Search results for: content based image retrieval (CBIR)

Authors: Patricia Portugal Marques de Carvalho Lourenco

Abstract:

Big Bang is like a dirty martini embroiled in a stew of personal individual scandals that have rocked the group’s image and perception, from G-Dragon’s and T.O.P. marijuana episodes in 2011 and 2016, respectively, to Daesung’s building illicit entertainment activities in 2018to the Burning Sun shebang that led to the Titanic sink of Big Bang’s youngest member Seungri in 2019 and the positive sentiment migration to the antithetical side. BTS, on the other hand, are like a martini, clear, clean, attracting as many crowds to their performances and online content as the Pope attracts believers to Sunday Mass in the Vatican, as exemplified by their latest MVs. Big Bang’s 2022 Still Life achieved 16.4 million views on Youtube in 24hours, whilst BTS Permission to Dance achieved 68.5 million in the same period of time. The difference is significant when added Big Bang’s and BTS overall award wins, a total of 117 in contrast to 460. Both groups are uniquely talented and exceptional performers that have been contributing greatly to the dissemination of Korean Pop Music on a global scale in their own inimitable ways. Both are exceptional in their own right and while the artists cannot, ought not, should not be compared for the grave injustice made in comparing one individual planet with one solar system, a contrast is merited and hence done. The reality, nonetheless, is about disengagement from a group that lives life humanly, learning and evolving with each challenge and mistake without a clean, perfect tag attached to it, demonstrating not only an inability to disassociate the person from the artist and the music but also an inability to understand the difference between a private and public life.

Keywords: K-Pop, big bang, BTS, music, public image, entertainment, korean entertainment

Procedia PDF Downloads 79

Authors: Sidra Saleemi, Raja Fahad Qureshi, Farooq Ahmed, Rabia Almas, Tahir Jameel

Abstract:

This research aimed to decrease formaldehyde content in substrates printed by pigments using different fixation temperature and concentration of urea in order to produce eco-friendly textiles. Substrates were printed by hand screen printing method as per recipe followed by drying and curing. Standard test methods were adapted to measure formaldehyde content washing and rubbing fastness. Formaldehyde content is instantaneously decreased by raising the temperature during curing printed fabric. Good results of both dry and wet rubbing fastness were found at 160˚C slightly improved dry rubbing results are achieved with 2% urea at a curing temperature of 150˚C.

Keywords: formaldehyde content, pigment printing, urea, washing fastness, rubbing fastness

Procedia PDF Downloads 289

Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

Abstract:

Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: features extraction, image segmentation, medical images, tumor detection

Procedia PDF Downloads 145

Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

Abstract:

Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.

Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation

Procedia PDF Downloads 249

Authors: Teja Sai Puligadda

Abstract:

Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

Procedia PDF Downloads 137

Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

Abstract:

Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

Procedia PDF Downloads 104

Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

Abstract:

A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

Procedia PDF Downloads 90

Authors: Won Young Choi, Kwan Kyu Park

Abstract:

Recently, the road depression happening in the urban area is different from the cause of the sink hole and the generation mechanism occurring in the limestone area. The main cause of sinkholes occurring in the city center is the loss of soil due to the damage of old underground buried materials and groundwater discharge due to large underground excavation works. The method of detecting the sinkhole in the urban area is mostly using the Ground Penetration Radar (GPR). However, it is challenging to implement compact system and detecting watery state since it is based on electromagnetic waves. Although many ultrasonic underground detection studies have been conducted, near-ground detection (several tens of cm to several meters) has been developed for bulk systems using geophones as a receiver. The goal of this work is to fabricate a miniaturized sinkhole detecting system based on low-cost ultrasonic transducers of 40 kHz resonant frequency with high transmission pressure and receiving sensitivity. Motived by biomedical ultrasonic imaging methods, we detect air layers below the ground such as asphalt through the pulse-echo method. To improve image quality using multi-channel, linear array system is implemented, and image is acquired by classical synthetic aperture imaging method. We present the successful feasibility test of multi-channel sinkhole detector based on ultrasonic transducer. In this work, we presented and analyzed image results which are imaged by single channel pulse-echo imaging, synthetic aperture imaging.

