Search results for: MLP back propagation

Authors: Wael Elkholy, Ashraf Sakr, Mahmoud Qandeel, Adam Elkholy

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Lumbar disc herniation is a common pathology that may cause significant low back pain and radicular pain that could profoundly impair daily life activities of individuals. Patients who undergo surgical treatment for lumbar disc herniation usually present with radiculopathy along with low back pain (LBP) instead of radiculopathy alone. When discectomy is performed, improvement in leg radiating pain is observed due to spinal nerve irritation. However, long-term LBP due to degenerative changes in the disc may occur postoperatively. In addition, limited research has been reported on the short-term (within 1 year) improvement in LBP after discectomy. In this study we would like to share our minimally invasive open technique for lumbar discectomy with annuloplasty and nuceloplasty as a technique for effective reduction of both axial and radicular pain.

Keywords: nucleoplasty, sinuvertebral nerve cauterization, annuloplasty, discogenic low back pain, axial pain, radicular pain, minimally invasive lumbar discectomy

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Authors: Jiujie Cai, Fengxia LI, Haibo Wang

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After years of research, offshore oil and gas development now are shifted to unconventional reservoirs, where multi-stage hydraulic fracturing technology has been widely used. However, the simulation of complex hydraulic fractures in tight reservoirs is faced with geological and engineering difficulties, such as large burial depths, sand-shale interbeds, and complex stress barriers. The objective of this work is to simulate the hydraulic fracture propagation in the tight sandstone matrix of the marine-continental transitional reservoirs, where the Shanxi Formation in Tianhuan syncline of the Dongsheng gas field was used as the research target. The characteristic parameters of the vertical rock samples with rich beddings were clarified through rock mechanics experiments. The influence of rock mechanical parameters, vertical stress difference of pay-zone and bedding layer, and fracturing parameters (such as injection rates, fracturing fluid viscosity, and number of perforation clusters within single stage) on fracture initiation and propagation were investigated. In this paper, a 3-D fracture propagation model was built to investigate the complex fracture propagation morphology by boundary element method, considering the strength of bonding surface between layers, vertical stress difference and fracturing parameters (such as injection rates, fluid volume and viscosity). The research results indicate that on the condition of vertical stress difference (3 MPa), the fracture height can break through and enter the upper interlayer when the thickness of the overlying bedding layer is 6-9 m, considering effect of the weak bonding surface between layers. The fracture propagates within the pay zone when overlying interlayer is greater than 13 m. Difference in fluid volume distribution between clusters could be more than 20% when the stress difference of each cluster in the segment exceeds 2MPa. Fracture cluster in high stress zones cannot initiate when the stress difference in the segment exceeds 5MPa. The simulation results of fracture height are much higher if the effect of weak bonding surface between layers is not involved. By increasing the injection rates, increasing fracturing fluid viscosity, and reducing the number of clusters within single stage can promote the fracture height propagation through layers. Optimizing the perforation position and reducing the number of perforations can promote the uniform expansion of fractures. Typical curves of fracture height estimation were established for the tight sandstone of the Lower Permian Shanxi Formation. The model results have good consistency with micro-seismic monitoring results of hydraulic fracturing in Well 1HF.

Keywords: fracture propagation, boundary element method, fracture height, offshore oil and gas, marine-continental transitional reservoirs, rock mechanics experiment

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: T. Yu, L. Audibert, J. F. Chaix, D. Komatitsch, V. Garnier, J. M. Henault

