Search results for: image of the country

Authors: Emmanuel Anim

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Ghana has been touted as an oasis of peace in Africa following her relatively peaceful democratic elections, proliferated number of the media, and freedom of speech. Besides, the former Gold Coast country is yet to experience any major incidence of terrorism. Nevertheless, the somewhat occasional simmering violence and conflicts arising from political, religious and chieftaincy skirmishes, largely at its northern part portrays that it is not immune to the political violence of terrorism. The predominantly-based qualitative research reveals that current conditions of socio-politico-economic, and religious issues in Ghana places the West African country on the possible sidelines of the phenomenon of terrorism, when its status quo is juxtaposed with the factors enumerated to have culminated in the rise of Boko Haram, and its accompanying insurgency in Nigeria. Arguing from the perspective of the theory of Social Movement, the analyses and discussions note that the current state of affairs in Ghana could foster domestic terrorism in the country. What is more, the research shows that Ghana faces threats from transnational terrorism given the tendency for elements in Ghana to sympathize and subscribe to the ideological dictates and appeals from Boko Haram and other terrorist organizations. As a consequence, the study recommends that adverse conditions of poverty, poor governance, unemployment, and rising levels of (Islamic) religious radicalization should be remedied by economic improvements, good governance, job creation, and de-radicalization programs by government officials to aid mitigate the incidence of terrorism in the country.

Keywords: Boko Haram, Ghana, Nigeria, terrorism

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Authors: Tudor Barbu

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We present a robust nonlinear parabolic partial differential equation (PDE)-based denoising scheme in this article. Our approach is based on a second-order anisotropic diffusion model that is described first. Then, a consistent and explicit numerical approximation algorithm is constructed for this continuous model by using the finite-difference method. Finally, our restoration experiments and method comparison, which prove the effectiveness of this proposed technique, are discussed in this paper.

Keywords: anisotropic diffusion, finite differences, image denoising and restoration, nonlinear PDE model, anisotropic diffusion, numerical approximation schemes

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Authors: F. Rarbi, D. Dzahini, W. Uhring

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In this paper, a dynamic and power efficient 8-bit and 100-MSPS Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) is presented. The circuit uses a non-differential capacitive Digital-to-Analog (DAC) architecture segmented by 2. The prototype is produced in a commercial 65-nm 1P7M CMOS technology with 1.2-V supply voltage. The size of the core ADC is 208.6 x 103.6 µm². The post-layout noise simulation results feature a SNR of 46.9 dB at Nyquist frequency, which means an effective number of bit (ENOB) of 7.5-b. The total power consumption of this SAR ADC is only 1.55 mW at 100-MSPS. It achieves then a figure of merit of 85.6 fJ/step.

Keywords: CMOS analog to digital converter, dynamic comparator, image sensor application, successive approximation register

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Authors: B. O. Olawale, C. R. Chatwin, R. C. D. Young, P. M. Birch, F. O. Faithpraise, A. O. Olukiran

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Ortho-rectification is the process of geometrically correcting an aerial image such that the scale is uniform. The ortho-image formed from the process is corrected for lens distortion, topographic relief, and camera tilt. This can be used to measure true distances, because it is an accurate representation of the Earth’s surface. Ortho-rectification and geo-referencing are essential to pin point the exact location of targets in video imagery acquired at the UAV platform. This can only be achieved by comparing such video imagery with an existing digital map. However, it is only when the image is ortho-rectified with the same co-ordinate system as an existing map that such a comparison is possible. The video image sequences from the UAV platform must be geo-registered, that is, each video frame must carry the necessary camera information before performing the ortho-rectification process. Each rectified image frame can then be mosaicked together to form a seamless image map covering the selected area. This can then be used for comparison with an existing map for geo-referencing. In this paper, we present a four-step ortho-rectification procedure for real-time geo-referencing of video data from a low-cost UAV equipped with multi-sensor system. The basic procedures for the real-time ortho-rectification are: (1) Decompilation of video stream into individual frames; (2) Finding of interior camera orientation parameters; (3) Finding the relative exterior orientation parameters for each video frames with respect to each other; (4) Finding the absolute exterior orientation parameters, using self-calibration adjustment with the aid of a mathematical model. Each ortho-rectified video frame is then mosaicked together to produce a 2-D planimetric mapping, which can be compared with a well referenced existing digital map for the purpose of georeferencing and aerial surveillance. A test field located in Abuja, Nigeria was used for testing our method. Fifteen minutes video and telemetry data were collected using the UAV and the data collected were processed using the four-step ortho-rectification procedure. The results demonstrated that the geometric measurement of the control field from ortho-images are more reliable than those from original perspective photographs when used to pin point the exact location of targets on the video imagery acquired by the UAV. The 2-D planimetric accuracy when compared with the 6 control points measured by a GPS receiver is between 3 to 5 meters.

