Search results for: content based image retrieval (CBIR)

Authors: R. Daïra, V. Chalvidan

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We present the speckle interferometry method to determine the deformation of a piece. This method of holographic imaging using a CCD camera for simultaneous digital recording of two states object and reference. The reconstruction is obtained numerically. This latest method has the advantage of being simpler than the methods currently available, and it does not suffer the holographic configuration faults online. Furthermore, it is entirely digital and avoids heavy analysis after recording the hologram. This work was carried out in the laboratory HOLO 3 (optical metrology laboratory in Saint Louis, France) and it consists in controlling qualitatively and quantitatively the deformation of object by using a camera CCD connected to a computer equipped with software of Fringe Analysis.

Keywords: speckle, nondestructive testing, interferometry, image processing

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Authors: Nurkhairul Bariyah Baharun, Afzan Adam, Reena Rahayu Md Zin

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Tumor microenvironment (TME) in breast cancer is mainly composed of cancer cells, immune cells, and stromal cells. The interaction between cancer cells and their microenvironment plays an important role in tumor development, progression, and treatment response. The TME in breast cancer includes tumor-infiltrating lymphocytes (TILs) that are implicated in killing tumor cells. TILs can be found in tumor stroma (sTILs) and within the tumor (iTILs). TILs in triple negative breast cancer (TNBC) have been demonstrated to have prognostic and potentially predictive value. The international Immune-Oncology Biomarker Working Group (TIL-WG) had developed a guideline focus on the assessment of sTILs using hematoxylin and eosin (H&E)-stained slides. According to the guideline, the pathologists use “eye balling” method on the H&E stained- slide for sTILs assessment. This method has low precision, poor interobserver reproducibility, and is time-consuming for a comprehensive evaluation, besides only counted sTILs in their assessment. The TIL-WG has therefore recommended that any algorithm for computational assessment of TILs utilizing the guidelines provided to overcome the limitations of manual assessment, thus providing highly accurate and reliable TILs detection and classification for reproducible and quantitative measurement. This study is carried out to develop a TNBC digital whole slide image (WSI) dataset from H&E-stained slides and IHC (CD4+ and CD8+) stained slides. TNBC cases were retrieved from the database of the Department of Pathology, Hospital Canselor Tuanku Muhriz (HCTM). TNBC cases diagnosed between the year 2010 and 2021 with no history of other cancer and available block tissue were included in the study (n=58). Tissue blocks were sectioned approximately 4 µm for H&E and IHC stain. The H&E staining was performed according to a well-established protocol. Indirect IHC stain was also performed on the tissue sections using protocol from Diagnostic BioSystems PolyVue™ Plus Kit, USA. The slides were stained with rabbit monoclonal, CD8 antibody (SP16) and Rabbit monoclonal, CD4 antibody (EP204). The selected and quality-checked slides were then scanned using a high-resolution whole slide scanner (Pannoramic DESK II DW- slide scanner) to digitalize the tissue image with a pixel resolution of 20x magnification. A manual TILs (sTILs and iTILs) assessment was then carried out by the appointed pathologist (2 pathologists) for manual TILs scoring from the digital WSIs following the guideline developed by TIL-WG 2014, and the result displayed as the percentage of sTILs and iTILs per mm² stromal and tumour area on the tissue. Following this, we aimed to develop an automated digital image scoring framework that incorporates key elements of manual guidelines (including both sTILs and iTILs) using manually annotated data for robust and objective quantification of TILs in TNBC. From the study, we have developed a digital dataset of TNBC H&E and IHC (CD4+ and CD8+) stained slides. We hope that an automated based scoring method can provide quantitative and interpretable TILs scoring, which correlates with the manual pathologist-derived sTILs and iTILs scoring and thus has potential prognostic implications.

Keywords: automated quantification, digital pathology, triple negative breast cancer, tumour infiltrating lymphocytes

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Authors: Sher Muhammad, Mirza Muhammad Waqar

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It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79 to 24.85 degree in latitude and 66.91 to 66.97 degree in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image preprocessing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end-member extraction. Well-distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (white mangroves) and Avicennia Germinans (black mangroves) have been observed throughout the study area.