Keywords: road depression, sinkhole, synthetic aperture imaging, ultrasonic transducer

Procedia PDF Downloads 126

Authors: Maya S. Rathod, Bahadur Singh Hathan

Abstract:

Mustard leaves are rich in folates, vitamin A, K and B-complex. Mustard greens are low in calories and fats and rich in dietary fiber. They are rich in potassium, manganese, iron, copper, calcium, magnesium and low in sodium. It is very rich in antioxidants and Phytonutrients. For the optimization of process variables (moisture content and mustard leave powder), the experiments were conducted according to central composite Face Centered Composite design of RSM. The mustard leaves powder was replaced with composite flour (a combination of rice, chickpea and corn in the ratio of 70:15:15). The extrudate was extruded in a twin screw extruder at a barrel temperature of 120°C. The independent variables were mustard leaves powder (2-10 %) and moisture content (12-20 %). Responses analyzed were bulk density, water solubility index, water absorption index, lateral expansion, hardness, antioxidant activity, total phenolic content and overall acceptability. The optimum conditions obtained were 7.19 g mustard leaves powder in 100 g premix having 16.8 % moisture content (w.b).

Keywords: extrusion, mustard leaves powder, optimization, response surface methodology

Procedia PDF Downloads 517

Authors: Namik Kemal Sonmez

Abstract:

Based passive remote sensing technologies have been widely used in many plant species. However, use of these techniques in orange trees is limited. In this study, the relationships between chlorophyll content (Chl) and calculated red edge (RE) and vegetation index values of the citrus leave at different growth stages were formed the basis for the analysis. Canopy reflectance by hand-held spectroradiometer and total Chl analysis at the lab were measured simultaneously, from the random samples taken from four different parts of an orange orchard. Plant materials consisted of four different age groups of 15, 20, 25, and 30 years old orange trees. Reflectance measurements were conducted between 450 and 900 nanometer (nm) wavelength at four different bands (3 visible bands and 1 near-infrared band) at the four basic physiological periods (flowering, fruit setting, fruit maturity, and dormancy) of orange trees. According to the statistical analysis conducted, there was a strong relationship between the chlorophyll content and calculated indexes (p ≤ 0.01; R²= 0.925 at red edge and R²= 0.986 at vegetation index) at the fruit setting stage of 20 years old trees. Again at this stage, fruit setting, total Chl content values among all orange trees were significantly correlated at the RE and VI with the R² values of 0.672 and 0.635 at the 0.001 level, respectively. This indicated that the relationships between Chl content and index values were very strong at this stage, in comparison to the other stages.

Keywords: spectroradiometer, citrus, chlorophyll, reflectance, index

Procedia PDF Downloads 353

Authors: M. Al-Majidi, A. Lampropoulos, A. Cundy

Abstract:

Geopolymer (cement-free) concrete is the most promising green alternative to ordinary Portland cement concrete and other cementitious materials. While a range of different geopolymer concretes have been produced, a common feature of these concretes is heat curing treatment which is essential in order to provide sufficient mechanical properties in the early age. However, there are several practical issues with the application of heat curing in large-scale structures. The purpose of this study is to develop cement-free concrete without heat curing treatment. Experimental investigations were carried out in two phases. In the first phase (Phase A), the optimum content of water, polycarboxylate based superplasticizer contents and potassium silicate activator in the mix was determined. In the second stage (Phase B), the effect of ground granulated blast furnace slag (GGBFS) incorporation on the compressive strength of fly ash (FA) and Slag based geopolymer mixtures was evaluated. Setting time and workability were also conducted alongside with compressive tests. The results showed that as the slag content was increased the setting time was reduced while the compressive strength was improved. The obtained compressive strength was in the range of 40-50 MPa for 50% slag replacement mixtures. Furthermore, the results indicated that increment of water and superplasticizer content resulted to retarding of the setting time and slight reduction of the compressive strength. The compressive strength of the examined mixes was considerably increased as potassium silicate content was increased.

Keywords: fly ash, geopolymer, potassium silicate, slag

Procedia PDF Downloads 202

Authors: Aika Umemuro, Mitsuru Sato, Mizuki Narita, Saya Hori, Saya Sakurai, Tomomi Nakayama, Ayano Nakazawa, Toshihiro Ogura

Abstract:

Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful.