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Linear Ultrasonic Techniques play a major role in Non-Destructive Evaluation (NDE) for civil engineering structures in concrete since they can meet operational requirements. Interpretation of ultrasonic measurements could be improved by a better understanding of ultrasonic wave propagation in a multiple scattering medium. This work aims to develop a 2D numerical model of ultrasonic wave propagation in a heterogeneous medium, like concrete, integrating the multiple scattering phenomena in SPECFEM software. The coherent field of multiple scattering is obtained by averaging numerical wave fields, and it is used to determine the effective phase velocity and attenuation corresponding to an equivalent homogeneous medium. First, this model is applied to one scattering element (a cylinder) in a homogenous medium in a linear-elastic system, and its validation is completed thanks to the comparison with analytical solution. Then, some cases of multiple scattering by a set of randomly located cylinders or polygons are simulated to perform parametric studies on the influence of frequency and scatterer size, concentration, and shape. Also, the effective properties are compared with the predictions of Waterman-Truell model to verify its validity. Finally, the mortar viscoelastic behavior is introduced in the simulation in order to considerer the dispersion and the attenuation due to porosity included in the cement paste. In the future, different steps will be developed: The comparisons with experimental results, the interpretation of NDE measurements, and the optimization of NDE parameters before an auscultation.

Keywords: attenuation, multiple-scattering medium, numerical modeling, phase velocity, ultrasonic measurements

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Authors: Shahriar Shahbazpanahi, Alaleh Kamgar

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So far, the conventional experimental and theoretical analysis in fracture mechanics have been applied to study concrete flexural- cracked beams, which are strengthened using fiber reinforced polymer (FRP) composite sheets. However, there is still little knowledge about the shear capacity of a side face FRP- strengthened shear-cracked beam. A numerical analysis is herein presented to model the fracture mechanics of a four-point RC beam, with two inclined initial notch on the supports, which is strengthened with side face FRP sheets. In the present study, the shear crack is forced to conduct by using an initial notch in supports. The ABAQUS software is used to model crack propagation by conventional cohesive elements. It is observed that the FRP sheets play important roles in preventing the propagation of shear cracks.

Keywords: crack, FRP, shear, strengthening

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Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

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The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

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Authors: Amit Verma, Simranjeet Kaur, Sandeep Kaur

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Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.

Keywords: test case prioritization, classification, artificial neural networks, TF-IDF

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Authors: Lican Wang, Rongqian Chen, Yancheng You, Ruofan Qiu

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In the applications of jet engine, open-jet wind tunnel and airframe, there wildly exists a shear layer formed by the velocity and temperature gradients between jet flow and surrounded medium. The presence of shear layer will refract and reflect the sound path that consequently influences the measurement results in far-field. To investigate and evaluate the shear layer effect, a gradient term suppression and filtering method is adopted to simulate sound propagation through a steady sheared flow in three dimensions. Two typical configurations are considered: one is an incompressible and cold jet flow in wind tunnel and the other is a compressible and hot jet flow in turbofan engine. A numerically linear microphone array is used to localize the position of given sound source. The localization error is presented and linearly fitted.

Keywords: aeroacoustic, linearized Euler equation, acoustic propagation, source localization

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Authors: Adesola Odole, Nse Odunaiya, Samuel Adewale

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Chronic Mechanical Low Back Pain (CMLBP) is prevalent in the aging population; some studies have documented the association among pain intensity, functional disability and physical activity in the general population but very few studies in the elderly. This study was designed to investigate the association among pain intensity, functional disability and physical activity of elderly individuals with CMLBP in the University College Hospital (UCH), Ibadan, Nigeria and also to determine the difference in physical activity, pain intensity and functional disability between males and females. A total of 96 participants diagnosed with CMLBP participated in this cross-sectional survey. They were conveniently sampled from selected units in the UCH, Ibadan, Nigeria. Data on sex, marital status, occupation and duration of onset of pain of participants were obtained from the participants. The Physical Activity Scale for the Elderly, Visual Analogue Scale and Oswestry Disability Questionnaire were used to measure the physical activity, pain intensity and functional disability of the participants respectively. Data was analysed using Spearman correlation, independent t-test; and α was set at 0.05. Participants (25 males, 71 females) were aged 69.64±7.43 years. The majority (76.0%) of the participants were married, and over half (55.2%) were retirees. Participants’ mean pain intensity score was 5.21±2.03 and mean duration of onset of low back pain was 63.63 ± 90.01 months. The majority (67.6%) of the participants reported severe to crippled functional disability. Their mean functional disability was 46.91 ± 13.99. Participants’ mean physical activity score was 97.47 ± 82.55. There was significant association between physical activity and pain intensity (r = -0.21, p = 0.04). There was significant association between physical activity and functional disability (r = -0.47, p = 0.00). Male (87.26 ± 79.94) and female (101.07 ± 83.71) participants did not differ significantly in physical activity (t = 0.00, p = 0.48). In addition, male (5.48 ± 2.06) and female (5.11 ± 2.02) participants’ pain intensity were comparable (t = 0.26, p = 0.44). There was also no significant difference in functional disability (t = 0.05, p = 0.07) between male (42.56 ±13.85) and female (48.45 ± 13.81) participants. It can be concluded from this study that majority of the elderly individuals with chronic mechanical low back pain had a severe to crippled functional disability. Those who reported increased physical activity had reduced pain intensity and functional disability. Male and female elderly individuals with chronic mechanical low back pain are comparable in their pain intensity, functional disability, and physical activity. Elderly individuals with CMLBP should be educated on the importance of participating in physical activity which could reduce their pain symptoms and improve functional disability.

