Search results for: artificial roughness

Authors: Krishna Mohana Rao Gurram, R. Padmini, P. Vamsi Krishna

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As a part of extensive research for ecologically safe and operator friendly cutting fluids, this paper presents the experimental investigations on the performance of eco-friendly vegetable oil based nanofluids in turning operation. In order to assess the quality of nano cutting fluids used during machining, cutting temperatures, cutting forces and surface roughness under constant cutting conditions are measured. The influence of two types of nanofluids prepared from nano boric acid and CNT particles mixed separately with coconut oil, on machining performance during turning operation is examined. Comparative analysis of the results obtained is done under dry and lubricant environments. Results obtained using cutting fluids prepared from vegetable oil based nanofluids are encouraging and more pronouncing by the application of CCCNT at machining zone. The extent of improvement in reduction of cutting temperatures, main cutting force, tool wear and surface roughness is tracked to be 13%, 37.5%, 44% and 40% respectively by the application of CCCNT compared to dry machining.

Keywords: nanoparticles, vegetable oil, machining, MQL, surface roughness

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Authors: Kiyoumars Roushangar, Shabnam Mirheidarian

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This study proposes metamodel approaches as a new intelligent technique for the explicit formulation of friction factors of water conveyance structures. For this purpose, experimental data of a movable bed flume with dune bed form were used. Analyzing the result clears the high capability of metamodel approaches (MNE= 0.05, R= 0.92) as a powerful tool for optimizing and explicit simulation of Manning's roughness coefficients of water conveyance structures compared to other nonlinear approaches.

Keywords: intelligent techniques, explicit simulation, roughness coefficient, water conveyance structure

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Authors: Salah Ghamari

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In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.

Keywords: artificial neural networks, clustering, self organizing map, wheat variety

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Authors: Ilker Ali Ozkan

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In this study, an artificial neural network model has been developed to estimate chronic kidney failure which is a common disease. The patients’ age, their blood and biochemical values, and 24 input data which consists of various chronic diseases are used for the estimation process. The input data have been subjected to preprocessing because they contain both missing values and nominal values. 147 patient data which was obtained from the preprocessing have been divided into as 70% training and 30% testing data. As a result of the study, artificial neural network model with 25 neurons in the hidden layer has been found as the model with the lowest error value. Chronic kidney failure disease has been able to be estimated accurately at the rate of 99.3% using this artificial neural network model. The developed artificial neural network has been found successful for the estimation of chronic kidney failure disease using clinical data.

Keywords: estimation, artificial neural network, chronic kidney failure disease, disease diagnosis

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Authors: Mohieddine Benghersallah, Lakhdar Boulanouar, Salim Belhadi

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Currently, higher production rate with required quality and low cost is the basic principle in the competitive manufacturing industry. This is mainly achieved by using high cutting speed and feed rates. Elevated temperatures in the cutting zone under these conditions shorten tool life and adversely affect the dimensional accuracy and surface integrity of component. Thus it is necessary to find optimum cutting conditions (cutting speed, feed rate, machining environment, tool material and geometry) that can produce components in accordance with the project and having a relatively high production rate. Response surface methodology is a collection of mathematical and statistical techniques that are useful for modelling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. The work presented in this paper examines the effects of cutting parameters (cutting speed, feed rate and depth of cut) on to the surface roughness through the mathematical model developed by using the data gathered from a series of milling experiments performed.

Keywords: Statistical analysis (RSM), Bearing steel, Coating inserts, Tool life, Surface Roughness, End milling.

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Authors: Balkar Singh, Gurpreet Singh, Vivek Aggarwal, Sehijpal Singh

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The present research focused to improve the machinability of Hastelloy C-276 at different machining speeds such as 31, 55, and 79 m/min. The use of CO2 gas and Minimum quantity lubrication (MQL) was applied as coolant and lubrication purposes to enhance the machinability of the superalloy. The output in the form of surface roughness (S.R) and heat generation was monitored under dry, MQL, and MQL-CO2-cooled conditions. The Design of the Experiment was prepared using MINITAB software utilizing Taguchi L-27 orthogonal arrays followed by ANOVA analysis for finding the impact of input variables on output responses. At different speeds and lubrication conditions, different behavioral patterns for Surface Roughness and the temperature was observed. ANOVA analysis depicted that the cooling environment impacted the S.R. majorly (50%) followed by cutting speed (29.84%), feed rate (5.09%), and least through depth of cut (4.95%). On the other side, the temperature was greatly influenced by cutting speed (69.12%), Cryo-MQL (8.09%), feed rate (7.59%), and depth of cut (6.20%). Experimental results revealed that Cryo-MQL cooling enhanced the Surface roughness by 12% compared to MQL condition.

