Search results for: estimation of properties of the model
Commenced in January 2007
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Edition: International
Paper Count: 25360

Search results for: estimation of properties of the model

3700 Parkinson’s Disease Detection Analysis through Machine Learning Approaches

Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

Abstract:

Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

Procedia PDF Downloads 127
3699 Teaching Ethical Behaviour: Conversational Analysis in Perspective

Authors: Nikhil Kewalkrishna Mehta

Abstract:

In the past researchers have questioned the effectiveness of ethics training in higher education. Also, there are observations that support the view that ethical behaviour (range of actions)/ethical decision making models used in the past make use of vignettes to explain ethical behaviour. The understanding remains in the perspective that these vignettes play a limited role in determining individual intentions and not actions. Some authors have also agreed that there are possibilities of differences in one’s intentions and actions. This paper makes an attempt to fill those gaps by evaluating real actions rather than intentions. In a way this study suggests the use of an experiential methodology to explore Berlo’s model of communication as an action along with orchestration of various principles. To this endeavor, an attempt was made to use conversational analysis in the pursuance of evaluating ethical decision making behaviour among students and middle level managers. The process was repeated six times with the set of an average of 15 participants. Similarities have been observed in the behaviour of students and middle level managers that calls for understanding that both the groups of individuals have no cognizance of their actual actions. The deliberations derived out of conversation were taken a step forward for meta-ethical evaluations to portray a clear picture of ethical behaviour among participants. This study provides insights for understanding demonstrated unconscious human behaviour which may fortuitously be termed both ethical and unethical.

Keywords: ethical behaviour, unethical behavior, ethical decision making, intentions and actions, conversational analysis, human actions, sensitivity

Procedia PDF Downloads 248
3698 Comparative Studies of Distributed and Aggregated Energy Storage Configurations in Direct Current Microgrids

Authors: Frimpong Kyeremeh, Albert Y. Appiah, Ben B. K. Ayawli

Abstract:

Energy storage system (ESS) is an essential part of a microgrid (MG) because of its immense benefits to the economics and the stability of MG. For a direct current (DC) MG (DCMG) in which the generating units are mostly variable renewable energy generators, DC bus voltage fluctuation is inevitable; hence ESS is vital in managing the mismatch between load demand and generation. Besides, to accrue the maximum benefits of ESS in the microgrid, there is the need for proper sizing and location of the ESSs. In this paper, a performance comparison is made between two configurations of ESS; distributed battery energy storage system (D-BESS) and an aggregated (centralized) battery energy storage system (A-BESS), on the basis of stability and operational cost for a DCMG. The configuration consists of four households with rooftop PV panels and a wind turbine. The objective is to evaluate and analyze the technical efficiencies, cost effectiveness as well as controllability of each configuration. The MG is first modelled with MATLAB Simulink then, a mathematical model is used to determine the optimal size of the BESS that minimizes the total operational cost of the MG. The performance of the two configurations would be tested with simulations. The two configurations are expected to reduce DC bus voltage fluctuations, but in the cases of voltage stability and optimal cost, the best configuration performance will be determined at the end of the research. The work is in progress, and the result would help MG designers and operators to make the best decision on the use of BESS for DCMG configurations.

Keywords: aggregated energy storage system, DC bus voltage, DC microgrid, distributed battery energy storage, stability

Procedia PDF Downloads 155
3697 Empowering Volunteers at Tawanchai Centre for Patients with Cleft Lip and Palate

Authors: Suteera Pradubwong, Darawan Augsornwan, Pornpen Pathumwiwathana, Benjamas Prathanee, Bowornsilp Chowchuen

Abstract:

Background: Cleft lip and palate (CLP) congenital anomalies have a high prevalence in the Northeast of Thailand. A care team’s understand of treatment plan would help to guide the family of patients with CLP to achieve the treatment. Objectives: To examine the impact of the empowering volunteer project, established in the northeast Thailand. Materials and Methods: The Empowering Volunteer project was conducted in 2008 under the Tawanchai Royal Granted project. The patients and family’s general information, treatment, the group brainstorming, and satisfaction with the project were analyzed. Results: Participants were 12 children with CLP, their families and five volunteers with CLP; the participating patients were predominantly females and the mean, age was 12.2 years. The treatment comprised of speech training, dental hygiene care, bone graft and orthodontic treatment. Four issues were addressed including: problems in taking care of breast feeding; instructions’ needs for care at birth; difficulty in access information and society impact; and needs in having a network of volunteers. Conclusions: Empowering volunteer is important for holistic care of patients with CLP which provides easy access and multiple channels for patients and their families. It should be developed as part of the self-help and family support group, the development of community based team and comprehensive CLP care program.

