Search results for: lunar surface/subsurface detection

Authors: Xiaodi Su, Xin Ting Zheng, Laura Sutarlie, Nur Asinah binte Mohamed Salleh, Yong Yu

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Wound healing is a dynamic process with multiple phases. Rapid profiling and quantitative characterization of inflammation and infection remain challenging. We have developed paper-like battery-free multiplexed sensors for holistic wound assessment via quantitative detection of multiple inflammation and infection markers. In one of the designs, the sensor patch consists of a wax-printed paper panel with five colorimetric sensor channels arranged in a pattern resembling a five-petaled flower (denoted as a ‘Petal’ sensor). The five sensors are for temperature, pH, trimethylamine, uric acid, and moisture. The sensor patch is sandwiched between a top transparent silicone layer and a bottom adhesive wound contact layer. In the second design, a palm-like-shaped paper strip is fabricated by a paper-cutter printer (denoted as ‘Palm’ sensor). This sensor strip carries five sensor regions connected by a stem sampling entrance that enables rapid colorimetric detection of multiple bacteria metabolites (aldehyde, lactate, moisture, trimethylamine, tryptophan) from wound exudate. For both the “\’ Petal’ and ‘Palm’ sensors, color images can be captured by a mobile phone. According to the color changes, one can quantify the concentration of the biomarkers and then determine wound healing status and identify/quantify bacterial species in infected wounds. The ‘Petal’ and ‘Palm’ sensors are validated with in-situ animal and ex-situ skin wound models, respectively. These sensors have the potential for integration with wound dressing to allow early warning of adverse events without frequent removal of the plasters. Such in-situ and early detection of non-healing condition can trigger immediate clinical intervention to facilitate wound care management.

Keywords: wound infection, colorimetric sensor, paper fluidic sensor, wound care

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Authors: Ganesh Meshram, Gloria Biswal

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In this study, we present the numerical investigation of surface wettability on triangular micropillar surfaces by using a two-dimensional (2D) pseudo-potential multiphase lattice Boltzmann method with a D2Q9 model for various interaction parameters of the range varies from -1.40 to -2.50. Initially, simulation of the equilibrium state of a water droplet on a flat surface is considered for various interaction parameters to examine the accuracy of the present numerical model. We then imposed the microscale pillars on the bottom wall of the surface with different heights of the pillars to form the hydrophobic and superhydrophobic surfaces which enable the higher contact angle. The wettability of surfaces is simulated with water droplets of radius 100 lattice units in the domain of 800x800 lattice units. The present study shows that increasing the interaction parameter of the pillared hydrophobic surfaces dramatically reduces the contact area between water droplets and solid walls due to the momentum redirection phenomenon. Contact angles for different values of interaction strength have been validated qualitatively with the analytical results.

Keywords: contact angle, lattice boltzmann method, d2q9 model, pseudo-potential multiphase method, hydrophobic surfaces, wenzel state, cassie-baxter state, wettability

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Authors: Farah Marsusi, Mohammad Qasemnazhand

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Density-functional theory (DFT) was applied to investigate the geometry and electronic properties H-terminated Si-fullerene (Si-fullerane). Natural bond orbital (NBO) analysis confirms sp3 hybridization nature of Si-Si bonds in Si-fulleranes. Quantum confinement effect (QCE) does not affect band gap (BG) so strongly in the size between 1 to 1.7 nm. In contrast, the geometry and symmetry of the cage have significant influence on BG. In contrast to their carbon analogues, pentagon rings increase the stability of the cages. Functionalized Si-cages are stable and can be chemically very active. The electronic properties are highly sensitive to the surface chemistry via functionalization with different chemical groups. As a result, BGs and chemical activities of these cages can be drastically tuned through the chemistry of the surface.

