Search results for: Neural image processing

Authors: Rodrigo Pacheco-Ruiz, Jonathan Adams, Felix Pedrotti

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This paper introduces the applicability of underwater photogrammetric survey within challenging conditions as the main tool to enhance and enrich the process of documenting archaeological excavation through the creation of 4D models. Photogrammetry was being attempted on underwater archaeological sites at least as early as the 1970s’ and today the production of traditional 3D models is becoming a common practice within the discipline. Photogrammetry underwater is more often implemented to record exposed underwater archaeological remains and less so as a dynamic interpretative tool.  Therefore, it tends to be applied in bright environments and when underwater visibility is > 1m, reducing its implementation on most submerged archaeological sites in more turbid conditions. Recent years have seen significant development of better digital photographic sensors and the improvement of optical technology, ideal for darker environments. Such developments, in tandem with powerful processing computing systems, have allowed underwater photogrammetry to be used by this research as a standard recording and interpretative tool. Using multi-source photogrammetry (5, GoPro5 Hero Black cameras) this paper presents the accumulation of daily (4D) underwater surveys carried out in the Early Bronze Age (3,300 BC) to Late Ottoman (17th Century AD) archaeological site of Ropotamo in the Bulgarian Black Sea under challenging conditions (< 0.5m visibility). It proves that underwater photogrammetry can and should be used as one of the main recording methods even in low light and poor underwater conditions as a way to better understand the complexity of the underwater archaeological record.

Keywords: 4D modelling, Black Sea, maritime archaeology, underwater photogrammetry, Bronze Age, low visibility.

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Authors: Chang, Wei-Chen

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The purpose of this study is to research on thoughts transmitted from virtual fitting-room and to deduce discussion in an auxiliary narrative way. The research structure is based on 3D virtual fitting-room as the research subject. Initially, we will discuss the principles of narrate study, User Demand and so on by using a narrative design pattern to transmit their objective indications of “people-situation-reason-object", etc, and then to analyze the virtual fitting-room examples that are able to provide a new thinking for designers who engaged in clothing related industry – which comes in “story telling" and “user-centered design" forms. Clothing designs are not just to cover up the body to keep warm but to draw closer to people-s demand physiologically and psychologically through interactive designs so as to achieve cognition between people and environment. In the “outside" goal of clothing-s functional designs, we use tribal group-s behavior characteristics to “transform" the existing personal cultural stories, and “reform" them to design appropriate interactive products. Synthesizing the above matters, apart from being able to regard “narrate" as a kind of functional thinking process, we are also able to regard it as a kind of choice, arrangement and an activity of story expression, allowing interactive design-s spirit, product characteristics and experience ideas be transmitted to target tribal group in a visual image performance method. It is a far more confident and innovative attempt, and meanwhile, able to achieve entertainment, joyful and so forth fundamental interactive transmissions. Therefore, this study takes “user-centered design" thinking as a basis to establish a set of clothing designs with interactive experience patterns and to assist designers to examine the five sensual feeling of interactive demands in order to initiate a new value in textile industry.

Keywords: Virtual Fitting-room, Interactive Design, User Demand Evaluation, Intelligent Systems.

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Authors: Oriyomi M. Okeyinka, David A. Oloke, Jamal M. Khatib

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Large quantities of solid wastes being generated worldwide from sources such as household, domestic, industrial, commercial and construction demolition activities, leads to environmental concerns. Utilization of these wastes in making building construction materials can reduce the magnitude of the associated problems. When these waste products are used in place of other conventional materials, natural resources and energy are preserved and expensive and/or potentially harmful waste disposal is avoided. Recycling which is regarded as the third most preferred waste disposal option, with its numerous environmental benefits, stand as a viable option to offset the environmental impact associated with the construction industry. This paper reviews the results of laboratory tests and important research findings, and the potential of using these wastes in building construction materials with focus on sustainable development. Research gaps, which includes; the need to develop standard mix design for solid waste based building materials; the need to develop energy efficient method of processing solid waste use in concrete; the need to study the actual behavior or performance of such building materials in practical application and the limited real life application of such building materials have also been identified. A research is being proposed to develop an environmentally friendly, lightweight building block from recycled waste paper, without the use of cement, and with properties suitable for use as walling unit. This proposed research intends to incorporate, laboratory experimentation and modeling to address the identified research gaps.