Keywords: self-help and family support group, community based model, volunteer, cleft lip-cleft palate

Procedia PDF Downloads 277
3696 Bioeconomic Modelling for Barramundi (Lates calcarifer) in Queensland: Implications for Recreational Fishing Following Recent Gill Netting Closures

Authors: Sabiha S. Marine, Nicole Flint, John Rolfe

Abstract:

The Queensland state government introduced commercial gill net fishing closures in Cairns, Mackay, and Rockhampton in November 2015 to increase the recreational fishing opportunities, nature-based tourism, and economic benefits in these three regional areas. This management change is likely to improve the potential for more desirable stock structures through natural recruitment. Barramundi (Lates calcarifer) is one of the popular target fish for recreational and commercial fishers in Northern Australia. This investigation examines the effects of reduced commercial fishing from both biological and economic perspectives, particularly on the local Barramundi population of the Fitzroy River in Rockhampton, the largest river catchment flowing to the eastern coast of Australia. Data on different parameters of biological and economic aspects have been collated from secondary sources for analysis through a system simulation approach to identify the effectiveness of the commercial netting closures on recreational fishing effort, especially for the Barramundi population. The results have the potential to explain certain consequences of the netting closures in Queensland, which could serve to inform future fisheries management decisions. The study output as a whole will help in the better management of fisheries resources by evaluating recreational fishing opportunities in Queensland, where the potential for increases in recreation is high.

Keywords: Barramundi, bioeconomic model, fishery management, recreational fishing

Procedia PDF Downloads 164
3695 Modeling of Gas Extraction from a Partially Gas-Saturated Porous Gas Hydrate Reservoir with Respect to Thermal Interactions with Surrounding Rocks

Authors: Angelina Chiglintseva, Vladislav Shagapov

Abstract:

We know from the geological data that quite sufficient gas reserves are concentrated in hydrates that occur on the Earth and on the ocean floor. Therefore, the development of these sources of energy and the storage of large reserves of gas hydrates is an acute global problem. An advanced technology for utilizing gas is to store it in a gas-hydrate state. Under natural conditions, storage facilities can be established, e.g., in underground reservoirs, where quite large volumes of gas can be conserved compared with reservoirs of pure gas. An analysis of the available experimental data of the kinetics and the mechanism of the gas-hydrate formation process shows the self-conservation effect that allows gas to be stored at negative temperatures and low values of pressures of up to several atmospheres. A theoretical model has been constructed for the gas-hydrate reservoir that represents a unique natural chemical reactor, and the principal possibility of the full extraction of gas from a hydrate due to the thermal reserves of the reservoirs themselves and the surrounding rocks has been analyzed. The influence exerted on the evolution of a gas hydrate reservoir by the reservoir thicknesses and the parameters that determine its initial state (a temperature, pressure, hydrate saturation) has been studied. It has been established that the shortest time of exploitation required by the reservoirs with a thickness of a few meters for the total hydrate decomposition is recorded in the cyclic regime when gas extraction alternated with the subsequent conservation of the gas hydrate deposit. The study was performed by a grant from the Russian Science Foundation (project No.15-11-20022).

Keywords: conservation, equilibrium state, gas hydrate reservoir, rocks

Procedia PDF Downloads 298
3694 A Framework Factors Influencing Accounting Information Systems Adoption Success

Authors: Manirath Wongsim

Abstract:

AIS plays an important role in business management, strategic and can provide assistance in all phases of decision making. Thus, many organisations needs to be seen as well adopting AIS, which is critical to a company in order to organise, manage and operate process in all sections. In order to implement AIS successfully, it is important to understand the underlying factors that influence the AIS adoption. Therefore, this research intends to study this perspective of factors influence and impact on AIS adoption’s success. The model has been designed to illustrate factors influences in AIS adoption. It also attempts to identify the critical success factors that organisations should focus on, to ensure the adoption on accounting process. This framework will be developed from case studies by collecting qualitative and quantitative data. Case study and survey methodology were adopted for this research. Case studies in two Thai- organisations were carried out. The results of the two main case studies suggested 9 factors that may have impact on in AIS adoption. Survey instrument was developed based on the findings from case studies. Two large-scale surveys were sent to selected members of Thailand Accountant, and Thailand Computer Society to further develop and test the research framework. The top three critical factors for ensuring AIS adoption were: top management commitment, steering committees, and Technical capability of AIS personnel. That is, it is now clear which factors impact in AIS adoption, and which of those factors are critical success factors for ensuring AIS adoption successes

Keywords: accounting information system, accounting information systems adoption, and inflecting AIS adoption

Procedia PDF Downloads 397
3693 Empirical Roughness Progression Models of Heavy Duty Rural Pavements

Authors: Nahla H. Alaswadko, Rayya A. Hassan, Bayar N. Mohammed

Abstract:

Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data.

Keywords: roughness progression, empirical model, pavement performance, heavy duty pavement

Procedia PDF Downloads 167
3692 Experimental Investigation of Heat Transfer on Vertical Two-Phased Closed Thermosyphon

Authors: M. Hadi Kusuma, Nandy Putra, Anhar Riza Antariksawan, Ficky Augusta Imawan

Abstract:

Heat pipe is considered to be applied as a passive system to remove residual heat that generated from reactor core when incident occur or from spent fuel storage pool. The objectives are to characterized the heat transfer phenomena, performance of heat pipe, and as a model for large heat pipe will be applied as passive cooling system on nuclear spent fuel pool storage. In this experimental wickless heat pipe or two-phase closed thermosyphon (TPCT) is used. Variation of heat flux are 611.24 Watt/m2 - 3291.29 Watt/m2. Variation of filling ratio are 45 - 70%. Variation of initial pressure are -62 to -74 cm Hg. Demineralized water is used as working fluid in the TPCT. The results showed that increasing of heat load leads to an increase of evaporation of the working fluid. The optimum filling ratio obtained for 60% of TPCT evaporator volume, and initial pressure variation gave different TPCT wall temperature characteristic. TPCT showed best performance with 60% filling ratio and can be consider to be applied as passive residual heat removal system or passive cooling system on spent fuel storage pool.