Keywords: geo-referencing, ortho-rectification, video frame, self-calibration

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Authors: Sayed Jamal Ud Din Heravi

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The development of educational institutions has an important role in the progress and advancement of the state, in the stability and security of the state and its exposure, in the flourishing of minds, in devoting the role of science, developing society, and meeting people’s desires and needs. Afghanistan is a Muslim country located in Central Asia on the borders of Pakistan, Iran, Tajikistan, and Uzbekistan, and it also borders China's Xing yang. Unfortunately, these oppressed people have been living in wars that have been going on for four decades, in which educational institutions, schools and institutes have not developed. Rather, the war destroyed the infrastructure of this country, and no city or village remained in it but tasted the bloody wars. Now with the new government, we see that many government educational institutions are closed in this country, even if the state promises that it will open them quickly. As for universities and private institutions, they work in Afghanistan diligently and diligently, and among them, there is sharp competition in the use of professors and taking advantage of the available means for the sake of knowledge. It laid the building blocks for a bright dawn in which it seeks to keep pace with the procession of development and prosperity in the world.

Keywords: Afghanistan, higher education, Herat province, opportunities, challenges

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Authors: Hao Mi, Ming Yang, Tian-yue Yang

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Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: remote monitoring, non-destructive testing, embedded Linux system, image processing

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Authors: Simon Strande Henriksen

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When a city and country decide to undertake an Olympic Games, they do so with the notion that hosting the Olympics will provide direct financial benefits to the city, country, and national companies. Like many activities, the Olympic Games tend to be more popular when it is warm, and the athletes are known, and therefore this paper will only focus on the two latest Olympic Summer Games. Cities and countries continue to invest billions of dollars in infrastructure to secure the role of being Olympic hosts. The multiple investments expect to provide both economic growth and a lasting legacy for the citizens. This study aims to determine whether host country companies experience superior economic impact from the Olympics. Building on existing work within the Olympic field of research, it asks: Do companies in host countries of the Olympic Summer Games experience a superior increase in operating revenue and return on assets compared to other comparable countries? In this context, comparable countries are the two candidates following the host city in the bidding procedure. Based on methods used by scholars, a panel data regression was conducted on revenue growth rate and return on assets, to determine if host country companies see a positive relation with hosting the Olympic Games. Combined with an analysis of motivation behind hosting the Olympics, the regression showed no significant positive relations across all analyses, besides in one instance. Indications of a relationship between company performance and economic motivation were found to be present. With the results indicating a limited effect on company growth, it is recommended that prospective host cities and countries carefully consider possible implications the role of being an Olympic host might have on national companies.

Keywords: cross-country analysis, mega-event, multiple regression, quantitative analysis

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Authors: Felix Givois, Nicolas R. Gauger, Matthias Kabel

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The efficient digital material characterization is of great interest to many fields of application. It consists of the following three steps. First, a 3D reconstruction of 2D scans must be performed. Then, the resulting gray-value image of the material sample is enhanced by image processing methods. Finally, partial differential equations (PDE) are solved on the segmented image, and by averaging the resulting solutions fields, effective properties like stiffness or conductivity can be computed. Due to the high resolution of current CT images, the latter is typically performed with matrix-free solvers. Among them, a solver that uses the explicit formula of the Green-Eshelby operator in Fourier space has been proposed by Moulinec and Suquet. Its algorithmic, most complex part is the Fast Fourier Transformation (FFT). In our talk, we will discuss the potential quantum advantage that can be obtained by replacing the FFT with the Quantum Fourier Transformation (QFT). We will especially show that the data transfer for noisy intermediate-scale quantum (NISQ) devices can be improved by using appropriate boundary conditions for the PDE, which also allows using semi-classical versions of the QFT. In the end, we will compare the results of the QFT-based algorithm for simple geometries with the results of the FFT-based homogenization method.

