Search results for: cost prediction
4772 A Radiographic Superimposition in Orthognathic Surgery of Class III Skeletal Malocclusion
Authors: Albert Suryaprawira
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Patients requiring correction of severe Class III skeletal discrepancy historically has been among the most challenging treatments for orthodontists. Correction of an aesthetic and functional problem is crucially important. This is a case report of an adult male aged 18 years who complained of difficulty in chewing and speaking. Patient has a prominent profile with mandibular excess. The pre-treatment cephalometric radiograph was taken to analyse the skeletal problem and to measure the amount of bone movement and the prediction soft tissue response. The panoramic radiograph was also taken to analyse bone quality, bone abnormality, third molar impaction, etc. Before the surgery, the pre-surgical cephalometric radiograph was taken to re-evaluate the plan and to settle the final amount of bone cut. After the surgery, the post-surgical cephalometric radiograph was taken to confirm the result with the plan. The superimposition between those radiographs was performed to analyse the outcome. It includes the superimposition of the cranial base, maxilla, and mandible. Superimposition is important to describe the amount of hard and soft tissue movement. It is also important to predict the possibility of relapse after the surgery. The patient needs to understand all the surgical plan, outcome and relapse prevention. The surgery included mandibular set back by bilateral sagittal split osteotomies. Although the discrepancy was severe using this combination of treatment and the use of radiographic superimposition, an aesthetically pleasing and stable result was achieved.Keywords: cephalometric, mandibular set back, orthognathic, superimposition
Procedia PDF Downloads 2604771 Enhancement of coupler-based delay line filters modulation techniques using optical wireless channel and amplifiers at 100 Gbit/s
Authors: Divya Sisodiya, Deepika Sipal
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Optical wireless communication (OWC) is a relatively new technology in optical communication systems that allows for high-speed wireless optical communication. This research focuses on developing a cost-effective OWC system using a hybrid configuration of optical amplifiers. In addition to using EDFA amplifiers, a comparison study was conducted to determine which modulation technique is more effective for communication. This research examines the performance of an OWC system based on ASK and PSK modulation techniques by varying OWC parameters under various atmospheric conditions such as rain, mist, haze, and snow. Finally, the simulation results are discussed and analyzed.Keywords: OWC, bit error rate, amplitude shift keying, phase shift keying, attenuation, amplifiers
Procedia PDF Downloads 1434770 The Relationship between Coping Styles and Internet Addiction among High School Students
Authors: Adil Kaval, Digdem Muge Siyez
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With the negative effects of internet use in a person's life, the use of the Internet has become an issue. This subject was mostly considered as internet addiction, and it was investigated. In literature, it is noteworthy that some theoretical models have been proposed to explain the reasons for internet addiction. In addition to these theoretical models, it may be thought that the coping style for stressing events can be a predictor of internet addiction. It was aimed to test with logistic regression the effect of high school students' coping styles on internet addiction levels. Sample of the study consisted of 770 Turkish adolescents (471 girls, 299 boys) selected from high schools in the 2017-2018 academic year in İzmir province. Internet Addiction Test, Coping Scale for Child and Adolescents and a demographic information form were used in this study. The results of the logistic regression analysis indicated that the model of coping styles predicted internet addiction provides a statistically significant prediction of internet addiction. Gender does not predict whether or not to be addicted to the internet. The active coping style is not effective on internet addiction levels, while the avoiding and negative coping style are effective on internet addiction levels. With this model, % 79.1 of internet addiction in high school is estimated. The Negelkerke pseudo R2 indicated that the model accounted for %35 of the total variance. The results of this study on Turkish adolescents are similar to the results of other studies in the literature. It can be argued that avoiding and negative coping styles are important risk factors in the development of internet addiction.Keywords: adolescents, coping, internet addiction, regression analysis
Procedia PDF Downloads 1794769 Predicting Entrepreneurial Intentions among Undergraduates Using Theory of Planned Behaviour