Keywords: two-phase closed term syphon, heat pipe, passive cooling, spent fuel storage pool

Procedia PDF Downloads 329
3691 Numerical Investigation and Optimization of the Effect of Number of Blade and Blade Type on the Suction Pressure and Outlet Mass Flow Rate of a Centrifugal Fan

Authors: Ogan Karabas, Suleyman Yigit

Abstract:

Number of blade and blade type of centrifugal fans are the most decisive factor on the field of application, noise level, suction pressure and outlet mass flow rate. Nowadays, in order to determine these effects on centrifugal fans, numerical studies are carried out in addition to experimental studies. In this study, it is aimed to numerically investigate the changes of suction pressure and outlet mass flow rate values of a centrifugal fan according to the number of blade and blade type. Centrifugal fans of the same size with forward, backward and straight blade type were analyzed by using a simulation program and compared with each other. This analysis was carried out under steady state condition by selecting k-Ɛ turbulence model and air is assumed incompressible. Then, 16, 32 and 48 blade centrifugal fans were again analyzed by using same simulation program, and the optimum number of blades was determined for the suction pressure and the outlet mass flow rate. According to the results of the analysis, it was obtained that the suction pressure in the 32 blade fan was twice the value obtained in the 16 blade fan. In addition, the outlet mass flow rate increased by 45% with the increase in the number of blade from 16 to 32. There is no significant change observed on the suction pressure and outlet mass flow rate when the number of blades increased from 32 to 48. In the light of the analysis results, the optimum blade number was determined as 32.

Keywords: blade type, centrifugal fan, cfd, outlet mass flow rate, suction pressure

Procedia PDF Downloads 402
3690 APP-Based Language Teaching Using Mobile Response System in the Classroom

Authors: Martha Wilson

Abstract:

With the peak of Computer-Assisted Language Learning slowly coming to pass and Mobile-Assisted Language Learning, at times, a bit lacking in the communicative department, we are now faced with a challenging question: How can we engage the interest of our digital native students and, most importantly, sustain it? As previously mentioned, our classrooms are now experiencing an influx of “digital natives” – people who have grown up using and having unlimited access to technology. While modernizing our curriculum and digitalizing our classrooms are necessary in order to accommodate this new learning style, it is a huge financial burden and a massive undertaking for language institutes. Instead, opting for a more compact, simple, yet multidimensional pedagogical tool may be the solution to the issue at hand. This paper aims to give a brief overview into an existing device referred to as Student Response Systems (SRS) and to expand on this notion to include a new prototype of response system that will be designed as a mobile application to eliminate the need for costly hardware and software. Additionally, an analysis into recent attempts by other institutes to develop the Mobile Response System (MRS) and customer reviews of the existing MRSs will be provided, as well as the lessons learned from those projects. Finally, while the new model of MRS is still in its infancy stage, this paper will discuss the implications of incorporating such an application as a tool to support and to enrich traditional techniques and also offer practical classroom applications with the existing response systems that are immediately available on the market.

Keywords: app, clickers, mobile app, mobile response system, student response system

Procedia PDF Downloads 370
3689 Kinematic Analysis of Heel Height Effect on Knee Direction Correction in a Patient with Genu Recurvatum: A Case Study

Authors: Parya Salimitari, Farhad Tabatabai Ghomsheh, Siyamak Khorramymehr, Hossein Taghadosi, Mohammad Hossein Dashti

Abstract:

The aim of this study was to evaluate the effect of heel height on the knee joint direction in Genu recurvatum patients compared to normal state. The test was performed on a patient with Genu recurvatum and a healthy person with similar and match biomechanical conditions. Subjects were tested under six different positions of shoes with heels 0, 1, 2, 3, 4 and 5 cm after marking during the gate. The results of the spatial temporal geometry obtained from Vicon Motion System (six-camera T10 model, Oxford Metrics Ltd., Oxford, UK), and were used to compute and analyze the kinematic results. In this study, we tried to determine the effect of shoe heel intervention on knee joint direction correction. The results indicate that the 1 cm heel has been optimized and significantly improved in knee joint flexion and flexion-extension angle so that the difference in knee flexion-extension angle between the patient and the healthy person at some stages of walking has reached zero (good posture). The 3 cm heel compared with the 0 cm heel has reduced the knee recurvatum index (KRI) by up to 21.74% in the patient (from 219.233 mm to 47.6714 mm). According to the findings of this study, it can be concluded that heel increase is effective in correcting knee joints in Genu recurvatum and the optimum heel height is 1 cm.

