Search results for: drone images

Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

Procedia PDF Downloads 425

Authors: Mohamed K. Metwally, Sherif H. El-Gohary, Kyung Min Byun, Seung Moo Han, Soo Yeol Lee, Min Hyoung Cho, Gon Khang, Jinsung Cho, Tae-Seong Kim

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Photoacoustic imaging (PAI) is a non-invasive and non-ionizing imaging modality that combines the absorption contrast of light with ultrasound resolution. Laser is used to deposit optical energy into a target (i.e., optical fluence). Consequently, the target temperature rises, and then thermal expansion occurs that leads to generating a PA signal. In general, most image reconstruction algorithms for PAI assume uniform fluence within an imaging object. However, it is known that optical fluence distribution within the object is non-uniform. This could affect the reconstruction of PA images. In this study, we have investigated the influence of optical fluence distribution on PA back-propagation imaging using finite element method. The uniform fluence was simulated as a triangular waveform within the object of interest. The non-uniform fluence distribution was estimated by solving light propagation within a tissue model via Monte Carlo method. The results show that the PA signal in the case of non-uniform fluence is wider than the uniform case by 23%. The frequency spectrum of the PA signal due to the non-uniform fluence has missed some high frequency components in comparison to the uniform case. Consequently, the reconstructed image with the non-uniform fluence exhibits a strong smoothing effect.

Keywords: finite element method, fluence distribution, Monte Carlo method, photoacoustic imaging

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Authors: Rasheed A. Saliu, Sunday E. Ogundipe, Oluwaseun A. Adefila

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Information and Communication Technology (ICT) in recent time has transformed the means by which we inform ourselves, with world events and areas of personal interests, and further our learning. Today, for many, books and journals are no longer the first or primary source of information or learning. We now regularly rely on images, video, animations and sound to acquire information and to learn. Increased and improved access to the internet has accelerated this phenomenon. We now acquire and access information in ways fundamentally different from the pre-ICT era. But to what extent is academic staff in colleges of education, having access to and the utilising of ICT devices in their lecture deliveries especially in School of Science and Vocational and Technical? The main focus of this paper is to proffer solution to this salient question. It is essentially an empirical study carried out in five colleges of education in south-west zone of Nigeria. The target population was the academic staff in the selected institution. A total number of 150 male and female lecturers were contacted for the study. The main instrument was questionnaire. The finding reveals that male lecturers are much more ICT inclined than women folk in the academics. Some recommendations were made to endear academics to utilizing ICT at their disposal to foster qualitative delivery in this digital era.

Keywords: education, gender, ICT, Nigeria

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Authors: Rachita Lal

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Urban sprawl is a significant contributor to land use change in developing countries, where urbanization rates are high. The most important driver of environmental changes is also considered to be the shift in land use and land cover. Our local and regional land managers must carefully analyze urbanization and its effects on cities to make the best choices. This study uses satellite imagery to examine how urbanization affects the local ecosystem through geographic expansion. The following research focuses on the effects of city growth on the local environment, land use, and Land cover. The primary focus of this research is to study, To understand the role of urbanization on city expansion. To study the impact of spatial growth of urban areas on the Land cover. In this paper, the GIS tool will be used to analyze. For this purpose, four digital images are used for the years 2000, 2005, 2011, and 2019. The use of the approach in the Bhubaneswar Urban Core, one of the fastest developing and planned cities in India, has proved that it is highly beneficial and successful for monitoring urban sprawl. It offers a helpful tool for quantitative assessment, which is crucial for determining the spatial dynamics, variations, and changes of urban sprawl patterns in quickly increasing regions.

Keywords: LULC, urbanization, environment impact assessment, spatial growth

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Authors: Kerrin Burnell

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In a world of increasingly technology-dependent students, the English language classroom should ideally keep up with developments to keep students engaged as much as possible. Unfortunately, as is the case in Oman, funding is not always adequate to ensure students have the most up to date technology, and most institutions are still reliant on paper-based textbooks. In order to try and bridge the gap between the technology available (smartphones) and textbooks, augmented reality (AR) technology can be utilized to enhance classroom, homework, and extracurricular activities. AR involves overlaying media (videos, images etc) over the top of physical objects (posters, book pages etc) and then sharing the media. This case study involved introducing students to a freely available entry level AR app called Aurasma. Students were asked to augment their English textbooks, word walls, research project posters, and extracurricular posters. Through surveys, interviews and an analysis of time spent accessing the different media, a determination of the appropriateness of the technology for the classroom was determined. Results indicate that the use of AR has positive effects on many aspects of the English classroom. Increased student engagement, total time spent on task, interaction, and motivation were evident, along with a decrease in technology-related anxiety. As it is proving very difficult to get tablets or even laptops in classrooms in Oman, these preliminary results indicate that many positive outcomes will come from introducing students to this innovative technology.