Keywords: most likelihood amplitude estimation (MLQAE), numerical homogenization, quantum Fourier transformation (QFT), NISQ devises

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Authors: O. Abusaeeda, J. P. O. Evans, D. Downes

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We demonstrate the synthesis of intermediary views within a sequence of X-ray images that exhibit depth from motion or kinetic depth effect in a visual display. Each synthetic image replaces the requirement for a linear X-ray detector array during the image acquisition process. Scale invariant feature transform, SIFT, in combination with epipolar morphing is employed to produce synthetic imagery. Comparison between synthetic and ground truth images is reported to quantify the performance of the approach. Our work is a key aspect in the development of a 3D imaging modality for the screening of luggage at airport checkpoints. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, KDE, view synthesis

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Authors: Balraju Vadlakonda, Narasimha Mangadoddy

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The hydrodynamic behavior in a laboratory column flotation was analyzed using particle image velocimetry. For complete characterization of column flotation, it is necessary to determine the flow velocity induced by bubbles in the liquid phase, the bubble velocity and bubble characteristics:diameter,shape and bubble size distribution. An experimental procedure for analyzing simultaneous, phase-separated velocity measurements in two-phase flows was introduced. The non-invasive PIV technique has used to quantify the instantaneous flow field, as well as the time averaged flow patterns in selected planes of the column. Using the novel particle velocimetry (PIV) technique by the combination of fluorescent tracer particles, shadowgraphy and digital phase separation with masking technique measured the bubble velocity as well as the Reynolds stresses in the column. Axial and radial mean velocities as well as fluctuating components were determined for both phases by averaging the sufficient number of double images. Bubble size distribution was cross validated with high speed video camera. Average turbulent kinetic energy of bubble were analyzed. Different air flow rates were considered in the experiments.

Keywords: particle image velocimetry (PIV), bubble velocity, bubble diameter, turbulent kinetic energy

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

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Authors: Mei-Yi Wu, Shang-Ming Huang

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The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

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Authors: Abhisek Dash

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This study had three neural networks, one for number segmentation, one for number detection and one for number recognition all of which are coupled to one another. All networks were trained on the MNIST dataset and were convolutional. It was assumed that the images had lighter background and darker foreground. The segmentation network took 28x28 images as input and had sixteen outputs. Segmentation training starts when a dark pixel is encountered. Taking a window(7x7) over that pixel as focus, the eight neighborhood of the focus was checked for further dark pixels. The segmentation network was then trained to move in those directions which had dark pixels. To this end the segmentation network had 16 outputs. They were arranged as “go east”, ”don’t go east ”, “go south east”, “don’t go south east”, “go south”, “don’t go south” and so on w.r.t focus window. The focus window was resized into a 28x28 image and the network was trained to consider those neighborhoods which had dark pixels. The neighborhoods which had dark pixels were pushed into a queue in a particular order. The neighborhoods were then popped one at a time stitched to the existing partial image of the number one at a time and trained on which neighborhoods to consider when the new partial image was presented. The above process was repeated until the image was fully covered by the 7x7 neighborhoods and there were no more uncovered black pixels. During testing the network scans and looks for the first dark pixel. From here on the network predicts which neighborhoods to consider and segments the image. After this step the group of neighborhoods are passed into the detection network. The detection network took 28x28 images as input and had two outputs denoting whether a number was detected or not. Since the ground truth of the bounds of a number was known during training the detection network outputted in favor of number not found until the bounds were not met and vice versa. The recognition network was a standard CNN that also took 28x28 images and had 10 outputs for recognition of numbers from 0 to 9. This network was activated only when the detection network votes in favor of number detected. The above methodology could segment connected and overlapping numbers. Additionally the recognition unit was only invoked when a number was detected which minimized false positives. It also eliminated the need for rules of thumb as segmentation is learned. The strategy can also be extended to other characters as well.

