Search results for: city image

Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: Peter Baji

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In recent years, a growing body of literature emphasizes the increasingly negative impacts of urban road congestion in the everyday life of citizens. Although there are different responses from the public sector to decrease traffic congestion in urban regions, the most effective public intervention is using congestion charges. Because travel is an economic asset, its consumption can be controlled by extra taxes or prices effectively, but this demand-side intervention is often unpopular. Measuring traffic flows with the help of different methods has a long history in transport sciences, but until recently, there was not enough sufficient data for evaluating road traffic flow patterns on the scale of an entire road system of a larger urban area. European cities (e.g., London, Stockholm, Milan), in which congestion charges have already been introduced, designated a particular zone in their downtown for paying, but it protects only the users and inhabitants of the CBD (Central Business District) area. Through the use of Google Maps data as a resource for revealing urban road traffic flow patterns, this paper aims to provide a solution for a fairer and smarter congestion pricing method in cities. The case study area of the research contains three bordering districts of Budapest which are linked by one main road. The first district (5th) is the original downtown that is affected by the congestion charge plans of the city. The second district (13th) lies in the transition zone, and it has recently been transformed into a new CBD containing the biggest office zone in Budapest. The third district (4th) is a mainly residential type of area on the outskirts of the city. The raw data of the research was collected with the help of Google’s Distance Matrix API (Application Programming Interface) which provides future estimated traffic data via travel times between freely fixed coordinate pairs. From the difference of free flow and congested travel time data, the daily congestion patterns and hot spots are detectable in all measured roads within the area. The results suggest that the distribution of congestion peak times and hot spots are uneven in the examined area; however, there are frequently congested areas which lie outside the downtown and their inhabitants also need some protection. The conclusion of this case study is that cities can develop a real-time and place-based congestion charge system that forces car users to avoid frequently congested roads by changing their routes or travel modes. This would be a fairer solution for decreasing the negative environmental effects of the urban road transportation instead of protecting a very limited downtown area.

Keywords: Budapest, congestion charge, distance matrix API, application programming interface, pilot study

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Authors: Fhumulani R. Ramukhwatho, Roelien du Plessis, Suzan H. H. Oelofse

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There are a growing number of scientific papers, journals and reports on household food waste, the reason being that food waste has become a significant global issue that is costing billions of Rands in resources. To reduce food waste in a sustainable manner, it requires an understanding of the generation of food waste. This paper assesses household food wastage in the City of Tshwane Metropolitan Municipality (CTMM). A total of 210 interviewed participants using face-to-face interviews based on a structured questionnaire and the actual weighing of households’ food wasted was quantified using a weighing kitchen scale. Fifty-nine percent of respondents agreed that they wasted food, while 41% thought they did not waste food at all. Households wasted an average total of 6 kg of food waste per week per household. The study concluded that households buy and prepare more food that ends up wasted.

Keywords: assessment, developing country, food waste, household

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Authors: M. Khasro Miah, Chowdhury Hossan Golam, Muhammed Siddique Hossain

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Recently, financial institution brand image is turning out to be pretty weak due to the presence of strong local competitors and this in term is affecting their firm performance also. In this study, four major HR practices, namely employee commitment, empowerment, loyalty, and engagement are considered in order to measure its effects on the brand and financial performance of banking organization. This study finds that the banking institutions of Bangladesh are more customer oriented rather than internal employee oriented, which makes it quite obvious that the internal HR practices will have little or no effect on the banks brand performance. Employee Commitment has emerged out to be the most important predictor, followed by employee loyalty and empowerment. The employees are well-empowered, engaged, and shows loyalty towards the organization, but their activities are not well linked with the brand. Firms should concentrate to create a congenial working atmosphere and employees should feel like a part of the organization.