Keywords: joint alignment of knee, gait analysis, genu recurvatum, heel lift, kinematics, motion-analysis

Procedia PDF Downloads 200
3688 Infodemic Detection on Social Media with a Multi-Dimensional Deep Learning Framework

Authors: Raymond Xu, Cindy Jingru Wang

Abstract:

Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

Procedia PDF Downloads 253
3687 Geometric Optimization of Catalytic Converter

Authors: P. Makendran, M. Pragadeesh, N. Narash, N. Manikandan, A. Rajasri, V. Sanal Kumar

Abstract:

The growing severity of government-obligatory emissions legislation has required continuous improvement in catalysts performance and the associated reactor systems. IC engines emit a lot of harmful gases into the atmosphere. These gases are toxic in nature and a catalytic converter is used to convert these toxic gases into less harmful gases. The catalytic converter converts these gases by Oxidation and reduction reaction. Stoichiometric engines usually use the three-way catalyst (TWC) for simultaneously destroying all of the emissions. CO and NO react to form CO2 and N2 over one catalyst, and the remaining CO and HC are oxidized in a subsequent one. Literature review reveals that typically precious metals are used as a catalyst. The actual reactor is composed of a washcoated honeycomb-style substrate, with the catalyst being contained in the washcoat. The main disadvantage of a catalytic converter is that it exerts a back pressure to the exhaust gases while entering into them. The objective of this paper is to optimize the back pressure developed by the catalytic converter through geometric optimization of catalystic converter. This can be achieved by designing a catalyst with a optimum cone angle and a more surface area of the catalyst substrate. Additionally, the arrangement of the pores in the catalyst substrate can be changed. The numerical studies have been carried out using k-omega turbulence model with varying inlet angle of the catalytic converter and the length of the catalyst substrate. We observed that the geometry optimization is a meaningful objective for the lucrative design optimization of a catalytic converter for industrial applications.

Keywords: catalytic converter, emission control, reactor systems, substrate for emission control

Procedia PDF Downloads 903
3686 Comparison Conventional with Microwave-Assisted Drying Method on the Physicochemical Characteristics of Rice Bran Noodle

Authors: Chien-Chun Huang, Yi-U Chiou, Chiun-C.R. Wang

Abstract:

For longer shelf life of noodles, air-dried method is the traditional way for the noodle preparation. Microwave drying has the specific advantage of rapid and uniform heating due to the penetration of microwaves into the body of the product. Microwave-assisted facility offers a quick and energy saving method during food dehydration as compares to the conventional air-dried method. Recently, numerous studies in the rheological characteristics of pasta or spaghetti were carried out with microwave–assisted air driers and many agricultural products were dried successfully. There are few researches about the evaluation of physicochemical characteristics and cooking quality of microwave-assisted air dried salted noodles. The purposes of this study were to compare the difference between conventional and microwave-assisted drying method on the physicochemical properties and eating quality of rice bran noodles. Three different microwave power including 0.5 KW, 0.75 KW and 1.0 KW installing with 50℃ hot air were applied for dehydration of rice bran noodles in this study. Three proportion of rice bran ranging in 0-20% were incorporated into salted noodles processing. The appearance, optimum cooking time, cooking yield and losses, textural profiles analysis, sensory evaluation of rice bran noodles were measured in this study. The results indicated that high power (1.0 KW) microwave facility caused partially burnt and porous on the surface of rice bran noodles. However, no characteristic of noodle was appeared on the surface of noodles preparing by low power (0.5 KW) microwave facility. The optimum cooking time of noodles was decreased as higher power microwave or higher proportion of rice bran was incorporated into noodles preparation. The higher proportion of rice bran (20%) or higher power of microwave-assisted dried noodles obtained the higher color intensity and the higher cooking losses as compared with conventional air dried noodles. The firmness of cooked rice bran noodles slightly decreased in the cooked noodles which were dried by high power microwave-assisted method. The shearing force, tensile strength, elasticity and texture profiles of cooked rice noodles decreased with the progress of the proportion of rice bran. The results of sensory evaluation indicated conventional dried noodles obtained the higher springiness, cohesiveness and acceptability of cooked noodles than high power (1.0 KW) microwave-assisted dried noodles. However, low power (0.5 KW) microwave-assisted dried noodles showed the comparable sensory attributes and acceptability with conventional dried noodles. Moreover, the sensory attributes including firmness, springiness, cohesiveness decreased, but stickiness increased, with the increases of rice bran proportion. These results inferred that incorporation of lower proportion of rice bran and lower power microwave-assisted dried noodles processing could produce faster cooking time and acceptable quality of cooked noodles as compared to conventional dried noodles.

Keywords: microwave-assisted drying method, physicochemical characteristics, rice bran noodles, sensory evaluation

Procedia PDF Downloads 478
3685 Design of Smart Urban Lighting by Using Social Sustainability Approach

Authors: Mohsen Noroozi, Maryam Khalili

Abstract:

Creating cities, objects and spaces that are economically, environmentally and socially sustainable and which meet the challenge of social interaction and generation change will be one of the biggest tasks of designers. Social sustainability is about how individuals, communities and societies live with each other and set out to achieve the objectives of development model which they have chosen for themselves. Urban lightning as one of the most important elements of urban furniture that people constantly interact with it in public spaces; can be a significant object for designers. Using intelligence by internet of things for urban lighting makes it more interactive in public environments. It can encourage individuals to carry out appropriate behaviors and provides them the social awareness through new interactions. The greatest strength of this technology is its strong impact on many aspects of everyday life and users' behaviors. The analytical phase of the research is based on a multiple method survey strategy. Smart lighting proposed in this paper is an urban lighting designed on results obtained from a collective point of view about the social sustainability. In this paper, referring to behavioral design methods, the social behaviors of the people has been studied. Data show that people demands for a deeper experience of social participation, safety perception and energy saving with the meaningful use of interactive and colourful lighting effects. By using intelligent technology, some suggestions are provided in the field of future lighting to consider the new forms of social sustainability.