Keywords: Hastelloy C-276, minimum quantity lubrication, olive oil, cryogenic Cooling (CO2)

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Authors: Fernanda A. Vechietti, Natália O. B. Muniz, Laura C. Treccani, Kurosch. Rezwan, Luis Alberto dos Santos

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CoCr alloys are widely used in prosthetic implants due to their excellent mechanical properties, such as good tensile strength, elastic modulus and wear resistance. Their biocompatibility and lack of corrosion are also prominent features of this alloy. One of the most effective and simple ways to protect metal’s surfaces are treatments, such as electrochemical oxidation by passivation, which is used as a protect release of metallic ions. Another useful treatment is the electropolishing, which is used to reduce the carbide concentration and protrusion at the implanted surface. Electropolishing is a cheap and effective method for treatment of implants, which generally has complex geometries. The purpose of this study is surface modification of the alloy CoCr(ASTM F90-09) by different methods: polishing, electro polishing, passivation and heat treatment for application as biomaterials. The modification of the surface was studied and characterized by SEM, profilometry, wettability and compared to the surface of the samples untreated. The heat treatment and of passivation increased roughness (0.477 µm and 0.825 µm) the samples in relation the sample electropolished and polished(0.131 µm and 0.274 µm) and were observed the improve wettability’s with the increase the roughness.

Keywords: biomaterial, CoCr, surface treatment, heat treatment, roughness

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Authors: A. Manallah, C. Meier

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Confocal spectral interferometry (CSI) is an innovative optical method for determining microtopography of surfaces and thickness of transparent layers, based on the combination of two optical principles: confocal imaging, and spectral interferometry. Confocal optical system images at each instant a single point of the sample. The whole surface is reconstructed by plan scanning. The interference signal generated by mixing two white-light beams is analyzed using a spectrometer. In this work, five ‘rugotests’ of known standard roughnesses are investigated. The topography is then measured and illustrated, and the equivalent roughness is determined and compared with the standard values.

Keywords: confocal spectral interferometry, nondestructive testing, optical metrology, surface topography, roughness

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Authors: Haytam Kasem

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The problem of quick and easy reversible attachment has become of great importance in different fields of technology. For the reason, during the last decade, a new emerging field of adhesion science has been developed. Essentially inspired by some animals and insects, which during their natural evolution have developed fantastic biological attachment systems allowing them to adhere and run on walls and ceilings of uneven surfaces. Potential applications of engineering bio-inspired solutions include climbing robots, handling systems for wafers in nanofabrication facilities, and mobile sensor platforms, to name a few. However, despite the efforts provided to apply bio-inspired patterned adhesive-surfaces to the biomedical field, they are still in the early stages compared with their conventional uses in other industries mentioned above. In fact, there are some critical issues that still need to be addressed for the wide usage of the bio-inspired patterned surfaces as advanced biomedical platforms. For example, surface durability and long-term stability of surfaces with high adhesive capacity should be improved, but also the friction and adhesion capacities of these bio-inspired microstructures when contacting rough surfaces. One of the well-known prototypes for bio-inspired attachment systems is biomimetic wall-shaped hierarchical microstructure for gecko-like attachments. Although physical background of these attachment systems is widely understood, the influence of counter-face roughness and its relationship with the friction force generated when sliding against wall-shaped hierarchical microstructure have yet to be fully analyzed and understood. To elucidate the effect of the counter-face roughness on the friction of biomimetic wall-shaped hierarchical microstructure we have replicated the isotropic topography of 12 different surfaces using replicas made of the same epoxy material. The different counter-faces were fully characterized under 3D optical profilometer to measure roughness parameters. The friction forces generated by spatula-shaped microstructure in contact with the tested counter-faces were measured on a home-made tribometer and compared with the friction forces generated by the spatulae in contact with a smooth reference. It was found that classical roughness parameters, such as average roughness Ra and others, could not be utilized to explain topography-related variation in friction force. This has led us to the development of an integrated roughness parameter obtained by combining different parameters which are the mean asperity radius of curvature (R), the asperity density (η), the deviation of asperities high (σ) and the mean asperities angle (SDQ). This new integrated parameter is capable of explaining the variation of results of friction measurements. Based on the experimental results, we developed and validated an analytical model to predict the variation of the friction force as a function of roughness parameters of the counter-face and the applied normal load, as well.