Keywords: Recycling, solid waste, construction, building materials.

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Authors: Mohamed El Morsy, Gabriela Achtenová

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This paper presents modern vibration signalprocessing techniques for vehicle gearbox fault diagnosis, via the wavelet analysis and the Squared Envelope (SE) technique. The wavelet analysis is regarded as a powerful tool for the detection of sudden changes in non-stationary signals. The Squared Envelope (SE) technique has been extensively used for rolling bearing diagnostics. In the present work a scheme of using the Squared Envelope technique for early detection of gear tooth pit. The pitting defect is manufactured on the tooth side of a fifth speed gear on the intermediate shaft of a vehicle gearbox. The objective is to supplement the current techniques of gearbox fault diagnosis based on using the raw vibration and ordered signals. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of output joint shafts. The gearbox used for experimental measurements is the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive; a five-speed gearbox with final drive gear and front wheel differential. The results show that the approaches methods are effective for detecting and diagnosing localized gear faults in early stage under different operation conditions, and are more sensitive and robust than current gear diagnostic techniques.

Keywords: Wavelet analysis, Squared Envelope, gear faults.

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Authors: Mohamed El Morsy, Gabriela Achtenová

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Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs.This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves asthe internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order Cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of Cepstrum analysis in detection and diagnosis of the gear condition.

Keywords: Cepstrum analysis, fault diagnosis, gearbox.

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Authors: R. Suresh, Pavan Kumar Nimmagadda, Ming Zo Tan, Shane Hart, Sharp Ugwuocha

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Polycrystalline diamond compact (PDC) drill bits are extensively used in the oil and gas industry as well as the mining industry. Industry engineers continually improve upon PDC drill bit designs and hydraulic conditions. Optimized injection nozzles play a key role in improving the drilling performance and efficiency of these ever changing PDC drill bits. In the first part of this study, computational fluid dynamics (CFD) modelling is performed to investigate the hydrodynamic characteristics of drilling fluid flow around the PDC drill bit. An Open-source CFD software – OpenFOAM simulates the flow around the drill bit, based on the field input data. A specifically developed console application integrates the entire CFD process including, domain extraction, meshing, and solving governing equations and post-processing. The results from the OpenFOAM solver are then compared with that of the ANSYS Fluent software. The data from both software programs agree. The second part of the paper describes the parametric study of the PDC drill bit nozzle to determine the effect of parameters such as number of nozzles, nozzle velocity, nozzle radial position and orientations on the flow field characteristics and bit washing patterns. After analyzing a series of nozzle configurations, the best configuration is identified and recommendations are made for modifying the PDC bit design.

Keywords: ANSYS Fluent, computational fluid dynamics, nozzle configuration, OpenFOAM, PDC dill bit.

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Authors: Chongtham Jiten, Radhapiyari Laishram, K. Chandramani Singh

