Search results for: object weight

Authors: Sadia Basar, Naila Habib, Awais Adnan

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The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

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Authors: Marc Angelo C. Balon, Maxine Joy A. Yongoyong

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Female masturbation has been an age-old controversy. In fact, it is not widely talked about specifically in the Philippines since the Filipino culture still preserves the space for conservativeness. Although, considering the numerous and emerging studies on female masturbation, this study will focus on the perspectives of secular and non-secular male groups with regard to female masturbation. The objectives of this study is to identify the perceptions of these male groups and their taking on considering women who masturbate as their sexual partner, as a sexual object, and as a life partner and lastly, to have a comparative analysis of the perceptions of these male groups drawing out their sense of meaning on the masturbation of women. The researchers made use of purposive sampling technique and interview guide questionnaire. The secular male group were psychology students while the non-secular male group was drawn from a Catholic Church seminary in Tagaytay City, Cavite. Results showed that the secular male group had scientific perspectives such as exploring the genitals, contradicting moral perspectives on masturbation as a regular practice, while the non-secular male groups had theological perspectives in accordance with the fundamental moral theology, moral perspectives and perspectives on masturbation as a regular practice. Moreover, men who came from the non-secular group highly believe that masturbation is immoral. Otherwise, men who came from the secular group noted that masturbation is primary physiological need.

Keywords: secular, non-secular, masturbation, comparative analysis

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Javad Saeidaskari, Mohammad Hassan Baziar

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Soil structures have been frequently damaged during piping, earthquake and other types of failures. As far as adverse circumstances were developed subsequent to piping or other similar failure types, hydraulic parameters of soil such as hydraulic conductivity should be considered. As a result, acquiring an approach to diminish soil permeability is inevitable. There are many ground improvement methods to reduce seepage, which are classified under soil treatment and stabilization methods. Recently, one of the soil improvement methods is known as nanogeotechnology. This study aims to investigate the influence of Cloisite 30B nanoclay on permeability of compacted clayey sand soils. The samples are prepared by mixing two soil types, including Kaolin clay and Firouzkooh sand, in 1:9 and 1:5 clay:sand (by mass) proportions. In experimental procedure, initially, the optimum water content and maximum dry unit weight of each samples were obtained for compaction. Then, series of permeability tests were conducted by triaxial apparatus on prepared specimens with identical relative density of 95% of maximum dry density and water content of 1% wet of optimum for different weight percentages of nanoclay (1% to 4%). Therefore, in this paper, the effect of time on treated specimen was appraised, as well as two approaches of manual mixing and ball milling were compared to reveal the importance of dispersion issue. The results show that adding nanoclay up to 3%, as its optimum content, causes notable reduction in permeability (1.60e-03 to 5.51e-05 cm/s and 3.32e-04 to 8.44e-07 cm/s in samples with 1:9 and 1:5 mixture proportions, respectively). The hydraulic conductivity of treated clayey sand (1:5 mixture proportion with 3% nanoclay) decreases gradually from 8.44e-07 to 3.00e-07 cm/s within 90 days and then tends to be consistent. The influence of mixing method on permeability results shows that the utilization of ball mill mixing effectively leads to lower values than those of manual mixing, in other words, by adding 3% nanoclay, hydraulic conductivity of specimen declines from 8.44e-07 to 2.00e-07 cm/s. In order to evaluate the interaction between soil particles and, to ensure proper dispersion of nanoparticles through clayey sand mixture, they were magnified by means of scanning electron microscope (SEM). In conclusion, the nanoclay particles in vicinity of moisture can cause soil stabilization to prevent water penetration, which eventually result in lower usage of clay and operation costs.