Authors: Mohammed Abubakar Mawoli
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Theory of Planned Behavior (TPB) is a useful tool for predicting entrepreneurial intentions among individuals or groups of people. In view of the Nigerian government’s renewed educational policies and programs to prepare Nigerian undergraduates towards self-reliance and employers of labor after graduation, it becomes pertinent to empirically examine and predict the undergraduate’s entrepreneurial intentions at graduation. Thus, this study primarily examines the undergraduates entrepreneurial intentions using TPB, which includes perceived desirability, perceived social norm, and perceived feasibility factors. In so doing, a questionnaire research method was adopted in which 219 copies of a questionnaire distributed to final year undergraduates were belonging to five departments with a total population of 487 students. A combination of relative frequency, mean standard deviation and multiple regression statistical tools were employed for data analysis. The study found that TPB components exert a significant composite effect on undergraduate’s entrepreneurial intentions. Based on individual contribution of the independent variables, Perceived Desirability is the strongest predictor of the undergraduate’s entrepreneurial intentions, while Perceived Social Norm is a strong predictor of the undergraduate’s entrepreneurial intentions. However, Perceived Feasibility is not a strong predictor of student’s entrepreneurial intentions. The study therefore, recommends that the Perceived desirability, which is formed and shaped by ones level of education and skills acquisition, be improved upon to create the expected positive impact on graduates entrepreneurial intentions and possible venture creation.Keywords: entrepreneurship, entrepreneurship education, entrepreneurial intentions, planned behaviour, prediction, Nigeria
Procedia PDF Downloads 3064768 Influence of La0.1Sr0.9Co1-xFexO3-δ Catalysts on Oxygen Permeation Using Mixed Conductor
Authors: Y. Muto, S. Araki, H. Yamamoto
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The separation of oxygen is one key technology to improve the efficiency and to reduce the cost for the processed of the partial oxidation of the methane and the condensation of the carbon dioxide. Particularly, carbon dioxide at high concentration would be obtained by the combustion using pure oxygen separated from air. However, the oxygen separation process occupied the large part of energy consumption. Therefore, it is considered that the membrane technologies enable to separation at lower cost and lower energy consumption than conventional methods. In this study, it is examined that the separation of oxygen using membranes of mixed conductors. Oxygen permeation through the membrane is occurred by the following three processes. At first, the oxygen molecules dissociate into oxygen ion at feed side of the membrane, subsequently, oxygen ions diffuse in the membrane. Finally, oxygen ions recombine to form the oxygen molecule. Therefore, it is expected that the membrane of thickness and material, or catalysts of the dissociation and recombination affect the membrane performance. However, there is little article about catalysts for the dissociation and recombination. We confirmed the performance of La0.6Sr0.4Co1.0O3-δ (LSC) based catalyst which was commonly used as the dissociation and recombination. It is known that the adsorbed amount of oxygen increase with the increase of doped Fe content in B site of LSC. We prepared the catalysts of La0.1Sr0.9Co0.9Fe0.1O3-δ(C9F1), La0.1Sr0.9Co0.5Fe0.5O3-δ(C5F5) and La0.1Sr0.9Co0.3Fe0.7O3-δ(C7F3). Also, we used Pr2NiO4 type mixed conductor as a membrane material. (Pr0.9La0.1)2(Ni0.74Cu0.21Ga0.05)O4+δ(PLNCG) shows the high oxygen permeability and the stability against carbon dioxide. Oxygen permeation experiments were carried out using a homemade apparatus at 850 -975 °C. The membrane was sealed with Pyrex glass at both end of the outside dense alumina tubes. To measure the oxygen permeation rate, air was fed to the film side at 50 ml min-1, helium as the sweep gas and reference gas was fed at 20 ml min-1. The flow rates of the sweep gas and the gas permeated through the membrane were measured using flow meter and the gas concentrations were determined using a gas chromatograph. Then, the permeance of the oxygen was determined using the flow rate and the concentration of the gas on the permeate side of the membrane. The increase of oxygen permeation was observed with increasing temperature. It is considered that this is due to the catalytic activities are increased with increasing temperature. Another reason is the increase of oxygen diffusivity in the bulk of membrane. The oxygen permeation rate is improved by using catalyst of LSC or LSCF. The oxygen permeation rate of membrane with LSCF showed higher than that of membrane with LSC. Furthermore, in LSCF catalysts, oxygen permeation rate increased with the increase of the doped amount of Fe. It is considered that this is caused by the increased of adsorbed amount of oxygen.Keywords: membrane separation, oxygen permeation, K2NiF4-type structure, mixed conductor