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Alkaline niobate (Na_0.5K_0.5)NbO₃ ceramic system has attracted major attention in view of its potential for replacing the highly toxic but superior lead zirconate titanate (PZT) system for piezoelectric applications. Recently, a more detailed study of this system reveals that the ferroelectric and piezoelectric properties are optimized in the Li- and V-modified system having the composition (K_0.485Na_0.5Li_0.015)(Nb_0.98V_0.02)O₃. In the present work, we further study the pyroelectric behaviour of this composition along with another doped with Mn⁴⁺. So, (K_0.485Na_0.5Li_0.015)(Nb_0.98V_0.02)O₃ + x MnO₂ (x = 0, and 0.01 wt. %) ceramic compositions were synthesized by conventional ceramic processing route. X-ray diffraction study reveals that both the undoped and Mn⁴⁺-doped ceramic samples prepared crystallize into a perovskite structure having orthorhombic symmetry. Dielectric study indicates that Mn⁴⁺ doping has little effect on both the Curie temperature (T_c) and tetragonal-orthorhombic phase transition temperature (T_ot). The bulk density, room-temperature dielectric constant (ε_RT), and room-c The room-temperature coercive field (E_c) is observed to be lower in Mn⁴⁺ doped sample. The detailed analysis of the P-E hysteresis loops over the range of temperature from about room temperature to T_ot points out that enhanced ferroelectric properties exist in this temperature range with better thermal stability for the Mn⁴⁺ doped ceramic. The study reveals that small traces of Mn⁴⁺ can modify (K_0.485Na_0.5Li_0.015)(Nb_0.98V_0.02)O₃ system so as to improve its ferroelectric properties with good thermal stability over a wide range of temperature.

Keywords: Ceramics, dielectric properties, ferroelectric properties, lead-free, sintering, thermal stability.

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Authors: E.Sasikumar, T.Viruthagiri

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Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.

Keywords: Sugarcane bagasse, ethanol, optimization, Pachysolen tannophilus.

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Authors: Sambit Prasad Kar, P.Palanisamy

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In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.

Keywords: Frequency estimation, peak search, subspace-based method without eigen decomposition, quadratic convex function.

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI) is a hybrid e-framework for the development of a web-based instruction (WBI), which contributes towards instructional design and language development. WeCWI divides its contribution in instructional design into macro and micro perspectives. In macro perspective, being a 21st century educator by disseminating knowledge and sharing ideas with the in-class and global learners is initiated. By leveraging the virtue of technology, WeCWI aims to transform an educator into an aggregator, curator, publisher, social networker and ultimately, a web-based instructor. Since the most notable contribution of integrating technology is being a tool of teaching as well as a stimulus for learning, WeCWI focuses on the use of contemporary web tools based on the multiple roles played by the 21st century educator. The micro perspective in instructional design draws attention to the pedagogical approaches focusing on three main aspects: reading, discussion, and writing. With the effective use of pedagogical approaches through free reading and enterprises, technology adds new dimensions and expands the boundaries of learning capacity. Lastly, WeCWI also imparts the fundamental theories and models for web-based instructors’ awareness such as interactionist theory, cognitive information processing (CIP) theory, computer-mediated communication (CMC), e-learning interactionalbased model, inquiry models, sensory mind model, and leaning styles model.

Keywords: WeCWI, instructional discovery, technological discovery, pedagogical discovery, theoretical discovery.

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Authors: Jin Fan, M. Ala Saadeghvaziri

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Unmanned aerial vehicles (UAVs), also referred to as drones, equipped with various kinds of advanced detecting or surveying systems, are effective and low-cost in data acquisition, data delivery and sharing, which can benefit the building of infrastructures. This paper will give an overview of applications of drones in planning, designing, construction and maintenance of infrastructures. The drone platform, detecting and surveying systems, and post-data processing systems will be introduced, followed by cases with details of the applications. Challenges from different aspects will be addressed. Opportunities of drones in infrastructure include but not limited to the following. Firstly, UAVs equipped with high definition cameras or other detecting equipment are capable of inspecting the hard to reach infrastructure assets. Secondly, UAVs can be used as effective tools to survey and map the landscape to collect necessary information before infrastructure construction. Furthermore, an UAV or multi-UVAs are useful in construction management. UVAs can also be used in collecting roads and building information by taking high-resolution photos for future infrastructure planning. UAVs can be used to provide reliable and dynamic traffic information, which is potentially helpful in building smart cities. The main challenges are: limited flight time, the robustness of signal, post data analyze, multi-drone collaboration, weather condition, distractions to the traffic caused by drones. This paper aims to help owners, designers, engineers and architects to improve the building process of infrastructures for higher efficiency and better performance.