Keywords: HR in bank, employee commitment, empowerment, finance, employee commitment, loyalty and engagement

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Authors: Zayar Phyo, Ei Chaw Htoon

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In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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Authors: Christos N. Tsironis, Loanna Mitaftsi

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Currently, the various forms of tours and touristic visits to destinations associated with the “dark” facets of the past constitute one of the most dynamic fields of touristic initiatives and economic development. This analysis focuses on the potential development of urban dark routes. It aims a) to shed light to touristic, social, and ethical considerations and to describe some of the trends and links combining heritage and dark tourism in post-pandemic societies and b) to explore the possibilities of developing a new and polymorphic form of dark tourism in Thessaloniki, Greece, a distinctive heritage destination. The analysis concludes with a detailed dark route designed to serve a new, polymorphic and sustainable touristic product that describes a dark past with places, sights, and monuments and narrates stories and events stigmatized by death, disaster, and violence throughout the city’s history.

Keywords: dark tourism, dark urban route, local development, polymorphic tourism

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Authors: Siti Nurkhamidah, Yeni Rahmawati, Fadlilatul Taufany, Eamor M. Woo, I Made P. A. Merta, Deffry D. A. Putra, Pitsyah Alifiyanti, Krisna D. Priambodo

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Cellulose acetate/polyethylene glycol (CA/PEG) membrane was modified with varying amount of silica and carbon nanotube (CNT) to enhance its separation performance in the desalination process. These composite membranes were characterized for their hydrophilicity, morphology and permeation properties. The experiment results show that hydrophilicity of CA/PEG/Silica membranes increases with the increasing of silica concentration and the decreasing particle size of silica. From Scanning Electron Microscopy (SEM) image, it shows that pore structure of CA/PEG membranes increases with the addition of silica. Membrane performance analysis shows that permeate flux, salt rejection, and permeability of membranes increase with the increasing of silica concentrations. The effect of CNT on the hydrophylicity, morphology, and permeation properties was also discussed.

Keywords: carbon nanotube, cellulose acetate, desalination, membrane, PEG

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Authors: Salim Ouchtati, Aissa Belmeguenai, Mouldi Bedda

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In this study, we propose an offline system for the recognition of the fragmented handwritten numeric chains. Firstly, we realized a recognition system of the isolated handwritten digits, in this part; the study is based mainly on the evaluation of neural network performances, trained with the gradient backpropagation algorithm. The used parameters to form the input vector of the neural network are extracted from the binary images of the isolated handwritten digit by several methods: the distribution sequence, sondes application, the Barr features, and the centered moments of the different projections and profiles. Secondly, the study is extended for the reading of the fragmented handwritten numeric chains constituted of a variable number of digits. The vertical projection was used to segment the numeric chain at isolated digits and every digit (or segment) was presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits).

Keywords: features extraction, handwritten numeric chains, image processing, neural networks

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Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

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Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

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Authors: Jing Zhang, Yvonne Reinwald, Nick Poulson, Alicia El Haj, Chung See, Mike Somekh, Melissa Mather