Keywords: EEG scanner, eye-detector, mammography, observers

Procedia PDF Downloads 205

Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

Abstract:

Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

Procedia PDF Downloads 112

Authors: Yadpiroon Onmek, Jean Triboulet, Sebastien Druon, Bruno Jouvencel

Abstract:

The objective of this paper is to develop the 3D underwater reconstruction of archaeology object, which is based on the fusion between a sonar system and stereo camera system. The underwater images are obtained from a calibrated camera system. The multiples image pairs are input, and we first solve the problem of image processing by applying the well-known filter, therefore to improve the quality of underwater images. The features of interest between image pairs are selected by well-known methods: a FAST detector and FLANN descriptor. Subsequently, the RANSAC method is applied to reject outlier points. The putative inliers are matched by triangulation to produce the local sparse point clouds in 3D space, using a pinhole camera model and Euclidean distance estimation. The SFM technique is used to carry out the global sparse point clouds. Finally, the ICP method is used to fusion the sonar information with the stereo model. The final 3D models have a précised by measurement comparing with the real object.

Keywords: 3D reconstruction, archaeology, fusion, stereo system, sonar system, underwater

Procedia PDF Downloads 286

Authors: Ghadeer Aly, Yasmeen Hanafy

Abstract:

The way we research travel options and decide where to go has substantially changed in the digital age. Atypical search engines like social networking sites like TikTok have evolved, influencing the preferences of various generations. The influence of TikTok use as a search engine for choosing travel locations and its effect on a country's destination branding are both examined in this study. The study specifically focuses on the comparative preferences and actions of Generations Y and Z within the Egyptian community, shedding light on how these generations interact with travel related TikTok content and how it influences their perceptions of various destinations. It also investigates how TikTok Accounts use tourism branding techniques to promote a country's tourist destination. The investigation of how social media platforms are changing as unconventional search engines has theoretical relevance. This study can advance our knowledge of how digital platforms alter information-seeking behaviors and affect the way people make decisions. Furthermore, investigating the relationship between TikTok video and destination branding might shed light on the intricate interplay between social media, perceptions of locations, and travel preferences, enhancing theories about consumer behavior and communication in the digital age. Regarding the methodology of the research, the study is conducted in two stages: first, both generations are polled, and from the results, the top three destinations are chosen to be subjected to content analysis. As for the research's theoretical framework, it incorporates the tourism destination branding model as well as the conceptual model of nation branding. Through the use of the survey as a quantitative approach and the qualitative content analysis, the research will rely on both quantitative and qualitative methods. When it comes to the theoretical framework, both the Nation Branding Model and the Tourism Branding Model can offer useful frameworks for analyzing and comprehending the dynamics of using TikTok as a search engine to choose travel destinations, especially in the context of Generation Y and Generation Z in the Egyptian community. Additionally, the sample will be drawn specifically from both Gen-Y and Gen-Z. 100 members of Gen Z and 100 members of Gen Y will be chosen from TikTok users and followers of travel-related accounts, and the sample for the content analysis will be chosen based on the survey's results.

Keywords: tiktok, nation image, egyptian community, tourism branding

Procedia PDF Downloads 55

Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall

Abstract:

Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.

Keywords: ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear

Procedia PDF Downloads 278

Authors: Dennis Schmickle

Abstract:

Introductory statement: Augmented reality (AR) can be used to breathe life into traditional graphic design media, such as posters, book covers, and album art. AR superimposes a unique image/video on a user’s view of the real world, which makes it more immersive and realistic than traditional 2D media. This study developed a series of projects that utilize both traditional and AR media to teach the fundamental principles of graphic design. The results of this study suggest that AR can be an effective tool for teaching graphic design. Abstract: Traditional graphic design media, such as posters, book covers, and album art, could be considered to be “old media.” However, augmented reality (AR) can breathe life into these formats by making them more interactive and engaging for students and audiences alike. AR is a technology that superimposes a computer-generated image on a user’s view of the real world. This allows users to interact with digital content in a way that is more immersive and interactive than traditional 2D media. AR is becoming increasingly popular, as more and more people have access to smartphones and other devices that can support AR experiences. This study is comprised of a series of projects that utilize both traditional and AR media to teach the fundamental principles of graphic design. In these projects, students learn to create traditional design objects, such as posters, book covers, and album art. However, they are also required to create an animated version of their design and to use AR software to create an AR experience with which viewers can interact. The results of this study suggest that AR can be an effective and exciting tool for teaching graphic design. The students who participated in the study were able to learn the fundamental principles of graphic design, and they also developed the skills they need to create effective AR content. This study has implications for the future of graphic design education. As AR becomes more popular, it is likely that it will become an increasingly important tool for teaching graphic design.

