Search results for: mathematical-physics applications

Authors: Vahid Bayrami Rad

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In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

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Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

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Authors: L. J. de Bessa Neto, M. R. B. Guerra Vale, F. K. O. M. Varella Guerra

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In recent years, solar energy has established itself as one of the main sources of renewable energy, gaining a large space in electricity generation around the world. However, due to the low performance of photovoltaic panels, technologies need to be sought to maximize the production of electricity. In this regard, the present study aims to develop a prototype of solar tracker for didactics applications, controlled with the Arduino® platform, that enables the movement of photovoltaic plates in relation to the sun positions throughout the day through an electromechanical system, optimizing, thus, the efficiency of solar photovoltaic generation and improvements for the photovoltaic effect. The solar tracking technology developed in this work was presented of the shape oral and practical in two middle schools in the municipality of Mossoró/RN, being one of the public network and other of the private network, always keeping the average age of the students, in the case, around 16 years, contemplating an average of 60 students in each of the visits. Thus, it is concluded that the present study contributed substantially to the dissemination of knowledge concerning the photovoltaic solar generation, as well as the study of solar trackers, thus arousing the interest and curiosity of the students regarding the thematic approached.

Keywords: alternative energy, solar tracker, energy efficiency, photovoltaic panels

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Authors: Marco Tulio C. Faria

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Fixed-geometry hydrodynamic journal bearings are one of the best supporting systems for several applications of rotating machinery. Cylindrical journal bearings present excellent load-carrying capacity and low manufacturing costs, but they are subjected to the oil-film instability at high speeds. An attempt of overcoming this instability problem has been the development of non-circular journal bearings. This work deals with an analysis of oil-lubricated elliptical journal bearings using the finite element method. Steady-state and dynamic performance characteristics of elliptical bearings are rendered by zeroth- and first-order lubrication equations obtained through a linearized perturbation method applied on the classical Reynolds equation. Four-node isoparametric rectangular finite elements are employed to model the bearing thin film flow. Curves of elliptical bearing load capacity and dynamic force coefficients are rendered at several operating conditions. The results presented in this work demonstrate the influence of the bearing ellipticity on its performance at different loading conditions.

Keywords: elliptical journal bearings, non-circular journal bearings, hydrodynamic bearings, finite element method

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Authors: Bruno Bacci Fernandes, Stephan Mändl, Ataíde Ribeiro da Silva Junior, José Osvaldo Rossi, Mário Ueda

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Nitrogen implantation in aluminum and its alloys is acquainted for the difficulties in obtaining modified layers deeper than 200 nm. The present work addresses a new method to overcome such a problem; although, the coating with nitrogen and oxygen obtained by plasma immersion ion implantation (PIII) into a 7075 aluminum alloy surface was too shallow. This alloy is commonly used for structural parts in aerospace applications. Such a layer was characterized by secondary ion mass spectroscopy, electron microscopy, and nanoindentation experiments reciprocating wear tests. From the results, one can assume that the wear of this aluminum alloy starts presenting severe abrasive wear followed by an additional adhesive mechanism. PIII produced a slight difference, as shown in all characterizations carried out in this work. The results shown here can be used as the scientific basis for further nitrogen PIII experiments in aluminum alloys which have the goal to produce thicker modified layers or to improve their surface properties.

Keywords: aluminum alloys, plasma immersion ion implantation, tribological properties, hardness, nanofatigue

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Authors: Reda Abdel Azim, Tariq Shehab

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The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.

Keywords: naturally fractured reservoirs, artificial intelligence, fracture intensity, fractal dimension

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Authors: Dominic Wentworth-Linton, Shian Gao

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This project was aimed at investigating the effect of velocity stacks on the intakes of internal combustion engines for motorsport applications. The intake systems in motorsport are predominantly fuel injection with a plate mounted for the stacks. Using Computational Fluid Dynamics software, the relationship between the stack length and power and torque delivery across the engine’s rev range was investigated and the results were used to choose the best option for its intended motorsport discipline. The test results are expected to vary with engine geometry and its natural manufacturer characteristics. The test was also relevant in bridging between computational data and real simulation as the results show flow, pressure and velocity readings but the behaviour of the engine is inferred from the nature of each test. The results of the data analysis were tested in a real-life simulation on a dynamometer to prove the theory of stack length on power and torque delivery, which helps determine the most suitable stack for the Vauxhall engine for rallying in the Caribbean.

