Search results for: brand image transfer
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5854

Search results for: brand image transfer

3844 Shoreline Change Estimation from Survey Image Coordinates and Neural Network Approximation

Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

Abstract:

Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas

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3843 Deep Learning for Qualitative and Quantitative Grain Quality Analysis Using Hyperspectral Imaging

Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

Abstract:

Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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3842 The Physical Impact of Nano-Layer Due to Dispersions of Carbon Nano-Tubes through an Absorbent Channel: A Numerical Nano-Fluid Flow Model

Authors: Muhammad Zubair Akbar Qureshi, Abdul Bari Farooq

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The intention of the current study to analyze the significance of nano-layer in incompressible magneto-hydrodynamics (MHD) flow of a Newtonian nano-fluid consisting of carbon nano-materials has been considered through an absorbent channel with moving porous walls. Using applicable similarity transforms, the governing equations are converted into a system of nonlinear ordinary differential equations which are solved by using the 4th-order Runge-Kutta technique together with shooting methodology. The phenomena of nano-layer have also been modeled mathematically. The inspiration behind this segment is to reveal the behavior of involved parameters on velocity and temperature profiles. A detailed table is presented in which the effects of involved parameters on shear stress and heat transfer rate are discussed. Specially presented the impact of the thickness of the nano-layer and radius of the particle on the temperature profile. We observed that due to an increase in the thickness of the nano-layer, the heat transfer rate increases rapidly. The consequences of this research may be advantageous to the applications of biotechnology and industrial motive.

Keywords: carbon nano-tubes, magneto-hydrodynamics, nano-layer, thermal conductivity

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3841 Unsteady Natural Convection in a Square Cavity Partially Filled with Porous Media Using a Thermal Non-Equilibrium Model

Authors: Ammar Alsabery, Habibis Saleh, Norazam Arbin, Ishak Hashim

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Unsteady natural convection and heat transfer in a square cavity partially filled with porous media using a thermal non-equilibrium model is studied in this paper. The left vertical wall is maintained at a constant hot temperature and the right vertical wall is maintained at a constant cold temperature, while the horizontal walls are adiabatic. The governing equations are obtained by applying the Darcy model and Boussinesq approximation. COMSOL's finite element method is used to solve the non-dimensional governing equations together with specified boundary conditions. The governing parameters of this study are the Rayleigh number, the modified thermal conductivity ratio, the inter-phase heat transfer coefficien and the time independent. The results presented for values of the governing parameters in terms of streamlines in both fluid/porous layer, isotherms of fluid and solid porous layer, isotherms of fluid layer, and average Nusselt number.

Keywords: unsteady natural convection, thermal non-equilibrium model, Darcy model

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3840 Design and Māori Values: A Rebrand Project for the Social Enterprise Sector

Authors: M. Kiarna, S. Junjira, S. Casey, M. Nolwazi, M. S. Marcos, A. T. Tatiana, L. Cassandra

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This paper details a rebrand design project developed for a non-profitable organization called Te Roopu Waiora (TRW), which is currently located in Auckland, Aotearoa New Zealand. This social enterprise is dedicated to supporting the Māori community living with sensorial, physical and intellectual disabilities (whānau hauā). As part of a year three bachelor design brief, the rebrand project enabled students to reflect on Kaupapa Māori principles and appropriately address the values of the organisation. As such, the methodology used a pragmatic paradigm approach and mixed methods design practices involving a human-centred design to problem solving. As result, the student project culminated in the development in a range of cohesive design artefacts, aiming to improve the rentability and perception of the brand with the audience and stakeholders.