Keywords: mangrove, hyperspectral, hyperion, SAM, SFF, SID

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Authors: Anam Alam, Rahim Jamaluddin Kanji

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With the rapid growth of event in everywhere, event extraction has now become an important matter to retrieve the information from the unstructured data. One of the challenging problems is to extract the event from it. An event is an observable occurrence of interaction among entities. The paper investigates the effectiveness of event extraction capabilities of three software tools that are Wandora, Nitro and SPSS. We performed standard text mining techniques of these tools on the data sets of (i) Afghan War Diaries (AWD collection), (ii) MUC4 and (iii) WebKB. Information retrieval measures such as precision and recall which are computed under extensive set of experiments for Event Extraction. The experimental study analyzes the difference between events extracted by the software and human. This approach helps to construct an algorithm that will be applied for different machine learning methods.

Keywords: event extraction, Wandora, nitro, SPSS, event analysis, extraction method, AFG, Afghan War Diaries, MUC4, 4 universities, dataset, algorithm, precision, recall, evaluation

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Authors: Najia Zulfiqar

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Imparting moral education is the need of time, considering the obvious moral decline in society. Recent research shows the downfall of moral competence among university students. The main objective of the present study was to develop moral development intervention strategies for undergraduate students of Sports and Physical Education. Using an interpretative phenomenological approach, insight into field-specific moral issues was gained through interviews with 7 subject experts and a focus-group discussion session with 8 students. Two research assistants who were trained in qualitative interviewing collected, transcribed and analyzed data into the MAXQDA software using content and discourse analyses. The identified moral issues in Sports and Physical Education were sports gambling and betting, pay-for-play, doping, coach misconduct, tampering, cultural bias, gender equity/nepotism, bullying/discrimination, and harassment. Next, intervention modules were developed for each moral issue based on hypothetical situations, and followed by guided reflection and dilemma discussion questions. The third moral development strategy was community services that included posture screening, diet plan for different age groups, open fitness ground training, exercise camps for physical fitness, balanced diet awareness camp, gymnastic camp, shoe assessment as per health standards, and volunteering for public awareness at the playground, gymnasium, stadium, park, etc. The intervention modules were given to four subject specialists for expert validation who were from different backgrounds within Sport Sciences. Upon refinement and finalization, four students were presented with these intervention modules and questioned about accuracy, relevance, comprehension, and content organization. Iterative changes were made in the content of the intervention modules to tailor them to the moral development needs of undergraduate students. This intervention will strengthen positive moral values and foster mature decision-making about right and wrong acts. As this intervention is easy to apply as a remedial tool, academicians and policymakers can use this to promote students’ moral development.

Keywords: community service, dilemma discussion, morality, physical education, university students.

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Authors: M. Owlia, M. H. Azarsa, M. Khabbazan, A. Mirbagheri

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Proprioceptive neuromuscular facilitation exercises are a series of stretching techniques that are commonly used in rehabilitation and exercise therapy. Assessment of these exercises for true maneuvering requires extensive experience in this field and could not be down with patients themselves. In this paper, we developed software that uses Microsoft Kinect sensor, a spherical color marker, and real-time image processing methods to evaluate patient’s performance in generating true patterns of movements. The software also provides the patient with a visual feedback by showing his/her avatar in a Virtual Reality environment along with the correct path of moving hand, wrist and marker. Primary results during PNF exercise therapy of a patient in a room environment shows the ability of the system to identify any deviation of maneuvering path and direction of the hand from the one that has been performed by an expert physician.

Keywords: image processing, Microsoft Kinect, proprioceptive neuromuscular facilitation, upper extremities assessment, virtual reality

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Authors: Bal Deep Sharma, Suresh Ray Yadav