Keywords: density functional theory, sila-fullerens, NBO analysis, opto-electronic properties

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Authors: P. Novosad, L. Osuska, M. Tazky, T. Tazky

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Current trends in the building industry are oriented towards the reduction of maintenance costs and the ecological benefits of buildings or building materials. Surface treatment of building materials with photocatalytic active titanium dioxide added into concrete can offer a good solution in this context. Architectural concrete has one disadvantage – dust and fouling keep settling on its surface, diminishing its aesthetic value and increasing maintenance e costs. Concrete surface – silicate material with open porosity – fulfils the conditions of effective photocatalysis, in particular, the self-cleaning properties of surfaces. This modern material is advantageous in particular for direct finishing and architectural concrete applications. If photoactive titanium dioxide is part of the top layers of road concrete on busy roads and the facades of the buildings surrounding these roads, exhaust fumes can be degraded with the aid of sunshine; hence, environmental load will decrease. It is clear that options for removing pollutants like nitrogen oxides (NOx) must be found. Not only do these gases present a health risk, they also cause the degradation of the surfaces of concrete structures. The photocatalytic properties of titanium dioxide can in the long term contribute to the enhanced appearance of surface layers and eliminate harmful pollutants dispersed in the air, and facilitate the conversion of pollutants into less toxic forms (e.g., NOx to HNO₃). This paper describes verification of the photocatalytic properties of titanium dioxide and presents the results of mechanical and physical tests on samples of architectural lightweight self-compacting concretes (LWSCC). The very essence of the use of LWSCC is their rheological ability to seep into otherwise extremely hard accessible or inaccessible construction areas, or sections thereof where concrete compacting will be a problem, or where vibration is completely excluded. They are also able to create a solid monolithic element with a large variety of shapes; the concrete will at the same meet the requirements of both chemical aggression and the influences of the surrounding environment. Due to their viscosity, LWSCCs are able to imprint the formwork elements into their structure and thus create high quality lightweight architectural concretes.

Keywords: photocatalytic concretes, titanium dioxide, architectural concretes, Lightweight Self-Compacting Concretes (LWSCC)

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Authors: Bensacia Nabila, Hadj-Ziane Amel, Sefah Karima

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Carbon nanocomposites have received more attention in the last years in view of their special properties such as low density, high specific surface area, and thermal and mechanical stability. Taking into account the importance of these materials, many studies aimed at improving the synthesis process have been conducted. However, the presence of impurities could affect significantly the properties of these materials, and the characterization of these compounds is an important challenge to assure the quality of the new carbon nanocomposites. The present study aims to develop a new recyclable decontaminating material for dyes removal. This new material consists of an active element based on carbon nanotubes wrapped in a microcapsule of iron oxide. The adsorbent is characterized by Transmission electron microscopy, X-ray diffraction and the surface area was measured by the BET method.

Keywords: carbon nanocomposite, chitozen, elimination, dyes

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Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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Authors: Roli Saini, Pradeep Kumar

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A coagulation/flocculation process was adopted for the reduction of carbamate insecticide (carbofuran) from aqueous solution. Ferric chloride (FeCl₃) was used as a coagulant to treat the carbofuran. To exploit the reduction efficiency of pesticide concentration and COD, the jar-test experiments were carried out and process was optimized through response surface methodology (RSM). The effects of two independent factors; i.e., FeCl₃ dosage and pH on the reduction efficiency were estimated by using central composite design (CCD). The initial COD of the 30 mg/L concentrated solution was found to be 510 mg/L. Results exposed that the maximum reduction occurred at an optimal condition of FeCl₃ = 80 mg/L, and pH = 5.0, from which the reduction of concentration and COD 75.13% and 65.34%, respectively. The present study also predicted that the obtained regression equations could be helpful as the theoretical basis for the coagulation process of pesticide wastewater.

