Search results for: optical techniques

Authors: Ramzi Farra, Detre Teschner, Marc Willinger, Robert Schlögl

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Introduction: The conventional approach of characterizing solid catalysts under static conditions, i.e., before and after reaction, does not provide sufficient knowledge on the physicochemical processes occurring under dynamic conditions at the molecular level. Hence, the necessity of improving new in situ characterizing techniques with the potential of being used under real catalytic reaction conditions is highly desirable. In situ Prompt Gamma Activation Analysis (PGAA) is a rapidly developing chemical analytical technique that enables us experimentally to assess the coverage of surface species under catalytic turnover and correlate these with the reactivity. The catalytic HCl oxidation (Deacon reaction) over bulk ceria will serve as our example. Furthermore, the in situ Transmission Electron Microscopy is a powerful technique that can contribute to the study of atmosphere and temperature induced morphological or compositional changes of a catalyst at atomic resolution. The application of such techniques (PGAA and TEM) will pave the way to a greater and deeper understanding of the dynamic nature of active catalysts. Experimental/Methodology: In situ Prompt Gamma Activation Analysis (PGAA) experiments were carried out to determine the Cl uptake and the degree of surface chlorination under reaction conditions by varying p(O2), p(HCl), p(Cl2), and the reaction temperature. The abundance and dynamic evolution of OH groups on working catalyst under various steady-state conditions were studied by means of in situ FTIR with a specially designed homemade transmission cell. For real in situ TEM we use a commercial in situ holder with a home built gas feeding system and gas analytics. Conclusions: Two complimentary in situ techniques, namely in situ PGAA and in situ FTIR were utilities to investigate the surface coverage of the two most abundant species (Cl and OH). The OH density and Cl uptake were followed under multiple steady-state conditions as a function of p(O2), p(HCl), p(Cl2), and temperature. These experiments have shown that, the OH density positively correlates with the reactivity whereas Cl negatively. The p(HCl) experiments give rise to increased activity accompanied by Cl-coverage increase (opposite trend to p(O2) and T). Cl2 strongly inhibits the reaction, but no measurable increase of the Cl uptake was found. After considering all previous observations we conclude that only a minority of the available adsorption sites contribute to the reactivity. In addition, the mechanism of the catalysed reaction was proposed. The chlorine-oxygen competition for the available active sites renders re-oxidation as the rate-determining step of the catalysed reaction. Further investigations using in situ TEM are planned and will be conducted in the near future. Such experiments allow us to monitor active catalysts at the atomic scale under the most realistic conditions of temperature and pressure. The talk will shed a light on the potential and limitations of in situ PGAA and in situ TEM in the study of catalyst dynamics.

Keywords: CeO2, deacon process, in situ PGAA, in situ TEM, in situ FTIR

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Authors: Bharat Kumar, Deepak Kumar, Vijay Chaudhry

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Zirconium alloys are generally used for designing the core components of nuclear reactors due to their good mechanical and tribological properties. Some core components are subjected to flow-induced vibrations resulting in wear of these components due to their interaction with one another. To simulate these conditions, low amplitude reciprocating wear tests are conducted at room temperature and high temperature (260 degrees Celsius) between Zr-2.5Nb alloy and SS-410. The tests are conducted at a frequency range of 5 Hz to 25 Hz and an amplitude range of 200 µm to 600 µm. Friction and wear responses were recorded and correlated with the change in parameters. Worn surfaces are analysed using scanning electron microscopy (SEM) and optical profilometer. Elemental changes on the worn surfaces were determined using energy dispersive spectroscopy (EDS). The coefficient of friction (COF) increases with increasing temperature and decreases with increasing frequency. Adhesive wear is found to be the dominant wear mechanism which increases at high temperature.