Procedia PDF Downloads 5224767 A Hierarchical Method for Multi-Class Probabilistic Classification Vector Machines
Authors: P. Byrnes, F. A. DiazDelaO
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The Support Vector Machine (SVM) has become widely recognised as one of the leading algorithms in machine learning for both regression and binary classification. It expresses predictions in terms of a linear combination of kernel functions, referred to as support vectors. Despite its popularity amongst practitioners, SVM has some limitations, with the most significant being the generation of point prediction as opposed to predictive distributions. Stemming from this issue, a probabilistic model namely, Probabilistic Classification Vector Machines (PCVM), has been proposed which respects the original functional form of SVM whilst also providing a predictive distribution. As physical system designs become more complex, an increasing number of classification tasks involving industrial applications consist of more than two classes. Consequently, this research proposes a framework which allows for the extension of PCVM to a multi class setting. Additionally, the original PCVM framework relies on the use of type II maximum likelihood to provide estimates for both the kernel hyperparameters and model evidence. In a high dimensional multi class setting, however, this approach has been shown to be ineffective due to bad scaling as the number of classes increases. Accordingly, we propose the application of Markov Chain Monte Carlo (MCMC) based methods to provide a posterior distribution over both parameters and hyperparameters. The proposed framework will be validated against current multi class classifiers through synthetic and real life implementations.Keywords: probabilistic classification vector machines, multi class classification, MCMC, support vector machines
Procedia PDF Downloads 2234766 Protecting the Cloud Computing Data Through the Data Backups
Authors: Abdullah Alsaeed
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Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.
Procedia PDF Downloads 954765 Flow Characteristics around Rectangular Obstacles with the Varying Direction of Obstacles
Authors: Hee-Chang Lim
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The study aims to understand the surface pressure distribution around the bodies such as the suction pressure in the leading edge on the top and side-face when the aspect ratio of bodies and the wind direction are changed, respectively. We carried out the wind tunnel measurement and numerical simulation around a series of rectangular bodies (40d×80w×80h, 80d×80w×80h, 160d×80w×80h, 80d×40w×80h and 80d×160w×80h in mm3) placed in a deep turbulent boundary layer. Based on a modern numerical platform, the Navier-Stokes equation with the typical 2-equation (k-ε model) and the DES (Detached Eddy Simulation) turbulence model has been calculated, and they are both compared with the measurement data. Regarding the turbulence model, the DES model makes a better prediction comparing with the k-ε model, especially when calculating the separated turbulent flow around a bluff body with sharp edged corner. In order to observe the effect of wind direction on the pressure variation around the cube (e.g., 80d×80w×80h in mm), it rotates at 0º, 10º, 20º, 30º, and 45º, which stands for the salient wind directions in the tunnel. The result shows that the surface pressure variation is highly dependent upon the approaching wind direction, especially on the top and the side-face of the cube. In addition, the transverse width has a substantial effect on the variation of surface pressure around the bodies, while the longitudinal length has little or no influence.Keywords: rectangular bodies, wind direction, aspect ratio, surface pressure distribution, wind-tunnel measurement, k-ε model, DES model, CFD
Procedia PDF Downloads 2414764 Investigating the Relationship between Bank and Cloud Provider
Authors: Hatim Elhag
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Banking and Financial Service Institutions are possibly the most advanced in terms of technology adoption and use it as a key differentiator. With high levels of business process automation, maturity in the functional portfolio, straight through processing and proven technology outsourcing benefits, Banking sector stand to benefit significantly from Cloud computing capabilities. Additionally, with complex Compliance and Regulatory policies, combined with expansive products and geography coverage, the business impact is even greater. While the benefits are exponential, there are also significant challenges in adopting this model– including Legal, Security, Performance, Reliability, Transformation complexity, Operating control and Governance and most importantly proof for the promised cost benefits. However, new architecture designed should be implemented to align this approach.Keywords: security, cloud, banking sector, cloud computing