Keywords: carbofuran, coagulation, optimization, response surface methodology

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Authors: Samiul Islam Hazarika, Domngam Boje, Ananta Kumar Atta

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It is well familiar that solvents play a significant role in modern chemistry. Solvents can change the reactivity and physicochemical properties of molecules in a solution. Keeping this in mind, we have designed and synthesized a mono-triazolyl-linked pyrenyl-appended xylofuranose derivative for the detection of metal ions with changing solvent systems. The incorporation of a sugar backbone in the sensor increases the water solubility and biocompatibility. The experimental study revealed that the xylofuranose-based fluorescence probe did not exhibit any specific selectivity towards metal ions in acetonitrile (CH₃CN) solvent. Whereas, we revealed that triazole-linked pyrenyl-appended xylofuranose-based fluorescent sensor would exhibit high selectivity and sensitivity towards Au³⁺ ions in CH₃CN-H₂O (1/1, v/v) system. This observation might be explained by the viscosity and polarity differences of CH₃CN and CH₃CN-H₂O solvent systems. The formation of the sensor-Au³⁺ complex was also established by high-resolution mass spectrometry (HRMS) data of the complex.

Keywords: triazole, furanose, fluorometric, solvent dependent

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Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: S. A. M. Sabrina, Gouget Lammel, Anne Chantal, Chazalviel, Jean Noël, Ozanam François, Etcheberry Arnaud, Tighlit Fatma Zohra, B. Samia, Gabouze Noureddine

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The elaboration and characterization of hybrid nano materials give rise to considerable interest due to the new properties that arising. They are considered as an important category of new materials having innovative characteristics by combining the specific intrinsic properties of inorganic compounds (semiconductors) with the grafted organic species. This open the way to improved properties and spectacular applications in various and important fields, especially in the environment. In this work, nano materials based-semiconductors were elaborated by chemical route. The obtained surfaces were grafted with organic functional groups. The functionalization process was optimized in order to confer to the hybrid nano material a good stability as well as the right properties required for the subsequent applications. Different characterization techniques were used to investigate the resulting nano structures, such as SEM, UV-Visible, FTIR, Contact angle and electro chemical measurements. Finally, applications were envisaged in environmental area. The elaborated nano structures were tested for the detection and the elimination of pollutants.

Keywords: hybrid materials, porous silicon, peptide, metal detection

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Authors: Sahana Selladurai, Christine DeWolf

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Lung surfactant comprises a lipid-protein film that coats the alveolar surface and serves to prevent alveolar collapse upon repeated breathing cycles. Exposure of lung surfactant to high concentrations of airborne pollutants, for example tropospheric ozone in smog, can chemically modify the lipid and protein components. These chemical changes can impact the film functionality by decreasing the film’s collapse pressure (minimum surface tension attainable), altering it is mechanical and flow properties and modifying lipid reservoir formation essential for re-spreading of the film during the inhalation process. In this study, we use Langmuir monolayers spread at the air-water interface as model membranes where the compression and expansion of the film mimics the breathing cycle. The impact of ozone exposure on model lung surfactant films is measured using a Langmuir film balance, Brewster angle microscopy and a pendant drop tensiometer as a function of film and sub-phase composition. The oxidized films are analyzed using mass spectrometry where lipid and protein oxidation products are observed. Oxidation is shown to reduce surface activity, alter line tension (and film morphology) and in some cases visibly reduce the viscoelastic properties of the film when compared to controls. These reductions in functionality of the films are highly dependent on film and sub-phase composition, where for example, the effect of oxidation is more pronounced when using a physiologically relevant buffer as opposed to water as the sub-phase. These findings can lead to a better understanding on the impact of continuous exposure to high levels of ozone on the mechanical process of breathing, as well as understanding the roles of certain lung surfactant components in this process.