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Local soils are often chosen due to their widespread availability and low cost. However, these soils typically have poor durability, which can lead to significant limitations in their use for construction. To address this issue, various soil stabilization techniques have been developed and used over the years. This study investigates the viability of employing the mineral polymerization (MIP) technique to stabilize black soils, intending to enhance their suitability for construction applications. This technique involves the microstructural transformation of certain clay minerals into solid and stable compounds exhibiting characteristics similar to hydroxy sodalite, feldspathoid, or zeolite. This transformation occurs through the action of an alkaline reactant at atmospheric pressure and low temperature. The soil sample was characterized using grain size distribution, Atterberg limit test, organic content test, and pH-value tests. The unconfined compressive strength of the soil specimens, prepared with varying percentages of sodium hydroxide as an additive and sand as a filler by weight, was determined at the optimum moisture content. The unconfined compressive strength of the specimens was tested under three different conditions: dry, wet, and cycling. The maximum unconfined compressive strengths were 77.568 kg/cm², 38.85 kg/cm², and 56.3 kg/cm² for the dry, wet, and cycling specimens, respectively, while the unconfined compressive strength of the untreated soil was 7.38 kg/cm². The minimum unconfined compressive strength of the wet and cycling specimens was greater than that of the untreated soil. Based on these findings, it can be concluded that these soils can be effectively used as construction material after treatment with sodium hydroxide.

Keywords: soil stabilization technique, soft soil treatment, sodium hydroxide, unconfined compressive strength

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Authors: Imam Wierawansyah Eltara, Iftitah, Agus Ismail

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In the present work, cellulose nanowhiskers (CNW) extracted from coconut husk fibers, were incorporated in polylactide (PLA)-based composites. Prior to the blending, PLA chains were chemically grafted on the surface of CNW to enhance the compatibilization between CNW and the hydrophobic polyester matrix. Ring-opening polymerization of L-lactide was initiated from the hydroxyl groups available at the CNW surface to yield CNW-g-PLA nanohybrids. PLA-based nanocomposites were prepared by melt blending to ensure a green concept of the study thereby limiting the use of organic solvents. The influence of PLA-grafted cellulose nanoparticles on the mechanical and thermal properties of the ensuing nanocomposites was deeply investigated. The thermal behavior and mechanical properties of the nanocomposites were determined using differential scanning calorimetry (DSC) and dynamical mechanical and thermal analysis (DMTA), respectively. In theory, evidenced that the chemical grafting of CNW enhances their compatibility with the polymeric matrix and thus improves the final properties of the nanocomposites. Large modification of the crystalline properties such as the crystallization half-time was evidenced according to the nature of the PLA matrix and the content of nanofillers.

Keywords: cellulose nanowhiskers, nanocomposites, coconut husk fiber, ring opening polymerization

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Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Bărbuță Alina

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The inter-causal relationship between social inequalities and the digital divide raises the relation issue of gender and information and communication technologies (ICT) - a key element in achieving sustainable development. In preparing generations as future digital citizens and for active socio-economic participation, ICT plays a key role in respecting gender equality. Although several studies over the years have shown that gender plays an important role in digital exclusion, in recent years, many studies with a focus on economically developed or developing countries identify an improvement in these aspects and a gap narrowing. By measuring students' digital competencies level, this paper aims to identify and analyse the existing gender digital inequalities among students. Our analyses are based on a sample of 1526 middle school students residing in rural areas from Republic of Moldova (54.2% girls, mean age 14,00, SD = 1.02). During the online survey they filled in a questionnaire adapted from the (yDSI) ”The Youth Digital Skills Indicator”. The instrument measures the level of five digital competence areas indicated in The European Digital Competence Framework (DigiCom 2.3.). Our results, based on t-test, indicate that depending on gender, there are no statistically significant differences regarding the levels of digital skills in 3 areas: Information navigation and processing; Communication and interaction; Problem solving. However, were identified significant differences in the level of digital skills in the area of ”Digital content creation” [t(1425) = 4.20, p = .000] and ”Safety” [t(1421) = 2.49, p = .000], with higher scores recorded by girls. Our results contradicts the general stereotype regarding the low level of digital competence among girls, in our sample girls scores being on pear with boys and even bigger in knowledge related to digital content creation and online safety skills. Additional investigations related to boys competence on digital safety are necessary as the implication of their low scores on this dimension may suggest boys exposure to digital threats.