Keywords: augmented reality, classroom technology, classroom innovation, engagement

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Authors: Su-Ning Wang, Yao-Qiang Chen

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The CeO2-ZrO2-La2O3-Al2O3 composite oxides are synthesized using co-precipitation method by two different reactors (i.e. continuous stirred-tank reactor and batch reactor), and the corresponding Rh-only three-way catalysts are obtained by wet-impregnation approach. The textural, structural, morphology and redox properties of the support materials, as well as the catalytic performance of the Rh-only catalyst are investigated systematically. The results reveal that the materials (CZLA-C) synthesized by continuous stirred-tank reactor have a better physic-chemical properties than the counterpart material (CZLA-B) prepared by batch reactor. After aging treatment at 1000 ℃ for 5 h, the BET surface area and pore volume of S1 reach up to 76 m2 g-1 and 0.36 mL/g, respectively, which is higher than that of S2. The XRD and Raman results demonstrate that a high structural stability is obtained by S1 because of the negligible lattice variation and the slight grain growth after aging treatment. The SEM and TEM images display that the morphology of S1 is assembled by many homogeneous primary nanoparticles (about 6.12 nm) that are connected to form mesoporous structure The TPR measurement shows that S1 possesses a higher reduction ability than S2. Compared with the catalyst supported on the CZLA-B, the as-prepared CZLA-C demonstrates an improved three-way catalytic activity both before and after aging treatment.

Keywords: composite oxides, reactor, catalysis, catalytic performance

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Authors: E. Solfaroli Camillocci, C. Mancini-Terracciano, V. Bocci, A. Carollo, M. Colandrea, F. Collamati, M. Cremonesi, M. E. Ferrari, P. Ferroli, F. Ghielmetti, C. M. Grana, M. Marafini, S. Morganti, M. Patane, G. Pedroli, B. Pollo, L. Recchia, A. Russomando, M. Schiariti, M. Toppi, G. Traini, R. Faccini

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A Radio-Guided Surgery technique exploiting β− emitting radio-tracers has been suggested to overcome the impact of the large penetration of γ radiation. The detection of electrons in low radiation background provides a clearer delineation of the margins of lesioned tissues. As a start, the clinical cases were selected between the tumors known to express receptors to a β− emitting radio-tracer: 90Y-labelled DOTATOC. The results of tests on ex-vivo specimens of meningioma brain tumor and abdominal neuroendocrine tumors are presented. Voluntary patients were enrolled according to the standard uptake value (SUV > 2 g/ml) and the expected tumor-to-non-tumor ratios (TNR∼10) estimated from PET images after administration of 68Ga-DOTATOC. All these tests validated this technique yielding a significant signal on the bulk tumor and a negligible background from the nearby healthy tissue. Even injecting as low as 1.4 MBq/kg of radiotracer, tumor remnants of 0.1 ml would be detectable. The negligible medical staff exposure was confirmed and among the biological wastes only urine had a significant activity.

Keywords: ex-vivo test, meningioma, neuroendocrine tumor, radio-guided surgery

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Authors: Sanam Pudasaini, A. T. K. Perera, Ahmed Syed Shaheer Uddin, Sum Huan Ng, Chun Yang

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Development of high-efficiency and environment friendly bacterial inactivation methods is of great importance for preventing waterborne diseases which are one of the leading causes of death in the world. Traditional bacterial inactivation methods (e.g., ultraviolet radiation and chlorination) have several limitations such as longer treatment time, formation of toxic byproducts, bacterial regrowth, etc. Recently, an electroporation-based inactivation method was introduced as a substitute. Here, an electroporation-based continuous flow microfluidic device equipped with an array of micropillars is developed, and the device achieved high bacterial inactivation performance ( > 99.9%) within a short exposure time ( < 1 s). More than 99.9% reduction of Escherichia coli bacteria was obtained for the flow rate of 1 mL/hr, and no regrowth of bacteria was observed. Images from scanning electron microscope confirmed the formation of electroporation-induced nano-pore within the cell membrane. Through numerical simulation, it has been shown that sufficiently large electric field strength (3 kV/cm), required for bacterial electroporation, were generated using PDMS micropillars for an applied voltage of 300 V. Further, in this method of inactivation, there is no involvement of chemicals and the formation of harmful by-products is also minimum.