Keywords: lung surfactant, oxidation, ozone, viscoelasticity

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Authors: Angad S. Kushwaha, Rajeev Kumar, Monika Srivastava, S. K. Srivastava

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A lot of research work is going on in the field of graphene based SPR biosensor. In the conventional SPR based biosensor, graphene is used as a biomolecular recognition element. Graphene adsorbs biomolecules due to carbon based ring structure through sp2 hybridization. The proposed SPR based biosensor configuration will open a new avenue for efficient biosensing by taking the advantage of Graphene and its fascinating nanofabrication properties. In the present study, we have studied an SPR biosensor based on graphene mediated by Zinc Oxide (ZnO) and Gold. In the proposed structure, prism (BK7) base is coated with Zinc Oxide followed by Gold and Graphene. Using the waveguide approach by transfer matrix method, the proposed structure has been investigated theoretically. We have analyzed the reflectance versus incidence angle curve using He-Ne laser of wavelength 632.8 nm. Angle, at which the reflectance is minimized, termed as SPR angle. The shift in SPR angle is responsible for biosensing. From the analysis of reflectivity curve, we have found that there is a shift in SPR angle as the biomolecules get attached on the graphene surface. This graphene layer also enhances the sensitivity of the SPR sensor as compare to the conventional sensor. The sensitivity also increases by increasing the no of graphene layer. So in our proposed biosensor we have found minimum possible reflectivity with optimum level of sensitivity.

Keywords: biosensor, sensitivity, surface plasmon resonance, transfer matrix method

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Authors: Amaladhithyan Krishnamoorthy, Ruvaitha Banu

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Vision is considered as the most important sense in humans, without which leading a normal can be often difficult. There are many existing smart canes for visually impaired with obstacle detection using ultrasonic transducer to help them navigate. Though the basic smart cane increases the safety of the users, it does not help in filling the void of visual loss. This paper introduces the concept of Digi-Buddy which is an evolved smart cane for visually impaired. The cane consists for several modules, apart from the basic obstacle detection features; the Digi-Buddy assists the user by capturing video/images and streams them to the server using a wide-angled camera, which then detects the objects using Deep Convolutional Neural Network. In addition to determining what the particular image/object is, the distance of the object is assessed by the ultrasonic transducer. The sound generation application, modelled with the help of Natural Language Processing is used to convert the processed images/object into audio. The object detected is signified by its name which is transmitted to the user with the help of Bluetooth hear phones. The object detection is extended to facial recognition which maps the faces of the person the user meets in the database of face images and alerts the user about the person. One of other crucial function consists of an automatic-intimation-alarm which is triggered when the user is in an emergency. If the user recovers within a set time, a button is provisioned in the cane to stop the alarm. Else an automatic intimation is sent to friends and family about the whereabouts of the user using GPS. In addition to safety and security by the existing smart canes, the proposed concept devices to be implemented as a prototype helping visually-impaired visualize their surroundings through audio more in an amicable way.

Keywords: artificial intelligence, facial recognition, natural language processing, internet of things

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Authors: Arturs Macanovskis, Vitalijs Lusis, Andrejs Krasnikovs

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Work has three stages. In the first stage was examined pull-out process for steel fiber was embedded into a concrete by one end and was pulled out of concrete under the angle to pulling out force direction. Angle was varied. Length of steel fiber was 26 mm, diameter 0.5 mm. On the obtained force- displacement diagrams were observed jumps. For such mechanical behavior explanation, fiber channel in concrete surface microscopical experimental investigation, using microscope KEYENCE VHX2000, was performed. Surface of fiber channel in concrete matrix after pull-out test (fiber angle to pulling out force direction 70°). At the second stage were obtained diagrams for load- crack opening displacement for breaking homogeneously reinforced and layered fiber concrete prisms (with dimensions 10x10x40 cm) subjected to 4-point bending. After testing was analyzed main crack. On the main crack’s both surfaces were recognized all pulled out fibers their locations, angles to crack surface and lengths of pull-out fibers parts. At the third stage elaborated prediction model for the fiber-concrete beam, failure under bending, using the following data: a) diagrams for fibers pulling out at different angles; b) experimental data about steel-straight fibers locations in the main crack.