Keywords: digital divide, education, gender digital divide, digital literacy, remote learning

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Authors: A.Assariotakis, P. Vahamidis, P. Tarantilis, G. Economou

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Greece, due to its geographical location and the particular climatic conditions, presents high biodiversity of Medicinal and Aromatic Plants. Among them, the genus Origanum not only presents a wide distribution, but it also has great economic importance. After extensive surveys in Ikaria Island (Greece), 3 species of the genus Origanum were identified, namely, Origanum vulgare ssp. hirtum (Greek oregano), Origanum onites (Turkish oregano) and Origanum x intercedens (hybrid), a naturally occurring hybrid between O. hirtum and O. onites. The purpose of this study was to determine their morphological as well as their temporal variability in essential oil yield and composition under field conditions. For this reason, a plantation of each species was created using vegetative propagation and was established at the experimental field of the Agricultural University of Athens (A.U.A.). From the establishment year and for the following two years (3 years of observations), several observations were taken during each growing season with the purpose of identifying the morphological differences among the studied species. Each year collected plant (at bloom stage) material was air-dried at room temperature in the shade. The essential oil content was determined by hydrodistillation using a Clevenger-type apparatus. The chemical composition of essential oils was investigated by Gas Chromatography-Mass Spectrometry (GC – MS). Significant differences were observed among the three oregano species in terms of plant height, leaf size, inflorescence features, as well as concerning their biological cycle. O. intercedens inflorescence presented more similarities with O. hirtum than with O. onites. It was found that calyx morphology could serve as a clear distinction feature between O. intercedens and O. hirtum. The calyx in O. hirtum presents five isometric teeth whereas in O. intercedens two high and three shorter. Essential oil content was significantly affected by genotype and year. O. hirtum presented higher essential oil content than the other two species during the first year of cultivation, however during the second year the hybrid (O. intercedens) recorded the highest values. Carvacrol, p-cymene and γ-terpinene were the main essential oil constituents of the three studied species. In O. hirtum carvacrol content varied from 84,28 - 93,35%, in O. onites from 86,97 - 91,89%, whereas in O. intercedens it was recorded the highest carvacrol content, namely from 89,25 - 97,23%.

Keywords: variability, oregano biotypes, essential oil, carvacrol

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Authors: Youn Young Shim, Martin J. T. Reaney

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Flaxseed meal is rich in water-soluble gums and, as such, can improve texture in gluten-free products. Flaxseed bioactive-antioxidant peptides, linusorbs (LOs, a.k.a. cyclolinopeptides), are a class of molecules that may contribute health-promoting effects. The effects of dough preparation, baking, and storage on flaxseed-derived LOs stability in doughs and baked products are un-known. Gluten-free (GF) bread dough and bread were prepared with flaxseed meal and the LO content was determined in the flaxseed meal, bread flour containing the flaxseed meal, bread dough, and bread. The LO contents during storage (0, 1, 2, and 4 weeks) at different temperatures (−18 °C, 4 °C, and 22−23 °C) were determined by high-performance liquid chromatog-raphy-diode array detection (HPLC-DAD). The content of oxidized LOs like [1–9-NαC],[1(Rs, Ss)-MetO]-linusorb B2 (LO14) were substantially constant in flaxseed meal and flour produced from flaxseed meal under all conditions for up to 4 weeks. However, during GF-bread production LOs decreased. Due to microbial contamination dough could not be stored at either 4 or 21°C, and bread could only be stored for one week at 21°C. Up to 4 weeks storage was possible for bread and dough at −18 °C and bread at 4 °C without the loss of LOs. The LOs change mostly from processing and less so from storage. The concentration of reduced LOs in flour and meal were much higher than measured in dough and bread. There was not a corre-sponding increase in oxidized LOs. The LOs in flaxseed meal-fortified bread were stable for products stored at low temperatures. This study is the first of the impact of baking conditions on LO content and quality.

