Search results for: urban network space

Authors: Ebrahim Alrashed, Yousef Rafique

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Mobile devices have drastically changed the way we do things on the move. They are being extremely relied on to perform tasks that are analogous to desktop computer capability. There has been a rapid increase of computational power on these devices; however, battery technology is still the bottleneck of evolution. The primary modern approach day approach to tackle this issue is offloading computation to the cloud, proving to be latency expensive and requiring high network bandwidth. In this paper, we explore efforts to perform barter-based mobile-to-mobile offloading. We present define a protocol and present an architecture to facilitate the development of such a system. We further highlight the deployment and security challenges.

Keywords: computational offloading, power conservation, cloud, sandboxing

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Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Isha Rathore, Peeyush Jain, Elangovan Rajasekar

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The thermal capacity of the envelope impacts the cooling and heating demand of a building and modulates the peak electricity demand. This paper presents the thermal capacity tuning of a building envelope to minimize peak electricity demand for space cooling. We consider a 40 m² residential testbed located in Hyderabad, India (Composite Climate). An EnergyPlus model is validated using real-time data. A Parametric simulation framework for thermal capacity tuning is created using the Honeybee plugin. Diffusivity, Thickness, layer position, orientation and fenestration size of the exterior envelope are parametrized considering a five-layered wall system. A total of 1824 parametric runs are performed and the optimum wall configuration leading to minimum peak cooling demand is presented.

Keywords: thermal capacity, tuning, peak demand reduction, parametric analysis

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Authors: Taezoon Park, Wonil Hwang

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This study aims to build a design guideline for the effective visual display used for consumer products considering user characteristics; gender and age. Although a number of basic experiments identified the limits of human visual perception, the findings remain fragmented and many times in an unfriendly form. This study compiled a design cases along with tables aggregated from the experimental result of visual perception; brightness/contrast, useful field of view, color sensitivity. Visual design elements commonly used for consumer product, were selected and appropriate guidelines were developed based on the experimental result. Since the provided data with case example suggests a feasible design space, it will save time for a product designer to find appropriate design alternatives.

Keywords: design guideline, consumer product, visual design element, visual perception, emotional design

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Authors: John Hang Leung, Shyh-Yau Wang, Hei-Tung Yip, Fion, Ho Tsung-chin, Agnes LF Chan

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Objectives: Platinum-resistant ovarian cancer has a short overall survival of 9–12 months and limited treatment options. The combination of immunotherapy and targeted therapy appears to be a promising treatment option for patients with ovarian cancer, particularly to patients with platinum-resistant recurrent ovarian cancer (PRrOC). However, there are no direct head-to-head clinical trials comparing their efficacy and toxicity. We, therefore, used a network to directly and indirectly compare seven newer immunotherapies or targeted therapies combined with chemotherapy in platinum-resistant relapsed ovarian cancer, including antibody-drug conjugates, PD-1 (Programmed death-1) and PD-L1 (Programmed death-ligand 1), PARP (Poly ADP-ribose polymerase) inhibitors, TKIs (Tyrosine kinase inhibitors), and antiangiogenic agents. Methods: We searched PubMed (Public/Publisher MEDLINE), EMBASE (Excerpta Medica Database), and the Cochrane Library electronic databases for phase II and III trials involving PRrOC patients treated with immunotherapy or targeted therapy plus chemotherapy. The quality of included trials was assessed using the GRADE method. The primary outcomes compared were progression-free survival, the secondary outcomes were overall survival and safety. Results: Seven randomized controlled trials involving a total of 2058 PRrOC patients were included in this analysis. Bevacizumab plus chemotherapy showed statistically significant differences in PFS (Progression-free survival) but not OS (Overall survival) for all interested targets and immunotherapy regimens; however, according to the heatmap analysis, bevacizumab plus chemotherapy had a statistically significant risk of ≥grade 3 SAEs (Severe adverse effects), particularly hematological severe adverse events (neutropenia, anemia, leukopenia, and thrombocytopenia). Conclusions: Bevacizumab plus chemotherapy resulted in better PFS as compared with all interested regimens for the treatment of PRrOC. However, statistical differences in SAEs as bevacizumab plus chemotherapy is associated with a greater risk for hematological SAE.