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Biomedical imaging of native tissue using light offers the potential to obtain excellent structural and functional information in a non-invasive manner with good temporal resolution. Image contrast can be derived from intrinsic absorption, fluorescence, or scatter, or through the use of extrinsic contrast. A major challenge in applying optical microscopy to in vivo tissue imaging is the effects of light attenuation which limits light penetration depth and achievable imaging resolution. Recently Selective Plane Illumination Microscopy (SPIM) has been used to map the 3D distribution of fluorophores dispersed in biological structures. In this approach, a focused sheet of light is used to illuminate the sample from the side to excite fluorophores within the sample of interest. Images are formed based on detection of fluorescence emission orthogonal to the illumination axis. By scanning the sample along the detection axis and acquiring a stack of images, 3D volumes can be obtained. The combination of rapid image acquisition speeds with the low photon dose to samples optical sectioning provides SPIM is an attractive approach for imaging biological samples in 3D. To date all implementations of SPIM rely on the use of fluorescence reporters be that endogenous or exogenous. This approach has the disadvantage that in the case of exogenous probes the specimens are altered from their native stage rendering them unsuitable for in vivo studies and in general fluorescence emission is weak and transient. Here we present for the first time to our knowledge a label-free implementation of SPIM that has downstream applications in the clinical setting. The experimental set up used in this work incorporates both label-free and fluorescent illumination arms in addition to a high specification camera that can be partitioned for simultaneous imaging of both fluorescent emission and scattered light from intrinsic sources of optical contrast in the sample being studied. This work first involved calibration of the imaging system and validation of the label-free method with well characterised fluorescent microbeads embedded in agarose gel. 3D constructs of mammalian cells cultured in agarose gel with varying cell concentrations were then imaged. A time course study to track cell proliferation in the 3D construct was also carried out and finally a native tissue sample was imaged. For each sample multiple images were obtained by scanning the sample along the axis of detection and 3D maps reconstructed. The results obtained validated label-free SPIM as a viable approach for imaging cells in a 3D gel construct and native tissue. This technique has the potential use in a near-patient environment that can provide results quickly and be implemented in an easy to use manner to provide more information with improved spatial resolution and depth penetration than current approaches.

Keywords: bioimaging, optics, selective plane illumination microscopy, tissue imaging

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Authors: Tomoko Yaginuma, Rosa Cabecinhas

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Recently, the studies of the images about Japan and/or the Japanese people have been done in a Japanese language education context since the number of the students of Japanese as a Foreign Language (JFL) has been increasing worldwide, including in Portugal. It has been claimed that one of the reasons for this increase is the current popularity of Japanese pop-culture, namely anime (Japanese animations) and manga (Japanese visual novels), among young students. In the present study, the images about Japan and the Japanese held by JFL students in Portugal were examined by a questionnaire survey. The JFL students in higher education in Portugal (N=296) were asked to answer, among the other questions, their degree of agreement (using a Likert scale) with 24 pre-defined descriptions about the Japanese, which appear as relevant in a qualitative pilot study conducted before. The results show that the image of Japanese people by Portuguese JFL students is stressed around four dimensions: 1) diligence, 2) kindness, 3) conservativeness and 4) innovativeness. The students considered anime was the main source of information about the Japanese people and culture and anime was also strongly associated with the students’ interests in learning Japanese language.

Keywords: anime, cultural studies, images about Japan and Japanese people, Portugal

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Authors: Kiran P. Chadayamuri, Saransh Bagdi, Sai Vinod Boddu

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Pollution has been a major problem that has haunted India for years. Large amounts of industrial, automobile and domestic waste have resulted in heavy contamination of air, land and water. The Taj Mahal, one of the Seven Wonders of the World, has been and continues to be India’s symbol of a rich history around the globe. Over the years, the beauty of Taj Mahal has also suffered from increasing pollution. Its shiny white exterior has started to turn yellow because of air pollution and acid rain. Illegal factories and uncontrolled construction have played a major role in worsening its condition. Rapid population growth in the city (Agra) meant more water requirement which has led to ground water deterioration under the historical monument making its wooden foundations dry and weak. Despite various measures by the state and central government, there hasn’t been any satisfactory result. This paper aims at studying the various causes and their impacts affecting the Taj Mahal and method that could slow down its deterioration.

