Search results for: vision problems

Authors: Valeria Bondarenko

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In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates.

Keywords: fractional Brownian motion, Gausssian processes, approximation, time series, estimation of properties of the model

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Authors: Abram Zoltan

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Over the past hundred years, human activities, particularly the burning of fossil fuels, have released enough carbon dioxide and other greenhouse gases to dissipate additional heat into the lower atmosphere and affect the global climate. Climate change affects many social and environmental determinants of health: clean air, safe drinking water, and adequate food. Our aim is to draw attention to the effects of climate change on the health and health care system. Improving climate awareness and the knowledge related to climate change's health impacts are essential among medical students and practicing medical doctors. Therefore, in their everyday practice, they also need some assistance and up-to-date knowledge of how climate change can endanger human health and deal with these novel health problems. Our activity, based on the cooperation of more universities, aims to develop new curriculum outlines and learning materials on climate change's health impacts for medical schools. Special attention is intended to pay to the possible preventative measures against these impacts. For all of this, the project plans to create new curriculum outlines and learning materials for medical students, elaborate methodological guidelines and create training materials for medical doctors' postgraduate learning programs. The target groups of the project are medical students, educational staff of medical schools and universities, practicing medical doctors with special attention to the general practitioners and family doctors. We had searched various surveys, domestic and international studies about the effects of climate change and statistical estimation of the possible consequences. The health effects of climate change can be measured only approximately by considering only a fraction of the potential health effects and assuming continued economic growth and health progress. We can estimate that climate change is expected to cause about 250,000 more deaths. We conclude that climate change is one of the most serious problems of the 21st century, affecting all populations. In the short- to medium-term, the health effects of climate change will be determined mainly by human vulnerability. In the longer term, the effects depend increasingly on the extent to which transformational action is taken now to reduce emissions. We can contribute to reducing environmental pollution by raising awareness and by educating the population.

Keywords: climate change, health impacts, medical students, education

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Authors: Jai Prakash Verma, Khushboo Verma

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In the present paper, a pair of Mond-Weir type non-differentiable multiobjective second-order programming problems, involving two kernel functions, where each of the objective functions contains support function, is formulated. We prove weak, strong and converse duality theorem for the second-order symmetric dual programs under η-pseudoinvexity conditions.

Keywords: non-differentiable multiobjective programming, second-order symmetric duality, efficiency, support function, eta-pseudoinvexity

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Authors: Hu Zhenxing, Gao Jianxin

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Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

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Authors: Narumon Jiwattanasuk, Phrakrupalad Pannavoravat, Pataraporn Sirikanchana

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Mindfulness has become a perspective addressing positive wellbeing these days. The aims of this paper are to analyze the problems of executive meditation practitioners at the Buddhamahametta Foundation in Thailand and to provide recommendations on the process to develop peaceful wellbeing in executive meditation practitioners by applying the principles of the four foundations of mindfulness. This study is particularly focused on executives because there is not much research focusing on the well-being development of executives, and the researcher recognizes that executives can be an example within their organizations. This would be a significant influence on their employees and their families to be interested in practicing mindfulness. This improvement will then grow from an individual to the surrounding community such as family, workplace, society, and the nation. This would lead to happiness at the national level, which is the expectation of this research. The paper highlights mindfulness practices that can be performed on a daily basis. This study is qualitative research, and there are 10 key participants who are executives from various sectors such as hospitality, healthcare, retail, power energy, and so on. Three mindfulness-based courses were conducted over a period of 8 months, and in-depth interviews were done before the first course as well as at the end of every course. In total, four in-depth interviews were conducted. The information collected from the interviews was analyzed in order to create the process to develop peaceful well-being. Focus group discussions with the mindfulness specialists were conducted to help develop the mindfulness program as well. As a result of this research, it is found that the executives faced the following problems: stress, negative thinking loops, losing temper, seeking acceptance, worry about uncontrollable external factors, unable to control their words, and weight gain. The cultivation of the four foundations of mindfulness can develop peaceful wellbeing. The results showed that after the key informant executives attended the mindfulness courses and practiced mindfulness regularly, they have developed peaceful well-being in all aspects such as physical, psychological, behavioral, and intellectual by applying 12 mindfulness-based activities. The development of wellbeing, in the conclusion of this study, also includes various tools to support the continuing practice, including the handout of guided mindfulness practice, VDO clips about mindfulness practice, the online dhamma channel, and mobile applications to support regular mindfulness-based practices.