Keywords: elderly, functional disability, mechanical low back pain, pain intensity, physical activity

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Authors: K. B. Ghazaryan, R. A. Ghazaryan

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Based on the constitutive model and anti-plane equations of anisotropic elastic body of monoclinic symmetry we consider the problem of shear wave propagation in multi-layered disordered composite structure with point defect. Using transfer matrix method the analytic expression is obtained providing solutions of shear Floquet wave propagation in periodic disordered anisotropic structure. The usefulness of the obtained analytical expression was discussed also in reflection and refraction problems from multi-layered reflector as well as in vibration problem of multi-layered waveguides. Numerical results are presented highlighting the effects arising in disordered periodic structure due to defects of multi-layered structure.

Keywords: shear elastic waves, monoclinic anisotropic media, periodic structure, disordered multilayer laminae, multi-layered waveguide

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Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

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Authors: Hany Elsaid Fawaz Abdallah

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This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

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Authors: Barham J. Nareeman, Ilham I. Mohammed

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Excavations in urban developed area are generally supported by deep excavation walls such as; diaphragm wall, bored piles, soldier piles and sheet piles. In some cases, these walls may be braced by internal braces or tie back anchors. Tie back anchors are by far the predominant method for wall support, the large working space inside the excavation provided by a tieback anchor system has a significant construction advantage. This paper aims to analyze a deep excavation bracing system of contiguous pile wall braced by pre-stressed tie back anchors, which is a part of a huge residential building project, located in Turkey/Gaziantep province. The contiguous pile wall will be constructed with a length of 270 m that consists of 285 piles, each having a diameter of 80 cm, and a center to center spacing of 95 cm. The deformation analysis was carried out by a finite element analysis tool using PLAXIS. In the analysis, beam element method together with an elastic perfect plastic soil model and Soil Hardening Model was used to design the contiguous pile wall, the tieback anchor system, and the soil. The two soil clusters which are limestone and a filled soil were modelled with both Hardening soil and Mohr Coulomb models. According to the basic design, both soil clusters are modelled as drained condition. The simulation results show that the maximum horizontal movement of the walls and the maximum settlement of the ground are convenient with 300 individual case histories which are ranging between 1.2mm and 2.3mm for walls, and 15mm and 6.5mm for the settlements. It was concluded that tied-back contiguous pile wall can be satisfactorily modelled using Hardening soil model.

Keywords: deep excavation, finite element, pre-stressed tie back anchors, contiguous pile wall, PLAXIS, horizontal deflection, ground settlement

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Authors: P. Singh, R. M. Banik

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Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.

Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network

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Authors: Júlia Cristina Bonaldo, Christophe L. Martin, Martiniano Piccico, Keith Beale, Roop Kishore, Severine Romero-Baivier

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Refractory composite materials employed in steel casting applications are prone to cracking and material damage because of the very high operating temperature (thermal shock) and mismatched properties of the constituent phases. The fracture behavior of a model MgO-C composite refractory is investigated to quantify and characterize its thermal shock resistance, employing a cold crushing test and Brazilian test with fractographic analysis. The discrete element method (DEM) is used to generate numerical refractory composites. The composite in DEM is represented by an assembly of bonded particle clusters forming perfectly spherical aggregates and single spherical particles. For the stresses to converge with a low standard deviation and a minimum number of particles to allow reasonable CPU calculation time, representative volume element (RVE) numerical packings are created with various numbers of particles. Key microscopic properties are calibrated sequentially by comparing stress-strain curves from crushing experimental data. Comparing simulations with experiments also allows for the evaluation of crack propagation, fracture energy, and strength. The crack propagation during Brazilian experimental tests is monitored with digital image correlation (DIC). Simulations and experiments reveal three distinct types of fracture. The crack may spread throughout the aggregate, at the aggregate-matrix interface, or throughout the matrix.

Keywords: refractory composite, fracture mechanics, crack propagation, DEM

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Authors: Hafdaoui Hichem, Mehadjebia Cherifa, Benatia Djamel

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In this paper, we propose a new method for Bulk detection of an acoustic microwave signal during the propagation of acoustic microwaves in a piezoelectric substrate (Lithium Niobate LiNbO3). We have used the classification by probabilistic neural network (PNN) as a means of numerical analysis in which we classify all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity in order to build a model from which we note the Bulk waves easily. These singularities inform us of presence of Bulk waves in piezoelectric materials. By which we obtain accurate values for each of the coefficient attenuation and acoustic velocity for Bulk waves. This study will be very interesting in modeling and realization of acoustic microwaves devices (ultrasound) based on the propagation of acoustic microwaves.

Keywords: piezoelectric material, probabilistic neural network (PNN), classification, acoustic microwaves, bulk waves, the attenuation coefficient

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Authors: Seyedeh Nahal Sadiri, Ardalan Shariat

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Developing flexibility, by using pilates, would be useful for karate players by reducing the stiffness of muscles and tendons. This study aimed to determine the effects of 12-week pilates training on flexibility, and level of perceived exertion of back muscles among karate players. In this experimental study, 29 male karate players (age: 16-18 years) were randomized to pilates (n=15), and control (n=14) groups and the assessments were done in baseline and after 12-week intervention. Both groups completed 12-week of intervention (2 hours of training, 3 times weekly). The experimental group performed 30 minutes pilates within their warm-up and preparation phase, where the control group only attended their usual karate training. Digital backward flexmeter was used to evaluate the trunk extensors flexibility, and digital forward flexmeter was used to measure the trunk flexors flexibility. Borg CR-10 Scale was also used to determine the perceived exertion of back muscles. Independent samples t-test and paired sample t-test were used to analyze the data. There was a significant difference between the mean score of experimental and control groups in the level of backward trunk flexibility (P < 0.05), forward trunk flexibility (P < 0.05) after 12-week intervention. The results of Borg CR-10 scale showed a significant improvement in pilates group (P < 0.05). Karate instructors, coaches, and athletes can integrate pilates exercises with karate training in order to improve the flexibility, and level of perceived exertion of back muscles.

Keywords: pilates training, karate players, flexibility, Borg CR-10

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Authors: Jayson Cheyne, David Butler, Iain Bomphray