Keywords: Bridge, construction, drones, infrastructure, information.

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Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: Automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation.

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Authors: Praveen Kumar, Satish Kumar, Jashanpreet Singh

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Transportation of unrefined crude oil from the production unit to a refinery or large storage area by a pipeline is difficult due to the different properties of crude in various areas. Thus, the design of a crude oil pipeline is a very complex and time consuming process, when considering all the various parameters. There were three very important parameters that play a significant role in the transportation and processing pipeline design; these are: viscosity profile, temperature profile and the velocity profile of waxy crude oil through the crude oil pipeline. Knowledge of the Rheological computational technique is required for better understanding the flow behavior and predicting the flow profile in a crude oil pipeline. From these profile parameters, the material and the emulsion that is best suited for crude oil transportation can be predicted. Rheological computational fluid dynamic technique is a fast method used for designing flow profile in a crude oil pipeline with the help of computational fluid dynamics and rheological modeling. With this technique, the effect of fluid properties including shear rate range with temperature variation, degree of viscosity, elastic modulus and viscous modulus was evaluated under different conditions in a transport pipeline. In this paper, two crude oil samples was used, as well as a prepared emulsion with natural and synthetic additives, at different concentrations ranging from 1,000 ppm to 3,000 ppm. The rheological properties was then evaluated at a temperature range of 25 to 60 °C and which additive was best suited for transportation of crude oil is determined. Commercial computational fluid dynamics (CFD) has been used to generate the flow, velocity and viscosity profile of the emulsions for flow behavior analysis in crude oil transportation pipeline. This rheological CFD design can be further applied in developing designs of pipeline in the future.

Keywords: Natural surfactant, crude oil, rheology, CFD, viscosity.

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Authors: Ahmed Noor Al-Qayyim, Barlas Ozden Caglayan

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Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on to obtain very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. The study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using ‘Two Points Condensation (TPC) technique’. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices obtain from optimization the equation of motion using the measured test data. The current stiffness matrices compare with original (undamaged) stiffness matrices. The large percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element, where two cases consider. The method detects the damage and determines its location accurately in both cases. In addition, the results illustrate these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can be used also for big structures.

Keywords: Damage detection, two points–condensation, structural health monitoring, signals processing, optimization.

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Authors: N. G. Margiani, I. G. Kvartskhava, G. A. Mumladze, Z. A. Adamia

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Chemical doping with different elements and compounds at various amounts represents the most suitable approach to improve the superconducting properties of bismuth-based superconductors for technological applications. In this paper, the influence of partial substitution of Sr(BO₂)₂ for SrO on the phase formation kinetics and transport properties of (Bi,Pb)-2223 HTS has been studied for the first time. Samples with nominal composition Bi_1.7Pb_0.3Sr_2-xCa₂Cu₃O_y[Sr(BO₂)₂]_x, x=0, 0.0375, 0.075, 0.15, 0.25, were prepared by the standard solid state processing. The appropriate mixtures were calcined at 845 ^oC for 40 h. The resulting materials were pressed into pellets and annealed at 837 ^oC for 30 h in air. Superconducting properties of undoped (reference) and Sr(BO₂)₂-doped (Bi,Pb)-2223 compounds were investigated through X-ray diffraction (XRD), resistivity (ρ) and transport critical current density (J_c) measurements. The surface morphology changes in the prepared samples were examined by scanning electron microscope (SEM). XRD and J_c studies have shown that the low level Sr(BO₂)₂ doping (x=0.0375-0.075) to the Sr-site promotes the formation of high-T_c phase and leads to the enhancement of current carrying capacity in (Bi,Pb)-2223 HTS. The doped sample with x=0.0375 has the best performance compared to other prepared samples. The estimated volume fraction of (Bi,Pb)-2223 phase increases from ~25 % for reference specimen to ~70 % for x=0.0375. Moreover, strong increase in the self-field J_c value was observed for this dopant amount (J_c=340 A/cm²), compared to an undoped sample (J_c=110 A/cm²). Pronounced enhancement of superconducting properties of (Bi,Pb)-2223 superconductor can be attributed to the acceleration of high-T_c phase formation as well as the improvement of inter-grain connectivity by small amounts of Sr(BO₂)₂ dopant.

