volumetric ratio of paste to void between aggregate (paste content) of 1.1-1.3 with water-cement ratio zone of 0.30 to 0.67 and initial superplasticizer (naphthalene base) of 0.25%- 1.6% were tested for initial slump and slump loss for every 30 minutes for one and half hour by slump cone test. Those concretes with slump loss range from 10% to 90% were re-dosed and successfully recovered back to its initial slump. Slump after re-dosed was tested by slump cone test. From the result, it has been concluded that, slump loss was slower for those mix with high initial dose of superplasticizer due to addition of superplasticizer will disturb cement hydration. The required second dose of superplasticizer was affected by two major parameter, which were water-cement ratio and paste content, where lower water-cement ratio and paste content cause an increase in require second dose of superplasticizer. The amount of second dose of superplasticizer is higher as the solid content within the system is increase, solid can be either from cement particles or aggregate. The data was analyzed to form an equation use to estimate the amount of second dosage requirement of superplasticizer to recovery slump to its original.Keywords: estimation model, second superplasticizer dosage, slump loss, slump recovery
Procedia PDF Downloads 19512589 Permeability Prediction Based on Hydraulic Flow Unit Identification and Artificial Neural Networks
Authors: Emad A. Mohammed
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The concept of hydraulic flow units (HFU) has been used for decades in the petroleum industry to improve the prediction of permeability. This concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir rock quality index (RQI). Both indices are based on reservoir porosity and permeability of core samples. It is assumed that core samples with similar FZI values belong to the same HFU. Thus, after dividing the porosity-permeability data based on the HFU, transformations can be done in order to estimate the permeability from the porosity. The conventional practice is to use the power law transformation using conventional HFU where percentage of error is considerably high. In this paper, neural network technique is employed as a soft computing transformation method to predict permeability instead of power law method to avoid higher percentage of error. This technique is based on HFU identification where Amaefule et al. (1993) method is utilized. In this regard, Kozeny and Carman (K–C) model, and modified K–C model by Hasan and Hossain (2011) are employed. A comparison is made between the two transformation techniques for the two porosity-permeability models. Results show that the modified K-C model helps in getting better results with lower percentage of error in predicting permeability. The results also show that the use of artificial intelligence techniques give more accurate prediction than power law method. This study was conducted on a heterogeneous complex carbonate reservoir in Oman. Data were collected from seven wells to obtain the permeability correlations for the whole field. The findings of this study will help in getting better estimation of permeability of a complex reservoir.Keywords: permeability, hydraulic flow units, artificial intelligence, correlation
Procedia PDF Downloads 12812588 Optimal Continuous Scheduled Time for a Cumulative Damage System with Age-Dependent Imperfect Maintenance
Authors: Chin-Chih Chang
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Many manufacturing systems suffer failures due to complex degradation processes and various environment conditions such as random shocks. Consider an operating system is subject to random shocks and works at random times for successive jobs. When successive jobs often result in production losses and performance deterioration, it would be better to do maintenance or replacement at a planned time. A preventive replacement (PR) policy is presented to replace the system before a failure occurs at a continuous time T. In such a policy, the failure characteristics of the system are designed as follows. Each job would cause a random amount of additive damage to the system, and the system fails when the cumulative damage has exceeded a failure threshold. Suppose that the deteriorating system suffers one of the two types of shocks with age-dependent probabilities: type-I (minor) shock is rectified by a minimal repair, or type-II (catastrophic) shock causes the system to fail. A corrective replacement (CR) is performed immediately when the system fails. In summary, a generalized maintenance model to scheduling replacement plan for an operating system is presented below. PR is carried out at time T, whereas CR is carried out when any type-II shock occurs and the total damage exceeded a failure level. The main objective is to determine the optimal continuous schedule time of preventive replacement through minimizing the mean cost rate function. The existence and uniqueness of optimal replacement policy are derived analytically. It can be seen that the present model is a generalization of the previous models, and the policy with preventive replacement outperforms the one without preventive replacement.Keywords: preventive replacement, working time, cumulative damage model, minimal repair, imperfect maintenance, optimization
Procedia PDF Downloads 352