Search results for: nonuniform signal processing

Authors: Peter Joseph Basil Morris, Chhabi Nigam, S. Ramakrishnan, P. Radhakrishna

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data using the Range Migration Algorithm (RMA) for the spotlight mode of operation. Unlike in polar format algorithm (PFA), space-variant defocusing and geometric distortion effects are mitigated in RMA since it does not assume that the illuminating wave-fronts are planar. This facilitates the use of RMA for imaging scenarios involving severe differential range curvatures enabling the imaging of larger scenes at fine resolution and at shorter ranges with low center frequencies. The RMA algorithm for the spotlight mode of SAR is analyzed in this paper using the airborne data. Pre-processing operations viz: - range de-skew and motion compensation to a line are performed on the raw data before being fed to the RMA component. Various stages of the RMA viz:- 2D Matched Filtering, Along Track Fourier Transform and Slot Interpolation are analyzed to find the performance limits and the dependence of the imaging geometry on the resolution of the final image. The ability of RMA to compensate for severe differential range curvatures in the two-dimensional spatial frequency domain are also illustrated in this paper.

Keywords: range migration algorithm, spotlight SAR, synthetic aperture radar, matched filtering, slot interpolation

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Authors: Lydia Andrade, Kumar M. R. Bhat

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Heavy metals, especially lead, is considered to be a multi-organ toxicant. However, such heavy metals, are used in the preparation of traditional medicines. Nagabhasma is one of the traditional medicines. Lead is the metal used in its preparation. Lead is converted into a health beneficial, organometallic compound, when subjected to various traditional methods of purification. Therefore, this study is designed to evaluate the effect of such processed lead in various stages of traditionally prepared Nagabhasma on the histological structure of kidneys. Using the human equivalent doses of Nagabhasma, various stages of its preparation were fed orally for 30 days and 60 days (short term and long term). The treated and untreated rats were then sacrificed for the collection of kidneys. The kidneys were processed for histopathological study. The results show severe changes in the histological structure of kidneys. The animals treated with lead acetate showed changes in the epithelial cells lining the bowman’s capsule. The proximal and distal convoluted tubules were dilated leading to atrophy of their epithelial cells. The amount of inflammatory infiltrates was more in this group. A few groups also showed pockets of inter-tubular hemorrhage. These changes, however, were minimized as the stages progressed form stages 1 to 4 of Nagabhasma preparation. Therefore, it is necessary to stringently monitor the processing of lead acetate during the preparation of Nagabhasma.

Keywords: heavy metals, kidneys, lead acetate, Nagabhasma

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Mann Rattana-Areeyagon, Wutichai Namjaiprasert

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G-code is the main factor in computer numerical control (CNC) machine for controlling the tool-paths and generating the profile of the object’s features. For obtaining high surface accuracy of the surface finish, non-stop operation is required for CNC machine. Recently, to design a new product, the strategy that concerns about a change that has low impact on business and does not consume lot of resources has been introduced. Cost and time for designing minor changes can be reduced since the traditional geometric details of the existing models are applied. In order to support this strategy as the alternative channel for machining operation, this research proposes the automatic generating codes for CNC milling operation. Using this technique can assist the manufacturer to easily change the size and the geometric shape of the product during the operation where the time spent for setting up or processing the machine are reduced. The algorithm implemented on MATLAB platform is developed by analyzing and evaluating the geometric information of the part. Codes are created rapidly to control the operations of the machine. Comparing to the codes obtained from CAM, this developed algorithm can shortly generate and simulate the cutting profile of the part.

Keywords: geometric shapes, milling operation, minor changes, CNC Machine, G-code, cutting parameters

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Authors: Erica Elice Uy, Toshihiro Noda, Kentaro Nakai, Jonathan Dungca

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Deformation in a conventional cyclic triaxial test is normally measured by using point-wise measuring device. In this study, non-contact measurement technique was applied to be able to monitor and measure the occurrence of non-homogeneous behavior of the soil under cyclic loading. Non-contact measurement is executed through image processing. Two-dimensional measurements were performed using Lucas and Kanade optical flow algorithm and it was implemented Labview. In this technique, the non-homogeneous deformation was monitored using a mirrorless camera. A mirrorless camera was used because it is economical and it has the capacity to take pictures at a fast rate. The camera was first calibrated to remove the distortion brought about the lens and the testing environment as well. Calibration was divided into 2 phases. The first phase was the calibration of the camera parameters and distortion caused by the lens. The second phase was to for eliminating the distortion brought about the triaxial plexiglass. A correction factor was established from this phase. A series of consolidated undrained cyclic triaxial test was performed using a coarse soil. The results from the non-contact measurement technique were compared to the measured deformation from the linear variable displacement transducer. It was observed that deformation was higher at the area where failure occurs.