Keywords: convolutional neural networks, OCR, text detection, text segmentation

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Authors: Azadeh Rezafar

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Iran is one of the oldest countries with traditional culture in the world. All over the history Iranians had traditional architectural designs, which were at the same time sustainable, ecological, functional and environmental consistent. These human scale architectures were built for maximum use, comfort, climate adaptation with available resources and techniques. Climate variability of the country caused developing of variety design methods. More of these methods such as windcatchers in Yazd City or Panam (Insulation) were scientific solutions at the same time. Renewable energy resources were used in these methods that featured in them. While climate and ecological issues were dominant parts of these traditional designs, aesthetic and beauty issues were not ignored. Conformity with the community’s culture caused more compact designs that the visual aesthetics of them can be seen inside of them. Different organizations of space were used for these visual aesthetic issues inside the houses as well as historical urban designs. For example dry and hot climates in central parts of the country designed with centralized organization. Most central parts of these designs functioned as a courtyard for temperate the air in the summer. This paper will give summary descriptive information about traditional Iranian architectural style by figures all around the country with different climate conditions, while focus of the paper is traditional architectural design of the central part of the country, with dry and hot climate condition. This information may be useful for contemporary architectural designs, which are designed without noticing to the vernacular condition and caused cities look like each other.

Keywords: architectural design, traditional design, Iran, sustainability

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Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

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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

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Authors: Henrique Alpalhão

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This paper attempts to model the widely studied relationship between a country's economic growth and its level of democracy, with an emphasis on possible non-linearities. We adopt the concept of 'political capital' as a measure of democracy, which is extremely uncommon in the literature and brings considerable advantages both in terms of dynamic considerations and plausibility. While the literature is not consensual on this matter, we obtain, via panel Arellano-Bond regression analysis on a database of more than 60 countries over 50 years, significant and robust results that indicate that the impact of democratization on economic growth varies according to the stage of democratic development each country is in.

Keywords: democracy, economic growth, political capital, political economy

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Authors: Supaporn Prajongjai, Pannarungsri Inpayoung

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This research attempts to explore the perception and satisfaction of international tourists toward Thai economy, politics and Bangkok attributes. Due to tourism industry provides a high rate of revenue for Thailand, and the outcome from this business drives every section of Thailand such as business, residents’ living level. Unfortunately, some incidents in the country, such as some turmoil, have ruined the city’s image which obviously impacts to the tourism industry, the major source of revenue. The size of this research was 400 international tourists who visit Bangkok, Thailand during the 1st – 20th March 2009 and age between 20 – 65 years. The results reveal that tourists satisfy with all of Bangkok’s attributes including general attractions, heritage attraction, maintenance factors and cultural attraction. Also, tourists’ perception toward Thai politics is significantly related to their satisfaction of Bangkok’s attributes, but their perception toward Thai economy is not significantly correlated to their satisfaction of Bangkok’s attributes.

Keywords: international tourists' perception, tourists' satisfactions, Thai economy, tourism destination

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Authors: Hussain Ali Bekhet, Endang Jati Mat Sahid

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For the past few decades, the Malaysian economy has expanded at an impressive pace, whilst, the Malaysian population has registered a relatively high growth rate. These factors had driven the growth of final energy demand. The ballooning energy demand coupled with the country’s limited indigenous energy resources have resulted in an increased of the country’s net import. Therefore, acknowledging the precarious position of the country’s energy self-sufficiency, this study has identified three main concerns regarding energy security, namely; over-dependence on fossil fuel, increasing energy import dependency, and increasing energy consumption per capita. This paper discusses the recent energy demand and supply trends, highlights the policies that are affecting energy security in Malaysia and suggests strategic options towards achieving energy security. The paper suggested that diversifying energy sources, reducing carbon content of energy, efficient utilization of energy and facilitating low-carbon industries could further enhance the effectiveness of the measures as the introduction of policies and initiatives will be more holistic.