Keywords: nuclear reactor, Zr-2.5Nb, SS-410, friction and wear

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Authors: H. N. S. Silva, S. N. Silva

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Introduction: The latest WHO data published in 2014 states that Sri Lanka has reached 2,773 of total deaths and over 14000 individuals’ sustained injuries due to RTAs each year. It was noticed in previous studies that policemen, three wheel drivers and also pedestrians were the first to respond to RTAs but the victim’s condition was aggravated due to unskilled attempts made by the responders while management of the victim’s wounds, moving and positioning of the victims and also mainly while transportation of the victims. Objective: To observe the practices of the urban public in Sri Lanka who are encountered with RTAs. Methods: A qualitative study was done to analyze public behavior seen on video recordings of scenes of accidents purposefully selected from social media, news websites, YouTube and Google. Results: The results showed that all individuals who tried to help during the RTA were middle aged men, who were mainly pedestrians, motorcyclists and policemen during that moment. Vast majority were very keen to actively help the victims to get to hospital as soon as possible and actively participated in providing 'aid'. But main problem was the first aid attempts were disorganized and uncoordinated. Even though all individuals knew how to control external bleeding, none of them was aware of spinal prevention techniques or management of limb injuries. Most of the transportation methods and transfer techniques used were inappropriate and more injury prone. Conclusions: The public actively engages in providing aid despite their inappropriate practices in giving first aid.

Keywords: encountered, pedestrians, road traffic accidents, urban public

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Authors: Matthew Yeager, Christopher Willy, John Bischoff

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The conceptualization and design phases of a system lifecycle consume a significant amount of the lifecycle budget in the form of direct tasking and capital, as well as the implicit costs associated with unforeseeable design errors that are only realized during downstream phases. Ad hoc or iterative approaches to generating system requirements oftentimes fail to consider the full array of feasible systems or product designs for a variety of reasons, including, but not limited to: initial conceptualization that oftentimes incorporates a priori or legacy features; the inability to capture, communicate and accommodate stakeholder preferences; inadequate technical designs and/or feasibility studies; and locally-, but not globally-, optimized subsystems and components. These design pitfalls can beget unanticipated developmental or system alterations with added costs, risks and support activities, heightening the risk for suboptimal system performance, premature obsolescence or forgone development. Supported by rapid advances in learning algorithms and hardware technology, sensors and sensor systems have become commonplace in both commercial and industrial products. The evolving array of hardware components (i.e. sensors, CPUs, modular / auxiliary access, etc…) as well as recognition, data fusion and communication protocols have all become increasingly complex and critical for design engineers during both concpetualization and implementation. This work seeks to develop and utilize a non-deterministic approach for sensor system design within the multi-attribute tradespace exploration (MATE) paradigm, a technique that incorporates decision theory into model-based techniques in order to explore complex design environments and discover better system designs. Developed to address the inherent design constraints in complex aerospace systems, MATE techniques enable project engineers to examine all viable system designs, assess attribute utility and system performance, and better align with stakeholder requirements. Whereas such previous work has been focused on aerospace systems and conducted in a deterministic fashion, this study addresses a wider array of system design elements by incorporating both traditional tradespace elements (e.g. hardware components) as well as popular multi-sensor data fusion models and techniques. Furthermore, statistical performance features to this model-based MATE approach will enable non-deterministic techniques for various commercial systems that range in application, complexity and system behavior, demonstrating a significant utility within the realm of formal systems decision-making.

Keywords: multi-attribute tradespace exploration, data fusion, sensors, systems engineering, system design

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

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: biological pathway, gene identification, object detection, Siamese network

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Authors: C. L Popa, C.S. Ciobanu, S. L. Iconaru, P. Chapon, A. Costescu, P. Le Coustumer, D. Predoi

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In this paper, the preparation and characterization of silver doped hydroxyapatite thin films and their antimicrobial activity characterized is reported. The resultant Ag: HAp films coated on commercially pure Si disks substrates were systematically characterized by Scanning Electron Microscopy (SEM) coupled with X-ray Energy Dispersive Spectroscopy detector (X-EDS), Glow Discharge Optical Emission Spectroscopy (GDOES) and Fourier Transform Infrared spectroscopy (FT-IR). GDOES measurements show that a substantial Ag content has been deposited in the films. The X-EDS and GDOES spectra revealed the presence of a material composed mainly of phosphate, calcium, oxygen, hydrogen and silver. The antimicrobial efficiency of Ag:HAp thin films against Escherichia coli and Staphylococcus aureus bacteria was demonstrated. Ag:HAp thin films could lead to a decrease of infections especially in the case of bone and dental implants by surface modification of implantable medical devices.