Keywords: behavior pattern, internet of things, social sustainability, urban lighting

Procedia PDF Downloads 193
3684 BEATRICE: A Low-Cost Manipulator Arm for an Educational Planetary Rover

Authors: T. Pakulski, L. Kryza, A. Linossier

Abstract:

The BEar Articulated TeleRobotic Inspection and Clasping Extremity is a lightweight, 5 DoF robotic manipulator for the Berlin Educational Assistant Rover (BEAR). BEAR is one of the educational planetary rovers developed under the Space Rover projects at the Chair of Space Technology of the Technische Universität Berlin. The projects serve to conduct research and train engineers by developing rovers for competitions like the European Rover Challenge and the DLR SpaceBot Cup. BEATRICE is the result of a cost-driven design process to deliver a simple but capable platform for a variety of competition tasks: object grasping and manipulation, inspection, instrument wielding and more. The manipulator’s simple mechatronic design, based on a combination of servomotors and stepper motors with planetary gearboxes, also makes it a practical tool for developing embedded control systems. The platform’s initial implementation relies on tele-operated control but is fully instrumented for future autonomous functionality. This paper describes BEATRICE’s development from its preliminary link model to its structural and mechatronic design, embedded control and AI and T. In parallel, it examines the influence of budget constraints and high personnel turnover commonly associated with student teams on the manipulator’s design. Finally, it comments on the utility of robot design projects for educating future engineers.

Keywords: education, low-cost, manipulator, robotics, rover

Procedia PDF Downloads 253
3683 Sensitivity and Uncertainty Analysis of Hydrocarbon-In-Place in Sandstone Reservoir Modeling: A Case Study

Authors: Nejoud Alostad, Anup Bora, Prashant Dhote

Abstract:

Kuwait Oil Company (KOC) has been producing from its major reservoirs that are well defined and highly productive and of superior reservoir quality. These reservoirs are maturing and priority is shifting towards difficult reservoir to meet future production requirements. This paper discusses the results of the detailed integrated study for one of the satellite complex field discovered in the early 1960s. Following acquisition of new 3D seismic data in 1998 and re-processing work in the year 2006, an integrated G&G study was undertaken to review Lower Cretaceous prospectivity of this reservoir. Nine wells have been drilled in the area, till date with only three wells showing hydrocarbons in two formations. The average oil density is around 300API (American Petroleum Institute), and average porosity and water saturation of the reservoir is about 23% and 26%, respectively. The area is dissected by a number of NW-SE trending faults. Structurally, the area consists of horsts and grabens bounded by these faults and hence compartmentalized. The Wara/Burgan formation consists of discrete, dirty sands with clean channel sand complexes. There is a dramatic change in Upper Wara distributary channel facies, and reservoir quality of Wara and Burgan section varies with change of facies over the area. So predicting reservoir facies and its quality out of sparse well data is a major challenge for delineating the prospective area. To characterize the reservoir of Wara/Burgan formation, an integrated workflow involving seismic, well, petro-physical, reservoir and production engineering data has been used. Porosity and water saturation models are prepared and analyzed to predict reservoir quality of Wara and Burgan 3rd sand upper reservoirs. Subsequently, boundary conditions are defined for reservoir and non-reservoir facies by integrating facies, porosity and water saturation. Based on the detailed analyses of volumetric parameters, potential volumes of stock-tank oil initially in place (STOIIP) and gas initially in place (GIIP) were documented after running several probablistic sensitivity analysis using Montecalro simulation method. Sensitivity analysis on probabilistic models of reservoir horizons, petro-physical properties, and oil-water contacts and their effect on reserve clearly shows some alteration in the reservoir geometry. All these parameters have significant effect on the oil in place. This study has helped to identify uncertainty and risks of this prospect particularly and company is planning to develop this area with drilling of new wells.

Keywords: original oil-in-place, sensitivity, uncertainty, sandstone, reservoir modeling, Monte-Carlo simulation

Procedia PDF Downloads 196
3682 Analyses of Uniaxial and Biaxial Flexure Tests Used in Ceramic Materials

Authors: Barry Hojjatie

Abstract:

Uniaxial (e.g., three-point bending) and biaxial flexure tests are used frequently for determining the strength of ceramics. It is generally believed that the biaxial test has an advantage as compared to uniaxial test because it produces a state of pure tension on the lower surface of the specimen and the maximum tensile stress, which is usually responsible for crack initiation and failure is unaffected by the edge condition. However, inconsistent strength values have been reported for the same material and testing conditions. The objective of this study was to analyze the strength of dental porcelain materials using the two different test methods and evaluate the main contributions to variability in biaxial testing and to analyze the relative influence of variables such as specimen geometric conditions and loading conditions on calculated strength of porcelain subjected to biaxial testing. Porcelain disks (16 mm dia x 2 mm thick) were subjected to biaxial flexure (pin-on-three-ball), and flexure strength values were calculated. A 3-D finite element model was developed to simulate various biaxial flexure test conditions. Stresses were analyzed for ceramic thickness in the range of 1.0-3.0 mm. For a 2-mm-thick disk subjected to a point load of 200 N, the maximum tensile stress at the lower surface was 180 MPa. This stress decreased to 95, 77, 68, and 59 MPa for the radius of the load values of 0.15, 0.3, 0.6, and 1.0 mm, respectively. Tensile stresses which developed at the top surface near the site of loading were small for the radius of the load ≥ 0.6 mm.