Keywords: pollution, Taj Mahal, India, management

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Authors: Layla Mujahed

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Amman, the capital of Jordan, is the main political, economic, social and cultural center of Jordan and beyond. The city faces multitude demographic challenges related to the unstable political situation in the surrounded countries. It has regional and local migrants who left their homes to find better life in the capital. This resulted with random and unequaled population distribution. Some districts have high population and pressure on the infrastructure and services more than other districts.Government works to resolve this challenge in compliance with 100 Cities Resilience Framework (CRF). Amman participated in this framework as a member in December 2014 to work in achieving the four goals: health and welfare, infrastructure and utilities, economy and education as well as administration and government.  Previous research studies lack in studying Amman resilient work in neighborhood scale and the population growth as resilient challenge. For that, this study focuses on Al-Thahabiah neighborhood in Shafa Badran district in Amman. This paper studies the reasons and drivers behind this population growth during the selected period in this area then provide strategies to improve the resilient work in neighborhood scale. The methodology comprises of primary and secondary data. The primary data consist of interviews with chief officer in the executive part in Great Amman Municipality and resilient officer. The secondary data consist of papers, journals, newspaper, articles and book’s reading. The other part of data consists of maps and statistical data which describe the infrastructural and social situation in the neighborhood and district level during the studying period. Based upon those data, more detailed information will be found, e.g., the centralizing position of population and the provided infrastructure for them. This will help to provide these services and infrastructure to other neighborhoods and enhance population distribution. This study develops an analytical framework to assess urban demographical time series in accordance with the criteria of CRF to make accurate detailed projections on the requirements for the future development in the neighborhood scale and organize the human requirements for affordable quality housing, employment, transportation, health and education in this neighborhood to improve the social relations between its inhabitants and the community. This study highlights on the localization of resilient work in neighborhood scale and spread the resilient knowledge related to the shortage of its research in Jordan. Studying the resilient work from population growth challenge perspective helps improve the facilities provide to the inhabitants and improve their quality of life.

Keywords: city resilience framework, demography, population growth, stakeholders, urban resilience

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Authors: Nomin-Erdene Erdenetsogt, Tseedulam Khuut, Batsaikhan Tserenpil, Bayarsaikhan Enkhee

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As the framework of 60 years of development of Astronomical and Geophysical science in modern Mongolia, various geophysical methods (electrical tomography, ground-penetrating radar, and high-resolution reflection seismic profiles) were used to image an active fault in-depth range between few decimeters to few tens meters. An active fault was fractured by an earthquake magnitude 7.6 during 1967. After geophysical investigations, trench excavations were done at the sites to expose the fault surfaces. The complex geophysical survey in the Mogod fault, Bulgan region of central Mongolia shows an interpretable reflection arrivals range of < 5 m to 50 m with the potential for increased resolution. Reflection profiles were used to help interpret the significance of neotectonic surface deformation at earthquake active fault. The interpreted profiles show a range of shallow fault structures and provide subsurface evidence with support of paleoseismologic trenching photos, electrical surveys.

Keywords: Mogod fault, geophysics, seismic processing, seismic reflection survey

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Authors: Ali Abdallah, Shaima Al Mohannadi

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This study explores shopping tourism in the UK and examines it as an attraction tool for wealthy tourists to the UK’s capital city London. The study aims to identify the scope of shopping tourism used by countries such as the UK as a tool for attracting wealthy tourists. This study adopts the quantitative research approach through surveys in attaining the results required. Results demonstrate how the UK tourism market is an experience-based market and has recently become an attraction for luxurious brand shoppers. The term Trexit is introduced as a new form of tourism generated by the Brexit. If addressed appropriately the Trexit can assist in any negative economic retaliations of the Brexit. The study concludes that shopping tourism is yet to further incline in years to come, however, government support and cooperative planning with the retail industry is required as a means of further strengthening this developing sector.

Keywords: Brexit tourism, luxury shopping, UK tourism, wealthy tourists

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

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Authors: Mario Belseran

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The issue of climate change become world attention where one of them increase in air temperature due to greenhouse gas emissions. This climate change is caused by gases in the atmosphere, one of which is CO2. DKI Jakarta as the capital has a dense population with a variety of existing land use. Land use that is dominated by settlements resulting in fewer green space, which functions to absorb atmospheric CO2. Image interpretation SPOT-7 is used to determine the greenness level of vegetation on a green space using the vegetation index NDVI, EVI, GNDVI and OSAVI. Measuring the diameter and height of trees were also performed to obtain the value of biomass that will be used as the CO2 absorption value. The CO2 absorption value that spread in Jakarta are classified into three classes: high, medium, and low. The distribution pattern of CO2 absorption value at green space in Jakarta dominance in the medium class with the distribution pattern is located in South Jakarta, East Jakarta, North Jakarta and West Jakarta. The distribution pattern of green space in Jakarta scattered randomly and more dominate in East Jakarta and South Jakarta