Keywords: electroporation, high-efficiency, inactivation, microfluidics, micropillar

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Authors: Alfred Chen, Cheng Chieh Hsu, Yu-Pin Ma, Meng-Jie Lin, Fu Pai Chiu, Yi-Yan Sie

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This study is attempted to construct a human-computer interactive platform system that has mainly consisted of an augmented hardware system, a software system, a display table, and mixed media. This system has provided with human-computer interaction services through an interactive platform for the tourism industry. A well designed interactive platform, integrating of augmented reality and mixed media, has potential to enhance museum display quality and diversity. Besides, it will create a comprehensive and creative display mode for most museums and historical heritages. Therefore, it is essential to let public understand what the platform is, how it functions, and most importantly how one builds an interactive augmented platform. Hence the authors try to elaborate the construction process of the platform in detail. Thus, there are three issues to be considered, i.e.1) the theory and application of augmented reality, 2) the hardware and software applied, and 3) the mixed media presented. In order to describe how the platform works, Courtesy Door of Tainan Confucius Temple has been selected as case study in this study. As a result, a developed interactive platform has been presented by showing the physical entity object, along with virtual mixing media such as text, images, animation, and video. This platform will result in providing diversified and effective information that will be delivered to the users.

Keywords: human-computer interaction, mixed reality, mixed media, tourism

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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: Musatafa Abbas Abbood Albadr, Masri Ayob, Sabrina Tiun, Fahad Taha Al-Dhief, Mohammad Kamrul Hasan

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Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification.

Keywords: breast cancer, machine learning, online sequential extreme learning machine, artificial intelligence

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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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: 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: M.F. Elkady, Sahar Zaki, Desouky Abd-El-Haleem

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Silver nanoparticles (AgNPs) are already widely prepared using different technologies. However, there are limited data on the effects of hydrogen ion concentration on nano-silver production. In this investigation, the impact of the pH reaction medium toward the particle size, agglomeration and the yield of the produced bio-synthesized silver were established. Quasi-spherical silver nanoparticles were synthesized through the biosynthesis green production process using the Egyptian E. coli bacterial strain 23N at different pH values. The formation of AgNPs has been confirmed with ultraviolet–visible spectra through identification of their characteristic peak at 410 nm. The quantitative production yield and the orientation planes of the produced nano-silver were examined using X-ray spectroscopy (EDS) and X-ray diffraction (XRD). Quantitative analyses indicated that the silver production yield was promoted at elevated pH regarded to increase the reduction rate of silver precursor through both chemical and biological processes. As a result, number of the nucleus and thus the size of the silver nanoparticles were tunable through changing pH of the reaction system. Accordingly, the morphological structure and size of the produced silver and its aggregates were determined using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images. It was considered that the increment in pH value of the reaction media progress the aggregation of silver clusters. However, the presence of stain 23N biomass decreases the possibility of silver aggregation at the pH 7.

Keywords: silver nanoparticles, biosynthesis, reaction media pH, nano-silver characterization

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Authors: Miho Tsukamoto

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Since the initial creation of the Barbie doll in 1959, it became a symbol of US society. Likewise, the Licca-chan, a Japanese doll created in 1967, also became a Japanese symbolic doll of Japanese society. Prior to the introduction of Licca-chan, Barbie was already marketed in Japan but their sales were dismal. Licca-chan (an actual name: Kayama Licca) is a plastic doll with a variety of sizes ranging from 21.0 cm to 29.0 cm which many Japanese girls dream of having. For over 35 years, the manufacturer, Takara Co., Ltd. has sold over 48 million dolls and has produced doll houses, accessories, clothes, and Licca-chan video games for the Nintendo DS. Many First-generation Licca-chan consumers still are enamored with Licca-chan, and go to Licca-chan House, in an amusement park with their daughters. These people are called Licca-chan maniacs, as they enjoy touring the Licca-chan’s factory in Tohoku or purchase various Licca-chan accessories. After the successful launch of Licca-chan into the Japanese market, a mixed-like doll from the US and Japan, a doll, JeNny, was later sold in the same Japanese market by Takara Co., Ltd. in 1982. Comparison of these cultural iconic dolls, Barbie and Licca-chan, are analyzed in this paper. In fact, these dolls have concepts of girls’ dreams. By using concepts of mythology of Jean Baudrillard, these dolls can be represented idealized images of figures in the products for consumers, but at the same time, consumers can see products with different perspectives, which can cause controversy.

