Search results for: estimation of properties of the model

Authors: Urvi Shah, Anmol Jain

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The talks of a New Global Order have been doing rounds since the advent of 21st century. Similar change in global scenario was witnessed when the Bretton Woods System came up post the World War II. The changing world order has been analyzed by using the Purchasing Power Parity (PPP) and Nominal Gross Domestic Product (GDP) estimates. The PPP and Nominal GDP methods show the purchasing power and financial background of the countries respectively, which helps in knowing both real and nominal financial strength of the country. Today, the rising powers of BRICS are posing new challenges to the world order shaped by the West. BRICS, i.e. Brazil, Russia, India, China and South Africa, countries have at various instances represented the interests of developing countries at world forums. The pooled population of these nations accounts for 41.6% of the total world population which gives a very resilient idea of the workforce or human resources which is mobilized by them. They have a combined GDP (PPP) of around 30.57% of the total world GDP (PPP). The paper tries to analyze the prospects and impact of the New Development Bank (NDB) formerly known as the BRICS Bank, on world economy, which has the potential to act as a rival to West dominated IMF and World Bank. The paper studies the paradigm shift in the global order, impact of the NDB on third world nations and the developed nations. The study concluded that the relative positions of BRICS countries in the world economy are changing, irrespective of the measurement methodology being US$ or the PPP model.

Keywords: BRICS, New Development Bank, Nominal GDP, purchasing power parity

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Authors: Amit Sarkar, Jayanta K. Mahato, Tushar Bhattacharya, Amrita Kundu, P. C. Chakraborti

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With increasing the demand for safety and fuel efficiency of automobiles, automotive manufacturers are looking for light weight, high strength steel with excellent formability and corrosion resistance. Dual-phase steel is finding applications in automotive sectors, because of its high strength, good formability, and high corrosion resistance. During service automotive components suffer from environmental attack and thereby gradual degradation of the components occurs reducing the service life of the components. The objective of the present investigation is to assess the effect of deformation on corrosion behaviour of DP590 grade dual phase steel which is used in automotive industries. The material was received from TATA Steel Jamshedpur, India in the form of 1 mm thick sheet. Tensile properties of the steel at strain rate of 10-3 sec-1: 0.2 % Yield Stress is 382 MPa, Ultimate Tensile Strength is 629 MPa, Uniform Strain is 16.30% and Ductility is 29%. Rectangular strips of 100x10x1 mm were machined keeping the long axis of the strips parallel to rolling direction of the sheet. These strips were longitudinally deformed at a strain rate at 10-3 sec-1 to a different percentage of strain, e.g. 2.5, 5, 7.5,10 and 12.5%, and then slowly unloaded. Small specimens were extracted from the mid region of the unclamped portion of these deformed strips. These small specimens were metallographic polished, and corrosion behaviour has been studied by potentiodynamic polarization, electrochemical impedance spectra, and cyclic polarization and potentiostatic tests. Present results show that among three different environments, the 3.5 pct NaCl solution is most aggressive in case of DP 590 dual-phase steel. It is observed that with the increase in the amount of deformation, corrosion rate increases. With deformation, the stored energy increases and leads to enhanced corrosion rate. Cyclic polarization results revealed highly deformed specimen are more prone to pitting corrosion as compared to the condition when amount of deformation is less. It is also observed that stability of the passive layer decreases with the amount of deformation. With the increase of deformation, current density increases in a passive zone and passive zone is also decreased. From Electrochemical impedance spectroscopy study it is found that with increasing amount of deformation polarization resistance (Rp) decreases. EBSD results showed that average geometrically necessary dislocation density increases with increasing strain which in term increased galvanic corrosion as dislocation areas act as the less noble metal.