Keywords: ceramis, biaxial, flexure test, uniaxial

Procedia PDF Downloads 154
3681 Mobile Assembly of Electric Vehicles: Decentralized, Low-Invest and Flexible

Authors: Achim Kampker, Kai Kreiskoether, Johannes Wagner, Sarah Fluchs

Abstract:

The growing speed of innovation in related industries requires the automotive industry to adapt and increase release frequencies of new vehicle derivatives which implies a significant reduction of investments per vehicle and ramp-up times. Emerging markets in various parts of the world augment the currently dominating established main automotive markets. Local content requirements such as import tariffs on final products impede the accessibility of these micro markets, which is why in the future market exploitation will not be driven by pure sales activities anymore but rather by setting up local assembly units. The aim of this paper is to provide an overview of the concept of decentralized assembly and to discuss and critically assess some currently researched and crucial approaches in production technology. In order to determine the scope in which complementary mobile assembly can be profitable for manufacturers, a general cost model is set up and each cost driver is assessed with respect to varying levels of decentralization. One main result of the paper is that the presented approaches offer huge cost-saving potentials and are thus critical for future production strategies. Nevertheless, they still need to be further exploited in order for decentralized assembly to be profitable for companies. The optimal level of decentralization must, however, be specifically determined in each case and cannot be defined in general.

Keywords: automotive assembly, e-mobility, production technology, release capability, small series assembly

Procedia PDF Downloads 198
3680 A Dynamic Solution Approach for Heart Disease Prediction

Authors: Walid Moudani

Abstract:

The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

Procedia PDF Downloads 410
3679 Identification of Hepatocellular Carcinoma Using Supervised Learning Algorithms

Authors: Sagri Sharma

Abstract:

Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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3678 Saco Sweet Cherry: Phenolic Profile and Biological Activity of Coloured and Non-Coloured Fractions

Authors: Catarina Bento, Ana Carolina Gonçalves, Fábio Jesus, Luís Rodrigues Silva

Abstract:

Increasing evidence suggests that a diet rich in fruits and vegetables plays important roles in the prevention of chronic diseases, such as heart disease, cancer, stroke, diabetes, Alzheimer’s disease, among others. Fruits and vegetables gained prominence due their richness in bioactive compounds, being the focus of many studies due to their biological properties acting as health promoters. Prunus avium Linnaeus (L.), commonly known as sweet cherry has been the centre of attention due to its health benefits, and has been highly studied. In Portugal, most of the cherry production comes from the Fundão region. The Saco is one of the most important cultivar produced in this region, attributed with geographical protection. In this work, we prepared 3 extracts through solid-phase extraction (SPE): a whole extract, fraction I (non-coloured phenolics) and fraction II (coloured phenolics). The three extracts were used to determine the phenolic profile of Saco cultivar by liquid chromatography with diode array detection (LC-DAD) technique. This was followed by the evaluation of their biological potential, testing the extracts’ capacity to scavenge free-radicals (DPPH•, nitric oxide (•NO) and superoxide radical (O2●-)) and to inhibit α-glucosidase enzyme of all extracts. Additionally, we evaluated, for the first time, the protective effects against peroxyl radical (ROO•)-induced hemoglobin oxidation and hemolysis in human erythrocytes. A total of 16 non-coloured phenolics were detected, 3-O-caffeoylquinic and ρ-coumaroylquinic acids were the main ones, and 6 anthocyanins were found, among which cyanidin-3-O-rutinoside represented the majority. In respect to antioxidant activity, Saco showed great antioxidant potential in a concentration-dependent manner, demonstrated through the DPPH•,•NO and O2●-radicals, and greater ability to inhibit the α-glucosidase enzyme in comparison to the regular drug acarbose used to treat diabetes. Additionally, Saco proved to be effective to protect erythrocytes against oxidative damage in a concentration-dependent manner against hemoglobin oxidation and hemolysis. Our work demonstrated that Saco cultivar is an excellent source of phenolic compounds which are natural antioxidants that easily capture reactive species, such as ROO• before they can attack the erythrocytes’ membrane. In a general way, the whole extract showed the best efficiency, most likely due to a synergetic interaction between the different compounds. Finally, comparing the two separate fractions, the coloured fraction showed the most activity in all the assays, proving to be the biggest contributor of Saco cherries’ biological activity.