Keywords: nanoclay, cloisite 30b, clayey sand, hydraulic conductivity

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Authors: Walid Al-Qerem, Ruba Zumot

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Background: The rise of obesity among children and adolescents remains a primary challenge for healthcare providers globally and in the Middle East. The aim of the present study is to determine the prevalence of obesity among 5-20 years old Jordanians based on CDC criteria. Method: A total of 5722 Jordanians (37% males; 63% females) aged 5-20 years data were retrieved from the Jordanian Ministry of Health electronic database (Hakeem). As per the CDC selection criteria, the chosen data pertains exclusively to healthy Jordanian children and adolescents who are medically sound, not suffering from health conditions, and not undergoing any treatments that could hinder normal growth patterns, such as severe infection, chronic kidney disease (CKD), Down’s syndrome, attention deficit hyperactivity disorder, cancer, heart disease, lung disease, cystic fibrosis, Crohn’s disease, type 1 diabetes, hormonal disturbances, any stress-related conditions, hormonal therapy such as corticosteroids, Growth hormones (GHS) or gonadotropin-releasing hormone agonists, insulin, and amphetamines or any other stimulants. In addition, participants with missing or invalid data values for anthropometric measurements were excluded from the study. Weight for age and body mass index for age were analyzed comparatively for Jordanian children and adolescents against the international growth standards. The Z-score for each record was computed based on CDC equations. As per CDC classifications, BMI for age percentiles, values ≥85th and < 95th are classified as overweight, and value at ≥ 95th is classified as obesity. Results: The average age of the evaluated sample was 12.33 ±4.39 years (10.79 ±3.39 for males and 13.23 ± 4.66 for females). The mean weight for males and females were 33.16±14.17 Kg and 133.54±17.17 cm for males, 43.86 ±18.82 Kg, and 142.19±18.35 for females, while for BMI the mean was for boys and girls 17.81±3.88 and 20.52±5.03 respectively. The results indicated that based on CDC criteria, 8.9% of males were classified as children/adolescents with overweight, and 9.7% were classified as children/adolescents with obesity, while in females, 17.8% were classified as children/adolescents with overweight and 10.2% were classified as children/adolescents with obesity. Discussion: The high prevalence of obesity reported in the present study emphasizes the importance of applying different strategies to prevent childhood obesity, including encouraging physical activity, promoting healthier food options, and behavioral changes. Conclusion: The results presented in this study indicated the high prevalence of overweight/obesity among Jordanian adolescents and children, which must be tagged by healthcare planners and providers.

Keywords: CDC, obesity, childhood, Jordan

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Authors: S. Nandagopalan, N. Pradeep

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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, bayesian, echocardiographic image, feature vector

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Authors: Soner Guler, Fuat Korkut

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Recently, the using of lightweights concretes in construction sector is rapidly increasing all over the world. Faster construction, low density and thermal transmitting coefficient and high fire resistance are the remarkable characteristics of the lightweight concretes. Lightweight concrete can be described as a type of concrete which enhance the volume of the mixture while giving additional advantages such as to reduce the dead weight of the structures. It is lighter than the conventional concrete. The use of lightweight concrete has been widely spread across countries such as USA, United Kingdom, and Sweden. In this study, the necessity of the using of lightweights concretes in the construction sector is emphasized and evaluated briefly for the architectures and civil engineers.

Keywords: lightweights concretes, low density, low thermal coefficient, construction sector

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Authors: Rim Zgueb, Noureddine Yacoubi

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The objective of this study was to investigate the thermal property of magnesium oxychloride cement (MOC) using glass powder as a substitute. Glass powder by proportion 0%, 5%, 10%, 15% and 20% of cement’s weight was added to specimens. At the end of a drying time of 28 days, thermal properties, compressive strength and bulk density of samples were determined. Thermal property is measured by Photothermal Deflection Technique by comparing the experimental of normalized amplitude and the phase curves of the photothermal signal to the corresponding theoretical ones. The findings indicate that incorporation of glass powder decreases the thermal properties of MOC.

Keywords: magnesium oxychloride cement (MOC), phototharmal deflection technique, thermal properties, Ddensity

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Ekaterina Lukianchenko

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The present article addresses the nuances of teaching English vocabulary to Russian-speaking students. The experiment involving 39 participants aged 17 to 21 proves that the key to understanding spoken coinages is not only the knowledge of their constituents, but rather the understanding of the context and co-text. The volunteers who took part knew the constituents, but did not know the meaning of the words. The assumption of the authors consists in the fact that the structure of the concept has a direct relation with the form of the particular vocabulary unit, but its form is secondary to its meaning, if the word is a spoken coinage, which is partly proved by the fact that in modern slang words have multiple meanings, as well as one notion can have various embodiments that have virtually nothing in common. The choice of vocabulary items that youngsters use is not exactly arbitrary, but, even if complex nominals are taken into consideration, whose meaning seems clear, as it looks like a sum of their constituents’ meanings, they are still impossible to understand without any context or co-text, as a lot of them are idiomatic, non-transparent. It is further explained what methods might be effective in teaching students how to deal with new words they encounter in real-life situations and how student’s knowledge of vocabulary might be enhanced.