Procedia PDF Downloads 5124763 The Possibility of Using Somatosensory Evoked Potential(SSEP) as a Parameter for Cortical Vascular Dementia
Authors: Hyunsik Park
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As the rate of cerebrovascular disease increases in old populations, the prevalence rate of vascular dementia would be expected. Therefore, authors designed this study to find out the possibility of somatosensory evoked potentials(SSEP) as a parameter for early diagnosis and prognosis prediction of vascular dementia in cortical vascular dementia patients. 21 patients who met the criteria for vascular dementia according to DSM-IV,ICD-10and NINDS-AIREN with the history of recent cognitive impairment, fluctuation progression, and neurologic deficit. We subdivided these patients into two groups; a mild dementia and a severe dementia groups by MMSE and CDR score; and analysed comparison between normal control group and patient control group who have been cerebrovascular attack(CVA) history without dementia by using N20 latency and amplitude of median nerve. In this study, mild dementia group showed significant differences on latency and amplitude with normal control group(p-value<0.05) except patient control group(p-value>0.05). Severe dementia group showed significant differences both normal control group and patient control group.(p-value<0.05, <001). Since no significant difference has founded between mild dementia group and patient control group, SSEP has limitation to use for early diagnosis test. However, the comparison between severe dementia group and others showed significant results which indicate SSEP can predict the prognosis of vascular dementia in cortical vascular dementia patients.Keywords: SSEP, cortical vascular dementia, N20 latency, N20 amplitude
Procedia PDF Downloads 3074762 Using a Hybrid Method to Eradicate Bamboo Growth along the Route of Overhead Power Lines
Authors: Miriam Eduful
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The Electricity Company of Ghana (ECG) is under obligation, demanded by the Public Utility and Regulation Commission to meet set performance indices. However, in certain parts of the country, bamboo related power interruptions have become a challenge. Growth rate of the bamboo is such that the cost of regular vegetation maintenance along route of the overhead power lines has become prohibitive. To address the problem, several methods and techniques of bamboo eradication have being used. Some of these methods involved application of chemical compounds that are considered inimical and dangerous to the environment. In this paper, three methods of bamboo eradication along the route of the ECG overhead power lines have been investigated. A hybrid method has been found to be very effective and ecologically friendly. The method is locally available and comparatively inexpensive to apply.Keywords: bamboo, eradication, hybrid method, gly gold
Procedia PDF Downloads 3734761 A Study of Classification Models to Predict Drill-Bit Breakage Using Degradation Signals
Authors: Bharatendra Rai
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Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.Keywords: degradation signal, drill-bit breakage, random forest, multinomial logistic regression
Procedia PDF Downloads 3544760 H-Infinity Controller Design for the Switched Reluctance Machine
Authors: Siwar Fadhel, Imen Bahri, Man Zhang
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The switched reluctance machine (SRM) has undeniable qualities in terms of low cost and mechanical robustness. However, its highly nonlinear character and its uncertain parameters justify the development of complicated controls. In this paper, authors present the design of a robust H-infinity current controller for an 8/6 SRM with taking into account the nonlinearity of the SRM and with rejection of disturbances. The electromagnetic torque is indirectly regulated through the current controller. To show the performances of this control, a robustness analysis is performed by comparing the H-infinity and PI controller simulation results. This comparison demonstrates better performances for the presented controller. The effectiveness and robustness of the presented controller are also demonstrated by experimental tests.Keywords: current regulation, experimentation, robust H-infinity control, switched reluctance machine
Procedia PDF Downloads 3124759 Can Sustainability Help Achieve Social Justice?