Keywords: cyclic loading, non-contact measurement, non-homogeneous, optical flow

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Authors: Abdullah Kaya, Muammer Koc

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A levelized cost analysis of solar energy powered seawater desalination in The Emirate of Abu Dhabi is conducted to show that clean and renewable desalination is economically viable. The Emirate heavily relies on seawater desalination for its freshwater needs due to limited freshwater resources available. This trend is expected to increase further due to growing population and economic activity, rapid decline in limited freshwater reserves, and aggravating effects of climate change. Seawater desalination in Abu Dhabi is currently done through thermal desalination technologies such as multi-stage flash (MSF) and multi-effect distillation (MED) which are coupled with thermal power plants known as co-generation. Our analysis indicates that these thermal desalination methods are inefficient regarding energy consumption and harmful to the environment due to CO₂ emissions and other dangerous byproducts. Therefore, utilization of clean and renewable desalination options has become a must for The Emirate for the transition to a sustainable future. The rapid decline in the cost of solar PV system for energy production and RO technology for desalination makes the combination of these two an ideal option for a future of sustainable desalination in the Emirate of Abu Dhabi. A Levelized cost analysis for water produced by solar PV + RO system indicates that Abu Dhabi is well positioned to utilize this technological combination for cheap and clean desalination for the coming years. It has been shown that cap-ex cost of solar PV powered RO system has potential to go as low as to 101 million US $ (1111 $/m³) at best case considering the recent technological developments. The levelized cost of water (LCW) values fluctuate between 0.34 $/m³ for the baseline case and 0.27 $/m³ for the best case. Even the highly conservative case yields LCW cheaper than 100% from all thermal desalination methods currently employed in the Emirate. Exponential cost decreases in both solar PV and RO sectors along with increasing economic scale globally signal the fact that a cheap and clean desalination can be achieved by the combination of these technologies.

Keywords: solar PV, RO desalination, sustainable desalination, levelized cost of analysis, Emirate of Abu Dhabi

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Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

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The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

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Authors: Keivan Davami, Michael Munther, Lloyd Hackel

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The control of properties and material behavior by implementing thermal-mechanical processes is based on mechanical deformation and annealing according to a precise schedule that will produce a unique and stable combination of grain structure, dislocation substructure, texture, and dispersion of precipitated phases. The authors recently developed a thermal-mechanical technique to stabilize the microstructure of additively manufactured nickel-based superalloys even after exposure to high temperatures. However, the mechanism(s) that controls this stability is still under investigation. Laser peening (LP), also called laser shock peening (LSP), is a shock based (50 ns duration) post-processing technique used for extending performance levels and improving service life of critical components by developing deep levels of plastic deformation, thereby generating high density of dislocations and inducing compressive residual stresses in the surface and deep subsurface of components. These compressive residual stresses are usually accompanied with an increase in hardness and enhance the material’s resistance to surface-related failures such as creep, fatigue, contact damage, and stress corrosion cracking. While the LP process enhances the life span and durability of the material, the induced compressive residual stresses relax at high temperatures (>0.5Tm, where Tm is the absolute melting temperature), limiting the applicability of the technology. At temperatures above 0.5Tm, the compressive residual stresses relax, and yield strength begins to drop dramatically. The principal reason is the increasing rate of solid-state diffusion, which affects both the dislocations and the microstructural barriers. Dislocation configurations commonly recover by mechanisms such as climbing and recombining rapidly at high temperatures. Furthermore, precipitates coarsen, and grains grow; virtually all of the available microstructural barriers become ineffective.Our results indicate that by using “cyclic” treatments with sequential LP and annealing steps, the compressive stresses survive, and the microstructure is stable after exposure to temperatures exceeding 0.5Tm for a long period of time. When the laser peening process is combined with annealing, dislocations formed as a result of LPand precipitates formed during annealing have a complex interaction that provides further stability at high temperatures. From a scientific point of view, this research lays the groundwork for studying a variety of physical, materials science, and mechanical engineering concepts. This research could lead to metals operating at higher sustained temperatures enabling improved system efficiencies. The strengthening of metals by a variety of means (alloying, work hardening, and other processes) has been of interest for a wide range of applications. However, the mechanistic understanding of the often complex processes of interactionsbetween dislocations with solute atoms and with precipitates during plastic deformation have largely remained scattered in the literature. In this research, the elucidation of the actual mechanisms involved in the novel cyclic LP/annealing processes as a scientific pursuit is investigated through parallel studies of dislocation theory and the implementation of advanced experimental tools. The results of this research help with the validation of a novel laser processing technique for high temperature applications. This will greatly expand the applications of the laser peening technology originally devised only for temperatures lower than half of the melting temperature.