Keywords: executive, mindfulness activities, stress, wellbeing

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Authors: K. Akherfi, H. Harroud

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Cloud Computing (CC) and Mobile Cloud Computing (MCC) have advanced rapidly the last few years. Today, MCC undergoes fast improvement and progress in terms of hardware (memory, embedded sensors, power consumption, touch screen, etc.) software (more and more sophisticated mobile applications) and transmission (higher data transmission rates achieved with different technologies such as 3Gs). This paper presents a review on the concept of CC and MCC. Then, it discusses what has been done regarding middleware in CC and MCC. Later, it shows the architecture of our proposed middleware along with its functionalities which will be provided to mobile clients in order to overcome the well-known problems (such as low battery power, slow CPU speed and, little memory etc.).

Keywords: context-aware, cloud computing, middleware, mobile cloud computing

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Authors: Sandra Ghavam Shirazi, Mohsen Ramezan Shirazi, Mohammadreza Golhashem

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Nowadays by development of construction in modern world new techniques are introduced to civil engineering. As for geotechnical problems and demands of soil improvement, engineers are searching for decisive methods to ensure the safety of projects. As a popular material Geotextiles are used in almost every aspect of civil engineering. There is a vast variety of geotextiles and each kind has their own unique characteristics therefor to select the proper geotextile for a specific project their properties must be carefully examined. This review gathers and evaluates different parameters of geotextiles that are used in geotechnical field.

Keywords: geotextile, soft soils, fabric, stabilization, fiber

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Authors: Elionai Moura, José A. Cunha, César Analide

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This work introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, showing technics and technology.

Keywords: case-based reasoning, pedagogical advising, educational data-mining (EDM), machine learning

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Authors: Mostafa Sarabzadeh, Masoumeh Helalizadeh, Seyyed Mahmoud Hejazi

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Multiple Sclerosis is considered as diseases related to central nerve system, the chronic and progressive disease impress on sensory and motor function of people. Due to equilibrium problems in this patients that related to disorder of nerve conduction transmission from central nerve system to organs and the nature of elastic bands that can make changes in neuromuscular junctions and momentary actions, the aim of this research is evaluate elastic training effect by reactionary ropes on nerve conduction velocity (in lower and upper limb) and functional balance in female patients with Multiple Sclerosis. The study was a semi-experimental study that was performed based on pre and post-test method, The statistical community consisted of 16 women with MS in the age mean 25-40yrs, at low and intermediate levels of disease EDSS 1-4 (Expanded Disability Status Scale) that were divided randomly into elastic and control groups, so the training program of experimental group lasted six weeks, 3 sessions per week of elastic exercises with reactionary ropes. Electroneurography parameters (nerve conduction velocity- latency) of Upper and lower nerves (Median, Tibial, Sural, Peroneal) along with balance were investigated respectively by the Electroneurography system (ENG) and Timed up and go (TUG) functional test two times in before and after the training period. After that, To analyze the data were used of Dependent and Independent T-test (with sig level p<0.05). The results showed significant increase in nerve conduction velocity of Sural (p=0.001), Peroneal (p=0.01), Median (p=0.03) except Tibial and also development Latency Time of Tibial (p= 0), Peroneal (p=0), Median (p=0) except Sural. The TUG test showed significant decreases in execution time too (p=0.001). Generally, based on what the obtained data can indicate, modern training with elastic bands can contribute to enhanced nerve conduction velocity and balance in neurosis patients (MS) so lead to reduce problems, promotion of mobility and finally more life expectancy in these patients.