Authors: Maryam Davodi-Far
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Although sustainability offers a vision to preserve the earth’s resources while sustaining life on earth, there tends to be injustice and disparity in how resources are allocated across the globe. As such, the question that arises is whom will sustainability benefit? Will the rich grow richer and the poor become worse off? Is there a way to find balance between sustainability and still implement and achieve success with distributive justice theories? One of the facets of justice is distributive justice; the idea of balancing benefits and costs associated with the way in which we disseminate and consume goods. Social justice relies on how the cost and burdens of our resource allocation can be done reasonably and equitably and spread across a number of societies, and within each society spread across diverse groups and communities. In the end, the question is how to interact with the environment and diverse communities of today and of those communities of the future.Keywords: consumerism, sustainability, sustainable development, social justice, social equity, distributive justice
Procedia PDF Downloads 4094758 Strategies to Achieve Deep Decarbonisation in Power Generation: A Review
Authors: Abdullah Alotaiq
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The transition to low-carbon power generation is essential for mitigating climate change and achieving sustainability. This process, however, entails considerable costs, and understanding the factors influencing these costs is critical. This is necessary to cater to the increasing demand for low-carbon electricity across the heating, industry, and transportation sectors. A crucial aspect of this transition is identifying cost-effective and feasible paths for decarbonization, which is integral to global climate mitigation efforts. It is concluded that hybrid solutions, combining different low-carbon technologies, are optimal for minimizing costs and enhancing flexibility. These solutions also address the challenges associated with phasing out existing fossil fuel-based power plants and broadening the spectrum of low-carbon power generation options.Keywords: review, power generation, energy transition, decarbonisation
Procedia PDF Downloads 584757 Wind Speed Forecasting Based on Historical Data Using Modern Prediction Methods in Selected Sites of Geba Catchment, Ethiopia
Authors: Halefom Kidane
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This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights.Keywords: artificial neural networks, forecasting, min-max normalization, wind speed
Procedia PDF Downloads 804756 Composite Base Natural Fiber
Authors: Noureddine Mahmoudi
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The use of natural fibers in the development of composite materials is a sector in full expansion. These fibers were used for their low cost, their availability and their renewable character. The fibers of the palm (palm tree) were used as reinforcement in polypropylene (PP). The date palm fibers have some potential because of their ecological and economic interest. Both unmodified and compatibilized fibers are used. Compatibilization was carried out with the use of maleic anhydride copolymers. The morphology and mechanical properties were characterized by electron microscopy scanning (SEM) and tensile tests. The influence of fiber content on mechanical properties of composite PP / date palm has been evaluated and demonstrated, that the maximum stress and elongation decreases with increasing fiber volume rate. On the other hand, an increase of the tensile modulus has been noticed, but after the fibers improvement, the maximum stress increases significantly up to 25% weight.Keywords: plant fiber, palm, SEM, compatibilizer
Procedia PDF Downloads 4614755 Reliability Modeling on Drivers’ Decision during Yellow Phase
Authors: Sabyasachi Biswas, Indrajit Ghosh
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The random and heterogeneous behavior of vehicles in India puts up a greater challenge for researchers. Stop-and-go modeling at signalized intersections under heterogeneous traffic conditions has remained one of the most sought-after fields. Vehicles are often caught up in the dilemma zone and are unable to take quick decisions whether to stop or cross the intersection. This hampers the traffic movement and may lead to accidents. The purpose of this work is to develop a stop and go prediction model that depicts the drivers’ decision during the yellow time at signalised intersections. To accomplish this, certain traffic parameters were taken into account to develop surrogate model. This research investigated the Stop and Go behavior of the drivers by collecting data from 4-signalized intersections located in two major Indian cities. Model was developed to predict the drivers’ decision making during the yellow phase of the traffic signal. The parameters used for modeling included distance to stop line, time to stop line, speed, and length of the vehicle. A Kriging base surrogate model has been developed to investigate the drivers’ decision-making behavior in amber phase. It is observed that the proposed approach yields a highly accurate result (97.4 percent) by Gaussian function. It was observed that the accuracy for the crossing probability was 95.45, 90.9 and 86.36.11 percent respectively as predicted by the Kriging models with Gaussian, Exponential and Linear functions.Keywords: decision-making decision, dilemma zone, surrogate model, Kriging
Procedia PDF Downloads 3114754 Electromagnetic Source Direction of Arrival Estimation via Virtual Antenna Array
Authors: Meiling Yang, Shuguo Xie, Yilong Zhu
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Nowadays, due to diverse electric products and complex electromagnetic environment, the localization and troubleshooting of the electromagnetic radiation source is urgent and necessary especially on the condition of far field. However, based on the existing DOA positioning method, the system or devices are complex, bulky and expensive. To address this issue, this paper proposes a single antenna radiation source localization method. A single antenna moves to form a virtual antenna array combined with DOA and MUSIC algorithm to position accurately, meanwhile reducing the cost and simplify the equipment. As shown in the results of simulations and experiments, the virtual antenna array DOA estimation modeling is correct and its positioning is credible.Keywords: virtual antenna array, DOA, localization, far field
Procedia PDF Downloads 3784753 Effect of Boric Acid Content on the Structural and Optical Properties of In2O3 Films Prepared by Spray Pyrolysis Technique
Authors: Mustafa Öztas, Metin Bedir, Yahya Özdemir
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Boron doped of In2O3 films were prepared by spray pyrolysis technique at 350 °C substrate temperature, which is a low cost and large area technique to be well-suited for the manufacture of solar cells, using boric acid (H3BO3) as dopant source, and their properties were investigated as a function of doping concentration. X-ray analysis showed that the films were polycrystalline fitting well with a hexagonal structure and have preferred orientation in (220) direction. The changes observed in the energy band gap and structural properties of the films related to the boric acid concentration are discussed in detail.Keywords: spray pyrolysis, In2O3, boron, optical properties, boric acid
Procedia PDF Downloads 5924752 Plantar Neuro-Receptor Activation in Total Knee Arthroplasty Patients: Impact on Clinical Function, Pain, and Stiffness - A Randomized Controlled Trial
Authors: Woolfrey K., Woolfrey M., Bolton C. L., Warchuk D.