Keywords: dual phase 590 steel, prestrain, potentiodynamic polarization, cyclic polarization, electrochemical impedance spectra

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Authors: Xianghe Dai, Dennis Lam, Therese Sheehan, Naveed Rehman, Jie Yang

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Concrete is one of the most used construction materials that may be made onsite as fresh concrete and then placed in formwork to produce the desired shapes of structures. It has been recognized that the raw materials and mix proportion of concrete dominate the mechanical characteristics of hardened concrete, and the curing method and environment applied to the concrete in early stages of hardening will significantly influence the concrete properties, such as compressive strength, durability, permeability etc. In construction practice, there are various curing methods to maintain the presence of mixing water throughout the early stages of concrete hardening. They are also beneficial to concrete in hot weather conditions as they provide cooling and prevent the evaporation of water. Such methods include ponding or immersion, spraying or fogging, saturated wet covering etc. Also there are various curing methods that may be implemented to decrease the level of water lost which belongs to the concrete surface, such as putting a layer of impervious paper, plastic sheeting or membrane on the concrete to cover it. In the concrete material laboratory, accelerated strength gain methods supply the concrete with heat and additional moisture by applying live steam, coils that are subject to heating or pads that have been warmed electrically. Currently when determining the mechanical parameters of a concrete, the concrete is usually sampled from fresh concrete on site and then cured and tested in laboratories where standardized curing procedures are adopted. However, in engineering practice, curing procedures in the construction sites after the placing of concrete might be very different from the laboratory criteria, and this includes some standard curing procedures adopted in the laboratory that can’t be applied on site. Sometimes the contractor compromises the curing methods in order to reduce construction costs etc. Obviously the difference between curing procedures adopted in the laboratory and those used on construction sites might over- or under-estimate the real concrete quality. This paper presents the effect of three typical curing methods (air curing, water immersion curing, plastic film curing) and of maintaining concrete in steel moulds on the compressive strength development of normal concrete. In this study, Portland cement with 30% fly ash was used and different curing periods, 7 days, 28 days and 60 days were applied. It was found that the highest compressive strength was observed from concrete samples to which 7-day water immersion curing was applied and from samples maintained in steel moulds up to the testing date. The research results implied that concrete used as infill in steel tubular members might develop a higher strength than predicted by design assumptions based on air curing methods. Wrapping concrete with plastic film as a curing method might delay the concrete strength development in the early stages. Water immersion curing for 7 days might significantly increase the concrete compressive strength.

Keywords: compressive strength, air curing, water immersion curing, plastic film curing, maintaining in steel mould, comparison

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Authors: Abdessalam Hijab, Eric Henry, Hafida Boulekbache

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The complexity of the city makes sustainable management of the urban environment more difficult. Managers are required to make significant human and technical investments, particularly in household waste collection (focus of our research). The aim of this communication is to propose a collaborative geographic multi-actor device (MGCD) based on the link between information and communication technologies (ICT) and geo-web tools in order to involve urban residents in household waste collection processes. Our method is based on a collaborative/motivational concept between the city and its residents. It is a geographic collaboration dedicated to the general public (citizens, residents, and any other participant), based on real-time allocation and geographic location of topological, geographic, and multimedia data in the form of local geo-alerts (location-specific problems) related to household waste in an urban environment. This contribution allows us to understand the extent to which residents can assist and contribute to the development of household waste collection processes for a better protected urban environment. This suggestion provides a good idea of how residents can contribute to the data bank for future uses. Moreover, it will contribute to the transformation of the population into a smart inhabitant as an essential component of a smart city. The proposed model will be tested in the Lamkansa sampling district in Casablanca, Morocco.

Keywords: information and communication technologies, ICTs, GeoWeb, geo-collaboration, city, inhabitant, waste, collection, environment

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Authors: Ayman Abd-Elhamed, Sayed Mahmoud

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The present research work investigates the seismic response of reinforced concrete (RC) frame building considering the effect of modeling masonry infill (MI) walls. The seismic behavior of a residential 6-storey RC frame building, considering and ignoring the effect of masonry, is numerically investigated using response spectrum (RS) analysis. The considered herein building is designed as a moment resisting frame (MRF) system following the Egyptian code (EC) requirements. Two developed models in terms of bare frame and infill walls frame are used in the study. Equivalent diagonal strut methodology is used to represent the behavior of infill walls, whilst the well-known software package ETABS is used for implementing all frame models and performing the analysis. The results of the numerical simulations such as base shear, displacements, and internal forces for the bare frame as well as the infill wall frame are presented in a comparative way. The results of the study indicate that the interaction between infill walls and frames significantly change the responses of buildings during earthquakes compared to the results of bare frame building model. Specifically, the seismic analysis of RC bare frame structure leads to underestimation of base shear and consequently damage or even collapse of buildings may occur under strong shaking. On the other hand, considering infill walls significantly decrease the peak floor displacements and drifts in both X and Y-directions.