Keywords: spoken language, cognitive linguistics, complex nominals, nominals with the incorporated object, concept, EFL, communicative language teaching

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Authors: Elisa Bertagna

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A frame analysis of the work done by various energy multinational companies concerning diversity issues and gender equality is presented. Documents of four multinational companies - two from Finland and two from Italy - have been studied. The array of companies’ documents includes data from their websites, policies and so on. The Finnish and Italian contexts have been chosen as a sample of North and South Europe, of 'advanced' and 'less advanced'. The aim of the analysis is to understand if and how human resource and diversity management in Finnish and Italian multinational energy companies communicate their activity towards the employees. Attention is given on how employees are reacting in their role and on the consequences of its social positioning. The findings of this essay are crucially important. They show how the companies in object tend to focus on the HR and DM positive actions towards female employees’ struggles since the industry is characterized by multinationals with male-dominated employees. In this way, other categories, which are also depicted as sensitive such as young and elderly people or foreigners, do not receive the same amount of attention. Consequently, power hierarchies can be found: 'women' as a social category are given more importance and space in the companies’ data than others. Consequently, the present work analysis reflects on possible struggles that such companies might be facing concerning gender biases and further diverse issues.

Keywords: energy, diversity, gender, multinationals, power hierarchies

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Authors: Kamrun Nahar Koly, Saimul Islam

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Overweight and obesity is increasing at an alarming rate and a leading risk factor for morbidity throughout the world. In a country like Bangladesh where under nutrition and overweight both co-exist at the same time, but this issue has been underexplored as expected. The aim of the present study was to assess the knowledge, attitudes and identify the barriers of the physicians regarding overweight and obesity management on an urban hospital of Dhaka city in Bangladesh. A simple cross sectional study was conducted at two selected government and two private hospital to assess the knowledge, attitude and common barriers regarding overweight and obesity management among healthcare professionals. One hundred and fifty five physicians were surveyed. A standard questionnaire was constructed in local language and interview was administrated. Among the 155 physicians, majority 53 (34.20%) were working on SMC, 36 (23.20%) from DMC, 33 (21.30%) were based on SSMC and the rest 33 (21.30%) were from HFRCMH. Mean age of the study physicians were 31.88±5.92. Majority of the physicians 80 (51.60%) were not able to answer the correct prevalence of obesity but also a substantial number of them 75(48.40%) could mark the right answer. Among the physicians 150 (96.77%) reported BMI as a diagnostic index for overweight and obesity, where as 43 (27.74%) waist circumference, 30 (19.35%) waist hip ratio and 26 (16.77%) marked mid-arm circumference. A substantial proportion 71 (46.70%) of the physicians thought that they do not have much to do controlling weight problem in Bangladesh context though it has been opposed by 42 (27.60%) of the physicians and 39(25.70%) was neutral to comment. The majority of them 147 (96.1%) thought that a family based education program would be beneficial followed by 145 (94.8%) physicians mentioned about raising awareness among mothers as she is the primary caregiver. The idea of a school based education program will also help to early intervene referred by 142 (92.8%) of the physicians. Community based education program was also appreciated by 136 (89.5%) of the physicians. About 74 (47.7%) of them think that the patients still lack in motivation to maintain their weight properly at the same time too many patients to deal with can be a barrier as well assumed by 73 (47.1%) of them. Lack of national policy or management guideline can act as an obstacle told by 60 (38.7%) of the physicians. The relationship of practicing as a part of the general examination and chronic disease management was statistically significant (p<0.05) with physician occupational status. As besides, perceived barriers like lack of parents support, lack of a national policy was statistically significant (p<0.05) with physician occupational status. For the young physician, more training programme will be needed to transform their knowledge and attitude into practice. However, several important barriers interface for the physician treatment efforts and need to address.