Keywords: flaxseed, stability, gluten-free, antioxidant

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Authors: Daniel Gidey, Kunwar Siddarth Dadhwal, Tagel Wondimu

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There are numerous ways for ending conflict; hitherto, most conflicts are resolved either through negotiated or victor's peace, this article is about the former. Negotiations entail concessions, consensus-building, and mutual trust in order to transform a belligerent situation into a settlement. In such a context, regional and sub-regional organizations play a critical role in mediating conflicting parties so as to prevent, manage, and resolve conflicts between and among conflicting parties. This article is about the AU-led negotiated peace deal on the bloody conflict between the Tigray Peoples Liberation Front (TPLF) and the Federal Democratic Republic of Ethiopia (FDRE) by undertaking the Pretoria Peace Accord as a case study. In terms of research method, the article is based on a critical evaluation of the literature and content analysis on the very research topic. Findings of the study revealed that the AU, through Olusegun Obasanjo and other dignitaries, played a critical role in nurturing compromise and mutual trust between the TPLF and the Ethiopian federal government so as to take along the Pretoria peace deal. Through critical literature review and content analysis of the Peace deal, the article has concluded that negotiated peace is likely, at least, to achieve negative peace.

Keywords: regional organizations, peace promotion, African Union, negotiating conflicts, Northern Ethiopia, conflict resolution

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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Authors: Hsiao-Yung Wang

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This paper aims to elaborate methodology of visual rhetoric with constant reference to Mikhail Bakhtin’s concept of “chronotope”. First, it attempts to outline Ronald Barthes, the most representative scholar of visual rhetoric and structuralism, perspective on visual rhetoric and its time-space category by referring to the concurrent word-image, the symbolic systematicity, the outer dialogicity. Second, an alternative approach is explored for grasping the dynamics and functions of visual rhetoric by articulating Mikhail Bakhtin’s concept of “chronotope.” Furthermore, that visual rhetorical consciousness could be identified as “the meaning parabola which projects from word to image,” “the symbolic system which proceeds from sequence to disorder,” “the ideological environment which struggles from the local to the global.” Last but not least, primary vision of the 2014 Taipei LGBT parade would be analyzed preliminarily to evaluate the effectiveness and persuasiveness embodied by specific visual rhetorical strategies. How Bakhtin’s concept of “chronotope” to explain the potential or possible ideological struggle deployed by visual rhetoric might be interpreted empirically and extensively.

Keywords: barthes, chronotope, Mikhail Bakhtin, Taipei LGBT parade, visual rhetoric

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Hanan A. Algamdi, Huda Y. Alyami

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Learning object repositories contribute to developing educational process through its advantages; as they employ technology effectively, and use it to create new resources for effective learning, as well as they provide opportunities for collaboration in content through providing the ability for editing, modifying and developing it. This supports the relationships between communities that benefit from these repositories, and reflects positively on the content quality. Therefore, this study aims at exploring the most prominent learning topics in the 21st century, which should be included in learning object repositories, and identifying the necessary set of learning skills that the repositories should develop among today students. For conducting this study, the analytical descriptive method will be employed, and study sample will include a group of leaders, experts, and specialists in curricula and e-learning at ministry of education in Kingdom of Saudi Arabia.

Keywords: learning object, repositories, 21st century, quality

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Authors: Disha Batra

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The Industrial Revolution 4.0 is quite different, and a paradigm shift is underway in the media industry. With the advent of automated journalism and social media platforms, newspaper organizations have changed the way news was gathered and reported. The emergence of the fourth industrial revolution in the early 21st century has made the newspapers to adapt the changing technologies to remain relevant. This paper investigates the content of Indian business-papers in the era of the fourth industrial revolution and how these organizations have emerged in the time of convergence. The study is the content analyses of the top three Indian business dailies as per IRS (Indian Readership Survey) 2017 over a decade. The parametric analysis of the different parameters (source of information, use of illustrations, advertisements, layout, and framing, etc.) have been done in order to come across with the distinct adaptations and modifications by these dailies. The paper significantly dwells upon the thematic analysis of these newspapers in order to explore and find out the coverage given to various sub-themes of EBF (economic, business, and financial) journalism. Further, this study reveals the effect of high-speed algorithm-based trading, the aftermath of the fourth industrial revolution on the creative and investigative aspect of delivering financial stories by these respective newspapers. The study indicates a change heading towards an ongoing paradigm shift in the business newspaper industry with an adequate change in the source of information gathering along with the subtle increase in the coverage of financial news stories over the time.

Keywords: business-papers, business news, financial news, industrial revolution 4.0.

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Authors: Raghava Dhanya, Shashank S.