Keywords: silver, hydroxyapatite, thin films, GDOES, SEM, FTIR, antimicrobial effect

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Authors: Wanhyun Cho, Seongchae Seo, Soonja Kang

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In this work, we propose a variational technique for image contrast enhancement which utilizes global and local information around each pixel. The energy functional is defined by a weighted linear combination of three terms which are called on a local, a global contrast term and dispersion term. The first one is a local contrast term that can lead to improve the contrast of an input image by increasing the grey-level differences between each pixel and its neighboring to utilize contextual information around each pixel. The second one is global contrast term, which can lead to enhance a contrast of image by minimizing the difference between its empirical distribution function and a cumulative distribution function to make the probability distribution of pixel values becoming a symmetric distribution about median. The third one is a dispersion term that controls the departure between new pixel value and pixel value of original image while preserving original image characteristics as well as possible. Second, we derive the Euler-Lagrange equation for true image that can achieve the minimum of a proposed functional by using the fundamental lemma for the calculus of variations. And, we considered the procedure that this equation can be solved by using a gradient decent method, which is one of the dynamic approximation techniques. Finally, by conducting various experiments, we can demonstrate that the proposed method can enhance the contrast of colour images better than existing techniques.

Keywords: color image, contrast enhancement technique, variational approach, Euler-Lagrang equation, dynamic approximation method, EME measure

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Authors: Jaya Prasad Vanam, Vinay Anurag P, Vidya Sravya N S, Kishore Babu Nagamothu

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Constrained Groove Pressing (CGP) is one of the severe plastic deformation technique (SPD) by which we can process Ultra Fine Grained (UFG)/plane metallic materials. This paper discusses the effects of CGP on Cu-Zn alloy specimen at room temperature. A comprehensive study is made on the structural and mechanical properties of Brass specimen before and after Constrained grooves Pressing. Entire process is simulated in AFDEX CAE Software. It is found that most of the properties are superior with respect to brass samples such as yield strength, ultimate tensile strength, hardness, strain rate, etc., and they are found to be better for the CGP processed specimen. The results are discussed with respective graphs.

Keywords: constrained groove pressing, AFDEX, ultra fine grained materials, severe plastic deformation technique

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Authors: Ahmad Hashim, Masri Baharom

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The purpose of the study is to identify the age group of children 9 who have experienced delays in gross motor development. Instrument used in this study is Test Gross Motor Development / TGMD-2 (Ulrich, 2000) which was adopted at the international level. Gross motor development data were obtained by video recording (Sony (DRC-SR42 with a 40x optical zoom capability, and software Ultimate Studio 14) on locomotor and manipulative skills. A total n = 192 persons, children of 9 years (9.30 ± .431) at Sekolah Kebangsaan Mutiara Perdana, Bayan Lepas, Penang were involved as subjects. Children age 9 years experienced delays AELS (4.61 ± .69), AEMS (5:52 ± .62) and GMDQ (7.26 ± .2.14). The findings based on descriptive rating indicated that the performance of children age 9 years acquired low levels of AELS, MSS, AEMS and very low in LSS and GMDS.

Keywords: gross motor development score, locomotor standard score, age equivalent locomotor score, manipulative standard score, age equivalent manipulative score

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Valentina V. Goftman, Vladislav A. Pankratov, Alexey V. Markin, Tangi Aubert, Zeger Hens, Sarah De Saeger, Irina Yu. Goryacheva