Keywords: biological potential, coloured phenolics, non-coloured phenolics, sweet cherry

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3677 Critical Thinking and Creativity of Undergraduate Nursing Students: Descriptive and Disposition in Academic Levels

Authors: Kamolrat Turner, Chularat Howharn

Abstract:

Critical thinking and creativity are desirable competency for contemporary nurses although there are growing concerns supporting a disturbing paucity in its achievement. Nursing colleges in Thailand have developed teaching strategies and curricula that nurture critical thinking and creativity dispositions according academic levels. Objectives: This descriptive study identified critical thinking and creativity dispositions of Thai nursing students according academic levels. Methods: A cross-sectional questionnaire survey was conducted among 515 nursing students for four academic levels. All are studying at Boromarajonani College of Nursing Chon Buri, Thailand. Descriptive and univariate general linear model analysis were applied. Results: The scores on critical thinking disposition gradually increased as academic level is rising from the junior year throughout the senior year, but its scores are neutral. Scores on creativity skill is neutral and constant thorough the four academic years. The fourth grade students had slightly higher scores on creativity when compared to others. A significant relationship between critical thinking and creativity was also found. Conclusions: The scores on critical thinking disposition gradually improved which greatly increased in the senior year. However, creativity has neutrally progressed. The findings suggest the importance of targeting the development of curriculum and teaching strategies for all grades of nursing students to increase their critical thinking and creativity skills.

Keywords: critical thinking, creativity, undergraduate nursing students, competency

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3676 Vehicle Maneuverability on Horizontal Curves on Hilly Terrain: A Study on Shillong Highway

Authors: Surendra Choudhary, Sapan Tiwari

Abstract:

The driver has two fundamental duties i) controlling the position of the vehicle along the longitudinal and lateral direction of movement ii) roadway width. Both of these duties are interdependent and are concurrently referred to as two-dimensional driver behavior. One of the main problems facing driver behavior modeling is to identify the parameters for describing the exemplary driving conduct and car maneuver under distinct traffic circumstances. Still, to date, there is no well-accepted theory that can comprehensively model the 2-D driver conduct (longitudinal and lateral). The primary objective of this research is to explore the vehicle's lateral longitudinal behavior in the heterogeneous condition of traffic on horizontal curves as well as the effect of road geometry on dynamic traffic parameters, i.e., car velocity and lateral placement. In this research, with their interrelationship, a thorough assessment of dynamic car parameters, i.e., speed, lateral acceleration, and turn radius. Also, horizontal curve road parameters, i.e., curvature radius, pavement friction, are performed. The dynamic parameters of the various types of car drivers are gathered using a VBOX GPS-based tool with high precision. The connection between dynamic car parameters and curve geometry is created after the removal of noise from the GPS trajectories. The major findings of the research are that car maneuvers with higher than the design limits of speed, acceleration, and lateral deviation on the studied curves of the highway. It can become lethal if the weather changes from dry to wet.

Keywords: geometry, maneuverability, terrain, trajectory, VBOX

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3675 Bio-Oil Compounds Sorption Enhanced Steam Reforming

Authors: Esther Acha, Jose Cambra, De Chen

Abstract:

Hydrogen is considered an important energy vector for the 21st century. Nowadays there are some difficulties for hydrogen economy implantation, and one of them is the high purity required for hydrogen. This energy vector is still being mainly produced from fuels, from wich hydrogen is produced as a component of a mixture containing other gases, such as CO, CO2 and H2O. A forthcoming sustainable pathway for hydrogen is steam-reforming of bio-oils derived from biomass, e.g. via fast pyrolysis. Bio-oils are a mixture of acids, alcohols, aldehydes, esters, ketones, sugars phenols, guaiacols, syringols, furans, multi-functional compounds and also up to a 30 wt% of water. The sorption enhanced steam reforming (SESR) process is attracting a great deal of attention due to the fact that it combines both hydrogen production and CO2 separation. In the SESR process, carbon dioxide is captured by an in situ sorbent, which shifts the reversible reforming and water gas shift reactions to the product side, beyond their conventional thermodynamic limits, giving rise to a higher hydrogen production and lower cost. The hydrogen containing mixture has been obtained from the SESR of bio-oil type compounds. Different types of catalysts have been tested. All of them contain Ni at around a 30 wt %. Two samples have been prepared with the wet impregnation technique over conventional (gamma alumina) and non-conventional (olivine) supports. And a third catalysts has been prepared over a hydrotalcite-like material (HT). The employed sorbent is a commercial dolomite. The activity tests were performed in a bench-scale plant (PID Eng&Tech), using a stainless steel fixed bed reactor. The catalysts were reduced in situ in the reactor, before the activity tests. The effluent stream was cooled down, thus condensed liquid was collected and weighed, and the gas phase was analysed online by a microGC. The hydrogen yield, and process behavior was analysed without the sorbent (the traditional SR where a second purification step will be needed but that operates in steady state) and the SESR (where the purification step could be avoided but that operates in batch state). The influence of the support type and preparation method will be observed in the produced hydrogen yield. Additionally, the stability of the catalysts is critical, due to the fact that in SESR process sorption-desorption steps are required. The produced hydrogen yield and hydrogen purity has to be high and also stable, even after several sorption-desorption cycles. The prepared catalysts were characterized employing different techniques to determine the physicochemical properties of the fresh-reduced and used (after the activity tests) materials. The characterization results, together with the activity results show the influence of the catalysts preparation method, calcination temperature, or can even explain the observed yield and conversion.