Keywords: CFD simulation, Internal combustion engine, Intake system, Dynamometer test

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Authors: Arvind Dhingra, Tejinder Singh Saggu

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As the energy demands rise and the pollution levels grow, it becomes imperative for us to save energy in all the fields in which it is used. The industrial sector is the major commercial energy consuming sector in India, where electrical energy is the most common and widely used type of energy. As the demand and price of energy are increasing day by day, therefore, the subject of energy conservation is a concern for most energy users particularly industry. Judicious use of energy becomes imperative for third world developing country being presence of energy crisis. This paper provides some measure for energy saving that can be commonly recommended for a rolling unit of steel industry. A case of hot rolling unit in JSL Stainless Ltd., Hisar for energy conservation is given. Overall improvement in energy consumption in light of the stated recommendation is illustrated along with the proposed utilization of the techniques and their applications. Energy conservation in conventional motor with replacement or use of star delta star converter, reduction in cable losses, replacement of filament of LED lamps, replacement of conventional transformer with cast resin dry type transformer and provision of energy management system for energy conservation and per unit production cost reduction are elaborated in this paper.

Keywords: energy audit, energy conservation, energy efficient motors

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Authors: D. Vidhyaprakash, A. Elango

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In real-time applications, wheeled mobile robots are increasingly used and operated in extreme and diverse conditions traversing challenging surfaces such as a pitted, uneven terrain, natural flat, smooth terrain, as well as wet and dry surfaces. In order to accomplish such tasks, it is critical that the motion control functions without wheel slip and odometry error during the navigation of the two-wheeled mobile robot (WMR). Wheel slip and odometry error are disrupting factors on overall WMR performance in the form of deviation from desired trajectory, navigation, travel time and budgeted energy consumption. The wheeled mobile robot’s ability to operate at peak performance on various work surfaces without wheel slippage and odometry error is directly connected to four main parameters, which are the range of payload distribution, speed, wheel diameter, and wheel width. This paper analyses the effects of those parameters on overall performance and is concerned with determining the ideal range of parameters for optimum performance.

Keywords: wheeled mobile robot, terrain, wheel slippage, odometryerror, trajectory

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Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Hyunjoo Choi, Jeonghun Nam, Chae Seung Lim

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Acoustomicrofluidics has gained much attention due to the advantages, such as noninvasiveness and easy integration with other miniaturized systems, for clinical and biological applications. However, a limitation of acoustomicrofluidics is the complicated and costly fabrication process of electrodes. In this study, we propose a low-cost and lithography-free device using Lamb wave for blood analysis. Using a Lamb wave, calcium ion-removed blood plasma and coagulation reagents can be rapidly mixed for blood coagulation test. Due to the coagulation process, the viscosity of the sample increases and the viscosity change can be monitored by internal acoustic streaming of microparticles suspended in the sample droplet. When the acoustic streaming of particles stops by the viscosity increase is defined as the coagulation time. With the addition of calcium ion at 0-25 mM, the coagulation time was measured and compared with the conventional index for blood coagulation analysis, prothrombin time, which showed highly correlated with the correlation coefficient as 0.94. Therefore, our simple and cost-effective Lamb wave-based blood analysis device has the powerful potential to be utilized in clinical settings.

Keywords: acoustomicrofluidics, blood analysis, coagulation, lamb wave

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Authors: Mohammed Abed, Rita Nemes

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Cellular concrete powder (CCP) is not used widely as supplementary cementitious material, but in the literature, its efficiency is proved when it used as a replacement of cement in concrete mixtures. In this study, different amounts of raw CCP (CCP as a waste material without any industrial modification) will be used to investigate the characteristics of cement pastes and the effects of CCP on the properties of the cement pastes. It is an attempt to produce green binder paste, which is useful for sustainable construction applications. The fresh and hardened properties of a number of CCP blended cement paste will be tested in different life periods, and the optimized CCP volume will be reported with more significant investigations on durability properties. Different replacing of mass percentage (low and high) of the cement mass will be conducted (0%, 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%). The consistency, flexural strength, and compressive strength will be the base indicator for the further properties' investigations. The CCP replacement until 50% have been tested until 7 days, and the initial results showed a linear relationship between strength and the percentage of the replacement; that is an optimistic indicator for further replacement percentages of waste CCP.