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The most important requirements for biochemical applicability of quantum dots (QDs) are: 1) the surface cap should render intact or improved optical properties; 2) mono-dispersion and good stability in aqueous phase in a wide range of pH and ionic strength values; 3) presence of functional groups, available for bioconjugation; 4) minimal impact from the environment on the QDs’ properties and, vice versa, minimal influence of the QDs’ components on the environment; and 5) stability against chemical/biochemical/physical influence. The latter is especially important for in vitro and in vivo applications. For example, some physical intracellular delivery strategies (e.g., electroporation) imply a rapid high-voltage electric field impulse in order to temporarily generate hydrophilic pores in the cell plasma membrane, necessary for the passive transportation of QDs into the cell. In this regard, it is interesting to investigate how different capping layers, which can provide high stability and sufficient fluorescent properties of QDs in a water solution, behave under these abnormal conditions. In this contribution, hydrophobic core-shell CdSe/CdS/CdZnS/ZnS QDs (λem=600 nm), produced by means of the Successive Ion Layer Adsorption and Reaction (SILAR) technique, were transferred to a water solution using two of the most commonly used methods: (i) encapsulation in an amphiphilic brush polymer based on poly(maleic anhydride-alt-1-octadecene) (PMAO) modified with polyethylene glycol (PEG) chains and (ii) silica covering. Polymer encapsulation preserves the initial ligands on the QDs’ surface owing to the hydrophobic attraction between the hydrophobic groups of the amphiphilic molecules and the surface hydrophobic groups of the QDs. This covering process allows maintaining the initial fluorescent properties, but it leads to a considerable increase of the QDs’ size. However, covering with a silica shell, by means of the reverse microemulsion method, allows maintaining both size and fluorescent properties of the initial QDs. The obtained water solutions of polymer covered and silica-coated QDs in three different concentrations were exposed to a low-voltage electric field for a short time and the fluorescent properties were investigated. It is shown that the PMAO-PEG polymer acquires some additional charges in the presence of the electric field, which causes repulsion between the polymer and the QDs’ surface. This process destroys the homogeneity of the whole amphiphilic shell and it dramatically decreases the fluorescent properties (dropping to 10% from its initial value) because of the direct contact of the QDs with the strongly oxidative environment (water). In contrast, a silica shell possesses dielectric properties which allow retaining 90% of its initial fluorescence intensity, even after a longer electric impact. Thus, silica shells are clearly a preferable covering for bio-application of QDs, because – besides the high uniform morphology, controlled size and biocompatibility – it allows protecting QDs from oxidation, even under the influence of an electric field.

Keywords: electric field, polymer coating, quantum dots, silica covering, stability

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Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

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Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: data mining, k-means, road traffic accidents, Waze, Weka

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Authors: Humaira Khan, Mohsin Javed, Sammia Shahid

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The reinforced photocatalytic activity of graphene oxide (GO) along with composites of ZnO nanoparticles and copper-doped ZnO nanoparticles were studied by synthesizing ZnO and copper- doped ZnO nanoparticles by co-precipitation method. Zinc acetate and copper acetate were used as precursors, whereas graphene oxide was prepared from pre-oxidized graphite in the presence of H2O2.The supernatant was collected carefully and showed high-quality single-layer characterized by FTIR (Fourier Transform Infrared Spectroscopy), TEM (Transmission Electron Microscopy), SEM (Scanning Electron Microscopy), XRD (X-ray Diffraction Analysis), EDS (Energy Dispersive Spectrometry). The degradation of methylene blue as standard pollutant under UV-Visible irradiation gave results for photocatalytic activity of dopants. It could be concluded that shrinking of optical band caused by composites of Cu-dopped nanoparticles with GO enhances the photocatalytic activity.

Keywords: degradation, graphene oxide, photocatalysis, ZnO nanoparticles and copper-doped ZnO nanoparticles

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Authors: Malik Imran Afzal

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Cadmium supplied nanowires have unique electrical and optical properties and applications. To obtain cadmium supplied nanowires with regular and good aspect ratio, they can be synthesized by template synthesis method. Porous anodized aluminum oxide is the most promising template with regular hexagonal shapes. Their aspect ratio can be controlled by controlling the pores’ depth and diameter which greatly depend on anodization voltage and temperature of the electrolyte. In this research, high purity aluminium was used to prepare nanotemplates at 5-6°C in 1M phosphoric acid and cadmium supplied was deposited electrochemically using a co-solution of thiourea, cadmium acetate and ammonium acetate. pH was maintained at 11 in a heat bath at 75°C with the help of aqueous ammonia solution. Both porous anodized alumina and cadmium supplied nanowires were characterized suing SEM. A good quality Nanowires were obtained in bunches with reasonably high aspect ratio.