Keywords: obesity management, physician, awareness, barriers, Bangladesh

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Authors: Vinay P., Srinivas K. S.

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Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

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Authors: Laura Fernanda Pedreros Araque, Sebastian Rivera Pardo

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The massive removal phenomena have been one of the most frequent natural disasters in the world, causing thousands of deaths, victims, damage to homes and diseases. In Pitalito, and Campoalegre department of Huila municipalities - Colombia, disasters have occurred due to various events such as high rainfall, earthquakes; it has caused landslides, floods, among others, affected the economy, the community, and transportation. For this reason, a study was carried out on the area’s most prone to suffer these phenomena to take preventive measures in favor of the protection of the population, the resources of management, and the planning of civil works. For the proposed object, the Mora-Varshon method was used, which allows classifying the degree of susceptibility to landslides in which the areas are found. Also, various factors or parameters were evaluated such as the soil moisture, lithology, slope, seismicity, and rain, each of these indicators were obtained using information from IDEAM, Servicio Geologico Colombiano (SGC) and using geographic information for geoprocessing in the Arcgis software to realize a mapping to indicate the susceptibility to landslides, classifying the areas of the municipalities such as very low, low, medium, moderate, high or very high.

Keywords: geographic information system, landslide, mass removal phenomena, Mora-Varshon method

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Authors: Shashank Gupta, Shiva Garg

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The purpose of the present paper is to study the changes in the strength characteristics of autoclaved aerated concrete (AAC) and also the density when different expansion agents are used. The expansion agent so used releases air in the concrete thereby making it lighter by reducing its density. It also increases the workability of the concrete. The various air entraining agents used for this study are hydrogen peroxide, oleic acid, and olive oil. The addition of these agents causes the concrete to rise like cake but it reduces the strength of concrete due to the formation of air voids. The amount of agents chosen for concrete production are 0.5%, 1%, 1.5% by weight of cement.

Keywords: AAC, olive oil, hydrogen peroxide, oleic acid, steam curing

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Authors: Vipin Kumar Verma, Neeta Sehgal, Om Prakash

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Cyprinus carpio has a wide spread occurrence in the lakes and rivers of Europe and Asia. Heavy losses in natural environment due to anthropogenic activities, including pollution as well as pathogenic diseases have landed this fish in IUCN red list of vulnerable species. The significance of a suitable diet in preserving the health status of fish is widely recognized. In present study, artificial feed supplemented with leaves of two weed plants, Eichhornia crassipes and Ricinus communis were evaluated for their role on the fish immune system. To achieve this objective fish were acclimatized to laboratory conditions (25 ± 1 °C; 12 L: 12D) for 10 days prior to start of experiment and divided into 4 groups: non-challenged (negative control= A), challenged [positive control (B) and experimental (C & D)]. Group A, B were fed with non-supplemented feed while group C & D were fed with feed supplemented with 5% Eichhornia crassipes and 5% Ricinus communis respectively. Supplemented feeds were evaluated for their effect on growth, health, immune system and disease resistance in fish when challenged with Vibrio harveyi. Fingerlings of C. carpio (weight, 2.0±0.5 g) were exposed with fresh overnight culture of V. harveyi through bath immunization (concentration 2 Χ 105) for 2 hours on 10 days interval for 40 days. The growth was monitored through increase in their relative weight. The rate of mortality due to bacterial infection as well as due to effect of feed was recorded accordingly. Immune response of fish was analyzed through differential leucocyte count, percentage phagocytosis and phagocytic index. The effect of V. harveyi on fish organs were examined through histo-pathological examination of internal organs like spleen, liver and kidney. The change in the immune response was also observed through gene expression analysis. The antioxidant potential of plant extracts was measured through DPPH and FRAP assay and amount of total phenols and flavonoids were calculates through biochemical analysis. The chemical composition of plant’s methanol extracts was determined by GC-MS analysis, which showed presence of various secondary metabolites and other compounds. Investigation revealed immuno-modulatory effect of plants, when supplemented with the artificial feed of fish.