Keywords: cellular concrete powder, supplementary cementitious material, sustainable construction, green concrete

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Authors: Nurdiyana Zainal Abidin, Raja Nafida Raja Shahminan, Fawazul Khair Ibrahim

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Timber vernacular houses in Malaysia are unique heritage buildings which can be identified through their designs, structure, architectural elements and ornamentations. Woodcarvings are common forms of ornamentations and decorations in Traditional Malay Houses and they can be found throughout Malaysia including in Negeri Sembilan. As a multi-cultural, multi-racial, and multi-religion state which uniquely practices the matrilineal social system, Negeri Sembilan has a strong connection to its’ history and heritage and in particular the distinctive vernacular architecture. The purpose of this paper is to underline the factors that influence the woodcarvings in Traditional Malay Houses in Negeri Sembilan, Malaysia. The houses studied were from the archives of measured drawings in Center of Built Environment in the Malay World (KALAM), Universiti Teknologi Malaysia (UTM). The findings indicated several factors influencing the woodcarver’s works and also the applications of the woodcarvings such as religious factors, cultural factors and political factors. These factors among several other shows that woodcarvings were predetermined before being carved and that they were not just merely placed without reason but are functioning pieces of aesthetic ornamentation.

Keywords: influences, traditional Malay houses, woodcarvings, multi-cultural

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Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

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Authors: Buket Boz, Alvaro Diez

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Waste heat recovery by means of Organic Rankine Cycle is a promising technology for the recovery of engine exhaust heat. However, it is complex to find out the optimum cycle conditions with appropriate working fluids to match exhaust gas waste heat due to its high temperature. Hence, this paper focuses on comparing sub-critical and supercritical ORC conditions with eight working fluids on a combined diesel engine-ORC system. The model employs two ORC designs, Regenerative-ORC and Pre-Heating-Regenerative-ORC respectively. The thermodynamic calculations rely on the first and second law of thermodynamics, thermal efficiency and exergy destruction factors are the fundamental parameters evaluated. Additionally, in this study, environmental and safety, GWP (Global Warming Potential) and ODP (Ozone Depletion Potential), characteristic of the refrigerants are taken into consideration as evaluation criteria to define the optimal ORC configuration and conditions. Consequently, the studys outcomes reveal that supercritical ORCs with alkane and siloxane are more suitable for high temperature exhaust waste heat recovery in contrast to sub-critical conditions.

Keywords: internal combustion engine, organic Rankine cycle, waste heat recovery, working fluids

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Authors: Hanno Schmidt, Assaf Malik, Anne Bicker, Gesa Poetzsch, Aaron Avivi, Imad Shams, Thomas Hankeln

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The blind subterranean mole rat Spalax shows a remarkable tolerance to hypoxia, cancer-resistance and longevity. Unravelling the genomic basis of these adaptations will be important for biomedical applications. RNA-Seq gene expression data were obtained from normoxic and hypoxic Spalax and rat liver tissue. Hypoxic Spalax broadly downregulates genes from major liver function pathways. This energy-saving response is likely a crucial adaptation to low oxygen levels. In contrast, the hypoxiasensitive rat shows massive upregulation of energy metabolism genes. Candidate genes with plausible connections to the mole rat’s phenotype, such as important key genes related to hypoxia-tolerance, DNA damage repair, tumourigenesis and ageing, are substantially higher expressed in Spalax than in rat. Comparative liver transcriptomics highlights the importance of molecular adaptations at the gene regulatory level in Spalax and pinpoints a variety of starting points for subsequent functional studies.

Keywords: cancer, hypoxia, longevity, transcriptomics

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Authors: Hoda Aslani, Mohammad Moghiman, Mohammad Aslani

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Considering the demand to reduce global warming potential and importance of solidification in various applications, there is an increasing interest in energy storage systems to find the efficient phase change materials. Therefore, this paper presents an experimental study and comparison on the potential of titania nanofluids with and without surfactant for cooling energy storage systems. A designed cooling generation device based on compression refrigeration cycle is used to explore nanofluids solidification characteristics. In this work, titania nanoparticles of 0.01, 0.02 and 0.04 wt.% are dispersed in deionized water as base fluid. Measurement of phase change parameters of nanofluids illustrates that the addition of polyvinylpyrrolidone (PVP) as surfactant to titania nanofluids advances the onset nucleation time and leads to lower solidification time. Also, the experimental results show that only adding 0.02 wt.% titania nanoparticles, especially in the case of nanofluids with a surfactant, can evidently reduce the supercooling degree by nearly 70%. Hence, it is concluded that there is a great energy saving potential in the energy storage systems using titania nanofluid with PVP.