Keywords: design in Aotearoa New Zealand, Kaupapa Māori, branding, design education, human-centered design

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3839 Early Recognition and Grading of Cataract Using a Combined Log Gabor/Discrete Wavelet Transform with ANN and SVM

Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

Abstract:

Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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3838 Entropy Generation Analysis of Cylindrical Heat Pipe Using Nanofluid

Authors: Morteza Ghanbarpour, Rahmatollah Khodabandeh

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In this study, second law of thermodynamic is employed to evaluate heat pipe thermal performance. In fact, nanofluids potential to decrease the entropy generation of cylindrical heat pipes are studied and the results are compared with experimental data. Some cylindrical copper heat pipes of 200 mm length and 6.35 mm outer diameter were fabricated and tested with distilled water and water based Al2O3 nanofluids with volume concentrations of 1-5% as working fluids. Nanofluids are nanotechnology-based colloidal suspensions fabricated by suspending nanoparticles in a base liquid. These fluids have shown potential to enhance heat transfer properties of the base liquids used in heat transfer application. When the working fluid undergoes between different states in heat pipe cycle the entropy is generated. Different sources of irreversibility in heat pipe thermodynamic cycle are investigated and nanofluid effect on each of these sources is studied. Both experimental and theoretical studies reveal that nanofluid is a good choice to minimize the entropy generation in heat pipe thermodynamic cycle which results in higher thermal performance and efficiency of the system.

Keywords: heat pipe, nanofluid, thermodynamics, entropy generation, thermal resistance

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3837 Hyperspectral Mapping Methods for Differentiating Mangrove Species along Karachi Coast

Authors: Sher Muhammad, Mirza Muhammad Waqar

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

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

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3836 Mathematical Modeling of Thin Layer Drying Behavior of Bhimkol (Musa balbisiana) Pulp

Authors: Ritesh Watharkar, Sourabh Chakraborty, Brijesh Srivastava

Abstract:

Reduction of water from the fruits and vegetables using different drying techniques is widely employed to prolong the shelf life of these food commodities. Heat transfer occurs inside the sample by conduction and mass transfer takes place by diffusion in accordance with temperature and moisture concentration gradient respectively during drying. This study was undertaken to study and model the thin layer drying behavior of Bhimkol pulp. The drying was conducted in a tray drier at 500c temperature with 5, 10 and 15 % concentrations of added maltodextrin. The drying experiments were performed at 5mm thickness of the thin layer and the constant air velocity of 0.5 m/s.Drying data were fitted to different thin layer drying models found in the literature. Comparison of fitted models was based on highest R2(0.9917), lowest RMSE (0.03201), and lowest SSE (0.01537) revealed Middle equation as the best-fitted model for thin layer drying with 10% concentration of maltodextrin. The effective diffusivity was estimated based on the solution of Fick’s law of diffusion which is found in the range of 3.0396 x10-09 to 5.0661 x 10-09. There was a reduction in drying time with the addition of maltodextrin as compare to the raw pulp.

Keywords: Bhimkol, diffusivity, maltodextrine, Midilli model

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3835 Proprioceptive Neuromuscular Facilitation Exercises of Upper Extremities Assessment Using Microsoft Kinect Sensor and Color Marker in a Virtual Reality Environment

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

Abstract:

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

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

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3834 Albumin-Induced Turn-on Fluorescence in Molecular Engineered Fluorescent Probe for Biomedical Application

Authors: Raja Chinnappan, Huda Alanazi, Shanmugam Easwaramoorthi, Tanveer Mir, Balamurugan Kanagasabai, Ahmed Yaqinuddin, Sandhanasamy Devanesan, Mohamad S. AlSalhi

Abstract:

Serum albumin (SA) is a highly rich water-soluble protein in plasma. It is known to maintain the living organisms' health and help to maintain the proper liver function, kidney function, and plasma osmolality in the body. Low levels of serum albumin are an indication of liver failure and chronic hepatitis. Therefore, it is important to have a low-cost, accurate and rapid method. In this study, we designed a fluorescent probe, triphenylamine rhodanine-3-acetic acid (mRA), which triggers the fluorescence signal upon binding with serum albumin (SA). mRA is a bifunctional molecule with twisted intramolecular charge transfer (TICT)-induced emission characteristics. An aqueous solution of mRA has an insignificant fluorescence signal; however, when mRA binds to SA, it undergoes TICT and turns on the fluorescence emission. A SA dose-dependent fluorescence signal was performed, and the limit of detection was found to be less than ng/mL. The specific binding of SA was tested from the cross-reactivity study using similar structural or functional proteins.

