Search results for: urban data model

Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Pruthvi Nath Palleti, Sarmada Madhulika Kone

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Communities are formed based on the commonalities that exist in a set of individuals and when the group comes together on identifying those commonalities and to achieve their common goals. Thus, community planning with its vision to strengthen the community mostly involves with making or remaking of commons, which results in making or remaking of communities. This paper looks into different practices of planning around the world and tried to establish a link between commoning (the act of exercising the rights over commons by commoners) and participatory approach to community planning.

Keywords: commoners, commoning, community, participatory planning, urban local bodies

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Authors: Xiaohan Gao, Kai Liu

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As essential components of urban areas, primary and secondary schools are extensively distributed throughout various regions of the city. During times of urban disturbances, these schools become direct carriers of complex disruptions. Therefore, fostering resilient schools becomes a pivotal driving force to promote high-quality urban development and a cornerstone of sustainable school growth. This paper adopts the theory of spatial resilience and focuses on primary and secondary schools in Chinese cities as the research subject. The study first explores the potential disturbance risks faced by schools and delves into the origin and concept of spatial resilience in the educational context. Subsequently, the paper conducts a meta-analysis to characterize the spatial resilience of primary and secondary schools and devises a spatial resilience planning mechanism. Drawing insights from exemplary cases both domestically and internationally, the research formulates spatial and planning resilience strategies for primary and secondary schools to cope with perturbations. These strategies encompass creating an overall layout that integrates harmoniously with nature, promoting organic growth in the planning structure, fostering ecological balance in the landscape system, and enabling dynamic adaptation in architectural spaces. By cultivating the capacity for "resistance-adaptation-transformation," these approaches support sustainable development within the school space. The ultimate goal of this project is to establish a cohesive and harmonious layout that advances the sustainable development of primary and secondary schools while contributing to the overall resilience of urban areas.

Keywords: complex disruption, primary and secondary schools, spatial resilience, sustainable development

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Authors: Taner Izzet Acarer, Ece Ceylan Baba

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This paper examines green building certification systems and their current processes in comparison with anticipatory systems. Rapid growth of human population and depletion of natural resources are causing irreparable damage to urban and natural environment. In this context, the concept of ‘sustainable architecture’ has emerged in the 20th century so as to establish and maintain standards for livable urban spaces, to improve quality of urban life, and to preserve natural resources for future generations. The construction industry is responsible for a large part of the resource consumption and it is believed that the ‘green building’ designs that emerge in construction industry can reduce environmental problems and contribute to sustainable development around the world. A building must meet a specific set of criteria, set forth through various certification systems, in order to be eligible for designation as a green building. It is disputable whether methods used by green building certification systems today truly serve the purposes of creating a sustainable world. Accordingly, this study will investigate the sets of rating systems used by the most popular green building certification programs, including LEED (Leadership in Energy and Environmental Design), BREEAM (Building Research Establishment's Environmental Assessment Methods), DGNB (Deutsche Gesellschaft für Nachhaltiges Bauen System), in terms of ‘Anticipatory Systems’ in accordance with the certification processes and their goals, while discussing their contribution to architecture. The basic methodology of the study is as follows. Firstly analyzes of brief historical and literature review of green buildings and certificate systems will be stated. Secondly, processes of green building certificate systems will be disputed by the help of anticipatory systems. Anticipatory Systems is a set of systems designed to generate action-oriented projections and to forecast potential side effects using the most current data. Anticipatory Systems pull the future into the present and take action based on future predictions. Although they do not have a claim to see into the future, they can provide foresight data. When shaping the foresight data, Anticipatory Systems use feedforward instead of feedback, enabling them to forecast the system’s behavior and potential side effects by establishing a correlation between the system’s present/past behavior and projected results. This study indicates the goals and current status of LEED, BREEAM and DGNB rating systems that created by using the feedback technique will be examined and presented in a chart. In addition, by examining these rating systems with the anticipatory system that using the feedforward method, the negative influences of the potential side effects on the purpose and current status of the rating systems will be shown in another chart. By comparing the two obtained data, the findings will be shown that rating systems are used for different goals than the purposes they are aiming for. In conclusion, the side effects of green building certification systems will be stated by using anticipatory system models.