Keywords: laser shock peening, mechanical properties, indentation, high temperature stability

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Authors: Philemon Wokoma Iyagba, Obey Onenee Christie

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From the hindbrain, which is responsible for motor activities, to the forebrain, responsible for processing information related to complex cognitive activities, the human brain has continued to evolve over the years. This evolution- has been progressive, leading to advancements in science and technology. However, the development of science and technology in Africa, where ancient civilization arguably began, has been retrogressive. Dialectics was done by dissecting different opinions on the reason behind the stunted development of science and technology in Africa. The researchers proposed that the inability to sustain the technological advancements made by early Africans is due to poor or lack of replicability of the African knowledge-based system, almost no or poor documentation of adopted procedures and the approval-seeking mentality that cheaply paved the way for westernization which also led to the adulteration of the African way of life and education without making room for incorporating her identity and proper alignment of her rich cultural heritage in education and her enormous achievements before and during the middle age. This article discussed conceptual issues, with its positions based on established facts, the discussion was based on relevant literature and recommendations were made accordingly.

Keywords: forebrain, hindbrain, dialectics from African perspective, development in science and technology

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Authors: Bandar Alahmadi, Lethia Jackson

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Machine Learning model is used today in many real-life applications. The safety and security of such model is important, so the results of the model are as accurate as possible. One challenge of machine learning model security is the adversarial examples attack. Adversarial examples are designed by the attacker to cause the machine learning model to misclassify the input. We propose a method to generate adversarial examples to attack image classifiers. We are modifying the successfully classified images, so a classifier misclassifies them after the modification. In our method, we do not update the whole image, but instead we detect the important region, modify it, place it back to the original image, and then run it through a classifier. The algorithm modifies the detected region using two methods. First, it will add abstract image matrix on back of the detected image matrix. Then, it will perform a rotation attack to rotate the detected region around its axes, and embed the trace of image in image background. Finally, the attacked region is placed in its original position, from where it was removed, and a smoothing filter is applied to smooth the background with foreground. We test our method in cascade classifier, and the algorithm is efficient, the classifier confident has dropped to almost zero. We also try it in CNN (Convolutional neural network) with higher setting and the algorithm was successfully worked.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Eleni Peristeri, Georgia Fotiadou, Ianthi-Maria Tsimpli

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The local-global dimension has been studied extensively in healthy controls and preference for globally processed stimuli has been validated in both the visual and auditory modalities. Critically, the local-global dimension has an inherent interference resolution component, a type of cognitive control, and left-prefrontal-cortex-damaged (LPFC) individuals have exhibited inability to override habitual response behaviors in item recognition tasks that involve representational interference. Eight patients with damage in the left PFC (age range: 32;5 to 69;0. Mean age: 54;6 yrs) and twenty age- and education-matched language-unimpaired adults (mean age: 56;7yrs) have participated in the study. Distinct performance patterns were found between the language-unimpaired and the LPFC-damaged group which have mainly stemmed from the latter’s difficulty with inhibiting global stimuli in incongruent trials. Overall, the local-global attentional dimension affects LPFC-damaged individuals with non-fluent aphasia in non-language domains implicating distinct types of inhibitory processes depending on the level of processing.