Keywords: immuno-modulation, gc-ms, Cyprinus carpio, Eichhornia crassipes, Ricinus communis

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Authors: S. Reaz Ahmed, M. S. Kaiser

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The tribological behavior of commercially used Perspex was evaluated under dry and wet sliding condition using a pin-on-disc wear tester with different applied loads ranging from 2.5 to 20 N. Experiments were conducted with varying sliding distance from 0.2 km to 4.6 km, wherein the sliding velocity was kept constant, 0.64 ms^-1. The results reveal that the weight loss increases with applied load and the sliding distance. The nature of the wear rate was very similar in both the sliding environments in which initially the wear rate increased very rapidly with increasing sliding distance and then progressed to a slower rate. Moreover, the wear rate in wet sliding environment was significantly lower than that under dry sliding condition. The worn surfaces were characterized by optical microscope and SEM. It is found that surface modification has significant effect on sliding wear performance of Perspex.

Keywords: Perspex, wear, friction, SEM

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Authors: Priyankar P. Deka, Sutanu Samanta

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This paper describes the development of new class of epoxy based hybrid composites reinforced with jute and filled with rice husk flour. Rice husk flour is added in 0%, 1%, 3%, 5% by weight. Epoxy resin and triethylene tetramine (T.E.T.A) is used as matrix and hardener respectively. It investigates the mechanical properties of the composites and a comparison is done for monolithic jute composite and the filled ones. The specimens are prepared according to the ASTM standards and experimentation is carried out using INSTRON 8801. The result shows that with the increase of filler percentage the tensile properties increases but compressive and flexural properties decreases.

Keywords: jute, mechanical characterization, natural fiber, rice husk

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Authors: Dianxun Zheng, Wuxing Jing, Lin Hetong

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Optical remote sensing satellite, always running on the Sun-synchronous orbit, equipped laser warning equipment to alert CCD camera from laser attack. There have three ways to protect the CCD camera, closing the camera cover satellite attitude maneuver and satellite orbit avoidance. In order to enhance the safety of optical remote sensing satellite in orbit, this paper explores the strategy of satellite avoidance. The avoidance strategy is expressed as the evasion of pre-determined target points in the orbital coordinates of virtual satellite. The so-called virtual satellite is a passive vehicle which superposes a satellite at the initial stage of avoidance. The target points share the consistent cycle time and the same semi-major axis with the virtual satellite, which ensures the properties of the Sun-synchronous orbit remain unchanged. Moreover, to further strengthen the avoidance capability of satellite, it can perform multi-object avoid maneuvers. On occasions of fulfilling the orbit tasks of the satellite, the orbit can be restored back to virtual satellite through orbit maneuvers. There into, the avoid maneuvers adopts pulse guidance. and the fuel consumption is also optimized. The avoidance strategy discussed in this article is applicable to avoidance for optical remote sensing satellite when encounter the laser hostile attacks.

Keywords: optical remote sensing satellite, always running on the sun-synchronous

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Authors: Jamil Ahmed

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Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm.

Keywords: left to right-right most parsing, syntax analysis, bottom-up parsing algorithm

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Authors: H. Mohammadi Aliabadi, M. S. Mansouri

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The effect of two different transplanting date (March and November) in five pistachio cultivars ('Ahmad Aghaei', 'Akbri', Momtaz', 'Ghazvini', and 'Ohadi') were evaluated in Rafsanjan Azad University, Iran. Seeds were planted in plastic bags in March 2012. The seedlings were transplanted to a field in November 2012 and March 2013. Vegetative growing factors such as plant length, stem diameter, number of leaves and fresh and dry weight were measured in date. The results obtained from collected data indicated that no significant differences were found for the traits of interest. Therefore, growers should not be concerned regarding these two transplanting dates.