Keywords: graphic design, augmented reality, print media, new media, AR, old media

Procedia PDF Downloads 46

Authors: Samrah Saeed

Abstract:

Introduction: This study considers a measure of positive body image and the associations between body appreciation, beauty ideals internalization, dietary habits, and physical activity in young adults. Positive body image is assessed by Body Appreciation Scale 2. It is used to assess a person's acceptance of the body, the degree of positivity, and respect for the body.Regular physical activity and healthy eating arebasically important for the body, and they play an important role in creating a positive image of the body. Objectives: To identify the associations between body appreciation and beauty ideals internalization. To compare body appreciation and body ideals internalization among students of different physical activity. To explore the associations between dietary habits (unhealthy, healthy), body appreciation and body ideals internalization. Research methods and organization: Study participants were young adult students, aged 18-35, both male and female.The research questionnaire consisted of four areas: body appreciation, beauty ideals internalization, dietary habits, and physical activity.The questionnaire was created in Google Forms online survey platform.The questionnaire was filled out anonymously Result and Discussion: Physical dissatisfaction, diet, eating disorders and exercise disorders are found in young adults all over the world.Thorough nutrition helps people understand who they are by reassuring them that they are okay without judging or accepting themselves. Social media can positively influence body image in many ways.A healthy body image is important because it affect self-esteem, self-acceptance, and your attitude towards food and exercise.

Keywords: pysical activity, dietary habits, body image, beauty ideals internalization, body appreciation

Procedia PDF Downloads 78

Authors: M. R. Jokanović, V. M. Tomović, M. T. Jović, S. B. Škaljac, B. V. Šojić, P. M. Ikonić, T. A. Tasić

Abstract:

Proximate (moisture, protein, total fat, total ash) and mineral (K, P, Na, Mg, Ca, Zn, Fe, Cu and Mn) composition of chicken giblets (heart, liver and gizzard) were investigated. Phosphorous content, as well as proximate composition, were determined according to recommended ISO methods. The content of all elements, except phosphorus, of the giblets tissues were determined using inductively coupled plasma-optical emission spectrometry (ICP-OES), after dry ashing mineralization. Regarding proximate composition heart was the highest in total fat content, and the lowest in protein content. Liver was the highest in protein and total ash content, while gizzard was the highest in moisture and the lowest in total fat content. Regarding mineral composition liver was the highest for K, P, Ca, Mg, Fe, Zn, Cu, and Mn, while heart was the highest for Na content. The contents of almost all investigated minerals in analysed giblets tissues of chickens from Vojvodina were similar to values reported in the literature, i.e. in national food composition databases of other countries.

Keywords: chicken giblets, proximate composition, mineral composition, inductively coupled plasma-optical emission spectrometry (ICP-OES)

Procedia PDF Downloads 427

Authors: L. Strauta, S. Muižniece-Brasava

Abstract:

Even though legumes possess high nutritional value and have a rather high protein content for plant origin products, they are underutilized mostly due to their lengthy cooking time. To increase the presence of legume-based products in human diet, new extruded products were made of cow peas (Vigna unguiculata (L.) Walp.). But as it is known, adding different moisture content to flour before extrusion can change the physical properties of the extruded product. Experiments were carried out to estimate the optimal moisture content for cow pea extrusion. After extrusion, the pH level had dropped from 6.7 to 6.5 and the lowest hardness rate was observed in the samples with additional 9 g 100g^-1 of moisture - 28±4N, but the volume mass of the samples with additional 9 g100g^-1 of water was 263±3 g L^-1; all samples were approximately 7±1mm long.

Keywords: cow pea, extrusion–cooking, moisture, size

Procedia PDF Downloads 193

Authors: Saadelnour Abdueljabbar Adam

Abstract:

Wastes from slaughterhouses in most towns in Sudan are often poorly managed and sometimes discharged into adjoining streams due to poor implementation of standards, thus causing environmental and public health hazards and also there is a large amount of manure from dairy farms. This paper presents a solution of organic waste from cow dairy farms and slaughterhouse. We present the findings of experimental investigation of biogas production using cow manure, blood and rumen content were mixed at three proportions :72.3%, 61%, 39% manure, 6%, 8.5%, 22% blood; and 21.7%, 30.5%, 39% rumen content in volume for bio-digester 1,2,3 respectively. This paper analyses the quantitative and qualitative composition of biogas: gas content, and the concentration of methane. The highest biogas output 0.116L/g dry matter from bio-digester1 together with a high-quality biogas of 85% methane Was from the mixture of cow manure with blood and rumen content were mixed at 72.3%manure, 6%blood and 21.7%rumen content which is useful for combustion and energy production. While bio-digester 2 and 3 gave 0.012L/g dry matter and 0.013L/g dry matter respectively with the weak concentration of methane (50%).