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Objectives: Osteoarthritis is the most common joint disease of adults worldwide. Despite total knee arthroplasty (TKA) demonstrating high levels of success, 20% of patients report dissatisfaction with their result. VOXX Wellness Stasis Socks are embedded with a proprietary pattern of neuro-receptor activation points that have been proven to activate a precise neuro-response, according to the pattern theory of haptic perception, which stimulates improvements in pain and function. The use of this technology in TKA patients may prove beneficial as an adjunct to recovery as many patients suffer from deficits to their proprioceptive system caused by ligamentous damage and alterations to mechanoreceptors during the procedure. We hypothesized that VOXX Wellness Stasis Socks are a safe, cost-effective, and easily scalable strategy to support TKA patients through their recovery. Design: Double-blinded, placebo-controlled randomized trial. Participants: Patients scheduled to receive TKA were considered eligible for inclusion in the trial. Interventions: Intervention group (I): VOXX Wellness Stasis socks containing receptor point-activation technology. Control group (C): VOXX Wellness Stasis socks without receptor point-activation technology. Sock use during the waking hours x 6 weeks. Main Outcome Measures: Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) questionnaire completed at baseline, 2 weeks, and 6 weeks to assess pain, stiffness, and physical function. Results: Data analysis using SPSS software. P-values, effect sizes, and confidence intervals are reported to assess clinical relevance of the finding. Physical status classifications were compared using t-test. Within-subject and between-subject differences in the mean WOMAC were analyzed by ANOVA. Effect size was analyzed using Cramer’s V. Consistent improvement in WOMAC scores for pain and stiffness at 2 weeks post op in the I over the C group. The womac scores assessing physical function showed a consistent improvement at both 2 and 6 weeks post op in the I group compared to C group. Conclusions: VOXX proved to be a low cost, safe intervention in TKA to help patients improve with regard to pain, stiffness, and physical function. Disclosures: NoneKeywords: osteoarthritis, RCT, pain management, total knee arthroplasty
Procedia PDF Downloads 5374751 Autonomous Quantum Competitive Learning
Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally
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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.Keywords: competitive learning, quantum gates, quantum gates, winner-take-all
Procedia PDF Downloads 4764750 An Effective Approach to Knowledge Capture in Whole Life Costing in Constructions Project
Authors: Ndibarafinia Young Tobin, Simon Burnett
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In spite of the benefits of implementing whole life costing technique as a valuable approach for comparing alternative building designs allowing operational cost benefits to be evaluated against any initial cost increases and also as part of procurement in the construction industry, its adoption has been relatively slow due to the lack of tangible evidence, ‘know-how’ skills and knowledge of the practice, i.e. the lack of professionals in many establishments with knowledge and training on the use of whole life costing technique, this situation is compounded by the absence of available data on whole life costing from relevant projects, lack of data collection mechanisms and so on. This has proved to be very challenging to those who showed some willingness to employ the technique in a construction project. The knowledge generated from a project can be considered as best practices learned on how to carry out tasks in a more efficient way, or some negative lessons learned which have led to losses and slowed down the progress of the project and performance. Knowledge management in whole life costing practice can enhance whole life costing analysis execution in a construction project, as lessons learned from one project can be carried on to future projects, resulting in continuous improvement, providing knowledge that can be used in the operation and maintenance phases of an assets life span. Purpose: The purpose of this paper is to report an effective approach which can be utilised in capturing knowledge in whole life costing practice in a construction project. Design/methodology/approach: An extensive literature review was first conducted on the concept of knowledge management and whole life costing. This was followed by a semi-structured interview to explore the existing and good practice knowledge management in whole life costing practice in a construction project. The data gathered from the semi-structured interview was analyzed using content analysis and used to structure an effective knowledge capturing approach. Findings: From the results obtained in the study, it shows that the practice of project review is the common method used in the capturing of knowledge and should be undertaken in an organized and accurate manner, and results should be presented in the form of instructions or in a checklist format, forming short and precise insights. The approach developed advised that irrespective of how effective the approach to knowledge capture, the absence of an environment for sharing knowledge, would render the approach ineffective. Open culture and resources are critical for providing a knowledge sharing setting, and leadership has to sustain whole life costing knowledge capture, giving full support for its implementation. The knowledge capturing approach has been evaluated by practitioners who are experts in the area of whole life costing practice. The results have indicated that the approach to knowledge capture is suitable and efficient.Keywords: whole life costing, knowledge capture, project review, construction industry, knowledge management