Keywords: anticipatory systems, BREEAM, certificate systems, DGNB, green buildings, LEED

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Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

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Authors: Karima Megdouli, Bourhan tachtouch

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Ejector refrigeration cycles offer an alternative to conventional systems for producing cold from low-temperature heat. In this article, a thermodynamic model is presented. This model has the advantage of simplifying the calculation algorithm and describes the complex double-throttling mechanism that occurs in the ejector. The model assumption and calculation algorithm are presented first. The impact of each efficiency is evaluated. Validation is performed on several data sets. The ejector model is then used to simulate a RES (refrigeration ejector system), to validate its robustness and suitability for use in predicting thermodynamic cycle performance. A Taguchi and ANOVA optimization is carried out on a RES. TOPSIS analysis was applied to decide the optimum refrigerants with cost, safety, environmental and enviro economic concerns along with thermophysical properties.

Keywords: ejector, velocity distribution, shock circle, Taguchi and ANOVA optimization, TOPSIS analysis

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Authors: Samvel H. Sargsyan

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Together with the study of electron-optical properties of nanostructures and proceeding from experiment-based data, the study of the mechanical properties of nanostructures has become quite actual. For the study of the mechanical properties of fullerene, carbon nanotubes, graphene and other nanostructures one of the crucial issues is the construction of their adequate mathematical models. Among all mathematical models of graphene or carbon nano-tubes, this so-called discrete-continuous model is specifically important. It substitutes the interactions between atoms by elastic beams or springs. The present paper demonstrates the construction of the discrete-continual beam model for carbon nanotubes or graphene, where the micropolar beam model based on the theory of moment elasticity is accepted. With the account of the energy balance principle, the elastic moment constants for the beam model, expressed by the physical and geometrical parameters of carbon nanotube or graphene, are determined. By switching from discrete-continual beam model to the continual, the models of micropolar elastic cylindrical shell and micropolar elastic plate are confirmed as continual models for carbon nanotube and graphene respectively.

Keywords: carbon nanotube, discrete-continual, elastic, graphene, micropolar, plate, shell

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Authors: Medjadj Tarek, Ghribi Hayet

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This study aims to develop a flood sensitivity assessment tool using machine learning (ML) techniques and geographic information system (GIS). The importance of this study is integrating the geographic information systems (GIS) and machine learning (ML) techniques for mapping flood risks, which help decision-makers to identify the most vulnerable areas and take the necessary precautions to face this type of natural disaster. To reach this goal, we will study the case of the city of M'sila, which is among the areas most vulnerable to floods. This study drew a map of flood-prone areas based on the methodology where we have made a comparison between 3 machine learning algorithms: the xGboost model, the Random Forest algorithm and the K Nearest Neighbour algorithm. Each of them gave an accuracy respectively of 97.92 - 95 - 93.75. In the process of mapping flood-prone areas, the first model was relied upon, which gave the greatest accuracy (xGboost).

Keywords: Geographic information systems (GIS), machine learning (ML), emergency mapping, flood disaster management

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Authors: D. S. C. Soares, D. G. Costa, J. T. S., A. K. S. Abud, T. P. Nunes, A. M. Oliveira Júnior

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Mathematical models of drying are used for the purpose of understanding the drying process in order to determine important parameters for design and operation of the dryer. The jackfruit is a fruit with high consumption in the Northeast and perishability. It is necessary to apply techniques to improve their conservation for longer in order to diffuse it by regions with low consumption. This study aimed to analyse several mathematical models (Page, Lewis, and Midilli) to indicate one that best fits the conditions of convective drying process using performance indicators associated with each model: accuracy (Af) and noise factors (Bf), mean square error (RMSE) and standard error of prediction (% SEP). Jackfruit drying was carried out in convective type tray dryer at a temperature of 50°C for 9 hours. It is observed that the model Midili was more accurate with Af: 1.39, Bf: 1.33, RMSE: 0.01%, and SEP: 5.34. However, the use of the Model Midilli is not appropriate for purposes of control process due to need four tuning parameters. With the performance indicators used in this paper, the Page model showed similar results with only two parameters. It is concluded that the best correlation between the experimental and estimated data is given by the Page’s model.