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This paper delves into the intersection of chess and computer science, specifically focusing on the efficient representation of chess game states. We propose two methods: the Static Method and the Dynamic Method, each offering unique advantages in terms of space efficiency and computational complexity. The Static Method aims to represent the game state using a fixedlength encoding, allocating 192 bits to capture the positions of all pieces on the board. This method introduces a protocol for ordering and encoding piece positions, ensuring efficient storage and retrieval. However, it faces challenges in representing pieces no longer in play. In contrast, the Dynamic Method adapts to the evolving game state by dynamically adjusting the encoding length based on the number of pieces in play. By incorporating Alive Bits for each piece kind, this method achieves greater flexibility and space efficiency. Additionally, it includes provisions for encoding additional game state information such as castling rights and en passant squares. Our findings demonstrate that the Dynamic Method offers superior space efficiency compared to traditional Forsyth-Edwards Notation (FEN), particularly as the game progresses and pieces are captured. However, it comes with increased complexity in encoding and decoding processes. In conclusion, this study provides insights into optimizing the representation of chess game states, offering potential applications in chess engines, game databases, and artificial intelligence research. The proposed methods offer a balance between space efficiency and computational overhead, paving the way for further advancements in the field.

Keywords: chess, optimisation, encoding, bit manipulation

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Authors: Ki-Ho Nam, Haksoo Han

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Tetrapod zinc oxide whiskers (TZnO-Ws) were successfully synthesized by a thermal oxidation method. A series of transparent polyimide (PI)/TZnO-W composites were successfully synthesized via a solution-blending method. The structural and morphological features of TZnO-Ws and PI/TZnO-W composites were characterized by Fourier transform infrared spectroscopy (FT-IR), wide-angle X-Ray diffraction (WAXD), and field emission scanning electron microscope (FE-SEM). Dynamic stress behaviors were investigated in-situ during thermal imidization of the soft-baked PI/TZnO-W composite precursor and thermally cured composite films using a thin film stress analyzer (TFSA) by wafer bending technique. The PI/TZnO-W composite films exhibited an optical transparency greater than 80% at 550 nm (≤ 0.5 wt% TZnO-W content), a low coefficient of thermal expansion (CTE), and enhanced glass transition temperature. However, the thermal decomposition temperature decreased as the TZnO-W content increased. The water diffusion coefficient and water uptake of the PI/TZNO-W composite films were obtained by best fits to a Fickian diffusion model. The water resistance capacity of PI was greatly enhanced and moisture diffusion in the pure PI was retarded by incorporating the TZnO-W. The PI composite films based on TZNO-W resultantly may have potential applications in optoelectronic manufacturing processes as a flexible transparent substrate.

Keywords: polyimide (PI), tetrapod ZnO whisker (TZnO-W), transparent, dynamic stress behavior, water resistance

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Authors: Renata Adriana Labanca, Gabriela Rezende Costa, Nilton de Oliveira Couto e Silva, José Marcos Gontijo Mandarino, Rodrigo Santos Leite, Nilson César Castanheira Guimarães, Roberto Gonçalves Junqueira

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The objective of this study was to evaluate the differences in composition between six brands of conventional soybean and six genetically modified cultivars (GM), all of them from Minas Gerais State, Brazil. We focused on the isoflavones profile and mineral content questioning the substantial equivalence between conventional and GM organisms. The statement of compliance label for conventional grains was verified for the presence of genetic modified genes by real time polymerase chain reaction (PCR). We did not detect the presence of the 35S promoter in commercial samples, indicating the absence of transgene insertion. For mineral analysis, we used the method of inductively coupled plasma-optical emission spectrometry (ICP-OES). Isoflavones quantification was performed by high performance liquid chromatography (HPLC). The results showed no statistical difference between the conventional and transgenic soybean groups concerning isoflavone content and mineral composition. The concentration of potassium, the main mineral component of soy, was the highest in conventional soybeans compared to that in GM soy, while GM samples presented the highest concentrations of iron.

