Search results for: Distance bounding

Authors: A. Kampker, K. Kreisköther, C. Reinders

Abstract:

Since additive manufacturing technologies constantly advance, the use of this technology in mold making seems reasonable. Many manufacturers of additive manufacturing machines, however, do not offer any suggestions on how to parameterize the machine to achieve optimal results for mold making. The purpose of this research is to determine the interdependencies of different materials and parameters within the PolyJet process by using design of experiments (DoE), to additively manufacture molds, e.g. for thermoforming and injection molding applications. Therefore, the general requirements of thermoforming molds, such as heat resistance, surface quality and hardness, have been identified. Then, different materials and parameters of the PolyJet process, such as the orientation of the printed part, the layer thickness, the printing mode (matte or glossy), the distance between printed parts and the scaling of parts, have been examined. The multifactorial analysis covers the following properties of the printed samples: Tensile strength, tensile modulus, bending strength, elongation at break, surface quality, heat deflection temperature and surface hardness. The key objective of this research is that by joining the results from the DoE with the requirements of the mold making, optimal and tailored molds can be additively manufactured with the PolyJet process. These additively manufactured molds can then be used in prototyping processes, in process testing and in small to medium batch production.

Keywords: Additive manufacturing, design of experiments, mold making, PolyJet.

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Authors: Laurentiu Moruz, Jens Kitzhofer, Mircea Dinulescu

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The paper aims to extend the knowledge about jet behavior and jet interaction between five plane unventilated jets with large aspect ratio (AR). The distance between the single plane jets is two times the channel height. The experimental investigation applies 2D Particle Image Velocimetry (PIV) and static pressure measurements. Our study focuses on the influence of two different outlet nozzle geometries (triangular shape with 2 x 7.5° and blunt geometry) with respect to variation of Reynolds number from 5500 - 12000. It is shown that the outlet geometry has a major influence on the jet formation in terms of uniformity of velocity profiles downstream of the sudden expansion. Furthermore, we describe characteristic regions like converging region, merging region and combined region. The triangular outlet geometry generates most uniform velocity distributions in comparison to a blunt outlet nozzle geometry. The blunt outlet geometry shows an unstable behavior where the jets tend to attach to one side of the walls (ceiling) generating a large recirculation region on the opposite side. Static pressure measurements confirm the observation and indicate that the recirculation region is connected to larger pressure drop.

Keywords: 2D particle image velocimetry, parallel jet interaction, pressure drop, sudden expansion.

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Authors: M. Israil Hossain, T. P. Tiwari, Ashrafuzzaman Gulandaz, Nusrat Jahan

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Two-wheel tractor (power tiller) is a common tillage tool in Bangladesh agriculture for easy access in fragmented land with affordable price of small farmers. Traditional maize sheller needs to be carried from place to place by hooking with two-wheel tractor (2WT) and set up again for shelling operation which takes longer time for preparation of maize shelling. The mobile maize sheller eliminates the transportation problem and can start shelling operation instantly any place as it is attached together with 2WT. It is counterclockwise rotating cylinder, axial flow type sheller, and grain separated with a frictional force between spike tooth and concave. The maize sheller is attached with nuts and bolts in front of the engine base of 2WT. The operating power of the sheller comes from the fly wheel of the engine of the tractor through ‘V” belt pulley arrangement. The average shelling capacity of the mobile sheller is 2.0 t/hr, broken kernel 2.2%, and shelling efficiency 97%. The average maize shelling cost is Tk. 0.22/kg and traditional custom hire rate is Tk.1.0/kg, respectively (1 US$=Tk.78.0). The service provider of the 2WT can transport the mobile maize sheller long distance in operator’s seating position. The manufacturers started the fabrication of mobile maize sheller. This mobile maize sheller is also compatible for the other countries where 2WT is available for farming operation.

Keywords: Cost effective, mobile maize sheller, maize shelling capacity, small farmers, two-wheel tractor.

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Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: K-nearest neighbor, face detection, vitiligo, bone deformity.

