Search results for: weather

Authors: Timma Reddy, Srikonda Ramesh

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India has been traditionally vulnerable to natural disasters such as Floods, droughts, cyclones, earthquakes and landslides. It has become a recurrent phenomenon as observed in last five decades. The survey indicates that about 60% of the landmass is prone to earthquakes of various intensities; over 40 million hectares is prone to floods; about 8% of the total area is prone to cyclones and 68% of the area is susceptible to drought. Climate change is likely to be perceived through experience of extreme weather events. There is growing societal concern about climate change, given the potential impacts of associated natural hazards such as cyclones, flooding, earthquakes, landslides etc, hence it is essential and crucial to strengthening our settlements to respond to such calamities. So, the research paper focus is to analyze the effective planning strategy/mechanism to integrate disaster mitigation measures in coastal regions in general and Capital Region of Andhra Pradesh in particular. The basic hypothesis is to govern the appropriate special planning considerations would facilitate to have organized way of protective life and properties from natural disasters. And further to integrate the infrastructure planning with conscious direction would provide an effective mitigations measures. It has been planned and analyzed to Vijayawada city with conscious land use planning with reference to space syntax trajectory in accordance to required social infrastructure such as health facilities, institution areas and recreational and other open spaces. It has been identified that the geographically ideal location with reference to the population densities based on GIS tools the properness strategies can be effectively integrated to protect the life and to save the properties by means of reducing the damage/impact of natural disasters in general earth quake/cyclones or floods in particularly.

Keywords: modular, trajectories, social infrastructure, evidence based syntax, drills and equipments, GIS, geographical micro zoning, high resolution satellite image

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Authors: Khadija Refouh

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Culture bound-expressions have been a bottleneck for Natural Language Processing (NLP) and comprehension, especially in the case of machine translation (MT). In the last decade, the field of machine translation has greatly advanced. Neural machine translation NMT has recently achieved considerable development in the quality of translation that outperformed previous traditional translation systems in many language pairs. Neural machine translation NMT is an Artificial Intelligence AI and deep neural networks applied to language processing. Despite this development, there remain some serious challenges that face neural machine translation NMT when translating culture bounded-expressions, especially for low resources language pairs such as Arabic-English and Arabic-French, which is not the case with well-established language pairs such as English-French. Machine translation of opaque idioms from English into French are likely to be more accurate than translating them from English into Arabic. For example, Google Translate Application translated the sentence “What a bad weather! It runs cats and dogs.” to “يا له من طقس سيء! تمطر القطط والكلاب” into the target language Arabic which is an inaccurate literal translation. The translation of the same sentence into the target language French was “Quel mauvais temps! Il pleut des cordes.” where Google Translate Application used the accurate French corresponding idioms. This paper aims to perform NMT experiments towards better translation of opaque idioms using high quality clean multilingual corpus. This Corpus will be collected analytically from human generated idiom translation. AutoML translation, a Google Neural Machine Translation Platform, is used as a custom translation model to improve the translation of opaque idioms. The automatic evaluation of the custom model will be compared to the Google NMT using Bilingual Evaluation Understudy Score BLEU. BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Human evaluation is integrated to test the reliability of the Blue Score. The researcher will examine syntactical, lexical, and semantic features using Halliday's functional theory.

Keywords: multilingual corpora, natural language processing (NLP), neural machine translation (NMT), opaque idioms

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Authors: Firouz Amani, Adalat Hoseinian, Sajjad Hakimian