Keywords: left lateral prefrontal cortex damage (LPFC), local-global non-language attention, representational interference, non-fluent aphasia

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Authors: Yi-Feng Kao, Huey-Jine Chai, Chin-I Chang, Yi-Chen Chen, June-Ru Chen

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Microglia is a macrophage that resides in brain, and overactive microglia may result in brain neuron damage or inflammation. In this study, the phospholipids was extracted from squid skin and manufactured into a liposome (SQ liposome) to mimic apoptotic body. We then evaluated anti-inflammatory effects of SQ liposome on mouse microglial cell line (BV-2) by lipopolysaccharide (LPS) induction. First, the major phospholipid constituents in the squid skin extract were including 46.2% of phosphatidylcholine, 18.4% of phosphatidylethanolamine, 7.7% of phosphatidylserine, 3.5% of phosphatidylinositol, 4.9% of Lysophosphatidylcholine and 19.3% of other phospholipids by HPLC-UV analysis. The contents of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in the squid skin extract were 11.8 and 28.7%, respectively. The microscopic images showed that microglia cells can engulf apoptotic cells or SQ-liposome. In cell based studies, there was no cytotoxicity to BV-2 as the concentration of SQ-liposome was less than 2.5 mg/mL. The LPS induced pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), were significant suppressed (P < 0.05) by pretreated 0.03~2.5mg/ml SQ liposome. Oppositely, the anti-inflammatory cytokines transforming growth factor-beta (TGF-β) and interleukin-10 (IL-10) secretion were enhanced (P < 0.05). The results suggested that SQ-liposome possess anti-inflammatory properties on BV-2 and may be a good strategy for against neuro-inflammatory disease.

Keywords: apoptotic mimicry, neuroinflammation, microglia, squid processing by-products

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Authors: T. M. Samuel, O. O. Aremu, I. O. Ismaila, L. I. Onu, B. O. Adetifa, S. E. Adegbite, O. O. Olokoshe

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The imperative of anthropometry in designing to fit cannot be overemphasized. Of essence is the variability of measurements among population for which data is collected. In this paper anthropometric data were collected for the design of gari-frying facility such that work system would be designed to fit the gari-frying population in the Southwestern states of Nigeria comprising Lagos, Ogun, Oyo, Osun, Ondo, and Ekiti. Twenty-seven body dimensions were measured among 120 gari-frying processors. Statistical analysis was performed using SPSS package to determine the mean, standard deviation, minimum value, maximum value and percentiles (2nd, 5th, 25th, 50th, 75th, 95th, and 98th) of the different anthropometric parameters. One sample t-test was conducted to determine the variation within the population. The 50th percentiles of some of the anthropometric parameters were compared with those from other populations in literature. The correlation between the worker’s age and the body anthropometry was also investigated.The mean weight, height, shoulder height (sitting), eye height (standing) and eye height (sitting) are 63.37 kg, 1.57 m, 0.55 m, 1.45 m, and 0.67 m respectively.Result also shows a high correlation with other populations and a statistically significant difference in variability of data within the population in all the body dimensions measured. With a mean age of 42.36 years, results shows that age will be a wrong indicator for estimating the anthropometry for the population.

Keywords: anthropometry, cassava processing, design to fit, gari-frying, workstation design

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Authors: Shams Ul Khaliq, Khan Shahzada, Bashir Alam, Fawad Bilal, Mushtaq Zeb, Faizan Akbar

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Marble industry contributes its fair share in environmental deterioration, producing voluminous amounts of mud and other excess residues obtained from marble and granite processing, polluting soil, water and air. Reusing these products in other products will not just prevent our environment from polluting but also help with economy. In this research, an attempt has been made to study the expediency of waste Marble Powder (MP) in concrete production. Various laboratory tests were performed to investigate permeability, physical and mechanical properties, such as slump, compressive strength, split tensile test, etc. Concrete test samples were fabricated with varying MP content (replacing 5-30% cement), furnished from two different sources. 5% replacement of marble dust caused 6% and 12% decrease in compressive and tensile strength respectively. These parameters gradually decreased with increasing MP content up to 30%. Most optimum results were obtained with 10% replacement. Improvement in consistency and permeability were noticed. The permeability was improved with increasing MP proportion up to 10% without substantial decrease in compressive strength. Obtained results revealed that MP as an alternative to cement in concrete production is a viable option considering its economic and environment friendly implications.