Keywords: serum albumin, fluorescent sensing probe, liver diseases, twisted intramolecular charge transfer

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3833 Clustering Color Space, Time Interest Points for Moving Objects

Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

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3832 Using Machine Learning to Classify Different Body Parts and Determine Healthiness

Authors: Zachary Pan

Abstract:

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

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

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3831 CSR Communication Strategies: Stakeholder and Institutional Theories Perspective

Authors: Stephanie Gracelyn Rahaman, Chew Yin Teng, Manjit Singh Sandhu

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Corporate scandals have made stakeholders apprehensive of large companies and expect greater transparency in CSR matters. However, companies find it challenging to strategically communicate CSR to intended stakeholders and in the process may fall short on maximizing on CSR efforts. Given that stakeholders have the ability to either reward good companies or take legal action or boycott against corporate brands who do not act socially responsible, companies must create shared understanding of their CSR activities. As a result, communication has become a strategy for many companies to demonstrate CSR engagement and to minimize stakeholder skepticism. The main objective of this research is to examine the types of CSR communication strategies and predictors that guide CSR communication strategies. Employing Morsing & Schultz’s guide on CSR communication strategies, the study integrates stakeholder and institutional theory to develop a conceptual framework. The conceptual framework hypothesized that stakeholder (instrumental and normative) and institutional (regulatory environment, nature of business, mimetic intention, CSR focus and corporate objectives) dimensions would drive CSR communication strategies. Preliminary findings from semi-structured interviews in Malaysia are consistent with the conceptual model in that stakeholder and institutional expectations guide CSR communication strategies. Findings show that most companies use two-way communication strategies. Companies that identified employees, the public or customers as key stakeholders have started to embrace social media to be in-sync with new trends of communication. This is especially with the Gen Y which is their priority. Some companies creatively use multiple communication channels because they recognize different stakeholders favor different communication channels. Therefore, it appears that companies use two-way communication strategies to complement the perceived limitation of one-way communication strategies as some companies prefer a more interactive platform to strategically engage stakeholders in CSR communication. In addition to stakeholders, institutional expectations also play a vital role in influencing CSR communication. Due to industry peer pressures, corporate objectives (attract international investors and customers), companies may be more driven to excel in social performance. For these reasons companies tend to go beyond the basic mandatory requirement, excel in CSR activities and be known as companies that champion CSR. In conclusion, companies use more two-way than one-way communication and companies use a combination of one and two-way communication to target different stakeholders resulting from stakeholder and institutional dimensions. Finally, in order to find out if the conceptual framework actually fits the Malaysian context, companies’ responses for expected organizational outcomes from communicating CSR were gathered from the interview transcripts. Thereafter, findings are presented to show some of the key organizational outcomes (visibility and brand recognition, portray responsible image, attract prospective employees, positive word-of-mouth, etc.) that companies in Malaysia expect from CSR communication. Based on these findings the conceptual framework has been refined to show the new identified organizational outcomes.

Keywords: CSR communication, CSR communication strategies, stakeholder theory, institutional theory, conceptual framework, Malaysia

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3830 A Proposal for an Excessivist Social Welfare Ordering