Keywords: carbon dioxide, DKI Jakarta, green space, SPOT-7, vegetation index

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Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

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In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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Authors: Steven Woods

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The use of Corporate Social Responsibility Statements has become ubiquitous in society. The appeal to consumers by being a well-behaved social entity has become a strategy not just to ensure brand loyalty but also to further larger scale projects of corporate interests. Specifically, the use of CSR to position corporations as good planetary citizens involves not just self-promotion but also a way of transferring responsibility from systems to individuals. By using techniques labeled as “greenwashing” and emphasizing ethical consumption choices as the solution, corporations present themselves as good members of the community and pursuing sustainability. Ultimately, the primary function of Corporate Social Responsibility statements is to maintain the economic status quo of ongoing growth and consumption while presenting and environmentally progressive image to the public, as well as reassuring them corporate behavior is superior to government intervention. By analyzing the communication techniques utilized through content analysis of specific examples, along with an analysis of the frames of meaning constructed in the CSR statements, the practices of Corporate Responsibility and Sustainability will be addressed from an ethical perspective.

Keywords: corporate social responsibility, ethics, greenwashing, sustainability

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Authors: Nan KANG, Pierre Coddet, Hanlin Liao, Christian Coddet

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In this study, the almost dense eutectic Al-12Si alloys were fabricated by selective laser melting (SLM) from the powder mixture of pure Aluminum and pure Silicon, which show the mean particle sizes of 30 μm and 5μm respectively, under the argon environment. The image analysis shows that the highest value of relative density (95 %) was measured for the part obtained at the laser power of 280 W. X ray diffraction (XRD), Optical microscope (OM) and scanning electron microscope (SEM) equipped with X-ray energy dispersive spectroscopy (EDS) were employed to determine the microstructures of the SLM-processed Al-Si alloy, which illustrate that the SLM samples present the ultra-fine microstructure. The XRD results indicate that no clearly phase transformation happened during the SLM process. Additionally, the vaporization behavior of Aluminum was detected for the parts obtained at high laser power. Besides, the maximum microhardness value, about 95 Hv, was measured for the samples obtained at laser power of 280 W, and which shows the highest wear resistance.

Keywords: al-Si alloy, selective laser melting, wear behavior, microstructure

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: Minami Ito, Akihiro Iijima

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On March 11, 2011, the Great East Japan Earthquake occurred off the coast of Sanriku, Japan. It is important to build a sustainable society through the reconstruction process rather than simply restoring the infrastructure. To compare the goals of reconstruction plans of quake-stricken municipalities, Japanese language morphological analysis was performed by using text mining techniques. Frequently-used nouns were sorted into four main categories of “life”, “disaster prevention”, “economy”, and “harmony with environment”. Because Soma City is affected by nuclear accident, sentences tagged to “harmony with environment” tended to be frequent compared to the other municipalities. Results from cluster analysis and principle component analysis clearly indicated that the local government reinforces the efforts to reduce risks from radiation exposure as a top priority.

Keywords: eco-friendly reconstruction, harmony with environment, decontamination, nuclear disaster

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Authors: Volkan Isbuga, Joman M. Mahmood, Ali Firat Cabalar

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This study presents the site response analysis of mica-sand mixtures available in certain parts of the world including Izmir, a highly populated city and located in a seismically active region in western part of Turkey. We performed site response analyses by employing SHAKE, an equivalent linear approach, for the micaceous soil deposits consisting of layers with different amount of mica contents and thicknesses. Dynamic behavior of micaceous sands such as shear modulus reduction and damping ratio curves are input for the ground response analyses. Micaceous sands exhibit a unique dynamic response under a scenario earthquake with a magnitude of Mw=6. Results showed that higher amount of mica caused higher spectral accelerations.