Keywords: balance, elastic bands, multiple sclerosis, nerve conduction, velocity

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Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

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Authors: Tania Breton, Dorina Simeonov, Shauna MacEachern

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Ontario’s 10 Year Mental Health and Addictions Strategy has included the establishment of 18 Service Collaborative across the province; cross-sector tables in a specific region coming together to explore mental health and addiction system needs and adopting an intervention to address that need. The process is community led and supported by implementation teams from the Centre for Addiction and Mental Health (CAMH), using the framework of implementation science (IS) to enable evidence-based and sustained change. These justice initiatives are focused on the intersection of the justice system and the mental health and addiction systems. In this presentation, we will share the learnings, achievements and challenges of implementing innovative practices to the mental health and addictions needs of Ontarians within the justice system. Specifically, we will focus on the key points across the justice system - from early intervention and trauma-informed, culturally appropriate services to post-sentence support and community reintegration. Our approach to this work involves external implementation support from the CAMH team including coaching, knowledge exchange, evaluation, Aboriginal engagement and health equity expertise. Agencies supported the implementation of tools and processes which changed practice at the local level. These practices are being scaled up across Ontario and community agencies have come together in an unprecedented collaboration and there is a shared vision of the issues overlapping between the mental health, addictions and justice systems. Working with ministry partners has allowed space for innovation and created an environment where better approaches can be nurtured and spread.

Keywords: implementation, innovation, early identification, mental health and addictions, prevention, systems

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Authors: Przemyslaw Nogly, Tobias Weinert, Daniel James, Sergio Carbajo, Dmitry Ozerov, Antonia Furrer, Dardan Gashi, Veniamin Borin, Petr Skopintsev, Kathrin Jaeger, Karol Nass, Petra Bath, Robert Bosman, Jason Koglin, Matthew Seaberg, Thomas Lane, Demet Kekilli, Steffen Brünle, Tomoyuki Tanaka, Wenting Wu, Christopher Milne, Thomas A. White, Anton Barty, Uwe Weierstall, Valerie Panneels, Eriko Nango, So Iwata, Mark Hunter, Igor Schapiro, Gebhard Schertler, Richard Neutze, Jörg Standfuss

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Ultrafast isomerization of retinal is the primary step in a range of photoresponsive biological functions including vision in humans and ion-transport across bacterial membranes. We studied the sub-picosecond structural dynamics of retinal isomerization in the light-driven proton pump bacteriorhodopsin using an X-ray laser. Twenty snapshots with near-atomic spatial and temporal resolution in the femtosecond regime show how the excited all-trans retinal samples conformational states within the protein binding pocket prior to passing through a highly-twisted geometry and emerging in the 13-cis conformation. The aspartic acid residues and functional water molecules in proximity of the retinal Schiff base respond collectively to formation and decay of the initial excited state and retinal isomerization. These observations reveal how the protein scaffold guides this remarkably efficient photochemical reaction.

Keywords: bacteriorhodopsin, free-electron laser, retinal isomerization mechanism, time-resolved crystallography

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Authors: Comfort Aina

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Modern English, as we all know it to be a foreign language to many, will require training and re-training on the path of the teacher and learners alike. As a teacher, you cannot give that which you do not have. Teachers, many of whom are non-native speakers, are required to be competent in solving problems occurring in the teaching and learning processes. They should be conscious of up to date information about new approaches, methods, techniques as well as they should be capable in the use of information and communication technology (ICT) and, of course, should work on the improvement of their language components and competence. For teachers to be successful in these goals, they need to be encouraged and motivated. So, for EFL teachers to be successful, they are enrolled to in-service teacher training, ICT training, some of the training they undergo and the benefits accrued to it will be the focus of the paper.

Keywords: training, management, method, english language, EFL teachers

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Authors: Daniel Silander

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This article explores the EU Initiated European Neighborhood Policy (ENP) towards Ukraine. It also explores Russian geopolitics in the region. We argue that Ukraine is sandwiched between two regional powers in the EU and Russia. By analyzing EU democracy promotion towards Ukraine and neighbors, we assess a weak EU normative capacity. Instead of building a “ring of friends”, as argued by the EU Commission, in an enlarged democratic community, the EU has achieved poor democratic records in Ukraine which opened for a revival of Russia in the region and causes the international crisis over Crime of 2014.