Keywords: bunches, electrodeposition, hexagonal, thiourea

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Authors: C. Boubechou, A. Bouchoucha, H. Zaidi

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The aim of this paper is to study the tribological behavior of a dynamic contact steel-brass couple with electric current. This study looks at a dry contact brass-steel couple where friction and wear are studied in terms of mechanical and electrical parameters. For this reason, a tribometer, pin-rotary disc is used in an atmospheric atmosphere. The test parameters are as follows: the normal load (5-30N), the sliding speed (0.1 to 0.5 m / s) and the electric current (3-10A). The duration of each test is 30 minutes. The experimental results show that these parameters have a significant effect on the tribological behavior of the couple studied. The discussion of results is based on observations, using an optical microscope, MEB and a profilometer, worn surfaces and interface phenomena resulting from the process of sliding contact.

Keywords: brass-steel couple, dry friction, electrical current, morphology, normal load, sliding speeds, wear

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Authors: Drissi Mokhtaria, Chouaih Abdelkader, Fodil Hamzaoui

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Our work is about a comparison of experimental and theoretical results of the electron charge density distribution and the electrostatic potential around the M-Nitrophenol Molecule (m-NPH) kwon for its interesting physical characteristics. The molecular experimental results have been obtained from a high-resolution X-ray diffraction study. Theoretical investigations were performed under the Gaussian program using the Density Functional Theory at B3LYP level of theory at 6-31G*. The multipolar model of Hansen and Coppens was used for the experimental electron charge density distribution around the molecule, while we used the DFT methods for the theoretical calculations. The electron charge density obtained in both methods allowed us to find out the different molecular properties such us the electrostatic potential and the dipole moment which were finally subject to a comparison leading to an outcome of a good matching results obtained in both methods.

Keywords: electron charge density, m-nitrophenol, nonlinear optical compound, electrostatic potential, optimized geometric

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Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

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Authors: Edmund M. Muthigani

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Innovation in the construction industry has been characterized by new products and processes especially in slum upgrading. The need for low cost housing has motivated stakeholders to think outside the box in coming up with solutions. This paper explored innovative construction technologies that have been used in slum upgrading. The main objectives of the paper was to examine innovations in the construction housing sector and to show how incremental derived demand for decent housing has led to adoption of innovative technologies and materials. Systematic literature review was used to review studies on innovative construction technologies in slum upgrading. The review revealed slow process of innovations in the construction industry due to risk aversion by firms and the hesitance to adopt by firms and individuals. Low profit margins in low cost housing and lack of sufficient political support remain the major hurdles to innovative techniques adoption that can actualize right to decent housing. Conventional construction materials have remained unaffordable to many people and this has negated them decent housing. This has necessitated exploration of innovative materials to realize low cost housing. Stabilized soil blocks and sisal-cement roofing blocks are some of the innovative construction materials that have been utilized in slum upgrading. These innovative materials have not only lowered the cost of production of building elements but also eased costs of transport as the raw materials to produce them are readily available in or within the slum sites. Despite their shortcomings in durability and compressive strength, they have proved worthwhile in slum upgrading. Production of innovative construction materials and use of innovative techniques in slum upgrading also provided employment to the locals.

Keywords: construction, housing, innovation, slum, technology

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Authors: Vishwas Goel, Kapil Surve, Somnath Basu