Keywords: anaerobic digestion, bio-digester, blood, cow manure, rumen content

Procedia PDF Downloads 548

Authors: Zhipeng Dong, Jing Guo

Abstract:

Graphene-semiconductor contacts have been extensively studied recently, both as a stand-alone diode device for potential applications in photodetectors and solar cells, and as a building block to vertical transistors. Graphene is a two-dimensional nanomaterial with vanishing density-of-states at the Dirac point, which differs from conventional metal. In this work, image-charge-induced barrier lowering (BL) in graphene-semiconductor contacts is studied and compared to that in metal Schottky contacts. The results show that despite of being a semimetal with vanishing density-of-states at the Dirac point, the image-charge-induced BL is significant. The BL value can be over 50% of that of metal contacts even in an intrinsic graphene contacted to an organic semiconductor, and it increases as the graphene doping increases. The dependences of the BL on the electric field and semiconductor dielectric constant are examined, and an empirical expression for estimating the image-charge-induced BL in graphene-semiconductor contacts is provided.

Keywords: graphene, semiconductor materials, schottky barrier, image charge, contacts

Procedia PDF Downloads 280

Authors: Ming-Yang Guo, Cheng-Xian Wu, Wei-Xiang Chen, Chun-Yuan Lin, Yen-Jen Lin, Ann-Shyn Chiang

Abstract:

With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosophila Driver image, which can cover a set of Drosophila Driver/Neuron images. In order to solve this problem, the intersection/union region for a set of images should be computed at first, then a comparison work is used to calculate the similarities between the region and other images. In this paper, three encoding schemes, namely Integer, Boolean, Decimal, are proposed to encode each image as a one-dimensional structure. Then, the intersection/union region from these images can be computed by using the compare operations, Boolean operators and lookup table method. Finally, the comparison work is done as the union region computation, and the similarity score can be calculated by the definition of Tanimoto coefficient. The above methods for the region computation are also implemented in the multi-core CPUs environment with the OpenMP. From the experimental results, in the encoding phase, the performance by the Boolean scheme is the best than that by others; in the region computation phase, the performance by Decimal is the best when the number of images is large. The speedup ratio can achieve 12 based on 16 CPUs. This work was supported by the Ministry of Science and Technology under the grant MOST 106-2221-E-182-070.

Keywords: Drosophila driver image, Drosophila neuron images, intersection/union computation, parallel processing, OpenMP

Procedia PDF Downloads 214

Authors: Norah Almubairik, Wadha Almattar, Amani Alqarni

Abstract:

Social media applications are increasingly being used in our everyday communications. These applications utilise end-to-end encryption mechanisms, which make them suitable tools for criminals to exchange messages. These messages are preserved in the volatile memory until the device is restarted. Therefore, volatile forensics has become an important branch of digital forensics. In this study, the WormHex tool was developed to inspect the memory dump files of Windows and Mac-based workstations. The tool supports digital investigators to extract valuable data written in Arabic and English through web-based WhatsApp and Twitter applications. The results verify that social media applications write their data into the memory regardless of the operating system running the application, with there being no major differences between Windows and Mac.

Keywords: volatile memory, REGEX, digital forensics, memory acquisition

Procedia PDF Downloads 166

Authors: Alexander B. Barker, Megan Parkin, Shreesh Sinha, Emma Wilson, Rachael L. Murray

Abstract:

Objectives: Exposure to HFSS imagery is associated with consumption of foods high in fat, sugar, or salt (HFSS), and subsequently obesity, among young people. We report and compare the results of two content analyses, one of two popular terrestrial children’s television channels in the UK and the other of a selection of children’s programs available on video-on-demand (VOD) streaming sites. Design: Content analysis of three days’ worth of programs (including advertisements) on two popular children’s television channels broadcast on UK television (CBeebies and Milkshake) as well as a sample of 40 highest-rated children’s programs available on the VOD platforms, Netflix and Amazon Prime, using 1-minute interval coding. Setting: United Kingdom, Participants: None. Results: HFSS content was seen in 181 broadcasts (36%) and in 417 intervals (13%) on terrestrial television, ‘Milkshake’ had a significantly higher proportion of programs/adverts which contained HFSS content than ‘CBeebies’. In VOD platforms, HFSS content was seen in 82 episodes (72% of the total number of episodes), across 459 intervals (19% of the total number of intervals), with no significant difference in the proportion of programs containing HFSS content between Netflix and Amazon Prime. Conclusions: This study demonstrates that HFSS content is common in both popular UK children’s television channels and children's programs on VOD services. Since previous research has shown that HFSS content in the media has an effect on HFSS consumption, children’s television programs broadcast either on TV or VOD services are likely having an effect on HFSS consumption in children and legislative opportunities to prevent this exposure are being missed.