Authors: V. De Sandi

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In this paper, we characterize a class of rank-weighted social welfare orderings that we call ”Excessivist.” The Excessivist Social Welfare Ordering (eSWO) judges incomes above a fixed threshold θ as detrimental to society. To accomplish this, the identification of a richness or affluence line is necessary. We employ a fixed, exogenous line of excess. We define an eSWF in the form of a weighted sum of individual’s income. This requires introducing n+1 vectors of weights, one for all possible numbers of individuals below the threshold. To do this, the paper introduces a slight modification of the class of rank weighted class of social welfare function. Indeed, in our excessivist social welfare ordering, we allow the weights to be both positive (for individuals below the line) and negative (for individuals above). Then, we introduce ethical concerns through an axiomatic approach. The following axioms are required: continuity above and below the threshold (Ca, Cb), anonymity (A), absolute aversion to excessive richness (AER), pigou dalton positive weights preserving transfer (PDwpT), sign rank preserving full comparability (SwpFC) and strong pareto below the threshold (SPb). Ca, Cb requires that small changes in two income distributions above and below θ do not lead to changes in their ordering. AER suggests that if two distributions are identical in any respect but for one individual above the threshold, who is richer in the first, then the second should be preferred by society. This means that we do not care about the waste of resources above the threshold; the priority is the reduction of excessive income. According to PDwpT, a transfer from a better-off individual to a worse-off individual despite their relative position to the threshold, without reversing their ranks, leads to an improved distribution if the number of individuals below the threshold is the same after the transfer or the number of individuals below the threshold has increased. SPb holds only for individuals below the threshold. The weakening of strong pareto and our ethics need to be justified; we support them through the notion of comparative egalitarianism and income as a source of power. SwpFC is necessary to ensure that, following a positive affine transformation, an individual does not become excessively rich in only one distribution, thereby reversing the ordering of the distributions. Given the axioms above, we can characterize the class of the eSWO, getting the following result through a proof by contradiction and exhaustion: Theorem 1. A social welfare ordering satisfies the axioms of continuity above and below the threshold, anonymity, sign rank preserving full comparability, aversion to excessive richness, Pigou Dalton positive weight preserving transfer, and strong pareto below the threshold, if and only if it is an Excessivist-social welfare ordering. A discussion about the implementation of different threshold lines reviewing the primary contributions in this field follows. What the commonly implemented social welfare functions have been overlooking is the concern for extreme richness at the top. The characterization of Excessivist Social Welfare Ordering, given the axioms above, aims to fill this gap.

Keywords: comparative egalitarianism, excess income, inequality aversion, social welfare ordering

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3829 Toward a Methodology of Visual Rhetoric with Constant Reference to Mikhail Bakhtin’s Concept of “Chronotope”: A Theoretical Proposal and Taiwan Case Study

Authors: Hsiao-Yung Wang

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

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

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3828 Water Detection in Aerial Images Using Fuzzy Sets

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

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

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

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3827 Clinical Applications of Amide Proton Transfer Magnetic Resonance Imaging: Detection of Brain Tumor Proliferative Activity

Authors: Fumihiro Ima, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

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It is important to know growth rate of brain tumors before surgery because it influences treatment planning including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without administration of contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients and WHO grade 4 in 2 patients), meningioma WHO grade1 in 2 patients and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW-signals than that in low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW-signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

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3826 An Integrated Approach to Assessing Urban Nature as an Indicator to Mitigate Urban Heat Island Effect: A Case Study of Lahore, Pakistan

Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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Rapid urbanization significantly change land use, urban nature, land surface vegetation cover, and heat distribution, leading to the formation of urban heat island (UHI) effect and affecting the healthy growth of cities and the comfort of human living style. Past information and present changes in Land Surface Temperature (LST) and urban landscapes could be useful to geographers, environmentalists, and urban planners in an attempt to shape the urban development process and mitigate the effects of urban heat islands (UHI). This study aims at using Satellite Remote Sensing (SRS) and GIS techniques to develop an approach for assessing the urban nature and UHI effects in Lahore, Pakistan. The study employed the Radiative Transfer Method (RTM) in estimating LST to assess the SUHI effect during the interval of 20 years (2000-2020). The assessment was performed by the available Landsat 7/ETM+ and Landsat 8/OIL_TIRs data for the years 2000, 2010, and 2020 respectively. Pearson’s correlation and normalized mutual information were applied to investigate the relationship between green space characteristics and LST. The result of this work revealed that the influence of urban heat island is not always at the city centers but sometimes in the outskirt where a lot of development activities were going on towards the direction of expansion of Lahore, Pakistan. The present study explores the usage of image processing and spatial analysis in the drive towards achieving urban greening of Lahore and a sustainable urban environment in terms of urban planning, policy, and decision making and promoting the healthy and sustainable urban environment of the city.