Keywords: micaceous sands, site response, equivalent linear approach, SHAKE

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Authors: Masoumeh Khosravi

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Introduction: The complementary therapies and Qigong exercises is important in order to maintain physical and mental health. Objective: This study was done to compare and investigate well-being and mental health's state between practitioners of a Qigong practice (Falun Dafa) and non-practitioners. Method: It was a comparative study with 60 samples (30 practitioners of Falun Dafa, and 30 non-practitioners), who were selected by random sampling from Tehran city of Iran. Data were collected by mental health inventory (SCL90) and well-being questionnaire. Multivariate variance analyzing and t-test were used for analyzing data. Results: Results showed significant differences in most components of mental health including anxiety, aggressiveness, obsessive-compulsion, interpersonal sensitivity, somatization disorder, depression, phobia between practitioners and non-practitioners. Well-being was significantly higher in practitioners than non-practitioners. Conclusion: Accordingly, we concluded Falun Gong exercises have high impact on mental health and well-being in people.

Keywords: mental health, well-being, Qigong, Falun Dafa

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Authors: Roberto M. G. Velásquez, Jonas R. Gazoli, Nelson Ponce Jr, Valério L. Borges, Alessandro Sete, Fernanda M. C. Tomé, Julian D. Hunt, Heitor C. Lira, Cristiano L. de Souza, Fabio T. Bindemann, Wilmar Wounnsoscky

Abstract:

Nowadays, society is working toward reducing energy losses and greenhouse gas emissions, as well as seeking clean energy sources, as a result of the constant increase in energy demand and emissions. Energy loss occurs in the gas pressure reduction stations at the delivery points in natural gas distribution systems (city gates). Installing pressure reduction turbines (PRT) parallel to the static reduction valves at the city gates enhances the energy efficiency of the system by recovering the enthalpy of the pressurized natural gas, obtaining in the pressure-lowering process shaft work and generating electrical power. Currently, the Brazilian natural gas transportation network has 9,409 km in extension, while the system has 16 national and 3 international natural gas processing plants, including more than 143 delivery points to final consumers. Thus, the potential of installing PRT in Brazil is 66 MW of power, which could yearly avoid the emission of 235,800 tons of CO2 and generate 333 GWh/year of electricity. On the other hand, an economic viability analysis of these energy efficiency projects is commonly carried out based on estimates of the project's cash flow obtained from several variables forecast. Usually, the cash flow analysis is performed using representative values of these variables, obtaining a deterministic set of financial indicators associated with the project. However, in most cases, these variables cannot be predicted with sufficient accuracy, resulting in the need to consider, to a greater or lesser degree, the risk associated with the calculated financial return. This paper presents an approach applied to the technical-economic viability analysis of PRTs projects that explicitly considers the uncertainties associated with the input parameters for the financial model, such as gas pressure at the delivery point, amount of energy generated by TRP, the future price of energy, among others, using sensitivity analysis techniques, scenario analysis, and Monte Carlo methods. In the latter case, estimates of several financial risk indicators, as well as their empirical probability distributions, can be obtained. This is a methodology for the financial risk analysis of PRT projects. The results of this paper allow a more accurate assessment of the potential PRT project's financial feasibility in Brazil. This methodology will be tested at the Cuiabá thermoelectric plant, located in the state of Mato Grosso, Brazil, and can be applied to study the potential in other countries.