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Authors: Mohammad Heidari

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Horizontal wells are proven to be better producers because they can be extended for a long distance in the pay zone. Engineers have the technical means to forecast the well productivity for a given horizontal length. However, experiences have shown that the actual production rate is often significantly less than that of forecasted. It is a difficult task, if not impossible to identify the real reason why a horizontal well is not producing what was forecasted. Often the source of problem lies in the drilling of horizontal section such as permeability reduction in the pay zone due to mud invasion or snaky well patterns created during drilling. Although drillers aim to drill a constant inclination hole in the pay zone, the more frequent outcome is a sinusoidal wellbore trajectory. The two factors, which play an important role in wellbore tortuosity, are the inclination and side force at bit. A constant inclination horizontal well can only be drilled if the bit face is maintained perpendicular to longitudinal axis of bottom hole assembly (BHA) while keeping the side force nil at the bit. This approach assumes that there exists no formation force at bit. Hence, an appropriate BHA can be designed if bit side force and bit tilt are determined accurately. The Artificial Neural Network (ANN) is superior to existing analytical techniques. In this study, the neural networks have been employed as a general approximation tool for estimation of the bit side forces. A number of samples are analyzed with ANN for parameters of bit side force and the results are compared with exact analysis. Back Propagation Neural network (BPN) is used to approximation of bit side forces. Resultant low relative error value of the test indicates the usability of the BPN in this area.

Keywords: Artificial Neural Network, BHA, Horizontal Well, Stabilizer.

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Authors: Ibrahim Yakubu Seini, Oluwole Daniel Makinde

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MHD chemically reacting viscous fluid flow towards a vertical surface with slip and convective boundary conditions has been conducted. The temperature and the chemical species concentration of the surface and the velocity of the external flow are assumed to vary linearly with the distance from the vertical surface. The governing differential equations are modeled and transformed into systems of ordinary differential equations, which are then solved numerically by a shooting method. The effects of various parameters on the heat and mass transfer characteristics are discussed. Graphical results are presented for the velocity, temperature, and concentration profiles whilst the skin-friction coefficient and the rate of heat and mass transfers near the surface are presented in tables and discussed. The results revealed that increasing the strength of the magnetic field increases the skin-friction coefficient and the rate of heat and mass transfers toward the surface. The velocity profiles are increased towards the surface due to the presence of the Lorenz force, which attracts the fluid particles near the surface. The rate of chemical reaction is seen to decrease the concentration boundary layer near the surface due to the destructive chemical reaction occurring near the surface.

Keywords: Boundary layer, surface slip, MHD flow, chemical reaction, heat transfer, mass transfer.

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Authors: Tahsin Toma Sabbagh, Ihsan Al-Abboodi, Ali Al-Jazaairry

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Allowable-bearing capacity is the competency of soil to safely carries the pressure from the superstructure without experiencing a shear failure with accompanying excessive settlements. Ensuring a safe bearing pressure with respect to failure does not tolerate settlement of the foundation will be within acceptable limits. Therefore, settlement analysis should always be performed since most structures are settlement sensitive. When visualising the movement of a soil wedge in the bearing capacity criterion, both vertically and horizontally, it becomes clear that by confining the soil surrounding the foundation, both the bearing capacity and settlement values improve. In this study, two sizes of spread foundation were considered; (2×4) m and (3×5) m. These represent two real problem case studies of an existing building. The foundations were analysed in terms of dimension as well as position with respect to a confining wall (i.e., sheet piles on both sides). Assuming B is the least foundation dimension, the study comprised the analyses of three distances; (0.1 B), (0.5 B), and (0.75 B) between the sheet piles and foundations alongside three depths of confinement (0.5 B), (1 B), and (1.5 B). Nonlinear three-dimensional finite element analysis (ANSYS) was adopted to perform an analytical investigation on the behaviour of the two foundations contained by the case study. Results showed that confinement of foundations reduced the overall stresses near the foundation by 65% and reduced the vertical displacement by 90%. Moreover, the most effective distance between the confinement wall and the foundation was found to be 0.5 B.