Keywords: drying, models, jackfruit, biotechnology

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Authors: Mohammad Amjad, Muhammad Iqbal Zafar, Ashfaq Ahmed Maan, Muhammad Tayyab Kashif

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Obesity is an abnormal physical condition where an increased and undesirable fat accumulates in the human body. Obesity is an international phenomenon. In the present study, 12 schools were randomly selected from each district considering the areas i.e. Elite Private Schools in the private sector, Government schools in urban areas and Government schools in rural areas. Interviews were conducted with male students studying in grade 5 to grade 9 in each school. The sample size was 600 students; 300 from Faisalabad district and 300 from Rawalpindi district in Pakistan. A well-structured and pre-tested questionnaire was used for data collection. The calibrated scales were used to attain the heights and weights of the respondents. Obesity of school-going children depends on family types, family size, family history, junk food consumption, mother’s education, weekly time spent in walking, and sports facility at school levels. Academic performance, physical health and psychological health of school going children are affected with obesity. Concrete steps and policies could minimize the incidence of obesity in children in Pakistan.

Keywords: body mass index, cardiovascular disease, fast food, morbidity, overweight

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Authors: D. Thawinkarn, S. Wongbutlee

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The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: Ahmad Javid Habib, Tetsuo Kidokoro

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There is an increasing demand for developing urban land to provide better living conditions for all citizens in Afghanistan. Most of the development will involve the acquisition of land. And the current land acquisition method practiced by central government is expropriation, which is a cash-based transaction method that imposes heavy fiscal burden on local municipalities and central government, and it does not protect ownership rights and social equity of landowners besides it relocates the urban poor to remote areas with limited access to jobs and public services. The questionnaire analysis, backed by observations of different case studies in countries where land readjustment is used as a collaborative land development tool indicates that the method plays a key role in valuing landowners’ rights, giving other community members and stakeholders the opportunity to collaboratively implement urban development projects. The practice of the method is reducing the heavy fiscal burden on the local and central governments and is a better option to deal with the current development challenges in Afghanistan.

Keywords: collaboration, land readjustment, master plan, expropriation

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Luana Parisi, Sohrab Donyavi

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Cities have become the nodes of global networks, standing at the intersection points of the flows of capital, goods, workers, businesses and travellers, making them the spots where innovation, progress and economic development occur. The primary challenge for them is to create the most fertile ecosystems for triggering innovation activities. Design emerges as an essential feature in this process of laboratorisation of cities. This paper aims at exploring the spatial hubs of transformation within the knowledge economy, providing an overview of the current models of innovation spaces, before focusing on the innovation district of one of the cities that are riding the innovation wave, namely, Boston, USA. Useful lessons will be drawn from the case study of the innovation district in Boston, allowing to define precious tools for policymakers, in the form of a range of factors that define the broad strategy able to implement the model successfully. A mixed methodology is implemented, including information from observations, exploratory interviews to key stakeholders and on-desk data.

Keywords: Innovation District, innovation ecosystem, economic development, urban regeneration

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Authors: Ikenna Stephen Ezennia, Sebnem Onal Hoscara