Keywords: electricity, energy policy, energy security, Malaysia

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Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

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The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

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Authors: Yali Zheng, Peipei Luo, Shinan Chen, Jiasheng Hao, Hong Cheng

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Most of traditional visual indoor navigation algorithms and methods only consider the localization in ordinary daytime, while we focus on the indoor re-localization in low light in the paper. As RGB images are degraded in low light, less discriminative infrared and depth image pairs are taken, as the input, by RGB-D cameras, the most similar candidates, as the output, are searched from databases which is built in the bag-of-word framework. Epipolar constraints can be used to relocalize the query infrared and depth image sequence. We evaluate our method in two datasets captured by Kinect2. The results demonstrate very promising re-localization results for indoor navigation system in low light environments.

Keywords: indoor navigation, low light, RGB-D camera, vision based

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Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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Authors: Shih-Ching Wang, Mark Lang

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This paper examines the secondary effects and consequences of special displays on subsequent shopping behavior. Special displays are studied as a prominent form of in-store or shopper marketing activity. Two experiments are performed using special value and special quality-oriented displays in an online simulated store environment. The impact of exposure to special displays on mindsets and resulting product choices are tested in a shopping task. Impact on store image is also tested. The experiments find that special displays do trigger shopping mindsets that affect product choices and shopping basket composition and value. There are intended and unintended positive and negative effects found. Special value displays improve store price image but trigger a price sensitive shopping mindset that causes more lower-priced items to be purchased, lowering total basket dollar value. Special natural food displays improve store quality image and trigger a quality-oriented mindset that causes fewer lower-priced items to be purchased, increasing total basket dollar value. These findings extend the theories of product categorization, mind-sets, and price sensitivity found in communication research into the retail store environment. Findings also warn retailers to consider the total effects and consequences of special displays when designing and executing in-store or shopper marketing activity.

Keywords: special displays, mindset, shopping behavior, price consciousness, product categorization, store image

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Authors: Yaron Katz

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The investigation of immigrants' electoral choices has remained relatively uncharted territory despite the fact that numerous nations extend political rights to their expatriates. This paper centers its attention on the matter of public trust in democracy, with a focus on the intricacies of Israeli politics as a divided system. It delves into the potential implications of political and social transformations stemming from the involvement of expatriate voters in elections taking place in their country of origin. In doing so, the article endeavors to explore a pathway for resolving a persistent challenge facing the stability of the Israeli political landscape over the past decade: the difficulty in forming a resilient government that genuinely represents the majority of voters. An examination is conducted into the role played by a demographic with the capacity to exert significant influence on election outcomes, namely, individuals residing outside of Israel. The objective of this research is to delve into this subject, dissecting social developments and political prospects that may shape the country's trajectory in the coming decades. This inquiry is especially pertinent given the extensive engagement of migrants in Israeli politics and the link between Israelis living abroad and their home country. Nevertheless, the study's findings reveal that while former citizens exhibit extensive involvement in Israeli politics and are cognizant of the potential consequences of permitting them to participate in elections, they maintain steadfastly unfavorable views regarding the inclusion of Israelis living overseas in their home country's electoral processes.

Keywords: trust, globalization, policy, democracy

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Authors: Tatsuya Takino, Izuru Nomura, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

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We propose a method of detecting the craters from the image of the lunar surface. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) working group aiming at the pinpoint landing on the lunar surface and investigating scientific research. It is difficult to equip and use high-performance computers for the small space probe. So, it is necessary to use a small computer with an exclusive hardware such as FPGA. We have studied the crater detection using principal component analysis (PCA), In this paper, We implement detection algorithm into the FPGA, and the detection is performed on the data that was captured from the CMOS camera.

Keywords: crater detection, PCA, FPGA, image processing

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Authors: Cristina Azocar, Ivana Markova

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A survey of 565 male undergraduates examined the effects of exposure to social networking sites and entertainment media on young men’s body image. Exposure to social and to entertainment media was found to have negative effects on men’s body satisfaction, social comparison, and thin ideal internalization. Findings indicated significant differences in those men who were more exposed to social and to entertainment media than those who were not as exposed. Consistent with past studies, gay men were found to be more dissatisfied with their bodies than straight men. Gay men compared themselves to other better-looking individuals and internalized ideal body types seen in media significantly more than their straight counterparts. Surprisingly, straight men seem to care as much about their physical attractiveness/appearance as gay men do, but only in public settings such as at the beach, at athletic events (including gyms) and social events. Although on average ethnic groups were more similar than different, small but significant differences occurred with Asian men indicating significantly higher body dissatisfaction than White/European men and Middle Eastern/Arab men their counterparts. The study increases our knowledge about SNS and entertainment use and its associated body image, and body satisfaction affects among low-income ethnic minority men.