Keywords: Bearing capacity, cohesionless soils, spread footings, soil confinement, soil modelling.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: C. Ardil

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This paper introduces the concept of neutral sets (NSs) and explores various operations on NSs, along with their associated properties. The foundation of the Neutral Set framework lies in ontological neutrality and the principles of logic, including the Law of Non-Contradiction. By encompassing components for possibility, indeterminacy, and necessity, the NS framework provides a flexible representation of truth, uncertainty, and necessity, accommodating diverse ontological perspectives without presupposing specific existential commitments. The inclusion of Possibility acknowledges the spectrum of potential states or propositions, promoting neutrality by accommodating various viewpoints. Indeterminacy reflects the inherent uncertainty in understanding reality, refraining from making definitive ontological commitments in uncertain situations. Necessity captures propositions that must hold true under all circumstances, aligning with the principle of logical consistency and implicitly supporting the Law of Non-Contradiction. Subsequently, a neutral set-TOPSIS approach is applied in the maintenance strategy selection problem, demonstrating the practical applicability of the NS framework. The paper further explores uncertainty relations and presents the fundamental preliminaries of NS theory, emphasizing its role in fostering ontological neutrality and logical coherence in reasoning.

Keywords: Uncertainty sets, neutral sets, maintenance strategy selection multiple criteria decision-making analysis, MCDM, uncertainty decision analysis, distance function, multiple attribute, decision making, selection method, uncertainty, TOPSIS

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Authors: Anupama Pande, Vishik Goel

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A complex valued neural network is a neural network, which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in image and vision processing. In Neural networks, radial basis functions are often used for interpolation in multidimensional space. A Radial Basis function is a function, which has built into it a distance criterion with respect to a centre. Radial basis functions have often been applied in the area of neural networks where they may be used as a replacement for the sigmoid hidden layer transfer characteristic in multi-layer perceptron. This paper aims to present exhaustive results of using RBF units in a complex-valued neural network model that uses the back-propagation algorithm (called 'Complex-BP') for learning. Our experiments results demonstrate the effectiveness of a Radial basis function in a complex valued neural network in image recognition over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error on a neural network model with RBF units. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Radial BasisFunction, Image recognition.

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Authors: Sayyed R Mousavi

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The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.

Keywords: Bioinformatics, Far From Most Strings Problem, Hybrid metaheuristics, Matheuristics, Sequences consensus problems.

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Authors: Deng Zengming, Wang Mingjiang

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As 3D video is explored as a hot research topic in the last few decades, free-viewpoint TV (FTV) is no doubt a promising field for its better visual experience and incomparable interactivity. View synthesis is obviously a crucial technology for FTV; it enables to render images in unlimited numbers of virtual viewpoints with the information from limited numbers of reference view. In this paper, a novel hybrid synthesis framework is proposed and blending priority is explored. In contrast to the commonly used View Synthesis Reference Software (VSRS), the presented synthesis process is driven in consideration of the temporal correlation of image sequences. The temporal correlations will be exploited to produce fine synthesis results even near the foreground boundaries. As for the blending priority, this scheme proposed that one of the two reference views is selected to be the main reference view based on the distance between the reference views and virtual view, another view is chosen as the auxiliary viewpoint, just assist to fill the hole pixel with the help of background information. Significant improvement of the proposed approach over the state-of –the-art pixel-based virtual view synthesis method is presented, the results of the experiments show that subjective gains can be observed, and objective PSNR average gains range from 0.5 to 1.3 dB, while SSIM average gains range from 0.01 to 0.05.

Keywords: View synthesis, Gaussian mixture model, hybrid framework, fusion method.

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Authors: G. H. Senussi

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The present work is concerned with the effect of turning process parameters (cutting speed, feed rate, and depth of cut) and distance from the center of work piece as input variables on the chip micro-hardness as response or output. Three experiments were conducted; they were used to investigate the chip micro-hardness behavior at diameter of work piece for 30[mm], 40[mm], and 50[mm]. Response surface methodology (R.S.M) is used to determine and present the cause and effect of the relationship between true mean response and input control variables influencing the response as a two or three dimensional hyper surface. R.S.M has been used for designing a three factor with five level central composite rotatable factors design in order to construct statistical models capable of accurate prediction of responses. The results obtained showed that the application of R.S.M can predict the effect of machining parameters on chip micro-hardness. The five level factorial designs can be employed easily for developing statistical models to predict chip micro-hardness by controllable machining parameters. Results obtained showed that the combined effect of cutting speed at it?s lower level, feed rate and depth of cut at their higher values, and larger work piece diameter can result increasing chi micro-hardness.

Keywords: Machining Parameters, Chip Micro-Hardness, CNCMachining, 304-Austenic Stainless Steel.

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Authors: Frank Emmert-Streib, Matthias Dehmer, Jing Liu, Max Muhlhauser

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The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, generalized trees, graph alignment, DNA microarray data, cervical cancer.