Keywords: pistachio, seedling, success rate, transplanting date

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Authors: Daniel J. Patricio Jiménez

Abstract:

The term 'total compensation’ refers to salary, training, innovation, and development, and of course, motivation; total compensation is an open and flexible system which must facilitate personal and family conciliation and therefore cannot be isolated from social reality. Today, the challenge for any company that wants to have a future is to be sustainable, and women play a ‘special’ role in this. Spain, in its statutory and conventional development, has not given sufficient response to new phenomena such as ‘bonuses’, ‘stock options’ or ‘fringe benefits’ (constructed dogmatically and by court decisions), the new digital reality, where cryptocurrency, new collaborative models and service provision -such as remote work-, are always ahead of the law. To talk about compensation is to talk about the gender gap, and with the entry into force of RD.902 /2020 on 14 April 2021, certain measures are necessary under the principle of salary transparency; the valuation of jobs, the pay register (Rd. 6/2019) and the pay audit, are an example of this. Analyzing the methodologies, and in particular the determination and weight of the factors -so that the system itself is not discriminatory- is essential. The wage gap in Spain is smaller than in Europe, but the sources do not reflect the reality, and since the beginning of the pandemic, there has been a clear stagnation. A living wage is not the minimum wage; it is identified with rights and needs; it is that which, based on internal equity, reflects the competitiveness of the company in terms of human capital. Spain has lost and has not recovered the relative weight of its wages; this is having a direct impact on our competitiveness, consequently on the precariousness of employment and undoubtedly on the levels of extreme poverty. Training is becoming more than ever a strategic factor; the new digital reality requires that each component of the system is connected, the transversality is imposed on us, this forces us to redefine content, to give answers to the new demands that the new normality requires because technology and robotization are changing the concept of employability. The presence of women in this context is necessary, and there is a long way to go. The so-called emotional compensation becomes particularly relevant at a time when pandemics, silence, and disruption, are leaving after-effects; technostress (in all its manifestations) is just one of them. Talking about motivation today makes no sense without first being aware that mental health is a priority, that it must be treated and communicated in an inclusive way because it increases satisfaction, productivity, and engagement. There is a clear conclusion to all this: compensation systems do not respond to the ‘new normality’: diversity, and in particular women, cannot be invisible in human resources policies if the company wants to be sustainable.

Keywords: diversity, gender gap, human resources, sustainability.

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Authors: Demet Yavuz

Abstract:

Freeze-thaw cycles are one of the greatest threats to concrete durability. Lately, protection against this threat excites scientists’ attention. Air-entraining admixtures have been widely used to produce freeze-thaw resistant at concretes. The use of air-entraining agents (AEAs) enhances not only freeze-thaw endurance but also the properties of fresh concrete such as segregation, bleeding and flow ability. This paper examines the effects of air-entraining on compressive strength of concrete. Air-entraining is used between 0.05% and 0.4% by weight of cement. One control and four fiber reinforced concrete mixes are prepared and three specimens are tested for each mix. It is concluded from the test results that when air entraining is increased the compressive strength of concrete reduces for all mixes with AEAs.

Keywords: concrete, air-entraining, compressive strength, mechanical properties

Procedia PDF Downloads 277

Authors: Mikheil Kalmakhelidze

Abstract:

Record linkage (RL) problem has become more and more important in recent years due to the growing interest towards big data analysis. The problem can be formulated in a very simple way: Given two entries a and b of a database, decide whether they represent the same object or not. There are two classical deterministic and probabilistic ways of solving the RL problem. Using simple Bayes classifier in many cases produces useful results but sometimes they show to be poor. In recent years several successful approaches have been made towards solving specific RL problems by neural network algorithms including single layer perception, multilayer back propagation network etc. In our work, we model the RL problem for specific dataset of student applications in fuzzy description logic (FDL) where linkage of specific pair (a,b) depends on the truth value of corresponding formula A(a,b) in a canonical FDL model. As a main result, we build neural network for deciding truth value of FDL formulas in a canonical model and thus link RL problem to machine learning. We apply the approach to dataset with 10000 entries and also compare to classical RL solving approaches. The results show to be more accurate than standard probabilistic approach.

Keywords: description logic, fuzzy logic, neural networks, record linkage

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Authors: Seok Hong Min, Tae Kwon Ha

Abstract:

In the present study, hot-rolled sheets of Mg-xZn alloy s(x=6, 8, and 10 weight percent) were produced by employing casting, homogenization heat treatment, hot rolling, and annealing processes subsequently. Effect of Zn addition on the microstructure and mechanical properties of Mg-Zn alloys were also investigated in each process. Through calculation of phase equilibria of Mg-Zn alloys, solution treatment temperature was decided as temperatures from 350 oC, where supersaturated solid solution can be obtained. After solution treatment, hot rolling was successfully conducted by reduction of 60%. Compression and tension tests were carried out at room temperature on the samples as-cast, solution treated, hot-rolled and recrystallized after rolling.