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In-situ alloying in steel during the electro-slag remelting (ESR) process has already been achieved by the addition of necessary ferroalloys into the electro-slag remelting mold. However, the use of commercially available ferroalloys during ESR processing is often found to be financially less favorable, in comparison with the conventional alloying techniques. However, a process of alloying steel with elements like chromium and manganese using the electro-slag remelting route is under development without any ferrochrome addition. The process utilizes in-situ reduction of refined mineral chromite (Cr₂O₃) and resultant enrichment of chromium in the steel ingot produced. It was established in course of this work that this process can become more advantageous over conventional alloying techniques, both economically and environmentally, for applications which inherently demand the use of the electro-slag remelting process, such as manufacturing of superalloys. A key advantage is the lower overall CO₂ footprint of this process relative to the conventional route of production, storage, and the addition of ferrochrome. In addition to experimentally validating the feasibility of the envisaged reactions, a mathematical model to simulate the reduction of chromium (III) oxide and transfer to chromium to the molten steel droplets was also developed as part of the current work. The developed model helps to correlate the amount of chromite input and the magnitude of chromium alloying that can be achieved through this process. Experiments are in progress to validate the predictions made by this model and to fine-tune its parameters.

Keywords: alloying element, chromite, electro-slag remelting, ferrochrome

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Authors: Alper Akin, Ibrahim Aydogdu

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This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teaching-learning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Keywords: optimum structural design, hybrid techniques, teaching-learning based optimization, harmony search algorithm, minimum weight, steel space frame

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Authors: Taysir Soliman

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One of the current popular clustering techniques is Spectral Clustering (SC) because of its advantages over conventional approaches such as hierarchical clustering, k-means, etc. and other techniques as well. However, one of the disadvantages of SC is the time consuming process because it requires computing the eigenvectors. In the past to overcome this disadvantage, a number of attempts have been proposed such as the Power Iteration Clustering (PIC) technique, which is one of versions from SC; some of PIC advantages are: 1) its scalability and efficiency, 2) finding one pseudo-eigenvectors instead of computing eigenvectors, and 3) linear combination of the eigenvectors in linear time. However, its worst disadvantage is an inter-class collision problem because it used only one pseudo-eigenvectors which is not enough. Previous researchers developed Deflation-based Power Iteration Clustering (DPIC) to overcome problems of PIC technique on inter-class collision with the same efficiency of PIC. In this paper, we developed Parallel DPIC (PDPIC) to improve the time and memory complexity which is run on apache spark framework using sparse matrix. To test the performance of PDPIC, we compared it to SC, ESCG, ESCALG algorithms on four small graph benchmark datasets and nine large graph benchmark datasets, where PDPIC proved higher accuracy and better time consuming than other compared algorithms.

Keywords: spectral clustering, power iteration clustering, deflation-based power iteration clustering, Apache spark, large graph

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Authors: S. K. Khosrowshahi, E. Güler

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This study investigates the reinforcement function of geosynthetics on the shear strength and strain profile of sand. Conducting a series of simple shear tests, the shearing behavior of the samples under static and cyclic loads was evaluated. Three different types of geosynthetics including geotextile and geonets were used as the reinforcement materials. An image processing analysis based on the optical flow method was performed to measure the lateral displacements and estimate the shear strains. It is shown that besides improving the shear strength, the geosynthetic reinforcement leads a remarkable reduction on the shear strains. The improved layer reduces the required thickness of the soil layer to resist against shear stresses. Consequently, the geosynthetic reinforcement can be considered as a proper approach for the sustainable designs, especially in the projects with huge amount of geotechnical applications like subgrade of the pavements, roadways, and railways.

Keywords: image processing, soil reinforcement, geosynthetics, simple shear test, shear strain profile

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Authors: Kelly Jo Hollingsworth