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Authors: A. T. Eswara

Abstract:

This paper analyses the unsteady, two-dimensional stagnation point flow of an incompressible viscous fluid over a flat sheet when the flow is started impulsively from rest and at the same time, the sheet is suddenly stretched in its own plane with a velocity proportional to the distance from the stagnation point. The partial differential equations governing the laminar boundary layer forced convection flow are non-dimensionalised using semi-similar transformations and then solved numerically using an implicit finitedifference scheme known as the Keller-box method. Results pertaining to the flow and heat transfer characteristics are computed for all dimensionless time, uniformly valid in the whole spatial region without any numerical difficulties. Analytical solutions are also obtained for both small and large times, respectively representing the initial unsteady and final steady state flow and heat transfer. Numerical results indicate that the velocity ratio parameter is found to have a significant effect on skin friction and heat transfer rate at the surface. Furthermore, it is exposed that there is a smooth transition from the initial unsteady state flow (small time solution) to the final steady state (large time solution).

Keywords: Forced flow, Keller-box method, Stagnation point, Stretching flat sheet, Unsteady laminar boundary layer, Velocity ratio parameter.

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Authors: B. Likar, K. Širok

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The paper presents a new method for efficient innovation process management. Even though the innovation management methods, tools and knowledge are well established and documented in literature, most of the companies still do not manage it efficiently. Especially in SMEs the front end of innovation - problem identification, idea creation and selection - is often not optimally performed. Our eMIPS methodology represents a sort of "umbrella methodology" - a well-defined set of procedures, which can be dynamically adapted to the concrete case in a company. In daily practice, various methods (e.g. for problem identification and idea creation) can be applied, depending on the company's needs. It is based on the proactive involvement of the company's employees supported by the appropriate methodology and external experts. The presented phases are performed via a mixture of face-to-face activities (workshops) and online (eLearning) activities taking place in eLearning Moodle environment and using other e-communication channels. One part of the outcomes is an identified set of opportunities and concrete solutions ready for implementation. The other also very important result is connected to innovation competences for the participating employees related with concrete tools and methods for idea management. In addition, the employees get a strong experience for dynamic, efficient and solution oriented managing of the invention process. The eMIPS also represents a way of establishing or improving the innovation culture in the organization. The first results in a pilot company showed excellent results regarding the motivation of participants and also as to the results achieved.

Keywords: Creativity, distance learning, front end, innovation, problem.

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Authors: Hadi Gholizadeh, Ali Tajdin

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: Goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression.

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Authors: Jahangir Jafari, Nematollah Khorasani, Afshin Danehkar

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Having a very many number of pipelines all over the country, Iran is one of the countries consists of various ecosystems with variable degrees of fragility and robusticity as well as geographical conditions. This study presents a state-of-the-art method to estimate environmental risks of pipelines by recommending rational equations including FES, URAS, SRS, RRS, DRS, LURS and IRS as well as FRS to calculate the risks. This study was carried out by a relative semi-quantitative approach based on land uses and HVAs (High-Value Areas). GIS as a tool was used to create proper maps regarding the environmental risks, land uses and distances. The main logic for using the formulas was the distance-based approaches and ESI as well as intersections. Summarizing the results of the study, a risk geographical map based on the ESIs and final risk score (FRS) was created. The study results showed that the most sensitive and so of high risk area would be an area comprising of mangrove forests located in the pipeline neighborhood. Also, salty lands were the most robust land use units in the case of pipeline failure circumstances. Besides, using a state-of-the-art method, it showed that mapping the risks of pipelines out with the applied method is of more reliability and convenience as well as relative comprehensiveness in comparison to present non-holistic methods for assessing the environmental risks of pipelines. The focus of the present study is “assessment" than that of “management". It is suggested that new policies are to be implemented to reduce the negative effects of the pipeline that has not yet been constructed completely

Keywords: ERM, ESI, ERA, Pipeline, Assalouyeh

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Authors: Sungju Yun, Anjin Park, Keechul Jung