Keywords: Barbie, dolls, JeNny, idealization, Licca-chan

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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: Asiri Wijesinghe, N. D. Kodikara, Damitha Sandaruwan

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The Diabetic Retinopathy (DR) is a rapidly growing interrogation around the world which can be annotated by abortive metabolism of glucose that causes long-term infection in human retina. This is one of the preliminary reason of visual impairment and blindness of adults. Information on retinal pathological mutation can be recognized using ocular fundus images. In this research, we are mainly focused on resurrecting an automated diagnosis system to detect DR anomalies such as severity level classification of DR patient (Non-proliferative Diabetic Retinopathy approach) and vessel tortuosity measurement of untwisted vessels to assessment of vessel anomalies (Proliferative Diabetic Retinopathy approach). Severity classification method is obtained better results according to the precision, recall, F-measure and accuracy (exceeds 94%) in all formats of cross validation. In ROC (Receiver Operating Characteristic) curves also visualized the higher AUC (Area Under Curve) percentage (exceeds 95%). User level evaluation of severity capturing is obtained higher accuracy (85%) result and fairly better values for each evaluation measurements. Untwisted vessel detection for tortuosity measurement also carried out the good results with respect to the sensitivity (85%), specificity (89%) and accuracy (87%).

Keywords: fundus image, exudates, microaneurisms, hemorrhages, tortuosity, diabetic retinopathy, optic disc, fovea

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Authors: Newdeskarl Saint Fleur, Nathalie Feuillet, Raphaël Grandin, Éric Jacques, Jennifer Weil-Accardo, Yann Klinger

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The prevailing consensus is that the 2010 Mw7.0 Haiti earthquake left the Enriquillo–Plantain Garden strike-slip Fault (EPGF) unruptured but broke unmapped blind north-dipping thrusts. Using high-resolution topography, aerial images, bathymetry and geology we identified previously unrecognized south-dipping NW-SE-striking active thrusts in southern Haiti. One of them, Lamentin thrust (LT), cuts across the crowded city of Carrefour, extends offshore into Port-au-Prince Bay and connects at depth with the EPGF. We propose that both faults broke in 2010. The rupture likely initiated on the thrust and propagated further along the EPGF due to unclamping. This scenario is consistent with geodetic, seismological and field data. The 2010 earthquake increased the stress toward failure on the unruptured segments of the EPGF and on neighboring thrusts, significantly increasing the seismic hazard in the Port-au-Prince urban area. The numerous active thrusts recognized in that area must be considered for future evaluation of the seismic hazard.

Keywords: active faulting, enriquillo-plantain garden fault, Haiti earthquake, seismic hazard

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Authors: Eman Alzahrani

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Magnetic nanoparticles (MNPs) were fabricated using the chemical co-precipitation method followed by coating the surface of magnetic Fe3O4 nanoparticles with gum arabic (GA). The fabricated magnetic nanoparticles were characterised using transmission electron microscopy (TEM) which showed that the Fe3O4 nanoparticles and GA-MNPs nanoparticles had a mean diameter of 33 nm, and 38 nm, respectively. Scanning electron microscopy (SEM) images showed that the MNPs modified with GA had homogeneous structure and agglomerated. The energy dispersive X-ray spectroscopy (EDAX) spectrum showed strong peaks of Fe and O. X-ray diffraction patterns (XRD) indicated that the naked magnetic nanoparticles were pure Fe3O4 with a spinel structure and the covering of GA did not result in a phase change. The covering of GA on the magnetic nanoparticles was also studied by BET analysis, and Fourier transform infrared spectroscopy. Moreover, the present study reports a fast and simple method for removal and recovery of methylene blue dye (MB) from aqueous solutions by using the synthesised magnetic nanoparticles modified with gum arabic as adsorbent. The experimental results show that the adsorption process attains equilibrium within five minutes. The data fit the Langmuir isotherm equation and the maximum adsorption capacities were 8.77 mg mg-1 and 14.3 mg mg-1 for MNPs and GA-MNPs, respectively. The results indicated that the homemade magnetic nanoparticles were quite efficient for removing MB and will be a promising adsorbent for the removal of harmful dyes from waste-water.