Keywords: masonry infill, bare frame, response spectrum, seismic response

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Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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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

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Authors: Nikhil Kewalkrishna Mehta

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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

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

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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

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Authors: Madelyn N. Moawad, Hermine R. Z. Tadros, Mary G. Ghobrial, Ahmad R. Bassiouny, Kamal M. Kandeel, Athar Ata

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Seaweeds are potential renewable resources in marine environment. They provide an excellent source of bioactive substances such as dietary fibers and various functional polysaccharides that could potentially be used as ingredients for both human and animal health applications. The observations suggested that these bioactive compounds have strong antioxidant properties, which have beneficial effects on human health. The present research aimed at finding new chemical products from local marine macroalgae for natural medicinal uses and consumption for their nutritional values. Macroalgae samples were collected manually mainly from the Mediterranean Sea at shallow subtidal zone of Abu Qir Bay, Alexandria, Egypt. The chemical compositions of lyophilized materials of six selected macroalgal species; Colpomenia sinuosa, Sargassum linifolium, Padina pavonia, Pterocladiella capillacea, Laurencia pinnatifidia, and Caulerpa racemosa, were investigated for proteins using bovine serum albumin, and carbohydrates were assayed by phenol-sulfuric acid reaction. The macroalgae lipid was extracted with chloroform, methanol and phosphate buffer. Vitamins were extracted using trichloroacetic acid. Chlorophylls and total carotenoids were determined spectrophotometrically and total phenols were extracted with methanol. In addition, lipid-soluble, and water-soluble antioxidant, and anti α-glucosidase activities were measured spectrophotometrically. The antioxidant activity of hexane extracts was investigated using phosphomolybdenum reagent. The anti-α-glucosidase effect measurement was initiated by mixing α-glucosidase solution with p-nitrophenyl α-D-glucopyranoside. The results showed that the ash contents varied from 11.2 to 35.4 % on dry weight basis for P. capillacea and Laurencia pinnatifidia, respectively. The protein contents ranged from 5.63 % in brown macroalgae C. sinuosa to 8.73 % in P. pavonia. A relative wide range in carbohydrate contents was observed (20.06–46.75 %) for the test algal species. The highest lipid percentage was found in green alga C. racemosa (5.91%) followed by brown algae P. pavonia (3.57%) and C. sinuosa (2.64%). The phenolic contents varied from 1.32 mg GAE/g for C. sinuosa to 4.00 mg GAE/g in P. pavonia. The lipid-soluble compounds exhibited higher antioxidant capacity (73.18-145.95 µM/g) than that of the water-soluble ones ranging from 24.83 µM/g in C. racemosa to 74.07 µM/g in S. linifolium. The most potent anti-α-glucosidase activity was observed for P. pavonia with IC50 of 17.12 μg/ml followed by S. linifolium (IC50 = 71.75 μg/ml), C. racemosa (IC50 = 84.73 μg/ml), P. capillacea (IC50 = 92.16 μg/ml), C. sinuosa (IC50 = 112.44 μg/ml), and L. pinnatifida (IC50 = 115.11 μg/ml).