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Background: The mortality due to Myocardial Infarction (MI) is often occur during the first hours after onset of symptom. So, for taking the necessary treatment and decreasing the mortality rate, timely visited of the hospital could be effective in this regard. The aim of this study was to investigate the impact of effective factors in mortality of MI patients by using Linear Logistic Regression. Materials and Methods: In this case-control study, all patients with Acute MI who referred to the Ardabil city hospital were studied. All of died patients were considered as the case group (n=27) and we select 27 matched patients without Acute MI as a control group. Data collected for all patients in two groups by a same checklist and then analyzed by SPSS version 24 software using statistical methods. We used the linear logistic regression model to determine the effective factors on mortality of MI patients. Results: The mean age of patients in case group was significantly higher than control group (75.1±11.7 vs. 63.1±11.6, p=0.001).The history of non-cardinal diseases in case group with 44.4% significantly higher than control group with 7.4% (p=0.002).The number of performed PCIs in case group with 40.7% significantly lower than control group with 74.1% (P=0.013). The time distance between hospital admission and performed PCI in case group with 110.9 min was significantly upper than control group with 56 min (P=0.001). The mean of delay time from Onset of symptom to hospital admission (patient delay) and the mean of delay time from hospital admissions to receive treatment (system delay) was similar between two groups. By using logistic regression model we revealed that history of non-cardinal diseases (OR=283) and the number of performed PCIs (OR=24.5) had significant impact on mortality of MI patients in compare to other factors. Conclusion: Results of this study showed that of all studied factors, the number of performed PCIs, history of non-cardinal illness and the interval between onset of symptoms and performed PCI have significant relation with morality of MI patients and other factors were not meaningful. So, doing more studies with a large sample and investigated other involved factors such as smoking, weather and etc. is recommended in future.

Keywords: acute MI, mortality, heart failure, arrhythmia

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Authors: Constanza Monterrubio-Solis, Jose Tomas Ibarra

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The fertile interdependence of social-ecological systems reveals itself in the interactions between native forests and seeds, home gardens, kitchens, foraging activities, local knowledge, and food practices, creating particular flavors and food meanings as part of cultural identities within territories. Resilience in local-food systems, from a relational perspective, can be understood as the balance between persistence and adaptability to change. Food growing, preparation, and consumption are constantly changing and adapting as expressions of agency of female and male indigenous peoples and peasants. This paper explores local food systems’ expressions of resilience in the la Araucanía region of Chile, namely: diversity, redundancy, buffer capacity, modularity, self-organization, governance, learning, equity, and decision-making. Applying ethnographic research methods (participant observation, focus groups, and semi-structured interviews), this work reflects on the experience developed through work with Mapuche women cultivating home gardens in the region since 2012; it looks to material and symbolic elements of resilience in the local indigenous food systems. Local food systems show indeed indicators of social-ecological resilience. The biocultural memory is expressed in affection to particular flavors and recipes, the cultural importance of seeds and reciprocity networks, as well as an accurate knowledge about the indicators of the seasons and weather, which have allowed local food systems to thrive with a strong cultural foundation. Furthermore, these elements turn into biocultural resistance in the face of the current institutional pressures for rural specialization, processes of cultural assimilation such as agroecosystems and diet homogenization, as well as structural threats towards the diversity and freedom of native seeds. Thus, the resilience-resistance dynamic shown by the social-ecological systems of the southern Andes is daily expressed in the local food systems and flavors and is key for diverse and culturally sound social-ecological health.

Keywords: biocultural heritage, indigenous food systems, social-ecological resilience, southern Andes

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Authors: Saeed Farhadypour, Majid Azadi, Habibolla Sayyari, Mahmood Mosavi, Shahram Irani, Aliakbar Bidokhti, Omid Alizadeh Choobari, Ziba Hamidi

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In the recent decades, frequencies of dust events have increased significantly in west and south west of Iran. First, a survey on the dust events during the period (1990-2013) is investigated using historical dust data collected at 6 weather stations scattered over west and south-west of Iran. After statistical analysis of the observational data, one of the most severe dust storm event that occurred in the region from 3rd to 6th July 2009, is selected and analyzed. WRF-Chem model is used to simulate the amount of PM10 and how to transport it to the areas. The initial and lateral boundary conditions for model obtained from GFS data with 0.5°×0.5° spatial resolution. In the simulation, two aerosol schemas (GOCART and MADE/SORGAM) with 3 options (chem_opt=106,300 and 303) were evaluated. Results of the statistical analysis of the historical data showed that south west of Iran has high frequency of dust events, so that Bushehr station has the highest frequency between stations and Urmia station has the lowest frequency. Also in the period of 1990 to 2013, the years 2009 and 1998 with the amounts of 3221 and 100 respectively had the highest and lowest dust events and according to the monthly variation, June and July had the highest frequency of dust events and December had the lowest frequency. Besides, model results showed that the MADE / SORGAM scheme has predicted values and trends of PM10 better than the other schemes and has showed the better performance in comparison with the observations. Finally, distribution of PM10 and the wind surface maps obtained from numerical modeling showed that the formation of dust plums formed in Iraq and Syria and also transportation of them to the West and Southwest of Iran. In addition, comparing the MODIS satellite image acquired on 4th July 2009 with model output at the same time showed the good ability of WRF-Chem in simulating spatial distribution of dust.