Keywords: fiberconcrete, pull-out, fiber channel, layered fiberconcrete

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Authors: Ambrish Singh

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The corrosion inhibition performance of pyran derivatives (AP) on mild steel in 15% HCl was investigated by electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, weight loss, contact angle, and scanning electron microscopy (SEM) measurements, DFT and molecular dynamic simulation. The adsorption of APs on the surface of mild steel obeyed Langmuir isotherm. The potentiodynamic polarization study confirmed that inhibitors are mixed type with cathodic predominance. Molecular dynamic simulation was applied to search for the most stable configuration and adsorption energies for the interaction of the inhibitors with Fe (110) surface. The theoretical data obtained are, in most cases, in agreement with experimental results.

Keywords: acidizing inhibitor, pyran derivatives, DFT, molecular simulation, mild steel, EIS

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Authors: Mohammadjavad Palimi, D. Y. Li, E. Kuru

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Emulsion-based drilling fluids containing mineral oil are commonly used for drilling operations, which generate a lubricating film to prevent direct contact between moving metal parts, thus reducing friction, wear, and corrosion. For long-lasting lubrication, the thin lubricating film formed on the metal surface should possess good anti-wear and anti-corrosion capabilities. This study aims to investigate the effects of two additives, TERGITOL NP-9 and PEG-10 oleyl phosphate, acting as surfactant and corrosion inhibitor, respectively, on the tribo-corrosion behavior of 1018 carbon steel immersed in 5% KCl solution at room temperature. A pin-on-disc tribometer attached to an electrochemical system was used to investigate the corrosive wear of the steel immersed in emulsion-based fluids containing the surfactant and corrosion inhibitor. The wear track, surface chemistry and composition of the protective film formed on the steel surface were analyzed with an optical profilometer, SEM, and SEM-EDX. Results of the study demonstrate that the performance of the emulsion-based drilling fluids was significantly improved by the corrosion inhibitor by a remarkable reduction in corrosion, coefficient of friction (COF) and wear.

Keywords: corrosion inhibitor, emulsion-based drilling fluid, tribo-corrosion, friction, wear

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Authors: Jerman Madonsela, Wallace Matizamhuka, Akiko Yamamoto, Ronald Machaka, Brendon Shongwe

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In this study, biocompatibility evaluation of nanostructured near beta Ti-24Nb-4Zr-8Sn (Ti2448) alloy with non-toxic elements produced utilizing Spark plasma sintering (SPS) of very fine microsized powders attained through mechanical alloying was performed. The results were compared with pure titanium and Ti-6Al-4V (Ti64) alloy. Cell proliferation test was performed using murine osteoblastic cells, MC3T3-E1 at two cell densities; 400 and 4000 cells/mL for 7 days incubation. Pure titanium took a lead under both conditions suggesting that the presence of other oxide layers influence cell proliferation. No significant difference in cell proliferation was observed between Ti64 and Ti2448. Potentiodynamic measurement in Hanks, 0.9% NaCl and cell culture medium showed no distinct difference on the anodic polarization curves of the three alloys, indicating that the same anodic reaction occurred on their surface but with different rates. However, Ti2448 showed better corrosion resistance in cell culture medium with a slightly lower corrosion rate of 2.96 nA/cm2 compared to 4.86 nA/cm2 and 5.62 nA/cm2 of Ti and Ti64 respectively. Ti2448 adsorbed less protein as compared to Ti and Ti64 though no notable difference in surface wettability was observed.

Keywords: biocompatibility, osteoblast, corrosion, surface wettability, protein adsorption

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Vicario Marina, Bustos Freddy, Olivares Jesús, Gómez Pilar

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This paper presents a didactic model and a tool as educational resources to support the learning of geometry; they focus on topics difficult to understand. The target population is elementary school students. The tool is based on a collaborative educational approach using multi-touch devices. The proposal is based on the challenges found in the instructional design and prototype implementation. Traditionally, elementary students have had many problems assimilating mathematical topics; this new Educatronic prototype facilitates the learning experience using exercises and they were tested with different children demonstrating the benefits of the prototype by improving their mathematical skills.