Procedia PDF Downloads 2634749 Modelling Vehicle Fuel Consumption Utilising Artificial Neural Networks
Authors: Aydin Azizi, Aburrahman Tanira
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The main source of energy used in this modern age is fossil fuels. There is a myriad of problems that come with the use of fossil fuels, out of which the issues with the greatest impact are its scarcity and the cost it imposes on the planet. Fossil fuels are the only plausible option for many vital functions and processes; the most important of these is transportation. Thus, using this source of energy wisely and as efficiently as possible is a must. The aim of this work was to explore utilising mathematical modelling and artificial intelligence techniques to enhance fuel consumption in passenger cars by focusing on the speed at which cars are driven. An artificial neural network with an error less than 0.05 was developed to be applied practically as to predict the rate of fuel consumption in vehicles.Keywords: mathematical modeling, neural networks, fuel consumption, fossil fuel
Procedia PDF Downloads 4084748 Solar Cell Using Chemical Bath Deposited PbS:Bi3+ Films as Electron Collecting Layer
Authors: Melissa Chavez Portillo, Mauricio Pacio Castillo, Hector Juarez Santiesteban, Oscar Portillo Moreno
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Chemical bath deposited PbS:Bi3+ as an electron collection layer is introduced between the silicon wafer and the Ag electrode the performance of the PbS heterojunction thin film solar thin film solar cells with 1 cm2 active area. We employed Bi-doping to transform it into an n-type semiconductor. The experimental results reveal that the cell response parameters depend critically on the deposition procedures in terms of bath temperature, deposition time. The device achieves an open-circuit voltage of 0.4 V. The simple and low-cost deposition method of PbS:Bi3+ films is promising for the fabrication.Keywords: Bi doping, PbS, thin films, solar cell
Procedia PDF Downloads 5184747 Feature Based Unsupervised Intrusion Detection
Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein
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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka
Procedia PDF Downloads 2994746 Elasto-Plastic Analysis of Structures Using Adaptive Gaussian Springs Based Applied Element Method
Authors: Mai Abdul Latif, Yuntian Feng
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Applied Element Method (AEM) is a method that was developed to aid in the analysis of the collapse of structures. Current available methods cannot deal with structural collapse accurately; however, AEM can simulate the behavior of a structure from an initial state of no loading until collapse of the structure. The elements in AEM are connected with sets of normal and shear springs along the edges of the elements, that represent the stresses and strains of the element in that region. The elements are rigid, and the material properties are introduced through the spring stiffness. Nonlinear dynamic analysis has been widely modelled using the finite element method for analysis of progressive collapse of structures; however, difficulties in the analysis were found at the presence of excessively deformed elements with cracking or crushing, as well as having a high computational cost, and difficulties on choosing the appropriate material models for analysis. The Applied Element method is developed and coded to significantly improve the accuracy and also reduce the computational costs of the method. The scheme works for both linear elastic, and nonlinear cases, including elasto-plastic materials. This paper will focus on elastic and elasto-plastic material behaviour, where the number of springs required for an accurate analysis is tested. A steel cantilever beam is used as the structural element for the analysis. The first modification of the method is based on the Gaussian Quadrature to distribute the springs. Usually, the springs are equally distributed along the face of the element, but it was found that using Gaussian springs, only up to 2 springs were required for perfectly elastic cases, while with equal springs at least 5 springs were required. The method runs on a Newton-Raphson iteration scheme, and quadratic convergence was obtained. The second modification is based on adapting the number of springs required depending on the elasticity of the material. After the first Newton Raphson iteration, Von Mises stress conditions