Keywords: urban nature, urban heat islands, urban green space, land use, Lahore

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3825 Study of Bolt Inclination in a Composite Single Bolted Joint

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

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

Keywords: damage, inclination, analyzed, carbon

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3824 Numerical Investigation of Hot Oil Velocity Effect on Force Heat Convection and Impact of Wind Velocity on Convection Heat Transfer in Receiver Tube of Parabolic Trough Collector System

Authors: O. Afshar

Abstract:

A solar receiver is designed for operation under extremely uneven heat flux distribution, cyclic weather, and cloud transient cycle conditions, which can include large thermal stress and even receiver failure. In this study, the effect of different oil velocity on convection coefficient factor and impact of wind velocity on local Nusselt number by Finite Volume Method will be analyzed. This study is organized to give an overview of the numerical modeling using a MATLAB software, as an accurate, time efficient and economical way of analyzing the heat transfer trends over stationary receiver tube for different Reynolds number. The results reveal when oil velocity is below 0.33m/s, the value of convection coefficient is negligible at low temperature. The numerical graphs indicate that when oil velocity increases up to 1.2 m/s, heat convection coefficient increases significantly. In fact, a reduction in oil velocity causes a reduction in heat conduction through the glass envelope. In addition, the different local Nusselt number is reduced when the wind blows toward the concave side of the collector and it has a significant effect on heat losses reduction through the glass envelope.

Keywords: receiver tube, heat convection, heat conduction, Nusselt number

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3823 Numerical Investigation of Phase Change Materials (PCM) Solidification in a Finned Rectangular Heat Exchanger

Authors: Mounir Baccar, Imen Jmal

Abstract:

Because of the rise in energy costs, thermal storage systems designed for the heating and cooling of buildings are becoming increasingly important. Energy storage can not only reduce the time or rate mismatch between energy supply and demand but also plays an important role in energy conservation. One of the most preferable storage techniques is the Latent Heat Thermal Energy Storage (LHTES) by Phase Change Materials (PCM) due to its important energy storage density and isothermal storage process. This paper presents a numerical study of the solidification of a PCM (paraffin RT27) in a rectangular thermal storage exchanger for air conditioning systems taking into account the presence of natural convection. Resolution of continuity, momentum and thermal energy equations are treated by the finite volume method. The main objective of this numerical approach is to study the effect of natural convection on the PCM solidification time and the impact of fins number on heat transfer enhancement. It also aims at investigating the temporal evolution of PCM solidification, as well as the longitudinal profiles of the HTF circling in the duct. The present research undertakes the study of two cases: the first one treats the solidification of PCM in a PCM-air heat exchanger without fins, while the second focuses on the solidification of PCM in a heat exchanger of the same type with the addition of fins (3 fins, 5 fins, and 9 fins). Without fins, the stratification of the PCM from colder to hotter during the heat transfer process has been noted. This behavior prevents the formation of thermo-convective cells in PCM area and then makes transferring almost conductive. In the presence of fins, energy extraction from PCM to airflow occurs at a faster rate, which contributes to the reduction of the discharging time and the increase of the outlet air temperature (HTF). However, for a great number of fins (9 fins), the enhancement of the solidification process is not significant because of the effect of confinement of PCM liquid spaces for the development of thermo-convective flow. Hence, it can be concluded that the effect of natural convection is not very significant for a high number of fins. In the optimum case, using 3 fins, the increasing temperature of the HTF exceeds approximately 10°C during the first 30 minutes. When solidification progresses from the surfaces of the PCM-container and propagates to the central liquid phase, an insulating layer will be created in the vicinity of the container surfaces and the fins, causing a low heat exchange rate between PCM and air. As the solid PCM layer gets thicker, a progressive regression of the field of movements is induced in the liquid phase, thus leading to the inhibition of heat extraction process. After about 2 hours, 68% of the PCM became solid, and heat transfer was almost dominated by conduction mechanism.