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Conversational Solfege, a research-based, 12-step music literacy instructional method using the sound-before-sight approach, was used to teach rhythm-reading to 128-second grade students at a public school in the southeastern United States. For each step, multiple scripted techniques are supplied to teach each skill. Unit one was the focus of this study, which is quarter note and barred eighth note rhythms. During regular weekly music instruction, students completed method steps one through five, which includes aural discrimination, decoding familiar and unfamiliar rhythm patterns, and improvising rhythmic phrases using quarter notes and barred eighth notes. Intact classes were randomly assigned to two treatment groups for teaching steps six through eight, which was the visual presentation and identification of quarter notes and barred eighth notes, visually presenting and decoding familiar patterns, and visually presenting and decoding unfamiliar patterns using said notation. For three weeks, students practiced steps six through eight during regular weekly music class. One group spent five-minutes of class time on steps six through eight technique work, while the other group spends ten-minutes of class time practicing the same techniques. A pretest and posttest were administered, and ANOVA results reveal both the five-minute (p < .001) and ten-minute group (p < .001) reached statistical significance suggesting Conversational Solfege is an efficient, effective approach to teach rhythm-reading to second grade students. After two weeks of no instruction, students were retested to measure retention. Using a repeated-measures ANOVA, both groups reached statistical significance (p < .001) on the second posttest, suggesting both the five-minute and ten-minute group retained rhythm-reading skill after two weeks of no instruction. Statistical significance was not reached between groups (p=.252), suggesting five-minutes is equally as effective as ten-minutes of rhythm-reading practice using Conversational Solfege techniques. Future research includes replicating the study with other grades and units in the text.

Keywords: conversational solfege, length of instructional time, rhythm-reading, rhythm instruction

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Authors: Ajit Brindhaban

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Background and Purpose: Computed Tomography (CT) scans have become the largest source of radiation in radiological imaging. The purpose of this study was to compare the quality of pediatric Computed Tomography (CT) images reconstructed using Filtered Back Projection (FBP) with images reconstructed using different strengths of Iterative Reconstruction (IR) technique, and to perform a feasibility study to assess the use of IR techniques as a dose reduction tool. Materials and Methods: An anthropomorphic phantom representing a 5-year old child was scanned, in two stages, using a Siemens Somatom CT unit. In stage one, scans of the head, chest and abdomen were performed using standard protocols recommended by the scanner manufacturer. Images were reconstructed using FBP and 5 different strengths of IR. Contrast-to-Noise Ratios (CNR) were calculated from average CT number and its standard deviation measured in regions of interest created in the lungs, bone, and soft tissues regions of the phantom. Paired t-test and the one-way ANOVA were used to compare the CNR from FBP images with IR images, at p = 0.05 level. The lowest strength value of IR that produced the highest CNR was identified. In the second stage, scans of the head was performed with decreased mA(s) values relative to the increase in CNR compared to the standard FBP protocol. CNR values were compared in this stage using Paired t-test at p = 0.05 level. Results: Images reconstructed using IR technique had higher CNR values (p < 0.01.) in all regions compared to the FBP images, at all strengths of IR. The CNR increased with increasing IR strength of up to 3, in the head and chest images. Increases beyond this strength were insignificant. In abdomen images, CNR continued to increase up to strength 5. The results also indicated that, IR techniques improve CNR by a up to factor of 1.5. Based on the CNR values at strength 3 of IR images and CNR values of FBP images, a reduction in mA(s) of about 20% was identified. The images of the head acquired at 20% reduced mA(s) and reconstructed using IR at strength 3, had similar CNR as FBP images at standard mA(s). In the head scans of the phantom used in this study, it was demonstrated that similar CNR can be achieved even when the mA(s) is reduced by about 20% if IR technique with strength of 3 is used for reconstruction. Conclusions: The IR technique produced better image quality at all strengths of IR in comparison to FBP. IR technique can provide approximately 20% dose reduction in pediatric head CT while maintaining the same image quality as FBP technique.

Keywords: filtered back projection, image quality, iterative reconstruction, pediatric computed tomography imaging

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Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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Authors: Bozena Tyliszczak, Anna Drabczyk, Sonia Kudlacik-Kramarczyk, Agnieszka Sobczak-Kupiec