Keywords: Bismuth-based superconductor, critical current density, phase formation, Sr(BO2)2 doping.

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Authors: Violina R. Angelova, Mariana N. Perifanova-Nemska, Galina P. Uzunova, Krasimir I. Ivanov, Huu Q. Lee

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A field study was conducted to evaluate the efficacy of the sunflower (Helianthus annuus L.) for phytoremediation of contaminated soils. The experiment was performed on an agricultural field contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. Field experiments with a randomized, complete block design with five treatments (control, compost amendments added at 20 and 40 t/daa, and vemicompost amendments added at 20 and 40 t/daa) were carried out. The accumulation of heavy metals in the sunflower plant and the quality of the sunflower oil (heavy metals and fatty acid composition) were determined. The tested organic amendments significantly influenced the uptake of Pb, Zn and Cd by the sunflower plant. The incorporation of 40 t/decare of compost and 20 t/decare of vermicompost to the soil led to an increase in the ability of the sunflower to take up and accumulate Cd, Pb and Zn. Sunflower can be subjected to the accumulators of Pb, Zn and Cd and can be successfully used for phytoremediation of contaminated soils with heavy metals. The 40 t/daa compost treatment led to a decrease in heavy metal content in sunflower oil to below the regulated limits. Oil content and fatty acids composition were affected by compost and vermicompost amendment treatments. Adding compost and vermicompost increased the oil content in the seeds. Adding organic amendments increased the content of stearic, palmitoleic and oleic acids, and reduced the content of palmitic and gadoleic acids in sunflower oil. The possibility of further industrial processing of seeds to oil and use of the obtained oil will make sunflowers economically interesting crops for farmers of phytoremediation technology.

Keywords: Heavy metals, organic amendments, phytoremediation, sunflower.

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Authors: Mohamed Fathy Heweage, Xiao Wen, Ayman Mokhtar, Ahmed Eldamarawy

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In this paper, we are interested in modeling, simulation, and measurement of the laser spot position with a quadrant detector. We enhance detection and tracking of semi-laser weapon decoding system based on microcontroller. The system receives the reflected pulse through quadrant detector and processes the laser pulses through a processing circuit, a microcontroller decoding laser pulse reflected by the target. The seeker accuracy will be enhanced by the decoding system, the laser detection time based on the receiving pulses number is reduced, a gate is used to limit the laser pulse width. The model is implemented based on Pulse Repetition Frequency (PRF) technique with two microcontroller units (MCU). MCU1 generates laser pulses with different codes. MCU2 decodes the laser code and locks the system at the specific code. The codes EW selected based on the two selector switches. The system is implemented and tested in Proteus ISIS software. The implementation of the full position determination circuit with the detector is produced. General system for the spot position determination was performed with the laser PRF for incident radiation and the mechanical system for adjusting system at different angles. The system test results show that the system can detect the laser code with only three received pulses based on the narrow gate signal, and good agreement between simulation and measured system performance is obtained.

Keywords: 4-quadrant detector, pulse code detection, laser guided weapons, pulse repetition frequency, ATmega 32 microcontrollers.