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Motion capture devices have been utilized in producing several contents, such as movies and video games. However, since motion capture devices are expensive and inconvenient to use, motions segmented from captured data was recycled and synthesized to utilize it in another contents, but the motions were generally segmented by contents producers in manual. Therefore, automatic motion segmentation is recently getting a lot of attentions. Previous approaches are divided into on-line and off-line, where on-line approaches segment motions based on similarities between neighboring frames and off-line approaches segment motions by capturing the global characteristics in feature space. In this paper, we propose a graph-based high-level motion segmentation method. Since high-level motions consist of several repeated frames within temporal distances, we consider all similarities among all frames within the temporal distance. This is achieved by constructing a graph, where each vertex represents a frame and the edges between the frames are weighted by their similarity. Then, normalized cuts algorithm is used to partition the constructed graph into several sub-graphs by globally finding minimum cuts. In the experiments, the results using the proposed method showed better performance than PCA-based method in on-line and GMM-based method in off-line, as the proposed method globally segment motions from the graph constructed based similarities between neighboring frames as well as similarities among all frames within temporal distances.

Keywords: Capture Devices, High-Level Motion, Motion Segmentation, Normalized Cuts

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Authors: S. Kulsri, M. Jaroensutasinee, K. Jaroensutasinee

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We developed a new method based on quasimolecular modeling to simulate the cavity flow in three cavity shapes: rectangular, half-circular and bucket beer in cgs units. Each quasi-molecule was a group of particles that interacted in a fashion entirely analogous to classical Newtonian molecular interactions. When a cavity flow was simulated, the instantaneous velocity vector fields were obtained by using an inverse distance weighted interpolation method. In all three cavity shapes, fluid motion was rotated counter-clockwise. The velocity vector fields of the three cavity shapes showed a primary vortex located near the upstream corners at time t ~ 0.500 s, t ~ 0.450 s and t ~ 0.350 s, respectively. The configurational kinetic energy of the cavities increased as time increased until the kinetic energy reached a maximum at time t ~ 0.02 s and, then, the kinetic energy decreased as time increased. The rectangular cavity system showed the lowest kinetic energy, while the half-circular cavity system showed the highest kinetic energy. The kinetic energy of rectangular, beer bucket and half-circular cavities fluctuated about stable average values 35.62 x 103, 38.04 x 103 and 40.80 x 103 ergs/particle, respectively. This indicated that the half-circular shapes were the most suitable shape for a shrimp pond because the water in shrimp pond flows best when we compared with rectangular and beer bucket shape.

Keywords: Quasi-molecular modelling, particle modelling, lid driven cavity flow.

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Authors: S. Golmohammadi, M. Noorian Bidgoli

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Tunneling progress is a key parameter in the blasting method of tunneling. Taking measures to enhance tunneling advance can limit the progress distance without a supporting system, subsequently reducing or eliminating the risk of damage. This paper focuses on modeling tunneling progress using three main groups of parameters (tunneling geometry, blasting pattern, and rock mass specifications) based on the Rock Engineering Systems (RES) methodology. In the proposed models, four main effective parameters on tunneling progress are considered as inputs (RMR, Q-system, Specific charge of blasting, Area), with progress as the output. Data from 86 blasts conducted at the tailrace tunnel in the Azad Dam, western Iran, were used to evaluate the progress value for each blast. The results indicated that, for the 86 blasts, the progress of the estimated model aligns mostly with the measured progress. This paper presents a method for building the interaction matrix (statistical base) of the RES model. Additionally, a comparison was made between the results of the new RES-based model and a Multi-Linear Regression (MLR) analysis model. In the RES-based model, the effective parameters are RMR (35.62%), Q (28.6%), q (specific charge of blasting) (20.35%), and A (15.42%), respectively, whereas for MLR analysis, the main parameters are RMR, Q (system), q, and A. These findings confirm the superior performance of the RES-based model over the other proposed models.

Keywords: Rock Engineering Systems, tunneling progress, Multi Linear Regression, Specific charge of blasting.