Keywords: Fe3O4 magnetic nanoparticles, gum arabic, co-precipitation, adsorption dye, methylene blue, adsorption isotherm

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Authors: Tshaiya Devi Thandauthapani, Adam J. Reeve, Adam S. Long, Ian J. Turner, James S. Sharp

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Fingermarks are a crucial form of evidence for identifying a person at a crime scene. However, visualising latent (hidden) fingermarks can be difficult, and the correct choice of techniques is essential to develop and preserve any fingermarks that might be present. Knives, firearms and other metal weapons have proven to be challenging substrates (stainless steel in particular) from which to reliably obtain fingermarks. In this study, time of flight secondary ion mass spectroscopy (ToF-SIMS) was used to image fingermarks on metal surfaces. This technique was compared to a conventional superglue based fuming technique that was accompanied by a series of contrast enhancing dyes (basic yellow 40 (BY40), crystal violet (CV) and Sudan black (SB)) on three different metal surfaces. The conventional techniques showed little to no evidence of fingermarks being present on the metal surfaces after a few days. However, ToF-SIMS images revealed fingermarks on the same and similar substrates with an exceptional level of detail demonstrating clear ridge definition as well as detail about sweat pore position and shape, that persist for over 26 days after deposition when the samples were stored under ambient conditions.

Keywords: conventional techniques, latent fingermarks, metal substrates, time of flight secondary ion mass spectroscopy

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Authors: Maged Syed Ahamd, Manal Mohamed Yasser, Essam Sholkamy

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In this paper, we reported that selenium (Se) nanoparticles were firstly biosynthesized with a simple and eco-friendly biological method. Their shape, size, FTIR (Fourier Transform Infrared spectroscopy), UV–vis spectra, TEM (Transmission Electron Microscopy) images and EDS (Energy Dispersive Spectroscopy) pattern have been analyzed. TEM analyses of the samples obtained at different stages indicated that the formation of these Se nanostructures was governed by an incubation time (12- 24- 48 hours). The Se nanoparticles were initially generated and then would transform into crystal seeds for the subsequent growth of nanowires; however obtaining stable Se nanowire with a diameter of about 15-100 nm. EDS shows that Se nanoparticles are entirely pure. The IR spectra showed the peaks at 550 cm-1, 1635 cm-1, 1994 cm-1 and 3430 cm-1 correspond to the presence of Se-O bending and stretching vibrations. The concentrations of Se-NPs (0, 1, 2, 5 µg/ml) did not give significantly effect on both two cell lines while the highest concentrations (10- 100 µg/ml gave significantly effects on them. The lethal dose (ID50%) of Se-NPs on Hep2 G and MCF-7 cells was obtained at 75.96 and 61.86 µg/ml, respectively. Results showed that Se nanoparticles as anticancer agent against MCF-7 cells were more effective than Hep2 G cells. Our results suggest that Se-NPs may be a candidate for further evaluation as a chemotherapeutic agent for breast and liver cancers.

Keywords: selenium nanoparticle, Streptomyces bikiniensis, nanowires, chemotherapeutic agent

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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

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Authors: Gayatri Kanwar

Abstract:

The purpose of this research paper is to explore the power of myth in changing human lives; it establishes patterns in the human psyche, affects the way of thinking, as myths unveil various subjects, ideas, and challenges. Through mythological stories one comes to understand the images behind the emotions and feelings, they influence him as it changes his thought patterns, their therapeutic sets the individual on the path of healing and transforms human lives. Every civilization in the olden times had a vast source of myths which they lived by. They were not ordinary stories of everyday life, but exemplary cases narrated through oral traditions in a sacred manner revealed the 'way to live life'. The mythical stories have a spiritual touch which brought him to the acceptance of suffering or finding a solution to his life problems. In modern times, the significance of the age old myth has lost their touch. Each one of us bears countless stories inside ourselves of our own lives and all its happenings. Therefore, each being is a natural narrator. Everybody tells stories about their lives; hence, one tends to know oneself as well as seeks understanding of others through them. When one remembers their stories they speak in narratives. As stated by Jung, these narratives grow into a personal mythology one lives by. Nonetheless, there are times when one becomes stuck in their own stories or myths. Hence, mythology can change one’s perception and can open pathways to other ways of discovering, feeling and experiencing one’s lives.