Keywords: glycine max, genetically modified organism, bioactive compounds, ICP-OES, HPLC

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Authors: Bibi Alajmi, Israa Alshammari

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This study investigates diversity strands covered in courses offered by library and information sciences (LIS) graduate programs. It aims to identify the extent to which these programs prepare students to work in diverse communities. Information was collected from 17 ALA-accredited MLIS programs. Diversity-related topics were identified and categorized. The methodology consisted of content analysis of course syllabi. The findings show that coverage of diversity-related content in LIS graduate curricula is increasing at a slow but significant rate, and is often a low priority. Apart from LIS graduate courses for future librarians and information professionals in public libraries, school libraries, and museums providing services to young adults and children, there is not enough interest in the provision of services to diverse communities.

Keywords: diversity, multiculturalism, inclusion, equality, gender

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Authors: Ahmed Fathi Mohamed, Nasir Shafiq, Muhd Fadhil Nuruddin, Ali Elheber Ahmed

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Steel fiber adds to Self-Compacting Concrete (SCC) to enhance it is properties and achieves the requirement. This research work focus on the using of different percentage of steel fiber in SCC mixture contains fly ash and microwave incinerator rice husk ash (MIRHA) as supplementary material. Fibers affect several characteristics of SCC in the fresh and the hardened state. To optimize fiber-reinforced self-compacting concrete (FSCC), The possible fiber content of a given mix composition is an essential input parameter. The aim of the research is to study the properties of fiber reinforced self–compacting (FRSCC) and to develop the expert system/computer program of mix proportion for calculating the steel fiber content and pozzolanic replacement that can be applied to investigate the compressive strength of FSCC mix.

Keywords: self-compacting concrete, silica fume, steel fiber, fresh taste

Procedia PDF Downloads 545

Authors: Krasimir Ivanov, Dimitar Dimitrov, Tatyana Tabakova, Stefka Kirkova, Anna Stoilova, Violina Angelova

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It has been suggested that nicotine, CO and tar in mainstream smoke are the most important substances and have been judged as the most harmful compounds, responsible for the health hazards of smoking. As nicotine is extremely important for smoking qualities of cigarettes and the tar yield in the tobacco smoke is significantly reduced due to the use of filters with various content and design, the main efforts of cigarettes researchers and manufacturers are related to the search of opportunities for CO content reduction. Highly active ceria supported gold catalyst was prepared by the deposition-precipitation method, and the possibilities for CO oxidation in the synthetic gaseous mixture were evaluated using continuous flow equipment with fixed bed glass reactor at atmospheric pressure. The efficiently of the catalyst in CO oxidation in the real cigarette smoke was examined by a single port, puf-by-puff smoking machine. Quality assessment of smoking using cigarette holder containing catalyst was carried out. It was established that the catalytic activity toward CO oxidation in cigarette smoke rapidly decreases from 70% for the first cigarette to nearly zero for the twentieth cigarette. The present study shows that there are two critical factors which do not permit the successful use of catalysts to reduce the CO content in the mainstream cigarette smoke: (i) significant influence of the processes of adsorption and oxidation on the main characteristics of tobacco products and (ii) rapid deactivation of the catalyst due to the covering of the catalyst’s grains with condensate.

Keywords: cigarette smoke, CO oxidation, gold catalyst, mainstream

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Authors: Faci Youcef, Ahmed Mebtouche, Djillali Allou, Maalem Badredine

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The inclination of the bolt in a fastened joint of composite material during a tensile test can be influenced by several parameters, including material properties, bolt diameter and length, the type of composite material being used, the size and dimensions of the bolt, bolt preload, surface preparation, the design and configuration of the joint, and finally testing conditions. These parameters should be carefully considered and controlled to ensure accurate and reliable results during tensile testing of composite materials with fastened joints. Our work focuses on the effect of the stacking sequence and the geometry of specimens. An experimental test is carried out to obtain the inclination of a bolt during a tensile test of a composite material using acoustic emission and digital image correlation. Several types of damage were obtained during the load. Digital image correlation techniques permit the obtaining of the inclination of bolt angle value during tensile test. We concluded that the inclination of the bolt during a tensile test of a composite material can be related to the damage that occurs in the material. It can cause stress concentrations and localized deformation in the material, leading to damage such as delamination, fiber breakage, matrix cracking, and other forms of failure.