Keywords: dust storm, MADE/SORGAM scheme, PM10, WRF-Chem

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Authors: Andrea Gion Saluz, Tal Hertig, Axel Heinrich, Stefan Stevanovic

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Higher temperatures, seasonal changes in precipitation, and extreme weather events are increasingly affecting trees. To counteract the increasing challenges of urban trees, strategies are increasingly being sought to preserve existing tree populations on the one hand and to prepare for the coming years on the other. One such strategy lies in strategic climate tree species selection. The search is on for species or varieties that can cope with the new climatic conditions. Many efforts in German-speaking countries deal with this in detail, such as the tree lists of the German Conference of Garden Authorities (GALK), the project Stadtgrün 2021, or the instruments of the Climate Species Matrix by Prof. Dr. Roloff. In this context, different methods for a correct species selection are offered. One possibility is to select certain physiological attributes that indicate the climate resilience of a species. To calculate the dissimilarity of the present climate of different geographic regions in relation to the future climate of any city, a weighted (standardized) Euclidean distance (SED) for seasonal climate values is calculated for each region of the Earth. The calculation was performed in the QGIS geographic information system, using global raster datasets on monthly climate values in the 1981-2010 standard period. Data from a European forest inventory were used to identify tree species growing in the calculated analogue climate regions. The inventory used is the compilation of georeferenced point data at a 1 km grid resolution on the occurrence of tree species in 21 European countries. In this project, the results of the methodological application are shown for the city of Zurich for the year 2060. In the first step, analog climate regions based on projected climate values for the measuring station Kirche Fluntern (ZH) were searched for. In a further step, the methods mentioned above were applied to generate tree species lists for the city of Zurich. These lists were then qualitatively evaluated with respect to the suitability of the different tree species for the Zurich area to generate a cleaned and thus usable list of possible future tree species.

Keywords: climate change, climate region, climate tree, urban tree

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Authors: Anamika Sahu

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The Himalayas, like many mountainous regions, is susceptible to multiple hazards. In recent times, the frequency of such disasters is continuously increasing due to extreme weather phenomena. These natural hazards are responsible for irreparable human and economic loss. The Indian Himalayas has repeatedly been ruptured by great earthquakes in the past and has the potential for a future large seismic event as it falls under the seismic gap. Damages caused by earthquakes are different in different localities. It is well known that, during earthquakes, damage to the structure is associated with the subsurface conditions and the quality of construction materials. So, for sustainable mountain development, prior estimation of site characterization will be valuable for designing and constructing the space area and for efficient mitigation of the seismic risk. Both geotechnical and geophysical investigation of the subsurface is required to describe the subsurface complexity. In mountainous regions, geophysical methods are gaining popularity as areas can be studied without disturbing the ground surface, and also these methods are time and cost-effective. The MASW method is used to calculate the Vs30. Vs30 is the average shear wave velocity for the top 30m of soil. Shear wave velocity is considered the best stiffness indicator, and the average of shear wave velocity up to 30 m is used in National Earthquake Hazards Reduction Program (NEHRP) provisions (BSSC,1994) and Uniform Building Code (UBC), 1997 classification. Parameters obtained through geotechnical investigation have been integrated with findings obtained through the subsurface geophysical survey. Joint interpretation has been used to establish inter-relationships among mineral constituents, various textural parameters, and unconfined compressive strength (UCS) with shear wave velocity. It is found that results obtained through the MASW method fitted well with the laboratory test. In both conditions, mineral constituents and textural parameters (grain size, grain shape, grain orientation, and degree of interlocking) control the petrophysical and mechanical properties of rocks and the behavior of shear wave velocity.