Keywords: friction, bio-mimetic micro-structure, counter-face roughness, analytical model

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Authors: Abdulmajeed Dabwan, Saqib Anwar, Ali Al-Samhan

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Electron Beam Melting (EBM) is a metal powder bed-based Additive Manufacturing (AM) technology, which uses computer-controlled electron beams to create fully dense three-dimensional near-net-shaped parts from metal powder. It gives the ability to produce any complex parts directly from a computer-aided design (CAD) model without tools and dies, and with a variety of materials. However, the quality of the surface finish in EBM process has limitations to meeting the performance requirements of additively manufactured components. The aim of this study is to investigate the cutting forces induced during milling Ti6Al4V produced by EBM as well as the surface quality of the milled surfaces. The effects of cutting speed and radial depth of cut on the cutting forces, surface roughness, and surface morphology were investigated. The results indicated that the cutting speed was found to be proportional to the resultant cutting force at any cutting conditions while the surface roughness improved significantly with the increase in cutting speed and radial depth of cut.

Keywords: electron beam melting, additive manufacturing, Ti6Al4V, surface morphology

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Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

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The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: surface roughness, Taguchi parameter design, CNC turning, CNC milling

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Authors: Amad Nasseef, Layan Zugail, Joud Musalli, Layan Shaikan

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Technology has become an essential part of our lives. We have also witnessed the significant emergence of artificial intelligence in so many areas. Throughout this research paper, the following will be discussed: an introduction on AI and Socratic application, we also did an overview on the application’s background and other similar applications, as for the methodology, we conducted a survey to collect results on users experience in using the Socratic application. The results of the survey strongly supported the usefulness and interest of users in the Socratic application. Finally, we concluded that Socratic is a meaningful tool for learning purposes due to it being supported by artificial intelligence, which made the application easy to use and familiar to users to deal with through a click of a button.

Keywords: Socratic, artificial intelligence, application, features

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Authors: Kylie Leonard

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Investment in artificial intelligence (AI) can be an attractive opportunity for business leaders as there are many easy-to-see benefits. These benefits include task completion rates, overall cost, and better forecasting. Business leaders are often unaware of the challenges that can accompany AI, such as data center costs, access to data, employee acceptance, and privacy concerns. In addition to the benefits and challenges of AI, it is important to practice AI ethics to ensure the safe creation of AI. AI ethics include aspects of algorithm bias, limits in transparency, and surveillance. To be a good business leader, it is critical to address all the considerations involving the challenges of AI and AI ethics.

Keywords: artificial intelligence, artificial intelligence ethics, business leaders, business concerns

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Authors: Haruka Kaji, Jae-Ho Kim, Yonezawa Susumu

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The surface of polycarbonate (PC) was modified with fluorine gas at 25℃ and 10-380 Torr for one h. The surface roughness of the fluorinated PC samples was approximately five times larger than that (1.2 nm) of the untreated thing. The results of Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy showed that the bonds (e.g., -C=O and C-Hx) derived from raw PC decreased and were converted into fluorinated bonds (e.g., -CFx) after surface fluorination. These fluorinated bonds showed higher electronegativity according to the zeta potential results. Fluorinated PC could be strained with the methylene blue basic dye because of the increased surface roughness and the negatively charged surface.

Keywords: dyeable layer, polycarbonate, surface fluorination, zeta potential

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Authors: Priyanka Bhatnagar, Malkeshkumar Patel, Joondong Kim, Joonpyo Hong

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Artificial skin and sensory memory platforms are produced using a flexible, transparent photovoltaic (TPV) device. The TPV device is composed of a metal oxide heterojunction (nZnO/p-NiO) and transmits visible light (> 50%) while producing substantial electric power (0.5 V and 200 μA cm-2 ). This TPV device is a transparent energy interface that can be used to detect signals and propagate information without an external energy supply. The TPV artificial skin offers a temperature detection range (0 C75 C) that is wider than that of natural skin (5 C48 °C) due to the temperature-sensitive pyrocurrent from the ZnO layer. Moreover, the TPV thermoreceptor offers sensory memory of extreme thermal stimuli. Much like natural skin, artificial skin uses the nociceptor mechanism to protect tissue from harmful damage via signal amplification (hyperalgesia) and early adaption (allodynia). This demonstrates the many features of TPV artificial skin, which can sense and transmit signals and memorize information under self-operation mode. This transparent photovoltaic skin can provide sustainable energy for use in human electronics.