Keywords: damage, inclination, analyzed, carbon

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Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

Abstract:

The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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Authors: Sawale Pravin Digambar, G. R. Patil, Shaik Abdul Hussain

Abstract:

Terminalia arjuna (TA), an important medicinal plant in Indian System of Medicine, is specifically recognized for its recuperative effect on heart ailments. Alcoholic extract of TA (both free and encapsulated) was incorporated into milk to obtain functional dairy beverages. The respective beverages were appropriately flavored and optimized using response surface methodology to improve the sensory appeal. The beverages were evaluated for their compositional, anti-oxidative and various other physico-chemical aspects. Addition of herb (0.3%) extract to flavoured dairy drink (Drink 1) resulted in significantly lowered (p>0.05) HMF content and increased antioxidant activity, total phenol content as compared with control (Control 1). Subsequently, a significant (p>0.05) increase in acidity and sedimentation was also observed. Encapsulated herb (1.8%) incorporated drink (Drink 2) had significantly (P>0.05) enhanced HMF value and decreased antioxidant activity, phenol content as compared to herb added vanilla chocolate dairy drink (Drink 1). It can be concluded that addition of encapsulated TA extract and non-encapsulated TA extract to chocolate dairy drink at 0.3% concentration altered the functional properties vanilla chocolate dairy drink which could be related to the interaction of herb components such as polyphenol with milk protein or maltodextrin/ gum Arabic matrix.

Keywords: Terminalia arjuna, encapsulate, antioxidant activity, physicochemical study

Procedia PDF Downloads 347

Authors: L. Dinco John Christian, C. Ramos Camille, C. Reyes Maria Eloisa

Abstract:

HIV/AIDS has been dubbed as one of the most stigmatised diseases of the recent century. Nelson Mandela pointed out that PLWHA (People Living With HIV/AIDS) are not killed by the disease, but by the stigma surrounding it. Despite the numerous studies on HIV/AIDS Stigmatisation globally, little is known about how evident and how powerful the media can be in framing the views of the readers when it comes to print in the Philippine context. This study dealt with a quantitative content analysis of HIV/AIDS-related news articles published by the top three broadsheets such as Philippine Daily Inquirer, Manila Bulletin and the Philippine Star in the span of one year. The HIV/AIDS-related news articles were collected and subjected to coding according to their tones, stigmatising statements/terminologies and news prominence. An analysis of the results had supported the researchers’ objectives (1) that there are different tones of HIV/AIDS-related news articles, (2) that there is a significant relation between the Stigmatizing Statements/Terminologies and the tone and that the (3) technical properties of HIV/AIDS related news articles determine the news prominence. Results revealed that despite the fact that the broadsheets were overtly reporting HIV/AIDS in Anti-Stigma-toned articles, they were covertly suggesting Stigma by the use of Stigmatising statements/terminologies present in it rather than plainly disseminating current medical knowledge about the transmission and treatments of the disease; the technical properties of the HIV/AIDS related news articles determined its prominence.

Keywords: HIV, AIDS, newspaper, content analysis

Procedia PDF Downloads 414

Authors: Julio Vega

Abstract:

Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

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Authors: Asmau Mukhtar Ahmed, Olga Duran

Abstract:

Hydrocarbon (HC) spills constitute a significant problem that causes great concern to the environment. With the latest technology (hyperspectral images) and state of the earth techniques (image processing tools), hydrocarbon spills can easily be detected at an early stage to mitigate the effects caused by such menace. In this study; a controlled laboratory experiment was used, and clay soil was mixed and homogenized with different hydrocarbon types (diesel, bio-diesel, and petrol). The different mixtures were scanned with HYSPEX hyperspectral camera under constant illumination to generate the hypersectral datasets used for this experiment. So far, the Short Wave Infrared Region (SWIR) has been exploited in detecting HC spills with excellent accuracy. However, the Near-Infrared Region (NIR) is somewhat unexplored with regards to HC contamination and how it affects the spectrum of soils. In this study, Deep Neural Network (DNN) was applied to the controlled datasets to detect and quantify the amount of HC spills in soils in the Near-Infrared Region. The initial results are extremely encouraging because it indicates that the DNN was able to identify features of HC in the Near-Infrared Region with a good level of accuracy.

Keywords: hydrocarbon, Deep Neural Network, short wave infrared region, near-infrared region, hyperspectral image

Procedia PDF Downloads 95