Keywords: platinum-resistant recurrent ovarian cancer, network meta-analysis, immune checkpoint inhibitors, target therapy, antiangiogenic agents

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Authors: Paolo Russu

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The purpose of the present paper is to highlight some features of an economic growth model with environmental negative externalities, giving rise to a three-dimensional dynamic system. In particular, we show that the economy, which is based on a Perfect-Substitution Technologies function of production, has no neither indeterminacy nor poverty trap. This implies that equilibrium select by economy depends on the history (initial values of state variable) of the economy rather than on expectations of economies agents. Moreover, by contrast, we prove that the basin of attraction of locally equilibrium points may be very large, as they can extend up to the boundary of the system phase space. The infinite-horizon optimal control problem has the purpose of maximizing the representative agent’s instantaneous utility function depending on leisure and consumption.

Keywords: Hopf bifurcation, open-access natural resources, optimal control, perfect-substitution technologies, Poincarè compactification

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Authors: Shervin Alaei, Reza Moradi

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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

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Authors: Fikre Belay Tekulu

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The Adigrat town lies in the Tigray region of Ethiopia. This region is mountainous and experiences a semiarid type of climate. Most of the rainfall occurs in four months of the year, which are June to September. During this season, flood is a common natural disaster, especially in urban areas. In this paper, an attempt is made to identify flood-prone areas in Adigrat town using Boolean logic with GIS and remote sensing techniques. Three parameters were incorporated as land use type, elevation, and slope. Boolean logic was used as land use equal to buildup land, elevation less than 2430 m, and slope less than 5 degrees. As a result, 0.575 km² was identified severely affected by floods during the rainy season.

Keywords: flood, GIS, hydrology, Adigrat

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Authors: Reza Mohammadi, Mahdieh Sahebi

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We develop a method based on polynomial quintic spline for numerical solution of fourth-order non-homogeneous parabolic partial differential equation with variable coefficient. By using polynomial quintic spline in off-step points in space and finite difference in time directions, we obtained two three level implicit methods. Stability analysis of the presented method has been carried out. We solve four test problems numerically to validate the proposed derived method. Numerical comparison with other existence methods shows the superiority of our presented scheme.

Keywords: fourth-order parabolic equation, variable coefficient, polynomial quintic spline, off-step points, stability analysis

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Authors: Eileen Kim

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As socioeconomic disparities grew in New York during the 1970s, artists represented new values that came with the times. Street art, in particular, was birthed from a distinctly urban, fringe setting to ultimately become one of the most lucrative forms of art today. Examining the economic and psychological reasons behind the rise of street art, this paper delves into the development of the art market as a parallel insight into human behaviors and economic models such as supply and demand. The purpose of this study is to show the role of the increasingly divided socioeconomic classes and the rise of art collecting as an asset-building form. This study concludes that the iconography and market value of street art represented distinct values that came from a series of intertwined social matters such as racial tensions and revolutions in industrial innovation.

Keywords: art industry, cultural representation, ethnicity, markets, public property, social classes, street art

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Authors: Gaurangi Saxena, Ravindra Saxena