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In recent years, lithium-ion batteries have been used increasingly for electric vehicles and large energy storage systems due to their high-power density and long lifespan. Despite this, thermal runaway remains a significant safety problem because of its uncontrollable and irreversible nature - which can lead to fires and explosions. In large-scale lithium-ion packs and modules, thermal runaway propagation between cells can escalate fire hazards and cause significant damage. Thus, safety measures are required to mitigate thermal runaway propagation. The current research explores composite phase change materials (PCM) containing expanded graphite (EG) for thermal runaway mitigation. PCMs are an area of significant interest for battery thermal management due to their ability to absorb substantial quantities of heat during phase change. Moreover, the introduction of EG can support heat transfer from the cells to the PCM (owing to its high thermal conductivity) and provide shape stability to the PCM during phase change. During the research, a thermal model was established for an array of 16 cylindrical cells to simulate heat dissipation with and without the composite PCM. Two conditions were modeled, including the behavior during charge/discharge cycles (i.e., throughout regular operation) and thermal runaway. Furthermore, parameters including cell spacing, composite PCM thickness, and EG weight percentage (WT%) were varied to establish the optimal material parameters for enabling thermal runaway mitigation and effective thermal management. Although numerical modeling is still ongoing, initial findings suggest that a 3mm PCM containing 15WT% EG can effectively suppress thermal runaway propagation while maintaining shape stability. The next step in the research is to validate the model through controlled experimental tests. Additionally, with the perceived fire safety concerns relating to PCM materials, fire safety tests, including UL-94 and Limiting Oxygen Index (LOI), shall be conducted to explore the flammability risk.

Keywords: battery safety, electric vehicles, phase change materials, thermal management, thermal runaway

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Authors: Jamal Takhchi

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The understanding of vibration propagation in complex structures such as automotive body in white remains a challenging issue in car design regarding NVH performances. The current analysis is limited to the low frequency range where modal concepts are dominant. Higher frequencies, between 200 and 1000 Hz, will become critical With the rise of electrification. EVs annoying sounds are mostly whines created by either Gears or e-motors between 300 Hz and 2 kHz. Structural intensity analysis was Experienced a few years ago on finite element models. The application was promising but limited by the fact that the propagating 3D intensity vector field is masked by a rotational Intensity field. This rotational field should be filtered using a differential operator. The expression of this operator in the framework of finite element modeling is not yet known. The aim of the proposed work is to implement this operator in the current dynamic solver (NASTRAN) of Stellantis and develop the Expected methodology for the mid-frequency structural analysis of electrified vehicles.

Keywords: structural intensity, NVH, body in white, irrotatational intensity

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Authors: Oanthata Jester Sealetsa, Richie Moalosi

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Musculoskeletal Disorders (MSDs) are reported to be amongst the leading contributing factors of low productivity in many industries across the world, and the most affected being New Emerging Economies (NEC) such as Botswana. This is due to lack of expertise and resources to deal with existing ergonomics challenges. This study was aimed to evaluate occupational postures and the prevalence of musculoskeletal disorders among diamond polishers in a diamond company in Botswana. A case study was conducted with about 106 diamond polishers in Gaborone, Botswana. A case study was chosen because it can investigate and explore an issue thoroughly and deeply, and record behaviour over time so changes in behaviour can be identified. The Corlett and Bishop Body Map was used to determine frequency of MSDs symptoms in different body parts of the workers. This was then followed by the use of the Rapid Entire Body Assessment (REBA) to evaluate the occupational postural risks of MSDs. Descriptive statistics, chi square, and logistic regression were used for data analysis. The results of the study reveal that workers experienced pain in the upper back, lower back, shoulders, neck, and wrists with the most pain reported in the upper back (44.6%) and lower back (44.2%). However, the mean REBA score of 6.07 suggests that sawing, bruiting and polishing were the most dangerous processes in diamond polishing. The study recommends that a redesign of the diamond polishing workstations is necessary to accommodate the anthropometry characteristic of Batswana (people from Botswana) to prevent the development of MSDs.

Keywords: assessment, Botswana, diamond polishing, ergonomics, musculoskeletal disorders, occupational postural risks

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Authors: A. Azari, S. S. K. Seyyedi

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One of the unaddressed and open challenges in the nano-networking is the characteristics of noise. The previous analysis, however, has concentrated on end-to-end communication model with no separate modelings for propagation channel and noise. By considering a separate signal propagation and noise model, the design and implementation of an optimum receiver will be much easier. In this paper, we justify consideration of a separate additive Gaussian noise model of a nano-communication system based on the molecular communication channel for which are applicable for MSK and MOSK modulation schemes. The presented noise analysis is based on the Brownian motion process, and advection molecular statistics, where the received random signal has a probability density function whose mean is equal to the mean number of the received molecules. Finally, the justification of received signal magnitude being uncorrelated with additive non-stationary white noise is provided.