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Authors: P. B. Sob, A. A. Alugongo, T. B. Tengen

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The activation volume of 6082T6 aluminum is investigated at different temperatures for grain size variants. The deformation activation volume was computed on the basis of the relationship between the Boltzmann’s constant k, the testing temperatures, the material strain rate sensitivity and the material yield stress grain size variants. The material strain rate sensitivity is computed as a function of yield stress and strain rate grain size variants. The effect of the material strain rate sensitivity and the deformation activation volume of 6082T6 aluminum at different temperatures of 3-D grain are discussed. It is shown that the strain rate sensitivities and activation volume are negative for the grain size variants during the deformation of nanostructured materials. It is also observed that the activation volume vary in different ways with the equivalent radius, semi minor axis radius, semi major axis radius and major axis radius. From the obtained results it is shown that the variation of activation volume increase and decrease with the testing temperature. It was revealed that, increase in strain rate sensitivity led to decrease in activation volume whereas increase in activation volume led to decrease in strain rate sensitivity.

Keywords: Nanostructured materials, grain size variants, temperature, yield stress, strain rate sensitivity, activation volume.

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Authors: Jungho Choi, Youngwan Cho

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This paper presents an algorithm for the recognition and tracking of moving objects, 1/10 scale model car is used to verify performance of the algorithm. Presented algorithm for the recognition and tracking of moving objects in the paper is as follows. SURF algorithm is merged with Lucas-Kanade algorithm. SURF algorithm has strong performance on contrast, size, rotation changes and it recognizes objects but it is slow due to many computational complexities. Processing speed of Lucas-Kanade algorithm is fast but the recognition of objects is impossible. Its optical flow compares the previous and current frames so that can track the movement of a pixel. The fusion algorithm is created in order to solve problems which occurred using the Kalman Filter to estimate the position and the accumulated error compensation algorithm was implemented. Kalman filter is used to create presented algorithm to complement problems that is occurred when fusion two algorithms. Kalman filter is used to estimate next location, compensate for the accumulated error. The resolution of the camera (Vision Sensor) is fixed to be 640x480. To verify the performance of the fusion algorithm, test is compared to SURF algorithm under three situations, driving straight, curve, and recognizing cars behind the obstacles. Situation similar to the actual is possible using a model vehicle. Proposed fusion algorithm showed superior performance and accuracy than the existing object recognition and tracking algorithms. We will improve the performance of the algorithm, so that you can experiment with the images of the actual road environment.

Keywords: SURF, Optical Flow Lucas-Kanade, Kalman Filter, object recognition, object tracking.

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Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

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The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement. On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: Automatic landing, multirotor, nonlinear control, parameters estimation, optical flow.

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Authors: Sarah Motiee, Azadeh Nematzadeh, Mehrnoush Shamsfard

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Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques to extract phrases from documents and the query and doing stemming on words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done flexible and in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Erh-Wen Hu, Cyril S. Ku, Andrew T. Russo, Bogong Su, Jian Wang

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Unlike general-purpose processors, digital signal processors (DSP processors) are strongly application-dependent. To meet the needs for diverse applications, a wide variety of DSP processors based on different architectures ranging from the traditional to VLIW have been introduced to the market over the years. The functionality, performance, and cost of these processors vary over a wide range. In order to select a processor that meets the design criteria for an application, processor performance is usually the major concern for digital signal processing (DSP) application developers. Performance data are also essential for the designers of DSP processors to improve their design. Consequently, several DSP performance benchmarks have been proposed over the past decade or so. However, none of these benchmarks seem to have included recent new DSP applications. In this paper, we use a new benchmark that we recently developed to compare the performance of popular DSP processors from Texas Instruments and StarCore. The new benchmark is based on the Selectable Mode Vocoder (SMV), a speech-coding program from the recent third generation (3G) wireless voice applications. All benchmark kernels are compiled by the compilers of the respective DSP processors and run on their simulators. Weighted arithmetic mean of clock cycles and arithmetic mean of code size are used to compare the performance of five DSP processors. In addition, we studied how the performance of a processor is affected by code structure, features of processor architecture and optimization of compiler. The extensive experimental data gathered, analyzed, and presented in this paper should be helpful for DSP processor and compiler designers to meet their specific design goals.