Keywords: regional neighborhood policy, European Union, Russia, Ukraine, domestic elites

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Authors: N. Kashif, M. K. Naseer

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This is an undeniable fact that parents are the very first role model for their children and children are the silent observers and followers of their parents. The environment they would be provided will leave either positive or negative lasting impact on their physical and mental behavior and abilities to grow, progress and conquer. This paper focuses on the observation particularly in South Asian countries where females have been facing problems in accessing education and getting financially independent or stable. This paper emphasizes on a survey conducted in rural areas of Punjab State in Pakistan. It explains how the parents’ educational background, financial status, conservative and interdependent accommodation style influence a prominent inequality of giving their female child right to study and get empowered. The forces behind this gender discrimination are not limited to parents’ life style impact but also include some major social problems like distant schools, gender-based harassment, and threat, insecurities, employment opportunities, so on. As a grass root level solution, it is proposed to develop an institution which collects data regarding child birth in their region and can contact the parent when their child is ready to start school. Building up trust based relationship with parents is the most crucial and significant factor. Secondly, celebrities and public figures can play an extraordinary role in running a campaign to advocate and encourage people living in rural areas, villages and small towns. All possible solutions can never be implemented without the support of the state government. Therefore, this paper invites more thoughtful actions, properly planned strategies, initiators to take the lead and make a platform for those who are underprivileged and deprived of their basic rights. Any country, where female constitute 49% of its entire population can never progress without promoting female empowerment and their right to compulsory education, and it is never late or impossible to admit the facts and practically start a flexible solution- oriented approach.

Keywords: employment opportunities, female empowerment, gender based harassment, gender discrimination, inequality, parents' life style impact

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Authors: Tapan Jain, Davender Singh Saini

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Clustering is a useful mechanism in wireless sensor networks which helps to cope with scalability and data transmission problems. The basic aim of our research work is to provide efficient clustering using Hierarchical agglomerative clustering (HAC). If the distance between the sensing nodes is calculated using their location then it’s quantitative HAC. This paper compares the various agglomerative clustering techniques applied in a wireless sensor network using the quantitative data. The simulations are done in MATLAB and the comparisons are made between the different protocols using dendrograms.

Keywords: routing, hierarchical clustering, agglomerative, quantitative, wireless sensor network

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Authors: F. Moghtaderi, M. Burke, J. Troelsen

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There has been a significant decline in active travel as well as the massive increase use of car-dependent travel mode in many countries during past two decades. Evidential risks for people’s physical and mental health problems are followed by this increased use of motorized travel mode. These problems range from overweight and obesity to increasing air pollution. In response to these rising concerns, local councils and other interested organizations around the world have introduced a variety of initiatives regarding reduce the dominance of cars for the daily journeys. However, the nature of these kinds of interventions, which related to the human behavior, make lots of complexities. People’s travel behavior and changing this behavior, has two different aspects. People’s attitudes and perceptions toward the sustainable and healthy modes of travel, and motorized travel modes (especially private car use) is one these two aspects. The other one related to people’s behavior change processes. There are no comprehensive model in order to guide policy interventions to increase the level of succeed of such interventions. A comprehensive theoretical framework is required in accordance to facilitate and guide the processes of data collection and analysis to achieve the best possible guidelines for policy makers. Regarding this gaps in the travel behavior change research, this paper attempted to identify and suggest a multidimensional framework in order to facilitate planning interventions. A structured mixed-method is suggested regarding the expand the scope and improve the analytic power of the result according to the complexity of human behavior. In order to recognize people’s attitudes, a theory with the focus on people’s attitudes towards a particular travel behavior was needed. The literature around the theory of planned behavior (TPB) was the most useful, and had been proven to be a good predictor of behavior change. Another aspect of the research, related to the people’s decision-making process regarding explore guidelines for the further interventions. Therefore, a theory was needed to facilitate and direct the interventions’ design. The concept of the transtheoretical model of behavior change (TTM) was used regarding reach a set of useful guidelines for the further interventions with the aim to increase active travel and sustainable modes of travel. Consequently, a combination of these two theories (TTM and TPB) had presented as an appropriate concept to identify and design implemented travel behavior change interventions.