Keywords: Power of Myths, Significance of myths in modern times, Transforming human lives, Benefits to Society

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Authors: Amritha Nair, Fleur Visser, Ian Maddock, Jonas Schoelynck

Abstract:

Inland waters such as streams sustain a rich variety of species and are essentially hotspots for biodiversity. Submerged aquatic vegetation, also known as SAV, forms an important part of ecologically healthy river systems. Direct and indirect human influences, such as climate change are putting stress on aquatic plant communities, ranging from the invasion of non-native species and grazing, to changes in the river flow conditions and temperature. There is a need to monitor SAV, because they are in a state of deterioration and their disappearance will greatly impact river ecosystems. Like terrestrial plants, SAV can show visible signs of stress. However, the techniques used to map terrestrial vegetation from its spectral reflectance, are not easily transferable to a submerged environment. Optical remote sensing techniques are employed to detect the stress from remotely sensed images through multispectral imagery and Structure from Motion photogrammetry. The effect of the overlying water column in the form of refraction, attenuation of visible and near infrared bands in water, as well as highly moving targets, are NIR) key challenges that arise when remotely mapping SAV. This study looks into the possibility of mapping the changes in spectral signatures from SAV and their response to certain stresses.

Keywords: submerged aquatic vegetation, structure from motion, photogrammetry, multispectral, spectroscopy

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Authors: Uchenna Sydney Mbamara, Bolu Olofinjana, Ezekiel Oladele B. Ajayi

Abstract:

Elaborate surface metrology of undoped ZnO thin films, deposited by organometallic chemical vapour deposition (OMCVD) technique at different precursor flow rates, was carried out. Dicarbomethyl-zinc precursor was used. The films were deposited on AISI304L steel and soda-lime glass substrates. Ultraviolet-visible-near-infrared (UV-Vis-NIR) spectroscopy showed that all the thin films were over 80% transparent, with an average bandgap of 3.39 eV, X-ray diffraction (XRD) results showed that the thin films were crystalline with a hexagonal structure, while Rutherford backscattering spectroscopy (RBS) results identified the elements present in each thin film as zinc and oxygen in the ratio of 1:1. Microscope and contactless profilometer results gave images with characteristic colours. The profilometer also gave the surface roughness data in both 2D and 3D. The asperity distribution of the thin film surfaces was Gaussian, while the average fractal dimension Da was in the range of 2.5 ≤ Da. The metrology proved the surfaces good for ‘touch electronics’ and coating mechanical parts for low friction.

Keywords: undoped ZnO, precursor flow rate, OMCVD, thin films, surface texture, tribology

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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

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Authors: Vivek Verma, Sanjeev Kumar

Abstract:

This study presents a novel quantum image encryption algorithm, using a 3D chaotic map and controlled qubit-level scrambling operations. The newly proposed 3D-BNM chaotic map effectively reduces the degradation of chaotic dynamics resulting from the finite word length effect. It facilitates the generation of highly unpredictable random sequences and enhances chaotic performance. The system’s efficacy is additionally enhanced by the inclusion of a SHA-256 hash function. Initially, classical plain images are converted into their quantum equivalents using the Novel Enhanced Quantum Representation (NEQR) model. The Generalized Quantum Arnold Transformation (GQAT) is then applied to disrupt the coordinate information of the quantum image. Subsequently, to diffuse the pixel values of the scrambled image, XOR operations are performed using pseudorandom sequences generated by the 3D-BNM chaotic map. Furthermore, to enhance the randomness and reduce the correlation among the pixels in the resulting cipher image, a controlled qubit-level scrambling operation is employed. The encryption process utilizes fundamental quantum gates such as C-NOT and CCNOT. Both theoretical and numerical simulations validate the effectiveness of the proposed algorithm against various statistical and differential attacks. Moreover, the proposed encryption algorithm operates with low computational complexity.

Keywords: 3D Chaotic map, SHA-256, quantum image encryption, Qubit level scrambling, NEQR

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Authors: Shafiullah Soomro

Abstract:

Active contour is one of the image segmentation techniques and its goal is to capture required object boundaries within an image. In this paper, we propose a novel image segmentation method by using an active contour method based on anisotropic diffusion feature enhancement technique. The traditional active contour methods use only pixel information to perform segmentation, which produces inaccurate results when an image has some noise or complex background. We use Perona and Malik diffusion scheme for feature enhancement, which sharpens the object boundaries and blurs the background variations. Our main contribution is the formulation of a new SPF (signed pressure force) function, which uses global intensity information across the regions. By minimizing an energy function using partial differential framework the proposed method captures semantically meaningful boundaries instead of catching uninterested regions. Finally, we use a Gaussian kernel which eliminates the problem of reinitialization in level set function. We use several synthetic and real images from different modalities to validate the performance of the proposed method. In the experimental section, we have found the proposed method performance is better qualitatively and quantitatively and yield results with higher accuracy compared to other state-of-the-art methods.

Keywords: active contours, anisotropic diffusion, level-set, partial differential equations

Procedia PDF Downloads 161