Keywords: body dissatisfaction, body image, entertainment media, gay men, race and ethnicity, social economic status, social comparison, social media

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Authors: Elisabete Alberdi, Irantzu Álvarez, Nerea Astigarraga, Heber Hernández

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The purpose of this research work is to study the emissions of certain substances that contribute to air pollution and, as far as possible, to try to eliminate or reduce them, to avoid damage to both health and the environment. This work focuses on analyzing and comparing air quality in 2019 and 2020 in the Autonomous Community of the Basque Country, especially near the UPV/EHU campuses. We use Geostatistics to develop a spatial model and to analyse the levels of pollutants in those areas where the scope of the monitoring stations is limited. Finally, different more sustainable transport alternatives for users have been proposed.

Keywords: air quality, pollutants, monitoring stations, environment, geostatistics

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

Abstract:

Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

Procedia PDF Downloads 125

Authors: Ayala Amir

Abstract:

The paper presents interdisciplinary research which draws on the literary study and the cultural study of photography to explore a literary genre defined by nostalgia – the photographed book for children. This genre, which was popular in the second half of the 20th century, presents the romantic, nostalgic image of childhood created in the visual arts in the 18th century (as suggested by Ann Higonnet). At the same time, it capitalizes on the nostalgia inherent in the event of photography as formulated by Jennifer Green-Lewis: photography frames a moment in the present while transforming it into a past longed for in the future. Unlike Freudian melancholy, nostalgia is an effect that enables representation by acknowledging the loss and containing it in the very experience of the object. The representation and preservation of the lost object (nature, childhood, innocence) are in the center of the genre of children's photography books – a modern version of ancient pastoral. In it, the unique synergia of word and image results in a nostalgic image of childhood in an era already conquered by modernization. The nostalgic effect works both in the representation of space – an Edenic image of nature already shadowed by its demise, and of time – an image of childhood imbued by what Gill Bartholnyes calls the "looking backward aesthetics" – under the sign of loss. Little critical attention has been devoted to this genre with the exception of the work of Bettina Kümmerling-Meibauer, who noted the nostalgic effect of the well-known series of photography books by Astrid Lindgren and Anna Riwkin-Brick. This research aims to elaborate Kümmerling-Meibauer's approach using the theories of the study of photography, word-image studies, as well as current studies of childhood. The theoretical perspectives are implemented in the case study of photography books created in one of the most innovative social structures in our time – the Israeli Kibbutz. This communal way of life designed a society where children will experience their childhood in a parentless rural environment that will save them from the fate of the Oedipal fall. It is suggested that in documenting these children in a fictional format, photographers and writers, images and words cooperated in creating nostalgic works situated on the border between nature and culture, imagination and reality, utopia and its realization in history.

Keywords: nostalgia, photography , childhood, children's books, kibutz

Procedia PDF Downloads 142

Authors: Ashish Ashish

Abstract:

In the last few decades, the discrete chaos of difference equations has gained a massive attention of academicians and scholars due to its tremendous applications in each and every branch of science, such as cryptography, traffic control models, secure communications, weather forecasting, and engineering. In this article, a generalized logistic discrete map is established and discrete chaos is reported through period doubling bifurcation, period three orbit and Lyapunov exponent. It is interesting to see that the generalized logistic map exhibits superior chaos due to the presence of an extra degree of freedom of an ordered parameter. The period doubling bifurcation and Lyapunov exponent are demonstrated for some particular values of parameter and the discrete chaos is determined in the sense of Devaney's definition of chaos theoretically as well as numerically. Moreover, the study discusses an extended chaos based image encryption and decryption scheme in cryptography using this novel system. Surprisingly, a larger key space for coding and more sensitive dependence on initial conditions are examined for encryption and decryption of text messages, images and videos which secure the system strongly from external cyber attacks, coding attacks, statistic attacks and differential attacks.

Keywords: chaos, period-doubling, logistic map, Lyapunov exponent, image encryption

Procedia PDF Downloads 151