Keywords: α-glucosidase, lyophilized, macroalgae, spectrophotometrically

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

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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

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

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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

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Authors: Angelina Chiglintseva, Vladislav Shagapov

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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

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Authors: Manirath Wongsim

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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

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

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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

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

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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

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Authors: Ogan Karabas, Suleyman Yigit

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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

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Authors: Martha Wilson

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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

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

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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

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Authors: Raymond Xu, Cindy Jingru Wang

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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

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

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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

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Authors: Mirjana Petronijević, Sanja Panić, Aleksandra Cvetanović, Branko Kordić, Nenad Grba

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Enzyme peroxidases are biological catalysts and play a major role in phenolic wastewater treatments and other environmental applications. The most studied species from the peroxidases family is horseradish peroxidase (HRP). In environmental processes, HRP could be used in its free or immobilized form. Enzyme immobilization onto solid support is performed to improve the enzyme properties, prolong its lifespan and operational stability and allow its reuse in industrial applications. One of the enzyme supports of a newer generation is magnetic particles (MPs). Fe₃O₄ MPs are the most widely pursued immobilization of enzymes owing to their remarkable advantages of biocompatibility and non-toxicity. Also, MPs can be easily separated and recovered from the water by applying an external magnetic field. On the other hand, metals and metal oxides are not suitable for the covalent binding of enzymes, so it is necessary to perform their surface modification. Fe₃O₄ MPs functionalization could be performed during the process of their synthesis if it takes place in the presence of plant extracts. Extracts of plant material, such as wild plants, herbs, even waste materials of the food and agricultural industry (bark, shell, leaves, peel), are rich in various bioactive components such as polyphenols, flavonoids, sugars, etc. When the synthesis of magnetite is performed in the presence of plant extracts, bioactive components are incorporated into the surface of the magnetite, thereby affecting its functionalization. In this paper, the suitability of bio-magnetite as solid support for covalent immobilization of HRP across glutaraldehyde was examined. The activity of immobilized HRP at different pH values (4-9) and temperatures (20-80°C) and reusability were examined. Bio-MP was synthesized by co-precipitation method from Fe(II) and Fe(III) sulfate salts in the presence of water extract of the Allium cepa peel. The water extract showed 81% of antiradical potential (according to DPPH assay), which is connected with the high content of polyphenols. According to the FTIR analysis, the bio-magnetite contains oxygen functional groups (-OH, -COOH, C=O) suitable for binding to glutaraldehyde, after which the enzyme is covalently immobilized. The immobilized enzyme showed high activity at ambient temperature and pH 7 (30 U/g) and retained ≥ 80% of its activity at a wide range of pH (5-8) and temperature (20-50°C). The HRP immobilized onto bio-MPs showed remarkable stability towards temperature and pH variations compared to the free enzyme form. On the other hand, immobilized HRP showed low reusability after the first washing cycle enzyme retains 50% of its activity, while after the third washing cycle retains only 22%.

Keywords: bio-magnetite, enzyme immobilization, water extracts, environmental protection

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Authors: Nicole C. Valdez, Vincent L. Borromeo, Conrad C. Chong, Ahmad F. Mazahery

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Breast cancer is the most prevalent cancer worldwide, where the majority of cases are estrogen-receptor positive and involve 2 receptor proteins. The binding of estrogen to estrogen receptor alpha (ERα) promotes breast cancer growth, while it's binding to estrogen-receptor beta (ERβ) inhibits tumor growth. While natural products have been a promising source of chemotherapeutic agents, the challenge remains in finding a bioactive compound that specifically targets cancer cells, minimizing side effects on normal cells. Flavonoids are natural products that act as phytoestrogens and induce the same response as estrogen. They are able to compete with estrogen for binding to ERα; however, it has a higher binding affinity for ERβ. Their abundance in nature and low toxicity make them a potential candidate for breast cancer treatment. This study aimed to determine which particular flavonoids can specifically recognize ERβ and potentially be used for breast cancer treatment through molecular docking. A total of 206 flavonoids comprised of 97 isoflavones and 109 flavanones were collected from ZINC15, while the 3D structures of ERβ and ERα were obtained from Protein Data Bank. These flavonoid subclasses were chosen as they bind more strongly to ERs due to their chemical structure. The structures of the flavonoid ligands were converted using Open Babel, while the estrogen receptor protein structures were prepared using Autodock MGL Tools. The optimal binding site was found using BIOVIA Discovery Studio Visualizer before docking all flavonoids on both ERβ and ERα through Autodock Vina. Genistein is a flavonoid that exhibits anticancer effects by binding to ERβ, so its binding affinity was used as a baseline. Eriodictyol and 4”,6”-Di-O-Galloylprunin both exceeded genistein’s binding affinity for ERβ and was lower than its binding affinity for ERα. Of the two, eriodictyol was pursued due to its antitumor properties on a lung cancer cell line and on glioma cells. It is able to arrest the cell cycle at the G2/M phase by inhibiting the mTOR/PI3k/Akt cascade and is able to induce apoptosis via the PI3K/Akt/NF-kB pathway. Protein pathway and gene analysis were also conducted using ChEMBL and PANTHER and it was shown that eriodictyol might induce anticancer effects through the ROS1, CA7, KMO, and KDM1A genes which are involved in cell proliferation in breast cancer, non-small cell lung cancer, and other diseases. The high binding affinity of eriodictyol to ERβ, as well as its potential affected genes and antitumor effects, therefore, make it a candidate for the development of new breast cancer treatment. Verification through in vitro experiments such as checking the upregulation and downregulation of genes through qPCR and checking cell cycle arrest using a flow cytometry assay is recommended.