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Authors: Satyasen Panda, Urmila Bhanja

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This paper presents a SAC-OCDMA code with zero cross correlation property to minimize the Multiple Access Interface (MAI) as New Zero Cross Correlation code (NZCC), which is found to be more scalable compared to the other existing SAC-OCDMA codes. This NZCC code is constructed using address segment and data segment. In this work, the proposed NZCC code is implemented in an optical system using the Opti-System software for the spectral amplitude coded optical code-division multiple-access (SAC-OCDMA) scheme. The main contribution of the proposed NZCC code is the zero cross correlation, which reduces both the MAI and PIIN noises. The proposed NZCC code reveals properties of minimum cross-correlation, flexibility in selecting the code parameters and supports a large number of users, combined with high data rate and longer fiber length. Simulation results reveal that the optical code division multiple access system based on the proposed NZCC code accommodates maximum number of simultaneous users with higher data rate transmission, lower Bit Error Rates (BER) and longer travelling distance without any signal quality degradation, as compared to the former existing SAC-OCDMA codes.

Keywords: Cross Correlation, Optical Code Division Multiple Access, Spectral Amplitude Coding Optical Code Division Multiple Access, Multiple Access Interference, Phase Induced Intensity Noise, New Zero Cross Correlation code.

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Authors: Hassan Zarei, Ali Vahidian Kamyad, Sohrab Effati

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In this paper, a mathematical model of human immunodeficiency virus (HIV) is utilized and an optimization problem is proposed, with the final goal of implementing an optimal 900-day structured treatment interruption (STI) protocol. Two type of commonly used drugs in highly active antiretroviral therapy (HAART), reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are considered. In order to solving the proposed optimization problem an adaptive memetic algorithm with population management (AMAPM) is proposed. The AMAPM uses a distance measure to control the diversity of population in genotype space and thus preventing the stagnation and premature convergence. Moreover, the AMAPM uses diversity parameter in phenotype space to dynamically set the population size and the number of crossovers during the search process. Three crossover operators diversify the population, simultaneously. The progresses of crossover operators are utilized to set the number of each crossover per generation. In order to escaping the local optima and introducing the new search directions toward the global optima, two local searchers assist the evolutionary process. In contrast to traditional memetic algorithms, the activation of these local searchers is not random and depends on both the diversity parameters in genotype space and phenotype space. The capability of AMAPM in finding optimal solutions compared with three popular metaheurestics is introduced.

Keywords: HIV therapy design, memetic algorithms, adaptivealgorithms, nonlinear integer programming.

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Authors: A. Bajit, M. Nahid, A. Tamtaoui, E. H. Bouyakhf

Abstract:

In this paper, we propose a Perceptually Optimized Embedded ZeroTree Image Coder (POEZIC) that introduces a perceptual weighting to wavelet transform coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to the coding quality obtained using the SPIHT algorithm only. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEZIC quality assessment. Our POEZIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) luminance masking and Contrast masking, 2) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting, 3) the Wavelet Error Sensitivity WES used to reduce the perceptual quantization errors. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.

Keywords: DWT, linear-phase 9/7 filter, 9/7 Wavelets Error Sensitivity WES, CSF implementation approaches, JND Just Noticeable Difference, Luminance masking, Contrast masking, standard SPIHT, Objective Quality Measure, Probability Score PS.

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Authors: Nagalingam Arun Prasanth, Ahmed Syed Adnan, S. H. Yeo

Abstract:

Surface topography plays a significant role in the functional performance of engineered parts. It is important to have a control on the surface geometry and understanding on the surface details to get the desired performance. Hence, in the current research contribution, a non-contact micro-texturing technique has been explored and developed. The technique involves ultrasonic excitation of a tool as a prime source of surface texturing for aluminum alloy workpieces. The specimen surface is polished first and is then immersed in a liquid bath containing 10% weight concentration of Ti6Al4V grade 5 spherical powders. A submerged slurry jet is used to recirculate the spherical powders under the ultrasonic horn which is excited at an ultrasonic frequency and amplitude of 40 kHz and 70 µm respectively. The distance between the horn and workpiece surface was remained fixed at 200 µm using a precision control stage. Texturing effects were investigated for different process timings of 1, 3 and 5 s. Thereafter, the specimens were cleaned in an ultrasonic bath for 5 mins to remove loose debris on the surface. The developed surfaces are characterized by optical and contact surface profiler. The optical microscopic images show a texture of circular spots on the workpiece surface indented by titanium spherical balls. Waviness patterns obtained from contact surface profiler supports the texturing effect produced from the proposed technique. Furthermore, water droplet tests were performed to show the efficacy of the proposed technique to develop hydrophilic surfaces and to quantify the texturing effect produced.

Keywords: Surface texturing, surface modification, topography, ultrasonic.