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Introduction: Nanomaterials become one of the leading materials in the synthesis of various compounds. This is a reason for the fact that nano-size materials exhibit other properties compared to their macroscopic equivalents. Such a change in size is reflected in a change in optical, electric or mechanical properties. Among nanomaterials, particular attention is currently directed into gold nanoparticles. They find application in a wide range of areas including cosmetology or pharmacy. Additionally, nanogold may be a component of modern wound dressings, which antibacterial activity is beneficial in the viewpoint of the wound healing process. Specific properties of this type of nanomaterials result in the fact that they may also be applied in cancer treatment. Studies on the development of new techniques of the delivery of drugs are currently an important research subject of many scientists. This is due to the fact that along with the development of such fields of science as medicine or pharmacy, the need for better and more effective methods of administering drugs is constantly growing. The solution may be the use of drug carriers. These are materials that combine with the active substance and lead it directly to the desired place. A role of such a carrier may be played by gold nanoparticles that are able to covalently bond with many organic substances. This allows the combination of nanoparticles with active substances. Therefore gold nanoparticles are widely used in the preparation of nanocomposites that may be used for medical purposes with special emphasis on drug delivery. Methodology: As part of the presented research, synthesis of composites was carried out. The mentioned composites consisted of the polymer matrix and gold nanoparticles that were introduced into the polymer network. The synthesis was conducted with the use of a crosslinking agent, and photoinitiator and the materials were obtained by means of the photopolymerization process. Next, incubation studies were conducted using selected liquids that simulated fluids are occurring in the human body. The study allows determining the biocompatibility of the tested composites in relation to selected environments. Next, the chemical structure of the composites was characterized as well as their sorption properties. Conclusions: Conducted research allowed for the preliminary characterization of prepared polymer composites containing gold nanoparticles in the viewpoint of their application for biomedical use. Tested materials were characterized by biocompatibility in tested environments. What is more, synthesized composites exhibited relatively high swelling capacity that is essential in the viewpoint of their potential application as drug carriers. During such an application, composite swells and at the same time releases from its interior introduced active substance; therefore, it is important to check the swelling ability of such material. Acknowledgements: The authors would like to thank The National Science Centre (Grant no: UMO - 2016/21/D/ST8/01697) for providing financial support to this project. This paper is based upon work from COST Action (CA18113), supported by COST (European Cooperation in Science and Technology).

Keywords: nanocomposites, gold nanoparticles, drug carriers, swelling properties

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Authors: Hui-Hsin Huang, Yi-Feng Lin, Che-Chia Hu

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To date, photocatalytic wastewater treatment using solar energy has attracted considerable attention. In this study, strontium titanates with various morphologies, i.e., nanofibers and cubic-like particles, were prepared as photocatalysts using the electrospinning (ES), solid-state (SS), and sol-gel (SG) methods. X-ray diffraction (XRD) analysis showed that ES and SS can be assigned to pure phase SrTiO3, while SG was referred to Sr2TiO4. These samples displayed optical absorption edges at 385-395 nm, indicating they can be activated in UV light irradiation. Scanning electron microscope (SEM) analyses revealed that ES SrTiO3 has a uniform fibrous structure with length and diameter of several microns and 100-200 nm, respectively. After loading of nanoparticulate Ag as a co-catalyst onto the surface of strontium titanates, ES sample exhibited highest photocatalytic activity to degrade methylene orange dye solution in comparison to that of SS and SG ones. These results indicate that Ag-loaded ES SrTiO3, which has a desirable SrTiO3 phase and a facile electron transfer along the preferential direction in fibrous structure, can be a promising photocatalyst.

Keywords: photocatalytic degradation, strontium titanate, electrospinning, co-catalyst

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Authors: Temesgen Geremew

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ZnO is currently receiving a lot of attention in the semiconductor industry due to its unique characteristics. ZnO is widely used in solar cells, heat-reflecting glasses, optoelectronic bias, and detectors. In this composition, we provide an overview of the ZnO thin flicks' packages, methods of characterization, and implicit operations. They consist of Transmission spectroscopy, Raman spectroscopy, Field emigration surveying electron microscopy, and X-ray diffraction. This review content also demonstrates how ZnO thin flicks function in electrical components for piezoelectric bias, optoelectronics, detectors, and renewable energy sources. Zinc oxide (ZnO) thin films offer a captivating tapestry of possibilities due to their unique blend of electrical, optical, and mechanical properties. This review delves into the realm of their potential applications and future prospects, highlighting the pivotal contributions of research endeavors aimed at tailoring their functionalities.

Keywords: Zinc oxide, raman spectroscopy, thin films, piezoelectric devices

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

Procedia PDF Downloads 106