Keywords: marble powder, strength, permeability, consistency, environment

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Authors: K. Myška, L. Pilařová

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The article deals with possibilities of using cheap mobile devices with the combination of free or open source software tools as an alternative to professional hardware and software equipment. Especially in social work, it is important to find cheap yet functional solution that can compete with complex but expensive solutions for digitizing paper materials. Our research was focused on the analysis of cheap and affordable solutions for digitizing the most frequently used paper materials that are being commonly used by terrain workers in social work. We used comparative analysis as a research method. Social workers need to process data from paper forms quite often. It is still more affordable, time and cost-effective to use paper forms to get feedback in many cases. Collecting data from paper quizzes and questionnaires can be done with the help of professional scanners and software. These technologies are very powerful and have advanced options for digitizing and processing digitized data, but are also very expensive. According to results of our study, the combination of open source software and mobile phone or cheap scanner can be considered as a cost-effective alternative to professional equipment.

Keywords: digitalization, e-learning, mobile devices, questionnaire

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Authors: Irshad Ali Khan, Jian-Ping Lu, Xiao-Hong Liu, Fu-Cheng Lin

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This study reports the functional analysis of a gene MoNUC1 in M. oryzae, which is homologous to the Saccharomyces cerevisiae NUC1 encoding a mitochondrial nuclease protein. The MoNUC1 having a gene locus MGG_05324 is 1002-bp in length and encodes an identical protein of 333 amino acids. We disrupted the gene through gene disruption strategy and isolated two mutants confirmed by southern blotting. The deleted mutants were then used for phenotypic studies and their phenotypes were compared to those of the Guy-11 strain. The mutants were first grown on CM medium to find the effect of MoNUC1 gene disruption on colony growth and the mutants were found to show normal culture colony growth similar to that of the Guy-11 strain. Conidial germination and appressorial formation were also similar in both the mutants and Guy-11 strains showing that this gene plays no significant role in these phenotypes. For pathogenicity, the mutants and Guy-11 mycelium blocks were inoculated on blast susceptible barley seedlings and it was found that both the strains exhibited full pathogenicity showing coalesced and necrotic blast lesions suggesting that this gene is not involved in pathogenicity. Mating of the mutants with 2539 strain formed numerous perithecia showing that MoNUC1 is not essential for sexual reproduction in M. oryzae. However, the mutants were found to form reduced conidia (1.06±8.03B and 1.08±9.80B) than those of the Guy-11 strain (1.46±10.61A) and we conclude that this protein is not required for the blast fungus to cause pathogenicity but plays significant role in conidiation. Proteins of signal transduction pathways that could be disrupted/ intervened genetically or chemically could lead to antifungal products of important fungal cereal diseases and reduce rice yield losses. Tipping the balance toward understanding the whole of pathogenesis, rather than simply conidiation will take some time, but clearly presents the most exciting challenge of all.

Keywords: appressorium formation, conidiation, NUC1, Magnaporthe oryzae, pathogenicity

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Authors: Rana Zeina

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Objective: The association between Sensory problems and cognitive abilities has been studied in individuals with Autism Spectrum Disorders (ASDs). In this study, we used a neuropsychological test to evaluate memory and attention in ASDs children with sensory problems compared to the ASDs children without sensory problems. Methods: Four visual memory tests of Cambridge Neuropsychological Test Automated Battery (CANTAB) including Big/Little Circle (BLC), Simple Reaction Time (SRT), Intra/Extra Dimensional Set Shift (IED), Spatial Recognition Memory (SRM), were administered to 14 ASDs children with sensory problems compared to 13 ASDs without sensory problems aged 3 to 12 with IQ of above 70. Results: ASDs Individuals with sensory problems performed worse than the ASDs group without sensory problems on comprehension, learning, reversal and simple reaction time tasks, and no significant difference between the two groups was recorded in terms of the visual memory and visual comprehension tasks. Conclusion: The findings of this study suggest that ASDs children with sensory problems are facing deficits in learning, comprehension, reversal, and speed of response to stimuli.

Keywords: visual memory, attention, autism spectrum disorders, CANTAB eclipse

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Authors: S. Chami, J. Chauvin, T. Demarest, Stan Ng, M. Straus, W. Jahner

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Biometrics tools such as fingerprint and iris are widely used in industry to protect critical assets. However, their vulnerability and lack of robustness raise several worries about the protection of highly critical assets. Biometrics based on Electrocardiographic (ECG) signals is a robust identification tool. However, most of the state-of-the-art techniques have worked on clinical signals, which are of high quality and less noisy, extracted from wearable devices like a smartwatch. In this paper, we are presenting a complete machine learning pipeline that identifies people using ECG extracted from an off-person device. An off-person device is a wearable device that is not used in a medical context such as a smartwatch. In addition, one of the main challenges of ECG biometrics is the variability of the ECG of different persons and different situations. To solve this issue, we proposed two different approaches: per person classifier, and one-for-all classifier. The first approach suggests making binary classifier to distinguish one person from others. The second approach suggests a multi-classifier that distinguishes the selected set of individuals from non-selected individuals (others). The preliminary results, the binary classifier obtained a performance 90% in terms of accuracy within a balanced data. The second approach has reported a log loss of 0.05 as a multi-class score.