Keywords: transparent, photovoltaics, thermal memory, artificial skin, thermoreceptor

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Authors: Narender Singh Thakur, Sunil Chamoli

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The use of roughness geometry in the rectangular channel duct is an effective technique to enhance the rate of heat transfer to the working fluid. The present research concentrates on the performance comparison of a rectangular channel with different roughness geometry of the test plate. The performance enhancement is compared by considering the statistical correlations developed by the various investigators for Nusselt number and friction factor. Among all the investigated geometries multiple v-shaped rib roughened rectangular channel found thermo hydraulically better than other investigated geometries under similar current and operating conditions.

Keywords: nusselt number, friction factor, thermohydraulic, performance parameter

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Authors: Chukwuma Mgboji

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Since the advent of Artificial Intelligence, robots have become a major stay in developing societies. Robots are deployed in Education, Health, Food and in other spheres of life. Nigeria a country in West Africa has a very low profile in the advancement of Artificial Intelligence especially in the grass roots. The benefits of Artificial intelligence are not fully maximised and harnessed. Advances in artificial intelligence are perceived as impossible or observed as irrelevant. This study seeks to ascertain the needed skills for the development of artificialintelligence amongst secondary schools in Nigeria. The study focused on South East Nigeria with Five states namely Imo, Abia, Ebonyi, Anambra and Enugu. The sample size is 1000 students drawn from Five Government owned Universities offering Computer Science, Computer Education, Electronics Engineering across the Five South East states. Survey method was used to solicit responses from respondents. The findings from the study identified mathematical skills, analytical skills, problem solving skills, computing skills, programming skills, algorithm skills amongst others. The result of this study to the best of the author’s knowledge will be highly beneficial to all stakeholders involved in the advancements and development of artificial intelligence.

Keywords: artificial intelligence, secondary school, robotics, skills

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Authors: Yiqiao Yin

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Many scholars and educators have dedicated their lives in K12 education system and there has been an exploding amount of attention to implement technical foundations for Artificial Intelligence Education for high school and precollege level students. This paper focuses on the development and use of resources to support K-12 education in Artificial Intelligence (AI). The author and his team have more than three years of experience coaching students from pre-college level age from 15 to 18. This paper is a culmination of the experience and proposed online tools, software demos, and structured activities for high school students. The paper also addresses a portfolio of AI concepts as well as the expected learning outcomes. All resources are provided with online videos and Github repositories for immediate use.

Keywords: K12 education, AI4ALL, pre-college education, pre-college AI

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Authors: Artur Matuck, Guilherme F. Nobre

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Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art

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Authors: Lipeng Zhang, Limei Li, Yanming Pearl Zhang

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This paper takes a philosophical view as axiom, and reveals the relationship between information theory and Natural Intelligence and Artificial Intelligence under real world conditions. This paper also derives the relationship between natural intelligence and nature. According to communication principle of information theory, Natural Intelligence can be divided into real part and virtual part. Based on information theory principle that Information does not increase, the restriction mechanism of Natural Intelligence creativity is conducted. The restriction mechanism of creativity reveals the limit of natural intelligence and artificial intelligence. The paper provides a new angle to observe natural intelligence and artificial intelligence.

Keywords: natural intelligence, artificial intelligence, creativity, information theory, restriction of creativity

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Authors: Mehdi Fuladipanah

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Sensitivity analysis as a technique is applied to determine influential input factors on model output. Variance-based sensitivity analysis method has more application compared to other methods because of including linear and non-linear models. In this paper, van Rijn’s movable bed roughness formula was selected to evaluate because of its reasonable results in sandy rivers. This equation contains four variables as: flow depth, sediment size,bBed form height and bed form length. These variable’s importance was determined using the first order of Fourier Amplitude Sensitivity Test. Sensitivity index was applied to evaluate importance of factors. The first order FAST based sensitivity indices test, explain 90% of the total variance that is indicating acceptance criteria of FAST application. More value of this index is indicating more important variable. Results show that bed form height, bed form length, sediment size and flow depth are more influential factors with sensitivity index: 32%, 24%, 19% and 15% respectively.