were used to calculate the stresses in the springs, and the springs are classified as elastic or plastic. Then transition springs, springs located exactly between the elastic and plastic region, are interpolated between regions to strictly identify the elastic and plastic regions in the cross section. Since a rectangular cross-section was analyzed, there were two plastic regions (top and bottom), and one elastic region (middle). The results of the present study show that elasto-plastic cases require only 2 springs for the elastic region, and 2 springs for the plastic region. This showed to improve the computational cost, reducing the minimum number of springs in elasto-plastic cases to only 6 springs. All the work is done using MATLAB and the results will be compared to models of structural elements using the finite element method in ANSYS.Keywords: applied element method, elasto-plastic, Gaussian springs, nonlinear
Procedia PDF Downloads 2264745 A Framework Based on Dempster-Shafer Theory of Evidence Algorithm for the Analysis of the TV-Viewers’ Behaviors
Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi
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In this paper, we propose an approach of detecting the behavior of the viewers of a TV program in a non-controlled environment. The experiment we propose is based on the use of three types of connected objects (smartphone, smart watch, and a connected remote control). 23 participants were observed while watching their TV programs during three phases: before, during and after watching a TV program. Their behaviors were detected using an approach based on The Dempster Shafer Theory (DST) in two phases. The first phase is to approximate dynamically the mass functions using an approach based on the correlation coefficient. The second phase is to calculate the approximate mass functions. To approximate the mass functions, two approaches have been tested: the first approach was to divide each features data space into cells; each one has a specific probability distribution over the behaviors. The probability distributions were computed statistically (estimated by empirical distribution). The second approach was to predict the TV-viewing behaviors through the use of classifiers algorithms and add uncertainty to the prediction based on the uncertainty of the model. Results showed that mixing the fusion rule with the computation of the initial approximate mass functions using a classifier led to an overall of 96%, 95% and 96% success rate for the first, second and third TV-viewing phase respectively. The results were also compared to those found in the literature. This study aims to anticipate certain actions in order to maintain the attention of TV viewers towards the proposed TV programs with usual connected objects, taking into account the various uncertainties that can be generated.Keywords: Iot, TV-viewing behaviors identification, automatic classification, unconstrained environment
Procedia PDF Downloads 2314744 From Economic Crisis to Environmental Sustainability: The Case of Greece
Authors: Marula Tsagkari
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Greece finds itself in challenging times, facing a severe economic slowdown since 2009. Despite the fact that Greece is in the epicenter of the global interest, to the best of our knowledge there is no extend research on how the crisis has affected the Greek environment (directly and indirectly), the past years. Thus, the present study aims to fill the aforementioned research gap by examining a number of environmental indicators related with air emissions, waste, water and energy. Our results indicate that the crisis affected the Greek environment in both positive and negative ways. For Greece, the main challenge is to recover from the present economic recession as soon as possible, but not at any cost to the environment. In this context, this research unfolds the interrelation between the economic and the environmental crisis and suggests a sustainable restructuring of the Greek economy.Keywords: Greece, economic crisis, environmental policy, environmental indicators
Procedia PDF Downloads 3424743 A Study of Standing-Wave Thermoacoustic Refrigerator
Authors: Patcharin Saechan, Isares Dhuchakallaya
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Thermoacoustic refrigerator is a cooling device which uses the acoustic waves to produce the cooling effect. The aim of this paper is to explore the experimental and numerical feasibility of a standing-wave thermoacoustic refrigerator. The effects of the stack length, position of stack and operating frequency on the cooling performance are carried out. The circular pore stacks are tested under the atmospheric pressure. A low-cost loudspeaker is used as an acoustic driver. The results show that the location of stack installed in resonator tube has a greater effect on the cooling performance than the stack length and operating frequency, respectively. The temperature difference across the ends of the stack can be generated up to 13.7°C, and the temperature of cold-end is dropped down by 5.3°C from the ambient temperature.Keywords: cooling performance, refrigerator, standing-wave, thermoacoustics
Procedia PDF Downloads 200