Keywords: educatronic prototype, geometry, multitouch surface, educational computing, primary school, mathematics, educational informatics

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Lakshmi E. Jayachandran, Manepally Rajkumar, Pavuluri Srinivasa Rao

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The objective of this research was to study the changes in eating quality of rice during storage under varying temperature and moisture regimes. Paddy (IR-36) with high amylose content (27%) was stored at a temperature range between 10 to 40°C and moisture content from 9 to 18% (d.b.) for 6 months. Drastic changes in color and parameters representing cooking qualities, cooked rice texture, and surface morphology occurred after 4 months of storage, especially at elevated temperature conditions. Head rice yield was stable throughout the storage except at extreme conditions of temperature and moisture content. Yellowing of rice was prominent at combinations of high temperature and moisture content, both of which had a synergistic effect on the b* values of rice. The cooking time, length expansion ratio and volume expansion ratio of all the rice samples increased with prolonged storage. The texture parameter, primarily, the hardness, cohesiveness, and adhesiveness of cooked rice samples were higher following storage at elevated temperature. Surface morphology was also significantly affected in stored rice as compared to fresh rice. Storage of rice at 10°C with a grain moisture content of 10% for 2 months gave cooked rice samples with good palatability and minimal cooking time. The temperature was found to be the most prominent storage parameter for rough rice, followed by moisture content and storage duration, influencing the quality of rice.

Keywords: rice, cooking quality, storage, surface morphology

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Authors: Iman Adnan Annon, Kadhim F. Alsultan

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This study investigate the internal corrosion of low carbon steel pipelines in the crude oil, as well as prepare and use natural and locally available plant as a natural corrosion inhibiter, the nature extraction achieved by two types of solvents in order to show the solvent effect on inhibition process, the first being distilled water and the second is diethyl ether. FT-IR spectra and using a chemical reagents achieved to detection the presence of many active groups and the presence of tannins, phenols, and alkaloids in the natural extraction. Some experiments were achieved to estimate the performance of a new inhibitor, one of these tests include corrosion measurement by simple immersion in crude oil within and without inhibitors which added in different amounts 30,40,50and 60 ppm at tow temperature 300 and 323k, where the best inhibition efficiencies which get when added the inhibitors in a critical amounts or closest to it, since for the aqueous extract (EB-A) the inhibition efficiency reached (94.4) and (86.71)% at 300 and 323k respectively, and for diethyl ether extract (EB-D) reached (82.87) and (84.6)% at 300 and 323k respectively. Optical microscopy examination have been conducted to evaluate the corrosion nature where it show a clear difference in the topography of the immersed samples surface after add the inhibitors at two temperatures. The results show that the new corrosion inhibitor is not only equivalent to a chemical inhibitor but has greatly improvement properties such as: high efficiency, low cost, non-toxic, easily to produce, and nonpolluting as compared with chemical inhibitor.

Keywords: corrosion in pipeline, inhibitors, crude oil, carbon steel, types of solvent

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Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

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A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: bistatic radar cross section, passive radar, propagation losses, radar coverage

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: S. M. Hamidi, M. Zamani

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Magneto-plasmonic (MP) structures have turned into essential tools for the amplification of magneto-optical (MO) responses via the combination of MO activity and surface Plasmon resonance (SPR). Both the plasmonic and the MO properties of the resulting MP structure become interrelated because the SPR of the metallic medium. This interconnection can be modified the wave vector of surface plasmon polariton (SPP) in MP multilayer [1] or enhanced the MO activity [2- 3] and also modified the sensor responses [4]. There are several types of MP structures which are studied to enhance MO response in miniaturized configuration. In this paper, we propose a new MP structure based on the nano-metal grating and we investigate the MO and optical properties of this new structure. Our new MP structure fabricate by DC magnetron sputtering method and our home made MO experimental setup use for characterization of the structure.