Keywords: MASW, mechanical, petrophysical, site characterization

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Authors: Arafan Traore, Teiji Watanabe

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Conakry, the capital city of the Republic of Guinea, has experienced a rapid urban expansion and population increased in the last two decades, which has resulted in remarkable local weather and climate change, raise energy demand and pollution and treating social, economic and environmental development. In this study, the spatiotemporal variation of the land surface temperature (LST) is retrieved to characterize the effect of urban growth on the thermal environment and quantify its relationship with biophysical indices, a normalized difference vegetation index (NDVI) and a normalized difference built up Index (NDBI). Landsat data TM and OLI/TIRS acquired respectively in 1986, 2000 and 2016 were used for LST retrieval and Land use/cover change analysis. A quantitative analysis based on the integration of a remote sensing and a geography information system (GIS) has revealed an important increased in the LST pattern in the average from 25.21°C in 1986 to 27.06°C in 2000 and 29.34°C in 2016, which was quite eminent with an average gain in surface temperature of 4.13°C over 30 years study period. Additionally, an analysis using a Pearson correlation (r) between (LST) and the biophysical indices, normalized difference vegetation index (NDVI) and a normalized difference built-up Index (NDBI) has revealed a negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. Which implies that an increase in the NDVI value can reduce the LST intensity; conversely increase in NDBI value may strengthen LST intensity in the study area. Although Landsat data were found efficient in assessing the thermal environment in Conakry, however, the method needs to be refined with in situ measurements of LST in the future studies. The results of this study may assist urban planners, scientists and policies makers concerned about climate variability to make decisions that will enhance sustainable environmental practices in Conakry.

Keywords: Conakry, land surface temperature, urban heat island, geography information system, remote sensing, land use/cover change

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Authors: Thimma Reddy Pothireddy, Ramesh Srikonda

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India is prone to natural disasters such as Floods, droughts, cyclones, earthquakes and landslides frequently due to its geographical considerations. It has become a persistent phenomenon as observed in last ten decades. The recent survey indicates that about 60% of the landmass is prone to earthquakes of various intensities with reference to Richard scale, over 40 million hectares is prone to floods; about 8% of the total area is prone to cyclones and 68% of the area is vulnerable to drought. Climate change is likely to be perceived through the experience of extreme weather events. There is growing societal concern about climate change, given the potential impacts of associated natural hazards such as cyclones, flooding, earthquakes, landslides etc. The recent natural calamities such as Cyclone Hudhud had crossed the land at Northern cost of AP, Vishakapatanam on 12 Oct’2014 with a wind speed ranging between 175 – 200 kmph and the records show that the tidal waves were reached to the height of 14mts and above; and it alarms us to have critical focus on planning issues so as to find appropriate solutions. The existing condition is effective is in terms of institutional set up along with responsive management mechanism of disaster mitigation but considerations at settlement planning level to allow mitigation operations are not adequate. This paper deals to understand the response to climate change will possibly happen through adaptation to climate hazards and essential to work out an appropriate mechanism and disaster receptive settlement planning for responding to natural (and climate-related) calamities particularly to cyclones and floods. The statistics indicate that 40 million hectares flood prone (5% of area), and 1853 kmts of cyclone prone coastal length in India so it is essential and crucial to have appropriate physical planning considerations to improve preparedness and to operate mitigation measures effectively to minimize the loss and damage. Vijayawada capital region which is susceptible to cyclonic and floods has been studied with respect to trajectory analysis to work out risk vulnerability and to integrated disaster mitigation physical planning considerations.