Keywords: Mg-Zn alloy, heat treatment, microstructure, mechanical properties, hot rolling

Procedia PDF Downloads 316

Authors: Jean De Dieu Ayabagabo, Paul A.Onjoro, Karubiu P. Migwi, Marie C. Dusingize

Abstract:

This study investigated the effects of feed on milk yield and quality through feed monitoring and quality assessment, and the consequent enteric methane gas emissions from smallholder dairy farms in drier areas of Rwanda, using the Tier II approach for four seasons in three zones, namely; Mayaga and peripheral Bugesera (MPB), Eastern Savanna and Central Bugesera (ESCB), and Eastern plateau (EP). The study was carried out using 186 dairy cows with a mean live weight of 292 Kg in three communal cowsheds. The milk quality analysis was carried out on 418 samples. Methane emission was estimated using prediction equations. Data collected were subjected to ANOVA. The dry matter intake was lower (p<0.05) in the long dry season (7.24 Kg), with the ESCB zone having the highest value of 9.10 Kg, explained by the practice of crop-livestock integration agriculture in that zone. The Dry matter digestibility varied between seasons and zones, ranging from 52.5 to 56.4% for seasons and from 51.9 to 57.5% for zones. The daily protein supply was higher (p<0.05) in the long rain season with 969 g. The mean daily milk production of lactating cows was 5.6 L with a lower value (p<0.05) during the long dry season (4.76 L), and the MPB zone having the lowest value of 4.65 L. The yearly milk production per cow was 1179 L. The milk fat varied from 3.79 to 5.49% with a seasonal and zone variation. No variation was observed with milk protein. The seasonal daily methane emission varied from 150 g for the long dry season to 174 g for the long rain season (p<0.05). The rain season had the highest methane emission as it is associated with high forage intake. The mean emission factor was 59.4 Kg of methane/year. The present EFs were higher than the default IPPC value of 41 Kg from developing countries in African, the Middle East, and other tropical regions livestock EFs using Tier I approach due to the higher live weight in the current study. The methane emission per unit of milk production was lower in the EP zone (46.8 g/L) due to the feed efficiency observed in that zone. Farmers should use high-quality feeds to increase the milk yield and reduce the methane gas produced per unit of milk. For an accurate assessment of the methane produced from dairy farms, there is a need for the use of the Life Cycle Assessment approach that considers all the sources of emissions.

Keywords: footprint, forage, girinka, tier

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Authors: H. Unal, A. Mimaroglu, I. Ozsoy

Abstract:

In this study, the mechanical properties of micro filled epoxy composites were investigated. The matrix material is epoxy. Micro fillers are Al2O3 and TiO2 added in 10-30 wt% by weight ratio. Test samples were prepared using an open mould type die. Tensile, three point bending and hardness tests were carried out. The tensile strength, elastic modulus, elongation at break, flexural strength, flexural modulus and the hardness of the composite materials were obtained and evaluated. It was seen from the results that the level of the mechanical properties of the epoxy composites is highly influenced by micro filler content.

Keywords: composites, epoxy, fillers, mechanical properties

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Authors: Marinela Istrate, Ionel Muntele, Alexandru Bănică

Abstract:

The authors propose the identification, analysis and prognosis of the quantitative and qualitative evolution of the elderly population in the functional urban areas. The present paper takes into account the analysis of some representative indicators (the weight of the elderly population, ageing index, dynamic index of economic ageing of productive population etc.) and the elaboration of an integrated indicator that would help differentiate the population ageing forms in the 48 functional urban areas that were defined based on demographic and social-economic criteria for all large and medium cities in Romania.

Keywords: ageing, demographic transition, functional urban areas, spatial resilience

Procedia PDF Downloads 351

Authors: Shi-Yu Xu

Abstract:

The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

Procedia PDF Downloads 89