Keywords: heat transfer enhancement, front solidification, PCM, natural convection

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3822 Hyperspectral Band Selection for Oil Spill Detection Using Deep Neural Network

Authors: Asmau Mukhtar Ahmed, Olga Duran

Abstract:

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

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

Procedia PDF Downloads 113
3821 Branding Destination for Major Event: A Case Study of Liverpool as the 2008 European Capital of Culture

Authors: Yi-De Liu

Abstract:

Destination branding is a popular practice adopted by many cities in the context of intensified tourism competition. However, branding for major event is a relatively new domain in the studies of destination marketing. Based on a case study of Liverpool as the 2008 European Capital of Culture, the aim of this paper is to explore the effectiveness of the key branding campaign - the ‘Look of the City’ programme. This study looks at quantitative data collected from on-street face-to-face survey. 611 questionnaires were distributed to and collected from local residents, visitors from the immediate hinterland, domestic tourists and overseas visitors. The analysis is done, first by investigating respondents’ impression on the Liverpool 08 brand and the branding campaign, and then by exploring the effects of campaign. The positioning of Liverpool compared with other similar cities is addressed in the end. The final section extracts lessons from this empirical investigation.

Keywords: destination branding, major event, European capital of culture, Liverpool

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3820 Architecture for Multi-Unmanned Aerial Vehicles Based Autonomous Precision Agriculture Systems

Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

Abstract:

The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

Procedia PDF Downloads 114
3819 Clinical Applications of Amide Proton Transfer Magnetic Resonance Imaging: Detection of Brain Tumor Proliferative Activity

Authors: Fumihiro Imai, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

Abstract:

It is important to know the growth rate of brain tumors before surgery because it influences treatment planning, including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without the administration of a contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after a clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients, and WHO grade 4 in 2 patients), meningioma WHO grade 1 in 2 patients, and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW signals than that low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

Procedia PDF Downloads 86
3818 Community Pharmacist's Perceptions Towards Generic Drugs in Algeria

Authors: M. Y. Achouri, O. A. Alleg, M. C. L. Moulai, M. A. Selka

Abstract:

This study aims to assess the perception and attitudes of community pharmacists in Sidi-Bel-Abbes (Algeria) towards generic drugs. This is a descriptive cross-sectional prospective survey and quantitative, conducted over a period of two months from April to May 2014. The target population consisted of 118 pharmacists practicing in pharmacies in Sidi-Bel-Abbes. Data collection was conducted through a questionnaire consisting of thirteen (13) items. Fifty six (67%) of community pharmacists in the town of Sidi-Bel-Abbes in the survey believe that generics have a lower quality compared to brand name medicines Only 42% of respondents viewed locally manufactured generic medicines as equal in quality compared to the imported generic medicines, and 63% believe that the generics substitution has led to change the relationship between a pharmacist and patient. In order to promote the practice of generic medicines in Algeria, an educational program should be implemented.

Keywords: generic drugs, perception, attitudes, community pharmacists

Procedia PDF Downloads 423
3817 Overcoming Mistrusted Masculinity: Analyzing Muslim Men and Their Aspirations for Fatherhood in Denmark

Authors: Anne Hovgaard Jorgensen

Abstract:

This study investigates how Muslim fathers in Denmark are struggling to overcome notions of mistrust from teachers and educators. Starting from school-home-cooperation (parent conferences, school-home communication, etc.), the study finds that many Muslim fathers do not feel acknowledged as a resource in the upbringing of their children. To explain these experiences further, the study suggest the notion of ‘mistrusted masculinity’ to grasp the controlling image these fathers meet in various schools and child-care-institutions in the Danish Welfare state. The paper is based on 9 months of fieldwork in a Danish school, a social housing area and in various ‘father groups’ in Denmark. Additional, 50 interviews were conducted with fathers, children, mothers, schoolteachers, and educators. By using Connell's concepts 'hegemonic' and 'marginalized' masculinity as steppingstones, the paper argues that these concepts might entail a too static and dualistic picture of gender. By applying the concepts of 'emergent masculinity' and 'emergent fatherhood' the paper brings along a long needed discussion of how Muslim men in Denmark are struggling to overcome and change the controlling images of them as patriarchal and/or ignorant fathers regarding the upbringing of their children. As such, the paper shows how Muslim fathers are taking action to change this controlling image, e.g. through various ‘father groups’. The paper is inspired by the phenomenological notions of ‘experience´ and in the light of this notion, the paper tells the fathers’ stories about their upbringing of their children and aspirations for fatherhood. These stories share light on how these fathers take care of their children in everyday life. The study also shows that the controlling image of these fathers have affected how some Muslim fathers are actually being fathers. The study shows that fear of family-interventions from teachers or social workers e.g. have left some Muslim fathers in a limbo, being afraid of scolding their children, and being confused of ‘what good parenting in Denmark is’. This seems to have led to a more lassie fair upbringing than these fathers actually wanted. This study is important since anthropologists generally have underexposed the notion of fatherhood, and how fathers engage in the upbringing of their children. Over more, the vast majority of qualitative studies of fatherhood have been on white middleclass fathers, living in nuclear families. In addition, this study is crucial at this very moment due to the major refugee crisis in Denmark and in the Western world in general. A crisis, which has resulted in a vast number of scare campaigns against Islam from different nationalistic political parties, which enforces the negative controlling image of Muslim fathers.

Keywords: fatherhood, Muslim fathers, mistrust, education

Procedia PDF Downloads 191
3816 Exploring the Relationship Between Past and Present Reviews: The Influence of User Generated Content on Future Hotel Guest Experience Perceptions

Authors: Sacha Joseph-Mathews, Leili Javadpour

Abstract:

In the tourism industry, hoteliers spend millions annually on marketing and positioning efforts for their respective hotels, all in an effort to create a specific image in the minds of the consumer. Yet despite extensive efforts to seduce potential hotel guests with sophisticated advertising messages generated by hotel entities, consumers continue to mistrust corporate branding, preferring instead to place their trust in the reviews of their consumer peers. In today’s complex and cluttered marketplace, online reviews can serve as a mediator for consumers who do not have actual knowledge and experiences with the brand, but are in the process of deciding whether or not to engage in a consumption exercise. Traditionally, consumers have used online reviews as a source of comfort and confirmation of a product/service’s positioning. But today, very few customers make any purchase decisions without first researching existing user reviews, making reviews more of a necessity, rather than a luxury in the purchase decision process. The influence of user generated content (UGC) is amplified in the tourism industry; as more than a third of potential hotel guests will not book a room without first reading a review. As corporate branding becomes less relevant and online reviews become more important, how much of the consumer’s stay expectations are being dictated by existing UGC? Moreover, as hotel guest experience a hotel through the lens of an existing review, how much of their stay and in turn their review, would have been influenced by those reviews that they read? Ultimately, there is the potential for UGC to dictate what potential guests will be most critical about, and or most focused on during their stay. If UGC is a stronger influencer in the purchase decision process than corporate branding, doesn’t it have the potential to dictate, the entire stay experience by influencing the expectations of the guest prior to them arriving on the property? For example, if a hotel is an eco-destination and they focus their branding on their website around sustainability and the retreat nature of the hotel. Yet, guest reviews constantly discuss how dissatisfactory the service and food was with no mention of nature or sustainability, will future reviews then focus primarily on the food? Using text analysis software to examine over 25,000 online reviews, we explore the extent to which new reviews are influenced by wording used in previous reviews for a hotel property, versus content generated by corporate positioning. Additionally, we investigate how distinct hotel related UGC is across different types of tourism destinations. Our findings suggest that UGC can have a greater impact on future reviews, than corporate branding and there is more cohesiveness across UGC of different types of hotel properties than anticipated. A model of User Generated Content Influence is presented and the managerial impact of the power of online reviews to trump corporate branding and shape future user experiences is discussed.

Keywords: user generated content, UGC, corporate branding, online reviews, hotels and tourism

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3815 Optimizing the Scanning Time with Radiation Prediction Using a Machine Learning Technique

Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

Abstract:

Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

Procedia PDF Downloads 79