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

Abstract:

This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: Visual search, deep learning, convolutional neural network, machine learning.

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

Abstract:

The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: Bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow.

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Authors: Divyanka Sontakke, Arpit Thakre, D. K Shinde, Sujata Parmeshwaran

Abstract:

Electrospinning is the most widely utilized method to create nanofibers because of the direct setup, the capacity to mass-deliver consistent nanofibers from different polymers, and the ability to produce ultrathin fibers with controllable diameters. Smooth and much arranged ultrafine Polyacrylonitrile (PAN) nanofibers with diameters going from submicron to nanometer were delivered utilizing Electrospinning technique. PAN powder was used as a precursor to prepare the solution utilized as a part of this process. At the point when the electrostatic repulsion contradicted surface tension, a charged stream of polymer solution was shot out from the head of the spinneret and along these lines ultrathin nonwoven fibers were created. The effect of electrospinning parameter such as applied voltage, feed rate, concentration of polymer solution and tip to collector distance on the morphology of electrospun PAN nanofibers were investigated. The nanofibers were heat treated for carbonization to examine the changes in properties and composition to make for electrical application. Scanning Electron Microscopy (SEM) was performed before and after carbonization to study electrical conductivity and morphological characterization. The SEM images have shown the uniform fiber diameter and no beads formation. The average diameter of the PAN fiber observed 365nm and 280nm for flat plat and rotating drum collector respectively. The four probe strategy was utilized to inspect the electrical conductivity of the nanofibers and the electrical conductivity is significantly improved with increase in oxidation temperature exposed.

Keywords: Electrospinning, polyacrylonitrile carbon nanofibres, heat treatment, electrical conductivity.

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Authors: S. S. Sharma, P. R. Prabhu, Rajagopal Chadaga

Abstract:

The main emphasis of metallurgists has been to process the materials to obtain the balanced mechanical properties for the given application. One of the processing routes to alter the properties is heat treatment. Nearly 90% of the structural applications are related to the medium carbon an alloyed steels and hence are regarded as structural steels. The major requirement in the conventional steel is to improve workability, toughness, hardness and grain refinement. In this view, it is proposed to study the mechanical and tribological properties of unalloyed structural (AISI 1140) steel with different thermal (heat) treatments like annealing, normalizing, tempering and hardening and compared with as brought (cold worked) specimen. All heat treatments are carried out in atmospheric condition. Hardening treatment improves hardness of the material, a marginal decrease in hardness value with improved ductility is observed in tempering. Annealing and normalizing improve ductility of the specimen. Normalized specimen shows ultimate ductility. Hardened specimen shows highest wear resistance in the initial period of slide wear where as above 25KM of sliding distance, as brought steel dominates the hardened specimen. Both mild and severe wear regions are observed. Microstructural analysis shows the existence of pearlitic structure in normalized specimen, lath martensitic structure in hardened, pearlitic, ferritic structure in annealed specimen.

Keywords: Annealing, hardness, heat treatment, normalizing, wear.

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Authors: Majid Saaly, Shahriar Tavousi Tafreshi, Mehdi Nazari Afshar

Abstract:

Most reinforced concrete structures are designed only under heavy loads have large transverse reinforcement spacing values, and therefore suffer severe failure after intense ground movements. The main goal of this paper is to compare the shear- and axial failure of concrete bending frames available in Tehran using Incremental Dynamic Analysis (IDA) under near- and far-field records. For this purpose, IDA of 5, 10, and 15-story concrete structures were done under seven far-fault records and five near-faults records. The results show that in two-dimensional models of short-rise, mid-rise and high-rise reinforced concrete frames located on Type-3 soil, increasing the distance of the transverse reinforcement can increase the maximum inter-story drift ratio values up to 37%. According to the existing results on 5, 10, and 15-story reinforced concrete models located on Type-3 soil, records with characteristics such as fling-step and directivity create maximum drift values between floors more than far-fault earthquakes. The results indicated that in the case of seismic excitation modes under earthquake encompassing directivity or fling-step, the probability values of failure and failure possibility increasing rate values are much smaller than the corresponding values of far-fault earthquakes. However, in near-fault frame records, the probability of exceedance occurs at lower seismic intensities compared to far-fault records.

Keywords: Directivity, fling-step, fragility curve, IDA, inter story drift ratio.v

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