Keywords: molecular, noise, diffusion, channel

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Authors: Yichao Ma, Chengsiong Chin, Wailok Woo

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Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and three-dimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who is the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: hdd noise, jury test, neural network model, psychoacoustic annoyance

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Authors: Tinu Rose Francis, S. Wilkinson, Y. Chang-Richards, S. Mannakkara

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The objective of this paper is to assess the implementation of Build Back Better (BBB) propositions for disaster risk reduction in the natural environment with regard to greater Christchurch, New Zealand, after the 2010–2011 earthquakes in the region. A set of indicators was established to analyse the extent of recovery attained in Christchurch. Disaster recovery in the region is an ongoing process, which gives us the opportunity to rate the progress made so far. Disasters cause significant damage to the built, social and economic environments and also have severe consequences for the natural environment. Findings show that greater Christchurch has made important progress and implemented a comprehensive natural environment recovery plan. The plan addresses the restoration of biodiversity, natural resources, disaster waste management and amenity values in greater Christchurch. This paper also surveys the risk reduction actions being implemented with regard to the natural environment. The findings of this study will help governing bodies to identify and fill the gaps in their natural environment recovery plans.

Keywords: build back better (BBB), natural environment, planning, recovery, reconstruction, resilience, risk reduction

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Authors: Ahmed N. Shmroukh

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This study examined a new solar still equipped with a movable inclined back, and this back is covered with a wick for seawater desalination. The tested backside inclination angles were 105, 125 and 160, respectively. The wick helped in increasing the seawater evaporation rate by increasing the evaporation surface area allowed for seawater in the still basin. The proposed modified solar still was compared with the conventional simple still. The results showed that the daily produced desalinated water of the modified solar still with angles 105, 125 and 160 increased by approximately 13.7%, 27.9%, and 39.2%, respectively, compared with the conventional solar still.

Keywords: solar still, inclined still, porous materials, Wick

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Authors: Sarra Khelifi, Youcef Guerabli, Ahcene Boumaiza

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Advances in techniques for measuring individual crystallographic orientations have made it possible to investigate the role of local crystallography during the plastic deformation of materials. In this study, the change in crystallographic orientation distribution during deformation by deep drawing in carbon steel has been investigated in order to understand their role in propagation and arrest of crack. The results show that the change of grain orientation from initial recrystallization texture components of {111}<112> to deformation orientation {111}<110> incites the initiation and propagation of cracks in the region of {111}<112> small grains. Moreover, the misorientation profile and local orientation are analyzed in detail to discuss the change from {111}<112> to {111}<110>. The deformation of the grain with {111}<110> orientation is discussed in terms of stops of the crack in carbon steel during drawing. The SEM-EBSD technique was used to reveal the change of orientation; XRD was performed for the characterization of the global evolution of texture for deformed samples.

Keywords: fracture, heterogeneity, misorientation profile, stored energy

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Authors: Mishu Gupta, Rama Gupta

Abstract:

It has been elucidated here that non- autonomous discrete non-linear Schrödinger equation is associated with saturable non-linearity through photo-refractive media. We have investigated the localized solution of non-autonomous saturable discrete non-linear Schrödinger equations. The similarity transformation has been involved in converting non-autonomous saturable discrete non-linear Schrödinger equation to constant-coefficient saturable discrete non-linear Schrödinger equation (SDNLSE), whose exact solution is already known. By back substitution, the solution of the non-autonomous version has been obtained. We have analysed our solution for the hyperbolic and periodic form of gain/loss term, and interesting results have been obtained. The most important characteristic role is that it helps us to analyse the propagation of electromagnetic waves in glass fibres and other optical wave mediums. Also, the usage of SDNLSE has been seen in tight binding for Bose-Einstein condensates in optical mediums. Even the solutions are interrelated, and its properties are prominently used in various physical aspects like optical waveguides, Bose-Einstein (B-E) condensates in optical mediums, Non-linear optics in photonic crystals, and non-linear kerr–type non-linearity effect and photo refracting medium.