Keywords: CO2 sorbent, enhanced steam reforming, hydrogen

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3674 An Improved Discrete Version of Teaching–Learning-Based ‎Optimization for Supply Chain Network Design

Authors: Ehsan Yadegari

Abstract:

While there are several metaheuristics and exact approaches to solving the Supply Chain Network Design (SCND) problem, there still remains an unfilled gap in using the Teaching-Learning-Based Optimization (TLBO) algorithm. The algorithm has demonstrated desirable results with problems with complicated combinational optimization. The present study introduces a Discrete Self-Study TLBO (DSS-TLBO) with priority-based solution representation that can solve a supply chain network configuration model to lower the total expenses of establishing facilities and the flow of materials. The network features four layers, namely suppliers, plants, distribution centers (DCs), and customer zones. It is designed to meet the customer’s demand through transporting the material between layers of network and providing facilities in the best economic Potential locations. To have a higher quality of the solution and increase the speed of TLBO, a distinct operator was introduced that ensures self-adaptation (self-study) in the algorithm based on the four types of local search. In addition, while TLBO is used in continuous solution representation and priority-based solution representation is discrete, a few modifications were added to the algorithm to remove the solutions that are infeasible. As shown by the results of experiments, the superiority of DSS-TLBO compared to pure TLBO, genetic algorithm (GA) and firefly Algorithm (FA) was established.

Keywords: supply chain network design, teaching–learning-based optimization, improved metaheuristics, discrete solution representation

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3673 Effect of Modified Atmosphere Packaging and Storage Temperatures on Quality of Shelled Raw Walnuts

Authors: M. Javanmard

Abstract:

This study was aimed at analyzing the effects of packaging (MAP) and preservation conditions on the packaged fresh walnut kernel quality. The central composite plan was used for evaluating the effect of oxygen (0–10%), carbon dioxide (0-10%), and temperature (4-26 °C) on qualitative characteristics of walnut kernels. Also, the response level technique was used to find the optimal conditions for interactive effects of factors, as well as estimating the best conditions of process using least amount of testing. Measured qualitative parameters were: peroxide index, color, decreased weight, mould and yeast counting test, and sensory evaluation. The results showed that the defined model for peroxide index, color, weight loss, and sensory evaluation is significant (p < 0.001), so that increase of temperature causes the peroxide value, color variation, and weight loss to increase and it reduces the overall acceptability of walnut kernels. An increase in oxygen percentage caused the color variation level and peroxide value to increase and resulted in lower overall acceptability of the walnuts. An increase in CO2 percentage caused the peroxide value to decrease, but did not significantly affect other indices (p ≥ 0.05). Mould and yeast were not found in any samples. Optimal packaging conditions to achieve maximum quality of walnuts include: 1.46% oxygen, 10% carbon dioxide, and temperature of 4 °C.

Keywords: shelled walnut, MAP, quality, storage temperature

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3672 Understanding Regional Circulations That Modulate Heavy Precipitations in the Kulfo Watershed

Authors: Tesfay Mekonnen Weldegerima

Abstract:

Analysis of precipitation time series is a fundamental undertaking in meteorology and hydrology. The extreme precipitation scenario of the Kulfo River watershed is studied using wavelet analysis and atmospheric transport, a lagrangian trajectory model. Daily rainfall data for the 1991-2020 study periods are collected from the office of the Ethiopian Meteorology Institute. Meteorological fields on a three-dimensional grid at 0.5o x 0.5o spatial resolution and daily temporal resolution are also obtained from the Global Data Assimilation System (GDAS). Wavelet analysis of the daily precipitation processed with the lag-1 coefficient reveals some high power recurred once every 38 to 60 days with greater than 95% confidence for red noise. The analysis also identified inter-annual periodicity in the periods 2002 - 2005 and 2017 - 2019. Back trajectory analysis for 3-day periods up to May 19/2011, indicates the Indian Ocean source; trajectories crossed the eastern African escarpment to arrive at the Kulfo watershed. Atmospheric flows associated with the Western Indian monsoon redirected by the low-level Somali winds and Arabian ridge are responsible for the moisture supply. The time-localization of the wavelet power spectrum yields valuable hydrological information, and the back trajectory approaches provide useful characterization of air mass source.

Keywords: extreme precipitation events, power spectrum, back trajectory, kulfo watershed

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3671 Data-Driven Performance Evaluation of Surgical Doctors Based on Fuzzy Analytic Hierarchy Processes

Authors: Yuguang Gao, Qiang Yang, Yanpeng Zhang, Mingtao Deng

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To enhance the safety, quality and efficiency of healthcare services provided by surgical doctors, we propose a comprehensive approach to the performance evaluation of individual doctors by incorporating insights from performance data as well as views of different stakeholders in the hospital. Exploratory factor analysis was first performed on collective multidimensional performance data of surgical doctors, where key factors were extracted that encompass assessment of professional experience and service performance. A two-level indicator system was then constructed, for which we developed a weighted interval-valued spherical fuzzy analytic hierarchy process to analyze the relative importance of the indicators while handling subjectivity and disparity in the decision-making of multiple parties involved. Our analytical results reveal that, for the key factors identified as instrumental for evaluating surgical doctors’ performance, the overall importance of clinical workload and complexity of service are valued more than capacity of service and professional experience, while the efficiency of resource consumption ranks comparatively the lowest in importance. We also provide a retrospective case study to illustrate the effectiveness and robustness of our quantitative evaluation model by assigning meaningful performance ratings to individual doctors based on the weights developed through our approach.

Keywords: analytic hierarchy processes, factor analysis, fuzzy logic, performance evaluation

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