Keywords: biometrics, electrocardiographic, machine learning, signals processing

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Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

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This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Nikolaos Papadakis, Constantinos Condaxakis, Konstantinos Savvakis

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The aim of this paper is to determine the elastic properties (elastic modulus and Poisson ratio) of a composite material based on noncontacting imaging methods. More specifically, the significantly reduced cost of digital cameras has given the opportunity of the high reliability of low-cost strain measurement. The open source platform Ncorr is used in this paper which utilizes the method of digital image correlation (DIC). The use of digital image correlation in measuring strain uses random speckle preparation on the surface of the gauge area, image acquisition, and postprocessing the image correlation to obtain displacement and strain field on surface under study. This study discusses technical issues relating to the quality of results to be obtained are discussed. [0]8 fabric glass/epoxy composites specimens were prepared and tested at different orientations 0[o], 30[o], 45[o], 60[o], 90[o]. Each test was recorded with the camera at a constant frame rate and constant lighting conditions. The recorded images were processed through the use of the image processing software. The parameters of the test are reported. The strain map output which is obtained through strain measurement using Ncorr is validated by a) comparing the elastic properties with expected values from Classical laminate theory, b) through finite element analysis.

Keywords: composites, Ncorr, strain map, videoextensometry

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Authors: Wilaisri Limphapayom

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Lime is one of the economically important produced in Thailand. The objective of this research is to increase utilization in food and cosmetic. Extraction of essential oil and pectin from lime (Citrus aurantifolia (Christm & Panz ) Swing) have been studied. Extraction of essential oil has been made by using hydro-distillation .The essential oil ranged from 1.72-2.20%. The chemical composition of essential oil composed of alpha-pinene , beta-pinene , D-limonene , comphene , a-phellandrene , g-terpinene , a-ocimene , O-cymene , 2-carene , Linalool , trans-ocimenol , Geraniol , Citral , Isogeraniol , Verbinol , and others when analyzed by using GC-MS method. Pectin extraction from lime waste , boiled water after essential oil extraction. Pectin extraction were found 40.11-65.81 g /100g of lime peel. The best extraction condition was found to be higher in yield by using ethanol extraction. The potential of this study had satisfactory results to improve lime processing system for value-added . The present study was also focused on Lime powder production as source of vitamin C or ascorbic acid and the potential of lime waste as a source of essential oil and pectin. Lime powder produced from Spray Dryer . Lime juice with 2 different level of maltodextrins DE 10 , 30 and 50% w/w was sprayed at 150 degrees celsius inlet air temperature and at 90-degree celsius outlet temperature. Lime powder with 50% maltodextrin gave the most desirable quality product. This product has vitamin C contents of 25 mg/100g (w/w).

Keywords: extraction, pectin, essential oil, lime

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

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The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Masaumi Nakahara, Sou Watanabe, Hiromichi Ogi, Atsuhiro Shibata, Kazunori Nomura

Abstract:

In the Japan Atomic Energy Agency, three types of experimental research, advanced reactor fuel reprocessing, radioactive waste disposal, and nuclear fuel cycle technology, have been carried out at the Chemical Processing Facility. The facility has generated high level radioactive liquid and solid wastes in hot cells. The high level radioactive solid waste is divided into three main categories, a flammable waste, a non-flammable waste, and a solid reagent waste. A plastic product is categorized into the flammable waste and molten with a heating mantle. The non-flammable waste is cut with a band saw machine for reducing the volume. Among the solid reagent waste, a used adsorbent after the experiments is heated, and an extractant is decomposed for its stabilization. All high level radioactive solid wastes in the hot cells are packed in a high level radioactive solid waste can. The high level radioactive solid waste can is transported to the 2nd High Active Solid Waste Storage in the Tokai Reprocessing Plant in the Japan Atomic Energy Agency.