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Successive governments in Nigeria are faced with the pressing problem of how to house an ever-expanding urban population, usually low-income earners. The question of housing and affordability presents a complex challenge for these governments, as the commodification of housing links it inextricably to markets and capital flows. Therefore, placing it as at the center of the government’s agenda. However, the provision of decent and affordable housing for average Nigerians has remained an illusion, despite copious schemes, policies and programs initiated and carried out by various successive governments. Similarly, this phenomenon has also been observed in many countries of Africa, which is largely a result of economic unpredictability, lack of housing finance and insecurity, among other factors peculiar to a struggling economy. This study reviews recent dynamics and factors challenging the provision and development of affordable housing for the low income urban populace of Nigeria. Thus, the aim of the study is to present a comprehensive approach for understanding recent trends in the provision of affordable housing for Nigerians. The approach is based on a new paradigm of research: transdisciplinarity; a form of inquiry that crosses the boundaries of different disciplines. Therefore, the review takes a retrospective gaze at the various housing development programs/schemes/policies taken by successive governments of Nigeria within the last few decades and exams recent efforts geared towards eradicating the problems of housing delivery. Sources of data included relevant English language articles and the results of literature search of Elsevier Science Direct, ISI Web of Knowledge, Pro Quest Central, Scopus, and Google Scholar. The findings reveal that factors such as; rapid urbanization, inadequate planning and land use control, lack of adequate and favorable finance, high prices of land, high prices of building material, youth/touts harassment of developers, poor urban infrastructure, multiple taxation, and risk share are the major factors posing as a hindrance to adequate housing delivery. The results show that the majority of Nigeria’s affordable housing schemes, programs and policies are in most cases poorly implemented and abandoned without proper coordination. Consequently, the study concludes that the affordable housing delivery strategies in Nigeria are an epitome of lip service politics by successive governments; and the current trend of leaving housing provision to the vagaries of market forces cannot be expected to support affordable housing especially for the low income urban populace.

Keywords: affordable housing, housing delivery, national housing policy, urban poor

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Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

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Authors: Lela Gadrani, Mariam Tsitsagi

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Human is a part of the urban landscape and responsible for it. Urbanization of cities includes the longest phase; thus none of the environment ever undergoes such anthropogenic impact as the area of large cities. The post-Soviet period is very interesting in terms of scientific research. The changes that have occurred in the cities since the collapse of the Soviet Union have not yet been analyzed best to our knowledge. In this context, the aim of this paper is to analyze the changes in the land use of the three large cities of Georgia (Tbilisi, Kutaisi, Batumi). Tbilisi as a capital city, Batumi as a port city, and Kutaisi as a former industrial center. Data used during the research process are conventionally divided into satellite and supporting materials. For this purpose, the largest topographic maps (1:10 000) of all three cities were analyzed, Tbilisi General Plans (1896, 1924), Tbilisi and Kutaisi historical maps. The main emphasis was placed on the classification of Landsat images. In this case, we have classified the images LULC (LandUse / LandCover) of all three cities taken in 1987 and 2016 using the supervised and unsupervised methods. All the procedures were performed in the programs: Arc GIS 10.3.1 and ENVI 5.0. In each classification we have singled out the following classes: built-up area, water bodies, agricultural lands, green cover and bare soil, and calculated the areas occupied by them. In order to check the validity of the obtained results, additionally we used the higher resolution images of CORONA and Sentinel. Ultimately we identified the changes that took place in the land use in the post-Soviet period in the above cities. According to the results, a large wave of changes touched Tbilisi and Batumi, though in different periods. It turned out that in the case of Tbilisi, the area of developed territory has increased by 13.9% compared to the 1987 data, which is certainly happening at the expense of agricultural land and green cover, in particular, the area of agricultural lands has decreased by 4.97%; and the green cover by 5.67%. It should be noted that Batumi has obviously overtaken the country's capital in terms of development. With the unaided eye it is clear that in comparison with other regions of Georgia, everything is different in Batumi. In fact, Batumi is an unofficial summer capital of Georgia. Undoubtedly, Batumi’s development is very important both in economic and social terms. However, there is a danger that in the uneven conditions of urban development, we will eventually get a developed center - Batumi, and multiple underdeveloped peripheries around it. Analysis of the changes in the land use is of utmost importance not only for quantitative evaluation of the changes already implemented, but for future modeling and prognosis of urban development. Raster data containing the classes of land use is an integral part of the city's prognostic models.

Keywords: analysis, geo information system, remote sensing, LULC

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Authors: Hoda A. Abdel Hafez

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Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: mining big data, big data, machine learning, telecommunication

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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The adsorptive ability of different carbon materials, tire char (TC), demineralized tire char (DTC), activated tire char (ATC) and Aldrich supplied commercial activated carbon (CAC) was studied for desulfurization of tire pyrolytic oil (TPO). TPO with an initial sulfur content of 7767.7 ppmw was used in this present study. Preparation of ATC was achieved by chemical treatment of raw TC using a potassium hydroxide (KOH) solution and subsequent activation at 800°C in the presence of nitrogen. The thermal behavior of TC, surface microstructure, and the surface functional groups of the carbon materials was investigated using TGA, SEM, and FTIR, respectively. Adsorptive desulfurization of TPO using the carbon materials was performed and they performed in the order of CAC>ATC>DTC>TC. Adsorption kinetics were studied, and pseudo-first order kinetic model displayed a better fit compared to pseudo-second order model. For isotherm studies, the Freundlich isotherm model fitted to the equilibrium data better than the Langmuir isotherm model.