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Lately, cloud computing is used to enhance the ability to attain corporate goals more effectively and efficiently at lower cost. This new computing paradigm “The Cloud Computing” has emerged as a powerful tool for optimum utilization of resources and gaining competitiveness through cost reduction and achieving business goals with greater flexibility. Realizing the importance of this new technique, most of the well known companies in computer industry like Microsoft, IBM, Google and Apple are spending millions of dollars in researching cloud computing and investigating the possibility of producing interface hardware for cloud computing systems. It is believed that by using the right middleware, a cloud computing system can execute all the programs a normal computer could run. Potentially, everything from most simple generic word processing software to highly specialized and customized programs designed for specific company could work successfully on a cloud computing system. A Cloud is a pool of virtualized computer resources. Clouds are not limited to grid environments, but also support “interactive user-facing applications” such as web applications and three-tier architectures. Cloud Computing is not a fundamentally new paradigm. It draws on existing technologies and approaches, such as utility Computing, Software-as-a-service, distributed computing, and centralized data centers. Some companies rent physical space to store servers and databases because they don’t have it available on site. Cloud computing gives these companies the option of storing data on someone else’s hardware, removing the need for physical space on the front end. Prominent service providers like Amazon, Google, SUN, IBM, Oracle, Salesforce etc. are extending computing infrastructures and platforms as a core for providing top-level services for computation, storage, database and applications. Application services could be email, office applications, finance, video, audio and data processing. By using cloud computing system a company can improve its customer relationship management. A CRM cloud computing system may be highly useful in delivering a sales team a blend of unique functionalities to improve agent/customer interactions. This paper attempts to first define the cloud computing as a tool for running business activities more effectively and efficiently at a lower cost; and then it distinguishes cloud computing with grid computing. Based on exhaustive literature review, authors discuss application of cloud computing in different disciplines of management especially in the field of marketing with special reference to use of cloud computing in CRM. Study concludes that CRM cloud computing platform helps a company track any data, such as orders, discounts, references, competitors and many more. By using CRM cloud computing, companies can improve its customer interactions and by serving them more efficiently that too at a lower cost can help gaining competitive advantage.

Keywords: cloud computing, competitive advantage, customer relationship management, grid computing

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Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: Yaprak Aydin

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The rural is no longer a space of only agricultural activities that gave into the global market demands; or an idyll to return after retirement; or only a reservoir of cultural values, but rather a vision to redefine the future in terms of production and consumption relations. Gulpınar in Turkey and Ashtarak in Armenia are two towns where a new ground of dialogue between two communities has been initiated: ‘energy democracy’, which is a significant driving force in a sense of gathering people of two historically conflicted communities around common future concerns; and in a sense of transforming the accepted knowledge on the rurality and all the social structures it represents. This paper seeks to provoke a discussion of to what extent such a rurality is attainable by contextualizing – through visits and meetings in person – two towns and two communities within a renewable energy project called 'Under the Same Sun' carried out by two local civil society organizations together at two public spaces.

Keywords: civil society, energy democracy, prosumer communities, renewable energy, transnational rurality

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Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: M. Pramila Devi, N. V. N. Indra Kiran

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Control charts, predominantly in the form of X-bar chart, are important tools in statistical process control (SPC). They are useful in determining whether a process is behaving as intended or there are some unnatural causes of variation. A process is out of control if a point falls outside the control limits or a series of point’s exhibit an unnatural pattern. In this paper, a study is carried out on four training algorithms for CCPs recognition. For those algorithms optimal structure is identified and then they are studied for type I and type II errors for generalization without early stopping and with early stopping and the best one is proposed.

Keywords: control chart pattern recognition, neural network, backpropagation, generalization, early stopping

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Authors: V. Bezverbny

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The actuality of the project deals with stable growing of deviant behavior’ statistics among Moscow citizens. During the recent years the socioeconomic health, wealth and life expectation of Moscow residents is regularly growing up, but the limits of crime and drug addiction have grown up seriously. Another serious Moscow problem has been economical stratification of population. The cost of identical residential areas differs at 2.5 times. The project is aimed at complex research and the development of methodology for main factors and reasons evaluation of deviant behavior growing in Moscow. The main project objective is finding out the links between the urban environment quality and dynamics of citizens’ deviant behavior in regional and municipal aspect using the statistical research methods and GIS modeling. The conducted research allowed: 1) to evaluate the dynamics of deviant behavior in Moscow different administrative districts; 2) to describe the reasons of crime increasing, drugs addiction, alcoholism, suicides tendencies among the city population; 3) to develop the city districts classification based on the level of the crime rate; 4) to create the statistical database containing the main indicators of Moscow population deviant behavior in 2010-2015 including information regarding crime level, alcoholism, drug addiction, suicides; 5) to present statistical indicators that characterize the dynamics of Moscow population deviant behavior in condition of expanding the city territory; 6) to analyze the main sociological theories and factors of deviant behavior for concretization the deviation types; 7) to consider the main theoretical statements of the city sociology devoted to the reasons for deviant behavior in megalopolis conditions. To explore the level of deviant behavior’ factors differentiation, the questionnaire was worked out, and sociological survey involved more than 1000 people from different districts of the city was conducted. Sociological survey allowed to study the socio-economical and psychological factors of deviant behavior. It also included the Moscow residents’ open-ended answers regarding the most actual problems in their districts and reasons of wish to leave their place. The results of sociological survey lead to the conclusion that the main factors of deviant behavior in Moscow are high level of social inequality, large number of illegal migrants and bums, nearness of large transport hubs and stations on the territory, ineffective work of police, alcohol availability and drug accessibility, low level of psychological comfort for Moscow citizens, large number of building projects.