Keywords: public health, epidemiology, obesity, content analysis

Procedia PDF Downloads 159

Authors: Harish Kumar Sharma, Garima Sengar

Abstract:

Rice bran oil is considered comparatively nutritionally superior than different fats/oils. Therefore, model blends prepared from pure rice bran oil (RBO) and sunflower oil (SFO) were explored for changes in the different physicochemical parameters. Repeated deep fat frying process was carried out by using dried potato in order to study the thermal behaviour of pure rice bran oil, sunflower oil and their model blends. Pure rice bran oil and sunflower oil had shown good thermal stability during the repeated deep fat frying cycles. Although, the model blends constituting 60% RBO + 40% SFO showed better suitability during repeated deep fat frying than the remaining blended oils. The quantification of pure rice bran oil in the blended oils, physically refined rice bran oil (PRBO): SnF (sunflower oil) was carried by different methods. The study revealed that regression equations based on the oryzanol content, palmitic acid composition and iodine value can be used for the quantification. The rice bran oil can easily be quantified in the blended oils based on the oryzanol content by HPLC even at 1% level. The palmitic acid content in blended oils can also be used as an indicator to quantify rice bran oil at or above 20% level in blended oils whereas the method based on ultrasonic velocity, acoustic impedance and relative association showed initial promise in the quantification.

Keywords: rice bran oil, sunflower oil, frying, quantification

Procedia PDF Downloads 290

Authors: Mehtab Alam, Mudiarasan Kuppusamy, Puvaneswaran Kunaserkaran

Abstract:

The purpose of this paper is to bridge the gap and complete the relationship between tourism destinations and image branding as a choice of edifice foreign policy. Such options became a crucial component for individuals interested in leisure and travel activities. The destination management factors have been evaluated and analyzed using the primary and secondary data in a mixed-methods approach (quantitative sample of 384 and qualitative 8 semi-structured interviews at saturated point). The study chose the Environmental Management Accounting (EMA) and Image Restoration (IR) theories, along with a schematic diagram and an analytical framework supported by NVivo software 12, for two locations in Abbottabad, KPK, Pakistan: Shimla Hill and Thandiani. This incorporates the use of PLS-SEM model for assessing validity of data while SPSS for data screening of descriptive statistics. The results show that destination management's promotion of tourism has significantly improved Pakistan's state image. The use of institutional setup, environmental drivers, immigration, security, and hospitality as well as recreational initiatives on destination management is encouraged. The practical ramifications direct the heads of tourism projects, diplomats, directors, and policymakers to complete destination projects before inviting people to Pakistan. The paper provides the extent of knowledge for academic tourism circles to use tourism destinations as brand ambassadors.

Keywords: tourism, management, state image, foreign policy, image branding

Procedia PDF Downloads 49

Authors: Hui Wei, Zheng Dong

Abstract:

Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

Procedia PDF Downloads 523

Authors: Bencherif Kada

Abstract:

In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

Procedia PDF Downloads 98

Authors: Javaria Farooqui

Abstract:

This study, “Transmogrification of the Danse Macabre Image: Capturing the Journey towards Creativity,” traces the evolution of the concept of Danse Macabre. In Every man death takes away the sinful when they least expect it, in Solyman and Perseda everyone falls prey to death irrespective of their deeds and in Tauba-tun-Nasuh, the sinner is plagued. The climatic point in this brief research comes with the Modern texts, The Moon and Sixpence, Roohe-e-Insani and Amédéé, ou Comment s’en débarrasser, when Danse Macabre extends its boundaries, uniting the idea of creativity with death. Similarly in the visual context, Danse Macabre image, initially a horrifying idea, becomes a part of the present day comics and serves an entertaining rather than a cathartic purpose.

Keywords: Danse macabre, transmogrification, Medieval, death, character

Procedia PDF Downloads 496