Keywords: behavior change theories, theoretical framework, travel behavior change interventions, urban research

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Authors: Fady Tawakol

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BitCoin is a decentralized cryptocurrency that can be used without the need of traditional central banks to accomplish any e-commerce trade. The use of such currency could facilitate new economic interactions and linkages. However, without effective and efficient regulations, cryptocurrency transactions are mostly used by criminals to commit crimes such as money laundering, theft, and blackmailing. And because law is one step behind technological developments, this paper discusses the importance of regulations and supervision for the BitCoin-system, to provide unified regulatory solutions for our digital future in the Middle East. It will provide a detailed analysis of the legal nature of BitCoin along with, its regulation with respect to criminal and civil law.

Keywords: BitCoin, financial protection, crypto currency, money laundering

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Authors: Wambugu Naftaly, Ruisheng Wang, Zhijun Wang

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Models based on convolutional neural networks (CNNs), in conjunction with Transformer, have excelled in semantic segmentation, a fundamental task for intelligent Earth observation using remote sensing (RS) imagery. Nonetheless, tokenization in the Transformer model undermines object structures and neglects inner-patch local information, whereas CNNs are unable to simulate global semantics due to limitations inherent in their convolutional local properties. The integration of the two methodologies facilitates effective global-local feature aggregation and interactions, potentially enhancing segmentation results. Inspired by the merits of CNNs and Transformers, we introduce a layer-level feature aggregation network (LLFA-Net) to address semantic segmentation of fine-resolution remote sensing (FRRS) images for land cover classification. The simple yet efficient system employs a transposed unit that hierarchically utilizes dense high-level semantics and sufficient spatial information from various encoder layers through a layer-level feature aggregation module (LLFAM) and models global contexts using structured Transformer blocks. Furthermore, the decoder aggregates resultant features to generate rich semantic representation. Extensive experiments on two public land cover datasets demonstrate that our proposed framework exhibits competitive performance relative to the most recent frameworks in semantic segmentation.

Keywords: land cover mapping, semantic segmentation, remote sensing, vision transformer networks, deep learning

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Authors: C. Ramamoorthy, R. Ranga Raj

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In olden days the Ramayana epic depicts the usage of invisible and fuel less aircraft named pushpavimana. The change of color in the reptile family chameleon paves way for the concept of color change phenomenon available in nature. In present scenario the aircrafts are visible so it is easily identified. So there are too many problems from the threatening. Research is still going on about this problem by using Liquid Crystal Display (LCD). Objective of this paper is to find much better to use the concept of invisible aircraft using plasma display through Couple Charged Device camera (CCD), which has a high resolution and can be used for many purposes like spying, defense, etc. Moreover it is cost wise cheap then, escaping the foe viewing.

Keywords: CCD camera, chameleon, invisible, plasma display

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Authors: Brahim Sabir

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Psycho-Communication disorders negatively affect the academic curriculum for students in higher education. Thus, understanding these disorders, their causes and effects will give education specialists a tool for the decision, which will lead to the resolution of problems related to the integration of students with Psycho-Communication disorders. It is in this context that a statistical study was conducted, targeting the population object of study, namely Moroccan students. Pathological voice samples were recorded and analyzed acoustically with PRAAT software, in order to build a model that will be the basis for the objective diagnostic.

Keywords: psycho-communication disorders, acoustic analysis, PRAAT

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Authors: Debarshi Bhattacharya

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In 2015, historic Land Boundary Agreement (LBA) executed between India and Bangladesh finally settled almost seven decades long overdue critical enclave problems of the two neighbouring countries. Enclaves within India and Bangladesh were the awful outcome of the partition of India in 1947. As a dire consequence, the populace within these enclaves enormously suffered from getting basic rights and opportunities and governmental support services till long 67 years after India’s independence and partition. As per LBA, 2015, 51 Bangladeshi (BD) enclaves inside Indian territory and 111 Indian enclaves inside Bangladesh territory were actually transferred to each other. But, by virtue of LBA, 1974 executed earlier between the two countries, one BD enclave situated inside India, namely Dohogram-Angarpota (D-A) twin enclave, had not yet been exchanged by means of LBA, 2015 and it still remains as an integral part, may not be contiguous, of Bangladesh completely surrounded by Indian territory. A study was undertaken through an extensive field survey to assess the impact of the existence of D-A BD enclave inside Indian territory from India’s perspective. Field survey was conducted for the purpose in the form of an interview, group discussion, questionnaire survey, personal interaction etc. to gather information from the Indian people residing adjacent to D-A enclave and Tin Bigha Corridor (TBC), people of D-A enclave, officials of Border Security Forces of India and Bangladesh, public representatives, representatives of political organizations etc. The issue of the existence of D-A BD enclave inside Indian territory seriously brought apprehension of future problems to the people of Kuchlibari Region of Mekhligunj Block, India, on its contiguity with Indian mainland due to 24-hour open access for the BD people through TBC. The anxiety of the local Indian people regarding threats to the national security of India as well as to the law and order issues of the locality due to the open border of D-A BD enclave in the region. On the other hand, it was observed that 24 hours opening of TBC brought significant positive changes to the people of D-A BD enclave in terms of their socio-economic condition and security status.