Keywords: high level radioactive solid waste, advanced reactor fuel reprocessing, radioactive waste disposal, nuclear fuel cycle technology

Procedia PDF Downloads 155

Authors: Winncy Du, Jeremy Nguyen, Harpinder Dhillon, Reinardus Justin Halim, Clayton Haske, Trent Hughes, Marissa Ortiz, Rozy Saini

Abstract:

Stroke often causes death or cerebro-vascular (CV) brain damage. Most patients with CV brain damage lost their motor control on their limbs. This paper focuses on developing a reliable, safe, and non-invasive EEG-based robot-assistant stroke rehabilitation system to help stroke survivors to rapidly restore their motor control functions for their limbs. An electroencephalogram (EEG) recording device (EPOC Headset) and was used to detect a patient’s brain activities. The EEG signals were then processed, classified, and interpreted to the motion intentions, and then converted to a series of robot motion commands. A six-axis articulated robot (AdeptSix 300) was employed to provide the intended motions based on these commends. To ensure the EEG device, the computer, and the robot can communicate to each other, an Arduino microcontroller is used to physically execute the programming codes to a series output pins’ status (HIGH or LOW). Then these “hardware” commends were sent to a 24 V relay to trigger the robot’s motion. A lookup table for various motion intensions and the associated EEG signal patterns were created (through training) and installed in the microcontroller. Thus, the motion intention can be direct determined by comparing the EEG patterns obtaibed from the patient with the look-up table’s EEG patterns; and the corresponding motion commends are sent to the robot to provide the intended motion without going through feature extraction and interpretation each time (a time-consuming process). For safety sake, an extender was designed and attached to the robot’s end effector to ensure the patient is beyond the robot’s workspace. The gripper is also designed to hold the patient’s limb. The test results of this rehabilitation system show that it can accurately interpret the patient’s motion intension and move the patient’s arm to the intended position.

Keywords: brain waves, EEG sensor, motion control, robot-assistant stroke rehabilitation

Procedia PDF Downloads 382

Authors: Ajibade T., Omotesho O. A., Ayinde O. E, Ajibade E. T., Muhammad-Lawal A.

Abstract:

This study was carried out to examine the extent and magnitude of food security amongst farming rural households in Nigeria. Data used for this study was collected from a total of two hundred and forty rural farming households using a two-stage random sampling technique. The main tools of analysis for this study include descriptive statistics and a constructed food security index using the identification and aggregation procedure. The headcount ratio in this study reveals that 71% of individuals in the study area were food secure with an average per capita calorie and protein availability of 4,213.92kcal and 99.98g respectively. The aggregated household daily calorie availability and daily protein availability per capita were 3,634.57kcal and 84.08g respectively which happens to be above the food security line of 2,470kcal and 65g used in this study. The food insecure households fell short of the minimum daily per capita calorie and protein requirement by 2.1% and 24.9%. The study revealed that the area is food insecure due to unequal distribution of the available food amongst the sampled population. The study recommends that the households should empower themselves financially in order to enhance their ability to afford the food during both on and off seasons. Also, processing and storage of farm produce should be enhanced in order to improve on availability throughout the year.

Keywords: farming household, food security, identification and aggregation, food security index

Procedia PDF Downloads 289

Authors: Emine Akar

Abstract:

The majority of privacy-related regulation has traditionally focused on concepts that are perceived to be well-understood or easily describable, such as certain categories of data and personal information or images. In the past century, such regulation appeared reasonably suitable for its purposes. However, technologies such as AI, combined with ever-increasing capabilities to collect, process, and store “big data”, not only require calibration of these traditional understandings but may require re-thinking of entire categories of privacy law. In the presentation, it will be explained, against the background of various emerging technologies under the umbrella term “emotional artificial intelligence”, why modern privacy law will need to embrace human emotions as potentially private subject matter. This argument can be made on a jurisprudential level, given that human emotions can plausibly be accommodated within the various concepts that are traditionally regarded as the underlying foundation of privacy protection, such as, for example, dignity, autonomy, and liberal values. However, the practical reasons for regarding human emotions as potentially private subject matter are perhaps more important (and very likely more convincing from the perspective of regulators). In that respect, it should be regarded as alarming that, according to most projections, the usefulness of emotional data to governments and, particularly, private companies will not only lead to radically increased processing and analysing of such data but, concerningly, to an exponential growth in the collection of such data. In light of this, it is also necessity to discuss options for how regulators could address this emerging threat.