Keywords: deviant behavior, megapolis, Moscow, urban environment, social stratification

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Authors: Jialin Wu, Zhiwei Lian, Jieyu Tang, Jingyun Shen

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Tornado is a serious and unpredictable natural disaster, which has an important impact on people's production and life. The probability of being hit by tornadoes in China was analyzed considering the principles of tornado formation. Then some suggestions on layout and shapes for newly-built buildings were provided combined with the characteristics of tornado wind fields. Fuzzy clustering and inverse closeness methods were used to evaluate the probability levels of tornado risks in various provinces based on classification and ranking. GIS was adopted to display the results. Finally, wind field single-vortex tornado was studied to discuss the optimized design of rural low-rise houses in Yancheng, Jiangsu as an example. This paper may provide enough data to support building and urban design in some specific regions.

Keywords: tornado probability, computational fluid dynamics, fuzzy mathematics, optimal design

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Authors: K. Matušínská, Z. Bednarčík, M. Klepek

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This paper examines international marketing in business practice of Czech exporting small and medium-sized enterprises (SMEs) with regard to the strategic perspectives. Research was focused on Czech exporting SMEs from Moravian-Silesia region and their behaviour on international markets. For purpose of collecting data, a questionnaire was given to 262 SMEs involved in international business. Statistics utilized in this research included frequency, mean, percentage, and chi-square test. Data were analysed by Statistical Package for the Social Sciences software. The research analysis disclosed that there is certain space for improvement in strategic marketing especially in marketing research, perception of cultural and social differences, product adaptation and usage of marketing communication tools.

Keywords: international marketing, marketing mix, marketing research, small and medium-sized enterprises, strategic marketing

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Authors: Ali Nouri

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Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.

Keywords: neuroeducation studies, neuroeducational theory, theory building, neuroeducation research

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Authors: Afshin Jahangirzadeh, Shatirah Akib, Keyvan Kimiaei, Hossein Basser

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Coastal defense structures were built to protect part of shore from beach erosion and flooding by sea water. Effects of coastal defense structures can be negative or positive. Some of the effects are beneficial in socioeconomic aspect, but environment matters should be given more concerns because it can bring bad consequences to the earth landscape and make the ecosystem be unbalanced. This study concerns on the negative impacts as they are dominant. Coastal structures can extremely impact the shoreline configuration. Artificial structures can influence sediment transport, split the coastal space, etc. This can result in habitats loss and lead to noise and visual disturbance of birds. There are two types of coastal defense structures, hard coastal structure and soft coastal structure. Both coastal structures have their own impacts. The impacts are induced during the construction, maintaining, and operation of the structures.

Keywords: ecosystem, environmental impact, hard coastal structures, soft coastal structures

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Authors: Khaled Shaaban

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Schools and hospitals are supposed to be located in silent zones. In these areas, it is expected to maintain low noise levels in order to promote a peaceful environment for studying or recovering. However, many of these facilities are located in urban areas and are subject to high levels of noise. In this study, an evaluation of traffic noise around schools and hospitals was conducted during different periods of the day. The results indicated that the noise is positively correlated with the traffic volume around these facilities. Locations with higher traffic volumes tend to have higher noise levels. The results also showed that the noise levels exceed the recommended values by the World Health Organization. Several solutions were suggested as potential courses of action to decrease the excessive level of noise around these facilities.

Keywords: traffic noise, road traffic, noise levels, traffic volume

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Authors: Sachin Kumar

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Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy.