Keywords: enclave, exchange of enclaves, land boundary agreement, Dohogram-Angarpota (D-A) Bangladeshi (BD) enclave, Tin Bigha Corridor

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Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

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Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

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Authors: Francesca Maria Melucci, Marco Panettieri, Rocco Roma

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Cities are at the forefront of achieving the sustainable development goals set out in the Sustainable Development Goals of Agenda 2030. For these reasons, increasing attention has been given to the creation of resilient, sustainable, inclusive and green cities and finding solutions to these problems is one of the greatest challenges faced by researchers today. In particular urban green infrastructures, including green roofs, play a key role in tackling environmental, social and economic problems. The starting point was an extensive literature review on 1. research developments on the benefits (environmental, economic and social) and implications of green roofs; 2. sustainability assessment and applied methodologies; 3. specific indicators to measure impacts on urban sustainability. Through this review, the appropriate qualitative and quantitative characteristics that are part of the complex 'green roof' system were identified, as studies that holistically capture its multifunctional nature are still lacking. So, this paper aims to find a method to improve community participation in green roof initiatives and support local governance processes in developing efficient proposals to achieve better sustainability and resilience of cities. To this aim, the multidimensional indicator-based framework, presented by Tapia in 2021, has been tested for the first time in the case of a green roof in the city of Madrid. The framework's set of indicators was implemented with other indicators such as those of waste management and circularity (OECD Inventory of Circular Economy indicators) and sustainability performance. The specific indicators to be used in the case study were decided after a consultation phase with relevant stakeholders. Data on the community's willingness to participate in green roof implementation initiatives were collected through interviews and online surveys with a heterogeneous sample of citizens. The results of the application of the framework suggest how the different aspects of sustainability influence the choice of a green roof and provide input on the main mechanisms involved in citizens' willingness to participate in such initiatives.

Keywords: urban agriculture, green roof, urban sustainability, indicators, multi-criteria analysis

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

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Authors: Saut Samuel Simamora

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PURPOSE: Nucleus drop is one of the most feared and severe complications of modern cataract surgery. The lens material may drop through iatrogenic breaks of the posterior capsule. The incidence of the nucleus as the complication of phacoemulsification increases concomitant to the increased frequency of phacoemulsification. Pars plana vitrectomy (PPV) followed by endofragmentation and secondary intraocular lens (IOL) implantation is the choice of management procedure. This case report aims to present the outcome of PPV for the treatment dropped nucleus after cataract surgery METHODS: A 65 year old female patient came to Vitreoretina department with chief complaints blurry vision in her left eye after phacoemulsification one month before. Ophthalmological examination revealed visual acuity of the right eye (VA RE) was 6/15, and the left eye (VA LE) was hand movement. The intraocular pressure (IOP) on the right eye was 18 mmHg, and on the left eye was 59 mmHg. On her left eye, there were aphakic, dropped lens nucleus and secondary glaucoma.RESULTS: The patient got antiglaucoma agent until her IOP was decreased. She underwent pars plana vitrectomy to remove dropped nucleus and iris fixated IOL. One week post operative evaluation revealed VA LE was 6/7.5 and iris fixated IOL in proper position. CONCLUSIONS: Nucleus drop generally occurs in phacoemulsification cataract surgery techniques. Retained lens nucleus or fragments in the vitreous may cause severe intraocular inflammation leading to secondary glaucoma. The proper and good management for retained lens fragments in nucleus drop give excellent outcome to patient.