Keywords: pressure reduction turbine, natural gas pressure drop station, energy efficiency, electricity generation, monte carlo methods

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Authors: Naheed Khan

Abstract:

A non-experimental study was conducted to evaluate the prevalence of anxiety and depression in middle-class women in Karachi, a metropolitan city of Pakistan. The Aga Khan University Anxiety and Depression Scale (AKUADS) was self -administered by a sample of 50 housewives and 50 professional women between the ages of 24 and 54 years. All the participants were at least graduates, married, had children, and were living in joint family systems. Results showed a 48% prevalence of anxiety and depression in housewives as compared to 34% in professional women. The data showed significant difference in mean of total scores on AKUADS and the calculated t-value of 1.957 with a df = 98 and α = 0.05. Two variables, that is, profession and a higher level of education were significantly related to the outcome. Hence acquiring higher education and taking up a job, even a part time one, may alleviate the symptoms of anxiety and depression in housewives. Other factors responsible for the relief of such symptoms, such as quality of relationship with husbands, may be investigated for both categories of women.

Keywords: anxiety, depression, housewives, professional women

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Authors: Sefa Aksu, Ünal Kızıl

Abstract:

For this study, a town based soil database created in Gümüşçay District of Biga Town, Çanakkale, Turkey. Crop and livestock production are major activities in the district. Nutrient management is mainly based on commercial fertilizer application ignoring the livestock manure. Within the boundaries of district, 122 soil sampling points determined over the satellite image. Soil samples collected from the determined points with the help of handheld Global Positioning System. Labeled samples were sent to a commercial laboratory to determine 11 soil parameters including salinity, pH, lime, organic matter, nitrogen, phosphorus, potassium, iron, manganese, copper and zinc. Based on the test results soil maps for mentioned parameters were developed using remote sensing, GIS, and geostatistical analysis. In this study we developed a GIS database that will be used for soil nutrient management. Methods were explained and soil maps and their interpretations were summarized in the study.

Keywords: geostatistics, GIS, nutrient management, soil mapping

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Authors: Sudhakar Saroj, Satya Vir Singh

Abstract:

Undoped and Fe doped TiO₂, Ti₁₋ₓFeₓO₂ (x=0.00, 0.01, 0.03, 0.05, 0.07 and 0.09) have been synthesized by solution combustion method using Titanium (IV) oxide as a precursor, and also were characterized by XRD, DRS, FTIR, XPS, SEM, and EDX. The formation of anatase phase of undoped and Fe TiO₂ nanoparticles were confirmed by XRD, and the average crystallite size was determined by Debye-Scherer's equation. The DRS analysis indicates the shifting of light absorbance in visible region from UV region with increasing the doping concentration in TiO₂. The vibrational band of the Ti-O lattice was confirmed by the FT-IR spectrum. The XPS results confirm the presence of elements of titanium, oxygen and iron in the synthesized samples and determine the binding energy of elements. SEM image of the above-synthesized nanoparticles showed the spherical shape of nanoparticles. The purities of the synthesized nanoparticles were confirmed by EDX analysis. The photocatalytic activities of the synthesized nanoparticles were tested by studying the degradation of dye (Direct Blue 199) in the photocatalytic reactor. The Ti₀.₉₇Fe₀.₀₃O₂ photocatalyst shows highest photodegradation activity among all the synthesized undoped and Fe doped TiO₂ photocatalyst.

Keywords: direct blue 199, nanoparticles, TiO₂, photodegradation

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Authors: Zahra Afshordi

Abstract:

Instagram, as an everyday life social network, hosts from the ultrasound image of an unborn fetus to the pictures of newly placed gravestones and funerals. It is a platform that allows its users to create a second identity independently from and at the same time in relation to the real space identity. The motives behind this identification are what this article is about. This article studies the motivations of Instagram users mourning for celebrities with a focus on the death of MohammadReza Shajarian. The Shajarian’s death had a wide reflection on Instagram Persian-speaking users. The purpose of this qualitative survey is to comprehend and study the user’s motivations in posting mourning and memorializing content. The methodology of the essay is a hybrid methodology consisting of content analysis and open-ended interviews. The results highlight that users' motives are more than just simple sympathy and include political protest, gaining cultural capital, reaching social status, and escaping from solitude.

Keywords: case study, celebrity, identity, Instagram, mourning, qualitative survey

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