Keywords: B-E-Bose-Einstein, DNLSE-Discrete non linear schrodinger equation, NLSE-non linear schrodinger equation, SDNLSE - saturable discrete non linear Schrodinger equation

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Authors: Marjan Golmaryami, Marzieh Behzadi

Abstract:

Recent developments in stock exchange highlight the need for an efficient and accurate method that helps stockholders make better decision. Since stock markets have lots of fluctuations during the time and different effective parameters, it is difficult to make good decisions. The purpose of this study is to employ artificial neural network (ANN) which can deal with time series data and nonlinear relation among variables to forecast next day stock price. Unlike other evolutionary algorithms which were utilized in stock exchange prediction, we trained our proposed neural network with metaheuristic bat algorithm, with fast and powerful convergence and applied it in stock price prediction for the first time. In order to prove the performance of the proposed method, this research selected a 7 year dataset from Parsian Bank stocks and after imposing data preprocessing, used 3 types of ANN (back propagation-ANN, particle swarm optimization-ANN and bat-ANN) to predict the closed price of stocks. Afterwards, this study engaged MATLAB to simulate 3 types of ANN, with the scoring target of mean absolute percentage error (MAPE). The results may be adapted to other companies stocks too.

Keywords: artificial neural network (ANN), bat algorithm, particle swarm optimization algorithm (PSO), stock exchange

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Authors: Mahendrapal Singh Pachlaniya, Laxmi Kumre

Abstract:

The AOI (AND – OR- INVERTER) based design of XOR gate is proposed in this paper with less number of gates. This new XOR gate required four basic gates and basic gate include only AND, OR, Inverter (AOI). Conventional XOR gate required five basic gates. Ripple Carry Adder (RCA) used in parallel addition but propagation delay time is large. RCA replaced with Carry Select Adder (CSLA) to reduce propagation delay time. CSLA design with dual RCA considering carry = ‘0’ and carry = ‘1’, so it is not an area efficient adder. To make area efficient, modified CSLA is designed with single RCA considering carry = ‘0’ and another RCA considering carry = ‘1’ replaced with Binary to Excess 1 Converter (BEC). Now replacement of conventional XOR gate by new design of XOR gate in modified CSLA reduces much area compared to regular CSLA and modified CSLA.

Keywords: CSLA, BEC, XOR gate, area efficient

Procedia PDF Downloads 329

Authors: Ş. Karabulut, A. Güllü, A. Güldaş, R. Gürbüz

Abstract:

This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis

Procedia PDF Downloads 421

Authors: Mikheil Kalmakhelidze

Abstract:

Record linkage (RL) problem has become more and more important in recent years due to the growing interest towards big data analysis. The problem can be formulated in a very simple way: Given two entries a and b of a database, decide whether they represent the same object or not. There are two classical deterministic and probabilistic ways of solving the RL problem. Using simple Bayes classifier in many cases produces useful results but sometimes they show to be poor. In recent years several successful approaches have been made towards solving specific RL problems by neural network algorithms including single layer perception, multilayer back propagation network etc. In our work, we model the RL problem for specific dataset of student applications in fuzzy description logic (FDL) where linkage of specific pair (a,b) depends on the truth value of corresponding formula A(a,b) in a canonical FDL model. As a main result, we build neural network for deciding truth value of FDL formulas in a canonical model and thus link RL problem to machine learning. We apply the approach to dataset with 10000 entries and also compare to classical RL solving approaches. The results show to be more accurate than standard probabilistic approach.

Keywords: description logic, fuzzy logic, neural networks, record linkage

Procedia PDF Downloads 242