Keywords: digital signal processors, DSP benchmark, instruction level parallelism, modified cyclomatic complexity, performance analysis.

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Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Felipe Piña García

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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimize the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain). To this end, a flight with this type of sensors has been planned, developed and analyzed. It has been applied to the archaeological site of Juliobriga (Cantabria, Spain). A strong dependence of the thermal sensor on the GSD, and the capability of this technique to interpret underground materials. This research allows to state that the thermal nature of the site does not provide main information about the site itself, but with combination with other types of information, such as the DEM, the typology of materials, etc., can produce very positive results with respect to the exploration and knowledge of the site. 

Keywords: process optimization, RGB models, thermal models, UAV, workflow

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Authors: Sarabjeet Kaur Kochhar

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With a surge of stream processing applications novel techniques are required for generation and analysis of association rules in streams. The traditional rule mining solutions cannot handle streams because they generally require multiple passes over the data and do not guarantee the results in a predictable, small time. Though researchers have been proposing algorithms for generation of rules from streams, there has not been much focus on their analysis. We propose Association rule profiling, a user centric process for analyzing association rules and attaching suitable profiles to them depending on their changing frequency behavior over a previous snapshot of time in a data stream. Association rule profiles provide insights into the changing nature of associations and can be used to characterize the associations. We discuss importance of characteristics such as predictability of linkages present in the data and propose metric to quantify it. We also show how association rule profiles can aid in generation of user specific, more understandable and actionable rules. The framework is implemented as SUPAR: System for Usercentric Profiling of Association Rules in streaming data. The proposed system offers following capabilities: i) Continuous monitoring of frequency of streaming item-sets and detection of significant changes therein for association rule profiling. ii) Computation of metrics for quantifying predictability of associations present in the data. iii) User-centric control of the characterization process: user can control the framework through a) constraint specification and b) non-interesting rule elimination.

Keywords: Data Streams, User subjectivity, Change detection, Association rule profiles, Predictability.

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Authors: Peiman Ariaii, Hamid Tavakolipour, Mohsen Pirdashti, Rabehe Izadi Amoli

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Raisin Concentrate (RC) are the most important products obtained in the raisin processing industries. These RC products are now used to make the syrups, drinks and confectionery productions and introduced as natural substitute for sugar in food applications. Iran is a one of the biggest raisin exporter in the world but unfortunately despite a good raw material, no serious effort to extract the RC has been taken in Iran. Therefore, in this paper, we determined and analyzed affected parameters on extracting RC process and then optimizing these parameters for design the extracting RC process in two types of raisin (round and long) produced in Khorasan region. Two levels of solvent (1:1 and 2:1), three levels of extraction temperature (60°C, 70°C and 80°C), and three levels of concentration temperature (50°C, 60°C and 70°C) were the treatments. Finally physicochemical characteristics of the obtained concentrate such as color, viscosity, percentage of reduction sugar, acidity and the microbial tests (mould and yeast) were counted. The analysis was performed on the basis of factorial in the form of completely randomized design (CRD) and Duncan's multiple range test (DMRT) was used for the comparison of the means. Statistical analysis of results showed that optimal conditions for production of concentrate is round raisins when the solvent ratio was 2:1 with extraction temperature of 60°C and then concentration temperature of 50°C. Round raisin is cheaper than the long one, and it is more economical to concentrate production. Furthermore, round raisin has more aromas and the less color degree with increasing the temperature of concentration and extraction. Finally, according to mentioned factors the concentrate of round raisin is recommended.

Keywords: Raisin concentrate, optimization, process parameters, round raisin, Iran.

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

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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: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

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Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, melon, optimization, processing.