Keywords: Magneto-plasmonic structures, magneto-optical effect, nano-garting

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Authors: Jaehoon Ha, Byungmo Kang, Kilho Hong, Jungsoo Park

Abstract:

Electro-optical (EO) stabilized platforms have been widely used for surveillance and reconnaissance on various types of vehicles, from surface ships to unmanned air vehicles (UAVs). EO stabilized platforms usually consist of an assembly of structure, bearings, and motors called gimbals in which a gyroscope is installed. EO elements such as a CCD camera and IR camera, are mounted to a gimbal, which has a range of motion in elevation and azimuth and can designate and track a target. In addition, a laser range finder (LRF) can be added to the gimbal in order to acquire the precise slant range from the platform to the target. Recently, a versatile functionality of target localization is needed in order to cooperate with the weapon systems that are mounted on the same platform. The target information, such as its location or velocity, needed to be more accurate. The accuracy of the target information depends on diverse component errors and alignment errors of each component. Specially, the type of moving platform can affect the accuracy of the target information. In the case of flying platforms, or UAVs, the target location error can be increased with altitude so it is important to measure altitude as precisely as possible. In the case of surface ships, target location error can be increased with obliqueness of the elevation angle of the gimbal since the altitude of the EO stabilized platform is supposed to be relatively low. The farther the slant ranges from the surface ship to the target, the more extreme the obliqueness of the elevation angle. This can hamper the precise acquisition of the target information. So far, there have been many studies on EO stabilized platforms of flying vehicles. However, few researchers have focused on ship-borne EO stabilized platforms of the surface ship. In this paper, we deal with a target localization method when an EO stabilized platform is located on the mast of a surface ship. Especially, we need to overcome the limitation caused by the obliqueness of the elevation angle of the gimbal. We introduce a well-known approach for target localization using Unscented Kalman Filter (UKF) and present the problem definition showing the above-mentioned limitation. Finally, we want to show the effectiveness of the approach that will be demonstrated through computer simulations.

Keywords: target localization, ship-borne electro-optical stabilized platform, unscented kalman filter

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Authors: Jonathan Heng, Yoong Cheah Huei

Abstract:

A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

Procedia PDF Downloads 175

Authors: Abdelmajid Timoumi, Salah Alamri, Hatem Alamri

Abstract:

TiO₂ Graphene Oxide (TiO₂-GO) nanocomposite was prepared using the spin coating technique of suspension of Graphene Oxide (GO) nanosheets and Titanium Tetra Isopropoxide (TIP). The prepared nanocomposites samples were characterized by X-ray diffractometer, Scanning Electron Microscope and Atomic Force Microscope to examine their structures and morphologies. UV-vis transmittance and reflectance spectroscopy was employed to estimate band gap energies. From the TiO₂-GO samples, a 0.25 μm thin layer on a piece of glass 2x2 cm was created. The X-ray diffraction analysis revealed that the as-deposited layers are amorphous in nature. The surface morphology images demonstrate that the layers grew in distributed with some spherical/rod-like and partially agglomerated TiGO on the surface of the composite. The Atomic Force Microscopy indicated that the films are smooth with slightly larger surface roughness. The analysis of optical absorption data of the layers showed that the values of band gap energy decreased from 3.46 eV to 1.40 eV, depending on the grams of GO doping. This reduction might be attributed to electron and/or hole trapping at the donor and acceptor levels in the TiO₂ band structure. Observed results have shown that the inclusion of GO in the TiO₂ matrix have exhibited significant and excellent properties, which would be promising for application in the photovoltaic application.

Keywords: titanium dioxide, graphene oxide, thin films, solar cells

Procedia PDF Downloads 158

Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

Abstract:

Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

Procedia PDF Downloads 255

Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

Abstract:

This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle

Procedia PDF Downloads 227