Keywords: AI, privacy law, data protection, big data

Procedia PDF Downloads 87

Authors: Abrar Abuzaid, Maha Alaaeddine, Haya Alesayi

Abstract:

This project is centered around understanding the usage and impact of Alexa, Amazon's popular virtual assistant, in everyday life. Alexa, known for its integration into devices like Amazon Echo, offers functionalities such as voice interaction, media control, providing real-time information, and managing smart home devices. Our primary focus is to conduct a straightforward survey aimed at uncovering how people use Alexa in their daily routines. We plan to reach out to a wide range of individuals to get a diverse perspective on how Alexa is being utilized for various tasks, the frequency and context of its use, and the overall user experience. The survey will explore the most common uses of Alexa, its impact on daily life, features that users find most beneficial, and improvements they are looking for. This project is not just about collecting data but also about understanding the real-world applications of a technology like Alexa and how it fits into different lifestyles. By examining the responses, we aim to gain a practical understanding of Alexa's role in homes and possibly in workplaces. This project will provide insights into user satisfaction and areas where Alexa could be enhanced to meet the evolving needs of its users. It’s a step towards connecting technology with everyday life, making it more accessible and user-friendly

Keywords: Amazon Alexa, artificial intelligence, smart speaker, natural language processing

Procedia PDF Downloads 60

Authors: N. Moradi, C. M. Lopez-Vazquez, H. Garcia Hernandez, F. Rubio Rincon, D. Brdanovic, Mark van Loosdrecht

Abstract:

Advanced oxidation processes have been widely used for disinfection, removal of residual organic material, and for the removal of emerging contaminants from drinking water and wastewater. Yet, the application of these technologies to sludge treatment processes has not gained enough attention, mostly, considering the complexity of the sludge matrix. In this research, ozone and UV/H₂O₂ treatment were applied for the removal of emerging contaminants from a digestate supernatant. The removal of the following compounds was assessed:(i) salicylic acid (SA) (a surrogate of non-stradiol anti-inflammatory drugs (NSAIDs)), and (ii) sulfamethoxazole (SMX), sulfamethazine (SMN), and tetracycline (TCN) (the most frequent human and animal antibiotics). The ozone treatment was carried out in a plexiglass bubble column reactor with a capacity of 2.7 L; the system was equipped with a stirrer and a gas diffuser. The UV and UV/H₂O₂ treatments were done using a LED set-up (PearlLab beam device) dosing H₂O₂. In the ozone treatment evaluations, 95 % of the three antibiotics were removed during the first 20 min of exposure time, while an SA removal of 91 % occurred after 8 hours of exposure time. In the UV treatment evaluations, when adding the optimum dose of hydrogen peroxide (H₂O₂:COD molar ratio of 0.634), 36% of SA, 82% of TCN, and more than 90 % of both SMX and SMN were removed after 8 hours of exposure time. This study concluded that O₃ was more effective than UV/H₂O₂ in removing emerging contaminants from the digestate supernatant.

Keywords: digestate sludge, emerging contaminants, ozone, UV-AOP

Procedia PDF Downloads 100

Authors: Rita Magdalena, N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Sofia Saidah, Bima Sakti

Abstract:

Vessel segmentation of retinal fundus is important for biomedical sciences in diagnosing ailments related to the eye. Segmentation can simplify medical experts in diagnosing retinal fundus image state. Therefore, in this study, we designed a software using MATLAB which enables the segmentation of the retinal blood vessels on retinal fundus images. There are two main steps in the process of segmentation. The first step is image preprocessing that aims to improve the quality of the image to be optimum segmented. The second step is the image segmentation in order to perform the extraction process to retrieve the retina’s blood vessel from the eye fundus image. The image segmentation methods that will be analyzed in this study are Morphology Operation, Discrete Wavelet Transform and combination of both. The amount of data that used in this project is 40 for the retinal image and 40 for manually segmentation image. After doing some testing scenarios, the average accuracy for Morphology Operation method is 88.46 % while for Discrete Wavelet Transform is 89.28 %. By combining the two methods mentioned in later, the average accuracy was increased to 89.53 %. The result of this study is an image processing system that can segment the blood vessels in retinal fundus with high accuracy and low computation time.

Keywords: discrete wavelet transform, fundus retina, morphology operation, segmentation, vessel

Procedia PDF Downloads 192