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Authors: Andres Piña, Amy Meléndez, Pablo Cano, Tomas Cahuich

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The purpose of this project is to propose a quick and environmentally friendly alternative to measure the quality of oils used in food industry. There is evidence that repeated and indiscriminate use of oils in food processing cause physicochemical changes with formation of potentially toxic compounds that can affect the health of consumers and cause organoleptic changes. In order to assess the quality of oils, non-destructive optical techniques such as Interferometry offer a rapid alternative to the use of reagents, using only the interaction of light on the oil. Through this project, we used interferograms of samples of oil placed under different heating conditions to establish the changes in their quality. These interferograms were obtained by means of a Mach-Zehnder Interferometer using a beam of light from a HeNe laser of 10mW at 632.8nm. Each interferogram was captured, analyzed and measured full width at half-maximum (FWHM) using the software from Amcap and ImageJ. The total of FWHMs was organized in three groups. It was observed that the average obtained from each of the FWHMs of group A shows a behavior that is almost linear, therefore it is probable that the exposure time is not relevant when the oil is kept under constant temperature. Group B exhibits a slight exponential model when temperature raises between 373 K and 393 K. Results of the t-Student show a probability of 95% (0.05) of the existence of variation in the molecular composition of both samples. Furthermore, we found a correlation between the Iodine Indexes (Physicochemical Analysis) and the Interferograms (Optical Analysis) of group C. Based on these results, this project highlights the importance of the quality of the oils used in food industry and shows how Interferometry can be a useful tool for this purpose.

Keywords: Food industry, interferometric, oils, quality control.

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Authors: Carlo Cernicchiaro, Pedro D. Gaspar, Martim L. Aguiar

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The agricultural sector is becoming more critical than ever in view of the expected overpopulation of the Earth. The introduction of robotic solutions in this field is an increasingly researched topic to make the most of the Earth's resources, thus going to avoid the problems of wear and tear of the human body due to the harsh agricultural work, and open the possibility of a constant careful processing 24 hours a day. This project is realized for a terrestrial autonomous robot aimed to navigate in an orchard collecting fallen peaches below the trees. When it receives the signal indicating the low battery, it has to return to the docking station where it will replace its battery and then return to the last work point and resume its routine. Considering a preset path in orchards with tree rows with variable length by which the robot goes iteratively using the algorithm D*. In case of low battery, the D* algorithm is still used to determine the fastest return path to the docking station as well as to come back from the docking station to the last work point. MATLAB simulations were performed to analyze the flexibility and adaptability of the developed algorithm. The simulation results show an enormous potential for adaptability, particularly in view of the irregularity of orchard field, since it is not flat and undergoes modifications over time from fallen branch as well as from other obstacles and constraints. The D* algorithm determines the best route in spite of the irregularity of the terrain. Moreover, in this work, it will be shown a possible solution to improve the initial points tracking and reduce time between movements.

Keywords: Path planning, fastest return path, agricultural terrestrial robot, autonomous, docking station.

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Authors: Gurjeet Singh, M. K. Pradhan, Ajay Verma

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The plastic industry plays very important role in the economy of any country. It is generally among the leading share of the economy of the country. Since metals and their alloys are very rarely available on the earth. Therefore, to produce plastic products and components, which finds application in many industrial as well as household consumer products is beneficial. Since 50% plastic products are manufactured by injection moulding process. For production of better quality product, we have to control quality characteristics and performance of the product. The process parameters plays a significant role in production of plastic, hence the control of process parameter is essential. In this paper the effect of the parameters selection on injection moulding process has been described. It is to define suitable parameters in producing plastic product. Selecting the process parameter by trial and error is neither desirable nor acceptable, as it is often tends to increase the cost and time. Hence, optimization of processing parameter of injection moulding process is essential. The experiments were designed with Taguchi’s orthogonal array to achieve the result with least number of experiments. Plastic material polypropylene is studied. Tensile strength test of material is done on universal testing machine, which is produced by injection moulding machine. By using Taguchi technique with the help of MiniTab-14 software the best value of injection pressure, melt temperature, packing pressure and packing time is obtained. We found that process parameter packing pressure contribute more in production of good tensile plastic product.

Keywords: Injection moulding, tensile strength, Taguchi method, poly-propylene.

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