Keywords: fractional PDE, fuzzy valued function, diffusion equation, Legendre polynomial, spectral method

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Authors: Huang Yajing

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Context: Computer-aided language learning (CALL) in China has undergone significant development over the past few decades, with distinct stages marking its evolution. This paper aims to provide a comprehensive review of the practice and research in this field in China, tracing its journey from the early stages of audio-visual education to the current multimedia network integration stage. Research Aim: The study aims to analyze the historical progression of CALL in China, identify key developments in the field, and provide recommendations for enhancing CALL practices in the future. Methodology: The research employs document analysis and literature review to synthesize existing knowledge on CALL in China, drawing on a range of sources to construct a detailed overview of the evolution of CALL practices and research in the country. Findings: The review highlights the significant advancements in CALL in China, showcasing the transition from traditional audio-visual educational approaches to the current integrated multimedia network stage. The study identifies key milestones, technological advancements, and theoretical influences that have shaped CALL practices in China. Theoretical Importance: The evolution of CALL in China reflects not only technological progress but also shifts in educational paradigms and theories. The study underscores the significance of cognitive psychology as a theoretical underpinning for CALL practices, emphasizing the learner's active role in the learning process. Data Collection and Analysis Procedures: Data collection involved extensive review and analysis of documents and literature related to CALL in China. The analysis was carried out systematically to identify trends, developments, and challenges in the field. Questions Addressed: The study addresses the historical development of CALL in China, the impact of technological advancements on teaching practices, the role of cognitive psychology in shaping CALL methodologies, and the future outlook for CALL in the country. Conclusion: The review provides a comprehensive overview of the evolution of CALL in China, highlighting key stages of development and emerging trends. The study concludes by offering recommendations to further enhance CALL practices in the Chinese context.

Keywords: English education, educational technology, computer-aided language teaching, applied linguistics

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Pius W. Molo Chin

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Real life problems such as the Huxley equation are always modeled as nonlinear differential equations. These problems need accurate and reliable methods for their solutions. In this paper, we propose a nonstandard finite difference method in time and the Galerkin combined with the compactness method in the space variables. This coupled method, is used to analyze a two dimensional Huxley equation for the existence and uniqueness of the continuous solution of the problem in appropriate spaces to be defined. We proceed to design a numerical scheme consisting of the aforementioned method and show that the scheme is stable. We further show that the stable scheme converges with the rate which is optimal in both the L2 as well as the H1-norms. Furthermore, we show that the scheme replicates the decaying qualities of the exact solution. Numerical experiments are presented with the help of an example to justify the validity of the designed scheme.

Keywords: Huxley equations, non-standard finite difference method, Galerkin method, optimal rate of convergence

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Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

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Authors: Jamaludin Sallim, Rozlina Mohamed, Roslina Abdul Hamid

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In this paper, we proposed an Ant Colony Optimization (ACO) algorithm together with Traveling Salesman Problem (TSP) approach to investigate the clustering problem in Protein Interaction Networks (PIN). We named this combination as ACOPIN. The purpose of this work is two-fold. First, to test the efficacy of ACO in clustering PIN and second, to propose the simple generalization of the ACO algorithm that might allow its application in clustering proteins in PIN. We split this paper to three main sections. First, we describe the PIN and clustering proteins in PIN. Second, we discuss the steps involved in each phase of ACO algorithm. Finally, we present some results of the investigation with the clustering patterns.

Keywords: ant colony optimization algorithm, searching algorithm, protein functional module, protein interaction network

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Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

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In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

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Authors: Natalia Oli, Abhinav Vaidya, Katja Pahkala, Gabriele Eiben, Alexandra Krettek

Abstract:

The nutritional transition towards a high fat and energy dense diet, decreasing physical activity level, and poor cardiovascular health knowledge contributes to a rising burden of cardiovascular diseases in Nepal. Dietary and physical activity behaviors are formed early in life and influenced by family, particularly by mothers in the social context of Nepal. The purpose of this study was to explore knowledge, attitude and behavior of mothers regarding diet and physical activity of their pre-school children. Cross-sectional study was conducted in the semi-urban area of Duwakot and Jhaukhel communities near the capital Kathmandu. Between August and November 2014, nine trained enumerators interviewed all mothers having children aged 2 to 7 years in their homes. Questionnaire contained information about mothers’ socio-demographic characteristics; their knowledge, attitude, and behavior regarding diet and physical activity as well as their children’s diet and physical activity. Knowledge, attitude and behavior responses were scored. SPSS version 22.0 was used for data analyses. Out of the 1,052 eligible mothers, 962 consented to participate in the study. The mean age was 28.9 ± 4.5 years. The majority of them (73%) were housewives. Mothers with higher education and income had higher knowledge, attitude, and behavior scores (All p < 0.001) whereas housewives and farmers had low knowledge score (p < 0.001). They, along with laborers, also exhibited lower attitude (p<0.001) and behavior scores (p < 0.001). Children’s diet score increased with mothers’ level of education (p <0.001) and income (p=0.041). Their physical activity score, however, declined with increasing level of their mothers’ education (p < 0.001) and income (p < 0.001). Children’s overall behavior score correlated poorly with mothers’ knowledge (r = 0.009, p=0.003), attitude (r =0.012, p=0.001), and behavior (r = 0.007, p= 0.008). Such poor correlation can be due to existence of the barriers among mothers. Mothers reported such barriers as expensive healthy food, difficulty to give up favorite food, taste preference of others family members and lack of knowledge on healthy food. Barriers for physical activity were lack of leisure time, lack of parks and playgrounds, being busy by caring for children and old people, feeling lazy and embarrassed in front of others. Additionally, among the facilitators for healthy lifestyle, mentioned by mothers, were better information, family eating healthy food and supporting physical activity, advice of medical personnel regarding healthy lifestyle and own ill health. The study demonstrated poor correlation of mothers’ knowledge and attitude with children’s behavior regarding diet and physical activity. Hence improving mothers’ knowledge or attitude may not be enough to improve dietary and physical activity habits of their children. Barriers and facilitators that affect mothers’ practices towards their children should also be addressed due to future intervention.

Keywords: attitude, behavior, diet, knowledge, mothers, physical activity

Procedia PDF Downloads 293

Authors: Jonathon Smith, Alba Agostino

Abstract:

Autism, also referred to as autism spectrum disorder (ASD), is commonly associated with difficulties in social and communication skills. Other characteristics common to autistic individuals include repetitive behaviours, difficulties adhering to routine, as well as paying attention. Recent findings indicate that autism is the fastest-growing neurodevelopmental disorder in North America, yet programming aimed at improving the quality of autistic individual’s real-world social interactions is limited. Although there are social skills programs for autistic youth, participation appears to improve social knowledge, but that knowledge does not improve social competence or transfer to the participant’s daily social interactions. Peers are less likely to interact with autistic people based thin slice judgements, meaning that even when an autistic youth has successfully completed a social skills program, they most likely will still be rejected by peers and not have a social group to participate in. Recently, many researchers are exploring therapeutic interventions using Dungeon and Dragons (D&D) for conditions such as social anxiety, loneliness, and identity exploration. D&D is a table-top role-playing game (TTRPG) based on social play experience where the players must communicate, plan, negotiate, and compromise with other players to achieve a shared goal. The game encourages players to assume the role of their character and act out their play within the rules of the game with the guidance of the games dungeon master. The popularity Dungeons and Dragons has increased at a rapid rate, and many suggest that there social-emotional benefits of joining and participating in these types of gaming experiences, however this is an under researched topic and studies examining the benefits of such games is lacking in the field. The main purpose of this exploratory study is to examine the autistic youth’s experiences of participating in a D&D club. Participants of this study were four high functioning autistic youth between the ages of 14-18 (average age – 16) enrolled in a D&D Club that was specifically designed for neurodiverse youth. The youth participation with the club ranged from 4 months to 8 months. All participants completed a 30–40-minute semi-structured interview where they were able to express their perceptions as participants of the D&D club. Preliminary findings suggest that the game provided a place for the youth to engage in authentic social interactions. Additionally, preliminary results suggest that the youth report being in a positive space with other neurodivergent youth created an atmosphere where they felt confident and could connect with others. The findings from this study will aid clinicians, researchers, and educators in developing programming aimed at improving social interactions and connections for autistic youth.

Keywords: autism, social connection, dungeons and dragons, neurodivergent affirming space

Procedia PDF Downloads 33