Keywords: ATC, desulfurization, pyrolysis, tire, TPO

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Authors: Kanchan Negi

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Background: Modern and urban occupational culture have driven demands for people to work long hours and weekends and take work to home at times. Research on the health effects of these exhaustive temporal work patterns is scant or contradictory. This study examines the relationship between work patterns and wellbeing in a sample of women living in the metropolitan hub of Delhi. Method: This study is based on the data collected from 360 currently married women between age 29 and 49 years, working in the urban capital hub of India, i.e., Delhi. The women interviewed were professionals from the education, health, banking and information and technology (IT) sector. Bivariate analysis was done to study the characteristics of the sample. Logistic regression analysis was used to estimate the physical and psychological wellbeing across occupational characteristics. Results: Most of the working women were below age 35 years; around 30% of women worked in the education sector, 23% in health, 21% in banking and 26% in the IT sector. Over 55% of women were employed in the private sector and only 36% were permanent employees. Nearly 30% of women worked for more than the standard 8 hours a day. The findings from logistic regression showed that compared to women working in the education sector, those who worked in the banking and IT sector more likely to have physical and psychological health issues (OR 2.07-4.37, CI 1.17-4.37); women who bear dual burden of responsibilities had higher odds of physical and psychological health issues than women who did not (OR 1.19-1.85 CI 0.96-2.92). Women who worked for more than 8 hours a day (OR 1.15, CI 1.01-1.30) and those who worked for more than five days a week (OR 1.25, CI 1.05-1.35) were more likely to have physical health issues than women who worked for 6-8 hours a day and five days e week, respectively. Also, not having flexible work timings and compensatory holidays increased the odds of having physical and psychological health issues among working women (OR 1.17-1.29, CI 1.01-1.47). Women who worked in the private sector, those employed temporarily and who worked in the non-conducive environments were more likely to have psychological health issues as compared to women in the public sector, permanent employees and those who worked in a conducive environment, respectively (OR 1.33-1.67, CI 1.09-2.91). Women who did not have poor work-life balance had reduced the odds of psychological health issues than women with poor work-life balance (OR 0.46, CI 0.25-0.84). Conclusion: Poor wellbeing significantly linked to strenuous and rigid work patterns, suggesting that modern and urban work culture may contribute to the poor wellbeing of working women. Noticing the recent decline in female workforce participation in Delhi, schemes like Flexi-timings, compensatory holidays, work-from-home and daycare facilities for young ones must be welcomed; these policies already exist in some private sector firms, and the public sectors companies should also adopt such changes to ease the dual burden as homemaker and career maker. This could encourage women in the urban areas to readily take up the jobs with less juggle to manage home and work.

Keywords: occupational characteristics, urban India, well-being, working women

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Ilhem Ouelhazi, Mouna Elakhdar, Lakdar Kairouani

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A computer simulation model for a combined ejector-vapor compression cycle that uses working fluid R134a. A refrigeration system was developed which combines a basic vapor compression refrigeration cycle with an ejector cooling cycle. A one-dimensional mathematical model was developed using the equations governing the flow and thermodynamics based on the constant area ejector flow model. The effects of the operating parameters on the cooling capacity, the performance coefficient, and the entrainment ratio are studied. The current model is based on the NIST-REFPROP database for refrigerants properties calculations. The simulated performance is compared with the available experimental data from the literature for validation.