Keywords: sdensitivity analysis, variance, movable bed roughness formula, Sandy River

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Authors: S. Benzitouni, M. Zaabat, A. Mahdjoub, A. Benaboud, T.Saidani ‎

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To improve the physical properties of ZnO nanostructures textured (103) by sol-gel ‎dip coating method, Al and In are used as dopant with different weight ratios (5%, 10%). ‎The comparative study between Al doped ZnO thin films (AZO) and In doped ZnO (IZO) ‎are made by different analysis technic. XRD showed that the films are Pollycristallins with ‎hexagonal wûrtzite structure and preferred orientation (002) and (103). UV-Vis ‎spectroscopy showed that all films have a high transmission (> 85%); the interference ‎fringes are only observed for IZO. The optical gap is reduced due to the introduction of In ‎‎(minimum value is 3.12 eV), but increased in the presence of Al (maximum value is 3.34 ‎eV). The thickness of the layers was obtained by modeling (using Forouhi Bloomer ‎method). AFM used to observe the surface texture of the films and determined grain size ‎and surface roughness (RMS) which varies in a small range [3.14 to 1.25] nm‎.

Keywords: ZnO, optical gap, roughness (RMS), nanostructures‎

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Authors: Irene Buj-Corral, Ali Bagheri, Alejandro Dominguez-Fernandez

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In recent years, use of ceramic prostheses as an implant in some parts of body has become common. In the present study, research has focused on replacement of the acetabulum bone, which is a part of the pelvis bone. Metallic prostheses have shown some problems such as release of metal ions into patient's blood. In addition, fracture of liners and squeezing between surface of femoral head and inner surface of acetabulum have been reported. Ceramic prostheses have the advantage of low debris and high strength, although they are more difficult to be manufactured than metallic ones. Specifically, new designs try to attempt an acetabulum in which the outer surface will be porous for proliferation of cells and fixation of the prostheses by means of osteointegration, while inner surface must be smooth enough to assure that the movement between femoral head and inner surface will be carried out with on feasibility. In the present study, 3D printing technologies are used for manufacturing ceramic prostheses. In Fused Deposition Modelling (FDM) process, 3D printed plastic prostheses are obtained by means of melting of a plastic filament and subsequent deposition on a glass surface. A similar process is applied to ceramics in which ceramic powders need to be mixed with a liquid polymer before depositing them. After 3D printing, parts are subjected to a sintering process in an oven so that they can achieve final strength. In the present paper, influence of printing parameters on surface roughness 3D printed ceramic parts are presented. Three parameter full factorial design of experiments was used. Selected variables were layer height, infill and nozzle diameter. Responses were average roughness Ra and mean roughness depth Rz. Regression analysis was applied to responses in order to obtain mathematical models for responses. Results showed that surface roughness depends mainly on layer height and nozzle diameter employed, while infill was found not to be significant. In order to get low surface roughness, low layer height and low infill should be selected. As a conclusion, layer height and infill are important parameters for obtaining good surface finish in ceramic 3D printed prostheses. However, use of too low infill could lead to prostheses with low mechanical strength. Such prostheses could not be able to bear the static and dynamic charges to which they are subjected once they are implanted in the body. This issue will be addressed in further research.

Keywords: ceramic, hip prostheses, surface roughness, 3D printing

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Authors: Maryam Firouzmandi, Moosa Miri