Keywords: secondary glaucoma, complication of phacoemulsification, nucleus drop, pars plana vitrectomy

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Authors: Ethan James

Abstract:

Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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Authors: Devinder Singh, Arvind Kumar, Rajneesh Kumar

Abstract:

The general solution of the equations for a homogeneous isotropic microstretch thermo elastic medium with mass diffusion for two dimensional problems is obtained due to normal and tangential forces. The integral transform technique is used to obtain the components of displacements, microrotation, stress and mass concentration, temperature change and mass concentration. A particular case of interest is deduced from the present investigation.

Keywords: normal force, tangential force, microstretch, thermoelastic, the integral transform technique, deforming force, microstress force, boundary value problem

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Authors: Helida Thays Gomes Soares, Conceicao De Maria Pinheiro Correia, Fabiano Maciel Soares, Kleymer Silva

Abstract:

There is great discussion around populational increase in urban areas of the global south, and, consequently, the growth of inappropriate housing and the different ways humans have found to solve housing problems around the world. Sao Luís, the capital of the state of Maranhao is a good example. The 1.6 million inhabitant metropole is a colonial tropical city that shelters 22% of the population of Maranhão, brazilian state that still carries the scars of slavery in past centuries. In 2016, Brazilian Institute of Geography and Statistic found that 20% of Maranhão’s inhabitants were living in houses with external walls made of non-durable materials, like recycled wood, cardboard or soil. Out of this problematic, this study aims to propose interventions not only in the physical structure of irregular housing, but also to serve as a guide to intervene in the way eco-friendly, communitarian housing is seen by extreme poor zones inside metropolitan regions around big cities in the global south. The adaptation and reuse of industrial containers from the Harbor of Itaqui for housing is also an aim of the project. The great volume of discarded industrial containers may be an opportunity to solve housing deficit in the city. That way, through field research in São Luís’ neighborhoods mostly occupied by inappropriate housing, the study intends to raise ethnographical and physical values that help to shape new uses of industrial containers and recycled building materials, bringing the community into the process of shaping new-housing for local housing programs, changing the mindset of a concrete/brick model of building. The study used a general feasibility analysis of local engineers regarding strength of the locally used container for construction purposes, and also researched in-loco the current impressions of risky areas inhabitants of housing, traditional housing and the role they played as city shapers, evaluating their perceptions of what means to live and how their houses represent their personality.

Keywords: container housing, civil construction, housing deficit, participatory design, sustainability

Procedia PDF Downloads 191

Authors: Mai Alshareef

Abstract:

The Saudi government considers the modernisation of the education system as a critical component of the national development plan, Saudi Vision 2030; however, this sudden reform creates tension amongst Saudis. This study examines first the reflection of the social and digital education reform on stakeholders and the general Saudi public, and second, the influence of information and communication technologies (ICTs) on the ethnoreligious conflict in Saudi Arabia. This study employs Cyberconflict theory to examine conflicts in the real world and cyberspace. The findings are based on a qualitative case study methodology that uses netnography, an analysis of 3,750 Twitter posts and semi-structural interviews with 30 individuals, including key actors in the Saudi education sector and Twitter activists during 2019\2020. The methods utilised are guided by thematic analysis to map an understanding of factors that influence societal conflicts in Saudi Arabia, which in this case include religious, national, and gender identity. Elements of Cyberconflict theory are used to better understand how conflicting groups build their identities in connection to their ethnic/religious/cultural differences and competing national identities. The findings correspond to the ethnoreligious components of the Cyberconflict theory. Twitter became a battleground for liberals, conservatives, the Saudi public and elites, and it is used in a novel way to influence public opinion and to challenge the media monopoly. Opposing groups relied heavily on a discourse of exclusion and inclusion and showed ethnic and religious affiliations, national identity, and chauvinism. The findings add to existing knowledge in the cyberconflict field of study, and they also reveal outcomes that are critical to the Saudi Arabian national context.

Keywords: education, cyberconflict, Twitter, national identity

Procedia PDF Downloads 174