Keywords: cooling energy storage, nanofluid, PVP, solidification, titania

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Authors: Oyugi Ngure Robert, Kallen Mulilo Nalyanya, Tabitha A. Amollo

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Nanomaterials have attracted significant attention in research because of their exemplary properties, making them suitable for diverse applications. This paper reports the successful synthesis as well as the structural properties of silver sulfide/reduced graphene oxide (Ag_2 S-rGO) nanocomposite. The nanocomposite was synthesized by the chemical reduction method. Scanning electron microscopy (SEM) showed that the reduced graphene oxide (rGO) sheets were intercalated within the Ag_2 S nanoparticles during the chemical reduction process. The SEM images also showed that Ag_2 S had the shape of nanowires. Further, SEM energy dispersive X-ray (SEM EDX) showed that Ag_2 S-rGO is mainly composed of C, Ag, O, and S. X-ray diffraction analysis manifested a high crystallinity for the nanowire-shaped Ag2S nanoparticles with a d-spacing ranging between 1.0 Å and 5.2 Å. Thermal gravimetric analysis (TGA) showed that rGO enhances the thermal stability of the nanocomposite. Ag_2 S-rGO nanocomposite exhibited strong optical absorption in the UV region. The formed nanocomposite is dispersible in polar and non-polar solvents, qualifying it for solution-based device processing.

Keywords: silver sulfide, reduced graphene oxide, nanocomposite, structural properties, optical properties

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Authors: Duygu Özdemir, Bilal Özçakır

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Usage of augmented reality in education helps students to make sense of the three-dimensional world of mathematics. In this study, it was aimed to develop activities about fractions for 5th-grade students by augmented reality and also aimed to assess these activities in terms of students’ understanding and views. Data obtained from 60 students in a private school in Marmaris, Turkey was obtained through classroom observations, students’ worksheets and semi-structured interviews during two weeks. Data analysis was conducted by using constant-comparative analysis which leads to meaningful categories of findings. Findings of this study indicated that usage of augmented reality is a facilitator to make concretize and provide real-life application for fractions. Moreover, students’ opinions about its usage were lead to categories as benefit for learning, enjoyment and creating awareness of usage of augmented reality in mathematics education. In general, this study could be a bridge to show the contributions of augmented reality applications to mathematics education and also highlights that augmented reality could be used with subjects like fractions rather than subjects only in geometry learning domain.

Keywords: augmented reality, mathematics, fractions, students

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Authors: J. P. Borah, R. D. Raland

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Hyperthermia is one of many techniques used destroys cancerous cell. It uses the physical methods to heat certain organ or tissue delivering an adequate temperature in an appropriate period of time, to the entire tumor volume for achieving optimal therapeutic results. Magnetic Metal ferrites nanoparticles (MFe₂O₄ where M = Mn, Zn, Ni, Co, Mg, etc.) are one of the most potential candidates for hyperthermia due to their tunability, biocompatibility, chemical stability and notable ability to mediate high rate of heat induction. However, to obtain the desirable properties for these applications, it is important to optimize their chemical composition, structure and magnetic properties. These properties are mainly sensitive to cation distribution of tetrahedral and octahedral sites. Among the ferrites, zinc ferrite (ZnFe₂O₄) and Manganese ferrite ((MnFe₂O₄) is one of a strong candidate for hyperthermia application because Mn and zinc have a non-magnetic cation and therefore the magnetic property is determined only by the cation distribution of iron, which provides a better platform to manipulate or tailor the properties. In this talk, influence of doping and surfactant towards cation re-distribution leading to an enhancement of magnetic properties of ferrite nanoparticles will be demonstrated. The efficiency of heat generation in association with the enhanced magnetic property is also well discussed in this talk.