Keywords: breast cancer, estrogen receptor, flavonoid, molecular docking

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Authors: Mohsen Noroozi, Maryam Khalili

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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

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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

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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

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Authors: Barry Hojjatie

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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

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Authors: Tamara Anderson, Neela Badrie

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Plant phenolics which are found in red grape wine, have received considerable attention due to their potential antioxidant activity. Grape by-products contain large amounts of phenolic compounds, mostly flavonoids at high concentrations of 1000-1800 mg/L. Plant phenolics contribute to the flavor, and nutritional value. Sorrel or roselle (Hibiscus sabdariffa L.) belongs to the family Malvaceae. The brilliant red pigments in sorrel calyces contain anthocyanins which are the major sources of antioxidant capacity. Consumers are demanding novel beverages that are healthier, convenient and have appealing consumer acceptance. The objectives of this study were to investigate the effects of adding grape polyphenols and the influence of presenting health claims on the sensory acceptability of the wines. Fresh red sorrel calyces were fermented into wines. The total soluble solids of the pectinase-treated sorrel puree were from 4°Brix to 23.8°Brix. Polyphenol in the form of grape pomace extract was added to sorrel wines (w/v) in specified levels to give 0. 25. 50 and 75 ppm. A focus group comprising of 12 panelists was use to select the level of polyphenol to be added to sorrel wines for sensory preference The sensory attributed of the wines which were evaluated were colour, clarity, aroma, flavor, mouth-feel, sweetness, astringency and overall preference. The sorrel wine which was most preferred from focus group evaluation was presented for hedonic rating. In the first stage of hedonic testing, the sorrel wine was served chilled at 7°C for 24 h prior to sensory evaluation. Each panelist was provided with a questionnaire and was asked to rate the wines on colour, aroma, flavor, mouth-feel, sweetness, astringency and overall acceptability using a 9-point hedonic scale. In the second stage of hedonic testing, the panelist were instructed to read a health abstract on the health benefits of polyphenolic compounds and again to rate sorrel wine with added 25 ppm polyphenol. Paired t-test was used for the analysis of the influence of presenting health information on polyphenols on hedonic scoring of sorrel wines. Focus groups found that the addition of polyphenol addition had no significant effect on sensory color and aroma but affected clarity and flavor. A 25 ppm wine was liked moderately in overall acceptability. The presentation of information on the health benefit of polyphenols in sorrel wines to panelists had no significant influence on the sensory acceptance of wine. More than half of panelists would drink this wine now and then. This wine had color L 19.86±0.68, chroma 2.10±0.12, hue° 16.90 ±3.10 and alcohol content of 13.0%. The sorrel wine was liked moderately in overall acceptability with the added polyphenols.

Keywords: sorrel wines, Roselle Hibiscus sabdariffa L, novel wine, polyphenols, health benefits, physicochemical properties

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

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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

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Authors: Walid Moudani

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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

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Authors: Sagri Sharma

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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

Procedia PDF Downloads 418