Keywords: meta analysis, vulnerability index, physical planning, trajectories

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Authors: Lorraine Joyce Chua, Sheena Fatima Ragas, Flora Mae Tantay, Carolyn Marie Sunio

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The Philippines is one of the countries most affected by weather-related disasters. The occurrence of natural disasters in this country increases due to environmental degradation making environment preservation a growing trend in the society including the corporate world. Most organizations implemented green practices in order to lower expenses unaware that some of these practices were already a part of a new trend in human resource management known as Green Human Resource Management (GHRM). GHRM is when business organizations implement HR policies programs processes and techniques that bring environmental impact and sustainability practices on the organization. In relation to this, the study hypothesizes that implementing GHRM practices in the workplace will spillover to an employees lifestyle and such lifestyle may moderate the impact of GHRM practices to his job performance. Private industries located in the Philippines National Capital Region (NCR) were purposively selected for the purpose of this study. They must be ISO14001 certified or are currently aiming for such certification. The employee respondents were randomly selected and were asked to answer a reliable and valid researcher-made questionnaire. Structural equation modeling (SEM) supported the hypothesis that GHRM practices may spillover to employees lifestyle stimulating such individual to start a green lifestyle which moderates the impact of GHRM to his job performance. It can also be implied that GHRM practices help shape employees to become environmentally aware and responsible which may help them in preserving the environment. The findings of this study may encourage Human Resource practitioners to implement GHRM practices in the workplace in order to take part in sustaining the environment while maintaining or improving employees job performance and keeping them motivated. This study can serve as a basis for future research regarding the importance of strengthening the GHRM implementation here in the Philippines. Future studies may focus more on the impact of GHRM to other factors, such as job loyalty and job satisfaction of the employees belonging to specific industries which would greatly contribute to the GHRM community in the Philippines.

Keywords: GHRM practices, Green Human Resource Management, Green Lifestyle, ISO14001, job performance, Philippines

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Authors: Gauri Sreekumar, Sabuj Kumar Mandal

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Contributing about 18% to India’s Gross Domestic Product, the agricultural sector plays a significant role in the Indian rural economy. Despite being the primary source of livelihood for more than half of India’s population, most of them are marginal and small farmers facing several challenges due to agro-climatic shocks. Climate change is expected to increase the risk in the regions that are highly agriculture dependent. With systematic and scientific evidence of changes in rainfall, temperature and other extreme climate events, migration started to emerge as a survival strategy for the farm households. In this backdrop, our present study aims to combine the two strands of literature and attempts to explore whether migration is the only adaptation strategy for the farmers once they experience crop failures due adverse climatic condition. Combining the temperature and rainfall information from the weather data provided by the Indian Meteorological Department with the household level panel data on Indian states belonging to the Eastern and Semi-Arid Tropics regions from the Village Dynamics in South Asia (VDSA) collected by the International Crop Research Institute for the Semi-arid Tropics, we form a rich panel data for the years 2010-2014. A Recursive Econometric Model is used to establish the three-way nexus between climate change-yield-migration while addressing the role of irrigation and local non-farm income diversification. Using Three Stage Least Squares Estimation method, we find that climate change induced yield loss is a major driver of farmers’ migration. However, irrigation and local level non-farm income diversification are found to mitigate the adverse impact of climate change on migration. Based on our empirical results, we suggest for enhancing irrigation facilities and making local non-farm income diversification opportunities available to increase farm productivity and thereby reduce farmers’ migration.

Keywords: climate change, migration, adaptation, mitigation

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Authors: Ali Heyder Alatas, D. Xin, L. Nai Ming

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An oil spill emergency can vary in size and complexity, subject to factors such as volume and characteristics of spilled oil, incident location, impacted sensitivities and resources required. A major incident typically involves numerous stakeholders; these include the responsible party, response organisations, government authorities across multiple jurisdictions, local communities, and a spectrum of technical experts. An incident management team will encounter numerous challenges. Factors such as limited access to location, adverse weather, poor communication, and lack of pre-identified resources can impede a response; delays caused by an inefficient response can exacerbate impacts caused to the wider environment, socio-economic and cultural resources. It is essential that all parties work based on defined roles, responsibilities and authority, and ensure the availability of sufficient resources. To promote steadfast coordination and overcome the challenges highlighted, an Incident Management System (IMS) offers an essential tool for oil spill response. It provides clarity in command and control, improves communication and coordination, facilitates the cooperation between stakeholders, and integrates resources committed. Following the preceding discussion, a comprehensive review of existing literature serves to illustrate the application of IMS in oil spill response to overcome common challenges faced in a major-scaled incident. With a primary audience comprising practitioners in mind, this study will discuss key principles of incident management which enables an effective response, along with pitfalls and challenges, particularly, the tension between government and industry; case studies will be used to frame learning and issues consolidated from previous research, and provide the context to link practice with theory. It will also feature the industry approach to incident management which was further crystallized as part of a review by the Joint Industry Project (JIP) established in the wake of the Macondo well control incident. The authors posit that a common IMS which can be adopted across the industry not only enhances response capacity towards a major oil spill incident but is essential to the global preparedness effort.