Keywords: combined refrigeration cycle, constant area ejector, R134a, ejector-cooling cycle, performance, mathematical simulation, vapor compression cycle

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Authors: A. Lakrim, D. Tahri

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This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

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Authors: N. Reppas, Y. L. Gui, B. Wetenhall, C. T. Davie, J. Ma

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A theoretical constitutive model describing the stress-strain behavior of rock subjected to different confining pressures is presented. A bounding surface plastic model with hardening effects is proposed which includes the effect of temperature drop. The bounding surface is based on a mapping rule and the temperature effect on rock is controlled by Poisson’s ratio. Validation of the results against available experimental data is also presented. The relation of deviatoric stress and axial strain is illustrated at different temperatures to analyze the effect of temperature decrease in terms of stiffness of the material.

Keywords: bounding surface, cooling of rock, plasticity model, rock deformation, elasto-plastic behavior

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Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib

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Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.

Keywords: climate change, pulses productivity, agriculture, Pakistan

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Authors: Mousumi Khandual, Amitt Chatterjee

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In order to validate the dimensions of Crime Prevention Through Environmental Design (CPTED) and the corresponding indicators, this study investigates the contribution of CPTED to the reduction of crime in Khandagiri, Bhubaneswar. Four primary dimensions are the focus of the research: territoriality, natural surveillance, access control, and exterior maintenance. A scale was developed to access the CPTED construct, administered through on-site observation, expert opinions, and resident surveys involving 151 respondents from a typical residential area of Khandagiri, Bhubaneswar. Confirmatory Factor Analysis (CFA) using AMOS has been used to validate the dimensions and indicators, with the analysis testing both first-order and second-order models. The study highlights key factors contributing to the measurement of the CPTED construct, offering valuable insights for urban planners and policymakers. The findings showed that territoriality, access control, and external maintenance produced an index of a good fit, with the RMSEA value being less than 0.06 and the values of GFI, CFI, and TLI exceeding 0.90.

Keywords: crime prevention, CFA, urban safety, environmental design, built environment, crime

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Authors: Marcela Dávalos López

Abstract:

In Mexico, the distribution of hygienistarchitecture during the 20th century had different rhythms. The culmination of the urban hygiene system (from sewers to showers, passing through garbage collection) forced neighbors and citizens to participate in the common welfare. This turned the urban references and dissociated the ways of living and led to comfort and health. However, the contrast between two Mexicancities, Cuernavaca and Mexico City shows us very different cultural practices regarding the use of hygienicarchitectures: in the first, thenature of its deepravines marked the destiny of residential architecture, while in Mexico City, state participation alteredthelandscape and homogenized the architectural models of domestic and intímate spaces.

Keywords: Cultural Practices, Dissociated Ways To Comfort, Hygiene Architecture , Mexico

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

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Authors: Zhao Liu, Kang Cao

Abstract:

Strategic spatial planning, which is taken as an effective and competitive way for the governors of the city to improve the development and management level of a city, has been blooming in recent years all over the world. In the context of globalization and informatization, strategic spatial planning must transfer its focus on three different levels: global, regional and urban. Internal and external changes in environmental conditions lead to new advances in strategic planning both theoretically and practically. However, such advances or changes respond differently to cities on account of different dynamic mechanisms. This article aims at two cities of Tianjin in China and Melbourne in Australia, through a comparative study on strategic planning, to explore the differentiation of mechanisms in urban planning. By comparison and exploration, the purpose of this article is to exhibit two different planning worlds, western and Chinese, in a new way. The article can be divided into four parts. The first part outlines strategic planning transformations in the new era on three levels, generally analysing the internal and external environmental factors of today. The second part indicates the concepts of strategic planning theoretically, demonstrating briefly its development background and process in western and China, respectively. The third part takes Tianjin and Melbourne urban strategic spatial planning as examples to mainly carry on the contrast research from the aspects of strategic planning mode, competitive mechanism, contents, strategy implementation and management. It is expected to summarize the differences and similarities of the two plans, meanwhile, to explore the inherent factors or mechanisms probably spatial, material, political and etc., which affect cities in the course of urban planning. The final part is a summary of general mechanisms of planning from the perspective of strategic spatial planning.

Keywords: differentiation, strategic planning, Melbourne, Australia, Tianjin, China

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

Abstract:

The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

Procedia PDF Downloads 183