Keywords: magnetic nanoparticle, hyperthermia, x-ray diffraction, TEM study

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Authors: Joe Amalraj, M. Arunkumar

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Haze is an atmospheric phenomenon that signicantly degrades the visibility of outdoor scenes. This is mainly due to the atmosphere particles that absorb and scatter the light. This paper introduces a novel single image approach that enhances the visibility of such degraded images. In this method is a fusion-based strategy that derives from two original hazy image inputs by applying a white balance and a contrast enhancing procedure. To blend effectively the information of the derived inputs to preserve the regions with good visibility, we filter their important features by computing three measures (weight maps): luminance, chromaticity, and saliency. To minimize artifacts introduced by the weight maps, our approach is designed in a multiscale fashion, using a Laplacian pyramid representation. This paper demonstrates the utility and effectiveness of a fusion-based technique for de-hazing based on a single degraded image. The method performs in a per-pixel fashion, which is straightforward to implement. The experimental results demonstrate that the method yields results comparative to and even better than the more complex state-of-the-art techniques, having the advantage of being appropriate for real-time applications.

Keywords: single image de-hazing, outdoor images, enhancing, DSP

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Authors: Edreese H. Alsharaeh, Feven Mattews Michael, Ayman Almohsin

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Self-healing hydrogels have many advantages since they can resist various types of stresses, including tension, compression, and shear, making them attractive for various applications. In this study, thermo-elastic and self-healing polymer composite hydrogels were prepared from polyacrylamide (PAM) and 2D fillers using in-situ method. In addition, the PAM and fillers were prepared in presence of organic crosslinkers, i.e., hydroquinone (HQ) and hexamethylenediamine (HMT). The swelling behavior of the prepared hydrogels was studied by hydrating the dried hydrogels. The thermal and rheological properties of the prepared hydrogels were evaluated before and after swelling study using thermogravimetric analysis, differential scanning calorimetric technique and dynamic mechanical analysis. From the results obtained, incorporating fillers into the PAM matrix enhanced the swelling degree of the hydrogels with satisfactory mechanical properties, attaining up to 77% self-healing efficiency compared to the neat-PAM (i.e., 29%). This, in turn, indicates addition of 2D fillers improved self-healing properties of the polymer hydrogel, thus, making the prepared hydrogels applicable for water shutoff treatments under high temperature.

Keywords: polymer hydrogels, 2D fillers, elastic self-healing hydrogels, water shutoff, swelling properties

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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Due to many applications and problems in the fields of plasma physics, geophysics, and other many topics, the interaction between the strain field and the magnetic field has to be considered. Adomian introduced the decomposition method for solving linear and nonlinear functional equations. This method leads to accurate, computable, approximately convergent solutions of linear and nonlinear partial and ordinary differential equations even the equations with variable coefficients. This paper is dealing with a mathematical model of generalized thermoelasticity of a half-space conducting medium. A magnetic field with constant intensity acts normal to the bounding plane has been assumed. Adomian’s decomposition method has been used to solve the model when the bounding plane is taken to be traction free and thermally loaded by harmonic heating. The numerical results for the temperature increment, the stress, the strain, the displacement, the induced magnetic, and the electric fields have been represented in figures. The magnetic field, the relaxation time, and the angular thermal load have significant effects on all the studied fields.

Keywords: Adomian’s decomposition method, magneto-thermoelasticity, finite conductivity, iteration method, thermal load

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Authors: Abdelrahman Alghazali, Youssef Kassem, Hüseyin Çamur, Ozan Erenay

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Savonius is a drag type vertical axis wind turbine. Savonius wind turbines have a low cut-in speed and can operate at low wind speed. This makes it suitable for electricity or mechanical generation in low-power applications such as individual domestic installations. Therefore, the primary purpose of this work was to investigate the relationship between the type of Savonius rotor and the torque and mechanical power generated. And it was to illustrate how the type of rotor might play an important role in the prediction of mechanical power of wind turbine powered car. The main purpose of this paper is to predict and investigate the aerodynamic effects by means of velocity analysis on the performance of a wind turbine powered car by converting the wind energy into mechanical energy to overcome load that rotates the main shaft. The predicted results based on theoretical analysis were compared with experimental results obtained from literature. The percentage of error between the two was approximately around 20%. Prediction of the torque was done at a wind speed of 4 m/s, and an angular velocity of 130 RPM according to meteorological statistics in Northern Cyprus.