Keywords: command and control, incident management system, oil spill response, response organisation

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Authors: Hassan Qandil

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Using a statistical algorithm incorporated in MATLAB, four types of non-imaging Fresnel lenses are designed; spot-flat, linear-flat, dome-shaped and semi-cylindrical-shaped. The optimization employs a statistical ray-tracing methodology of the incident light, mainly considering effects of chromatic aberration, varying focal lengths, solar inclination and azimuth angles, lens and receiver apertures, and the optimum number of prism grooves. While adopting an equal-groove-width assumption of the Poly-methyl-methacrylate (PMMA) prisms, the main target is to maximize the ray intensity on the receiver’s aperture and therefore achieving higher values of heat flux. The algorithm outputs prism angles and 2D sketches. 3D drawings are then generated via AutoCAD and linked to COMSOL Multiphysics software to simulate the lenses under solar ray conditions, which provides optical and thermal analysis at both the lens’ and the receiver’s apertures while setting conditions as per the Dallas-TX weather data. Once the lenses’ characterization is finalized, receivers are designed based on its optimized aperture size. Several cavity shapes; including triangular, arc-shaped and trapezoidal, are tested while coupled with a variety of receiver materials, working fluids, heat transfer mechanisms, and enclosure designs. A vacuum-reflective enclosure is also simulated for an enhanced thermal absorption efficiency. Each receiver type is simulated via COMSOL while coupled with the optimized lens. A lab-scale prototype for the optimum lens-receiver configuration is then fabricated for experimental evaluation. Application-based testing is also performed for the selected configuration, including that of a photovoltaic-thermal cogeneration system and solar furnace system. Finally, some future research work is pointed out, including the coupling of the collector-receiver system with an end-user power generator, and the use of a multi-layered genetic algorithm for comparative studies.

Keywords: COMSOL, concentrator, energy, fresnel, optics, renewable, solar

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Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Eslam Mohammed Abdelkader, Mohamed Marzouk, Tarek Zayed

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Infrastructure systems are crucial to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. Moreover, they are subjected to high level of deterioration because of the variable traffic loading, extreme weather conditions, cycles of freeze and thaw, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Deterioration models represent a very important aspect for the effective use of BMSs. This paper presents a probabilistic time-based model that is capable of predicting the condition ratings of the concrete bridge decks along its service life. The deterioration process of the concrete bridge decks is modeled using semi-Markov process. One of the main challenges of the Markov Chain Decision Process (MCDP) is the construction of the transition probability matrix. Yet, the proposed model overcomes this issue by modeling the sojourn times based on some probability density functions. The sojourn times of each condition state are fitted to probability density functions based on some goodness of fit tests such as Kolmogorov-Smirnov test, Anderson Darling, and chi-squared test. The parameters of the probability density functions are obtained using maximum likelihood estimation (MLE). The condition ratings obtained from the Ministry of Transportation in Quebec (MTQ) are utilized as a database to construct the deterioration model. Finally, a comparison is conducted between the Markov Chain and semi-Markov chain to select the most feasible prediction model.

Keywords: bridge management system, bridge decks, deterioration model, Semi-Markov chain, sojourn times, maximum likelihood estimation

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Authors: Ahmet Karagoz, Irfan Karagoz

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Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