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Aim and background: esthetic and structural reconstruction of anterior teeth may require the application of different restoration material. In this regard combination of direct composite veneer and ceramic crown is a common treatment option. Despite the initial matching, their long term harmony in term of optical and surface characteristics is a matter of concern. The purpose of this study is to evaluate and compare optical and surface characteristic of direct composite polished and glazed ceramic materials after exposure to tooth brush abrasion and staining solution. Materials and Methods: ten 2 mm thick disk shape specimens were prepared from IPS empress direct composite and twenty specimens from IPS e.max CAD blocks. Composite specimens and ten ceramic specimens were polished by using D&Z composite and ceramic polishing kit. The other ten specimens of ceramic were glazed with glazing liquid. Baseline measurement of roughness, CIElab coordinate, and luminance were recorded. Then the specimens underwent thermocycling, tooth brushing, and coffee staining. Afterword, the final measurements were recorded. Color coordinate were used to calculate ΔE76, ΔE00, translucency parameter, and contrast ratio. Data were analyzed by One-way ANOVA and post hoc LSD test. Results: baseline and final roughness of the study group were not different. At baseline, the order of roughness for the study group were as follows: composite < glazed ceramic < polished ceramic, but after aging, no difference. Between ceramic groups was not detected. The comparison of baseline and final luminance was similar to roughness but in reverse order. Unlike differential roughness which was comparable between the groups, changes in luminance of the glazed ceramic group was higher than other groups. ΔE76 and ΔE00 in the composite group were 18.35 and 12.84, in the glazed ceramic group were 1.3 and 0.79, and in polished ceramic were 1.26 and 0.85. These values for the composite group were significantly different from ceramic groups. Translucency of composite at baseline was significantly higher than final, but there was no significant difference between these values in ceramic groups. Composite was more translucency than ceramic at baseline and final measurement. Conclusion: Glazed ceramic surface was smoother than polished ceramic. Aging did not change the roughness. Optical properties (color and translucency) of the composite were influenced by aging. Luminance of composite, glazed ceramic, and polished ceramic decreased after aging, but the reduction in glazed ceramic was more pronounced.

Keywords: ceramic, tooth-brush abrasion, staining solution, composite resin

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

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Authors: Hafiz Arbab Sakandar, Sabahat Yaqub, Ayesha Sameen, Muhammad Imran, Sarfraz Ahmad

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Yoghurt is one of the famous nutritious fermented milk products which have myriad of positive health effects on human beings and curable against different intestinal diseases. This research was conducted to observe effects of different artificial sweeteners on the quality parameters of yoghurt with relation to storage. Some people are allergic to natural sweeteners so artificial sweetener will be helpful for them. Physical-chemical, Microbiology and various sensory evaluation tests were carried out with the interval of 7, 14, 21, and 28 days. It was outcome from this study that addition of artificial sweeteners in yoghurt has shown much harmful effects on the yoghurt microorganisms and other physicochemical parameters from quality point of view. Best results for acceptance were obtained when aspartame was added in yoghurt at level of 0.022 percent. In addition, growth of beneficial microorganisms in yoghurt was also improved as well as other sensory attributes were enhanced by the addition of aspartame.

Keywords: yoghurt, artificial sweetener, storage, quality parameters

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Siti Aslamyah, Yushinta Fujaya, Okto Rimaldi

Abstract:

One of the problems faced in the crab hatchery operations is the reliance on the use of natural feed. This study aims to analyze the response of larval development and determine the initial stages crab larvae begin to fully able to accept artificial feeding predigest with the help of probiotic Bacillus sp. The experiment was conducted in June 2014 through July 2014 at the location of the scale backyard hatcheries, Bojo village Mallusettasi sub-district, district Barru. This study was conducted in two stages larval rearing. The first stage is designed in a completely randomized design with 5 treatments and each with 3 repetitions, ie, without the use of artificial feeding; predigest feed given from zoea 1 - megalopa; predigest feed given since zoea 2 - megalopa; predigest feed given from zoea 3 - megalopa; and feed predigest given since zoea 4 - megalopa. The second stage of the two treatments, i.e. comparing artificial feeding without and with predigest. The results showed that the artificial feeding predigest able to replace the use of natural feed started zoea 3 generated based on the survival rate. Artificial feeding predigest provide a higher survival rate (16%) compared to artificial diets without predigest only 10.8%. However, feed predigest not give a different effect on the rate of development of stadia. Cell activity in larvae that received artificial feed predigest higher with RNA-DNA ratio of 8.88 compared with no predigest only 5:36. This research is very valuable information for crab hatchery hatchery scale households have limitations in preparing natural food.

Keywords: artificial feeding, development of stadia, larvae Portunus pelagicus, predigest

Procedia PDF Downloads 495

Authors: Nouf Nasser, Nada Alotaibi, Jazzal Kandiel

Abstract:

This research study is about the use of artificial intelligence in PhotoRoom. When an individual selects a photo, PhotoRoom automagically removes or separates the background from other parts of the photo through the use of artificial intelligence. This will allow an individual to select their desired background and edit it as they wish. The methodology used was an observation, where various reviews and parts of the app were observed. The review section's findings showed that many people actually like the app, and some even rated it five stars. The conclusion was that PhotoRoom is one of the best photo editing apps due to its speed and accuracy in removing backgrounds.

Keywords: removing background, app, artificial intelligence, machine learning

Procedia PDF Downloads 165