Keywords: mechanical power, torque, Savonius rotor, wind car

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Authors: Bassem Boshra Thabet, Mohammed Ibrahim Elsabagh, Mohammad Adly Talaat

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The number of cellular mobile phone users has increased enormously worldwide over the last two decades. Consequently, the monitoring of the performance of the Mobile Network Operators (MNOs) in terms of network coverage and broadband signal strength has become vital for both of the MNOs and regulators. This monitoring helps telecommunications operators and regulators keeping the market playing fair and most beneficial for users. However, the adopted methodologies to facilitate this continuous monitoring process are still problematic regarding cost, effort, and reliability. This paper introduces My Operator Coverage (MOC) system that is using Internet of Things (IoT) concepts and tools to monitor the MNOs performance using a crowd-sourced real-time methodology. MOC produces robust and reliable geographical maps for the user-perceived quality of the MNOs performance. MOC is also meant to enrich the telecommunications regulators with concrete, and up-to-date information that allows for adequate mobile market management strategies as well as appropriate decision making.

Keywords: mobile performance monitoring, crowd-sourced applications, mobile broadband performance, cellular networks monitoring

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Authors: Maria Alekxandra B. Sison, Reginald C. Mallare, Joseph Albert M. Mendoza

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Ammonia (NH₃) is the alternative carbon-free fuel of the future for its promising applications. Investigations on NH₃-fuel blends recommend using hydrogen (H₂) to increase the heating value of NH3, promote combustion performance, and improve NOx efflux mitigation. To further examine the effects of this concept, the study analyzed the combustion performance, in terms of turbulence, combustion efficiency (CE), and NOx emissions, of NH3/fuel with variations of combustor diameter ratio, H2 fuel mole fraction, and fuel mass flow rate (ṁ). The simulations were performed using Computational Fluid Dynamics (CFD) modeling to represent a non-premixed (NP) and partially premixed (PP) combustion under a two-dimensional ultra-low NOx Rich-Burn, Quick-Quench, Lean-Burn (RQL) combustor. Governed by the Detached Eddy Simulation model, it was found that the diameter ratio greatly affects the turbulence in PP and NP mode, whereas ṁ in PP should be prioritized when increasing CE. The NOx emission is minimal during PP combustion, but NP combustion suggested modifying ṁ to achieve higher CE and Reynolds number without sacrificing the NO generation from the reaction.

Keywords: combustion efficiency, turbulence, dual-stage combustor, NOx emission

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Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The color image is decomposed into red, green, and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using a key image that has same original size and is generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours of color image recovery can be obtained with accepted level of distortion using Canny edge detector. Experiments have demonstrated that proposed algorithm can fully encrypt 2D color image and completely reconstructed without any distortion. It has shown that the color image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: color image, wavelet transform, edge detector, Arnold transform, lossy image encryption

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Hannah Kolano, Paul Nadan, Jeremy Ryan, Sophia Nielsen

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The hooves of goats and other ruminants, or the family Ruminantia, are uniquely structured to adapt to rough terrain. Their hooves possess a hard outer shell and a soft interior that allow them to both conform to uneven surfaces and hook onto prominent features. In an effort to apply this unique mechanism to a robotics context, artificial feet for a hexapedal robot have been designed based on the hooves of ruminants to improve the robot’s ability to traverse unstructured environments such as those found on a rocky planet or asteroid, as well as in earth-based environments such as rubble, caves, and mountainous regions. The feet were manufactured using a combination of 3D printing and polyurethane casting techniques and attached to a commercially available hexapedal robot. The robot was programmed with a terrain-adaptive gait and proved capable of traversing a variety of uneven surfaces and inclines. This development of more adaptable robotic feet allows legged robots to operate in a wider range of environments and expands their possible applications.

Keywords: biomimicry, legged locomotion, robotic foot design, ruminant feet, unstructured terrain navigation

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Authors: Joelle Thng, Li Fang

Abstract:

Objective: As programming becomes a highly valued and sought-after skill in the economy, many universities have started offering Python courses to help students keep up with the demands of employers. This study focuses on designing a university module that effectively educates undergraduate students on financial analysis using Python programming. Methodology: To better satisfy the specific demands for each sector, this study adopted a qualitative research modus operandi to craft a module that would complement students’ existing financial skills. The lessons were structured using research-backed educational learning tools, and important Python concepts were prudently screened before being included in the syllabus. The course contents were streamlined based on criteria such as ease of learning and versatility. In particular, the skills taught were modelled in a way to ensure they were beneficial for financial data processing and analysis. Results: Through this study, a 6-week course containing the chosen topics and programming applications was carefully constructed for finance students. Conclusion: The findings in this paper will provide valuable insights as to how teaching programming could be customised for students hailing from various academic backgrounds.

Keywords: curriculum development, designing effective instruction, higher education strategy, python for finance students

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