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Authors: Yongjun Kim

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Since the agreement on the historicity of historical Buddha in eastern India, the beginning, heyday and decline of Buddhism in Early India have been discussed in urbanization, commercialism and state formation context, in short, Weberian socio-politico frame. Recent Scholarship, notably in archaeology and anthropology, has proposed ‘re-materialization of Buddhism in Early India’ based on what Buddhist had actually done rather than what they should do according to canonical teachings or philosophies. But its historical narrations still remain with a domain of socio-politico meta-narrative which tends to unjustifiably dismiss the naturally existing heterogeneity and often chaotic dynamic of diverse agencies, landscape perceptions, localized traditions, etc. An author will argue the multiplicity of theoretical standpoints for the reconstruction on the Buddhism in Early India. For this, at first, the diverse agencies, localized traditions, landscape patterns of Buddhist communities and monasteries in Trans-Himalayan regions; focusing Zanskar Valley and Spiti Valley in India will be illustrated based on an author’s field work. And then an author will discuss this anthropological landscape analysis is better appropriated with textual and archaeological evidences on the tension between urban monastic and forest Buddhism, the phenomena of sacred landscape, cemetery, garden, natural cave along with socio-economic landscape, the demographic heterogeneity in Early India. Finally, it will be attempted to compare between anthropological landscape of present Trans-Himalayan and archaeological one of ancient Western India. The study of Buddhism in Early India has hardly been discussed through multivalent theoretical archaeology and anthropology of religion, thus traditional and recent scholarship have produced historical meta-narrative though heterogeneous among them. The multidisciplinary approaches of textual critics, archaeology and anthropology will surely help to deconstruct the grand and all-encompassing historical description on Buddhism in Early India and then to reconstruct the localized, behavioral and multivalent narratives. This paper expects to highlight the importance of lesser-studied Buddhist archaeological sites and the dynamic views on religious landscape in Early India with a help of critical anthropology of religion.

Keywords: analogy by living traditions, Buddhism in Early India, landscape analysis, meta-narrative

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Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

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Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Rajender Lal, Seema Kaushik

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The FIFA World Cup, often simply called the World Cup, is an international association football competition contested by the senior men's national teams of the members of Fédération Internationale de Football Association (FIFA), the sport's global governing body. The championship has been awarded every four years since the inaugural tournament in 1930, except in 1942 and 1946 when it was not held because of the Second World War. Its 20th edition took place in Brazil from 12 June to 13 July 2014, which was won by Germany. The World Cup is the most widely viewed and followed sporting event in the world, exceeding even the Olympic Games; the cumulative audience of all matches of the 2006 FIFA World Cup was estimated to be 26.29 billion with an estimated 715.1 million people watching the final match, a ninth of the entire population of the planet. General-interest newspapers typically publish news articles and feature articles on national and international news as well as local news. The news includes political events and personalities, business and finance, crime, severe weather, and natural disasters; health and medicine, science, and technology; sports; and entertainment, society, food and cooking, clothing and home fashion, and the arts. It became curiosity to investigate that how much coverage is given to this most widely viewed international event as compared to other sports in India. Hence, the present study was conducted with the aim of examining the comparative coverage of FIFA World Cup 2014 and other sports in the four leading Newspapers of India including Hindustan Times, The Hindu, The Times of India, and The Tribune. Specific objectives were to measure the source of news, type of news items and the placement of news related to FIFA World Cup and other sports. Representative sample of ten editions each of the four English dailies was chosen for the purpose of the study. The analysis was based on the actual scanning of data from the representative sample of the dailies for the period of the competition. It can be concluded from the analysis that this event was given maximum coverage by the Hindustan Times while other sports were equally covered by The Hindu.

Keywords: coverage analysis, FIFA World Cup 2014, Hindustan Times, the Hindu, The Times of India, The Tribune

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Authors: Bruna P. De Souza, Ricardo C. De Almeida

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In some cities in the State of Parana – Brazil and in other countries atmospheric bromeliads (Tillandsia spp - Bromeliaceae) are considered weeds in trees, electric power lines, satellite dishes and other artificial supports. In this study, a numerical model was developed to simulate the seed dispersal of the Tillandsia recurvata species by wind with the objective of evaluating seeds displacement in the city of Ponta Grossa – PR, Brazil, since it is considered that the region is already infested. The model simulates the dispersal of each individual seed integrating parameters from the atmospheric boundary layer (ABL) and the local wind, simulated by the Weather Research Forecasting (WRF) mesoscale atmospheric model for the 2012 to 2015 period. The dispersal model also incorporates the approximate number of bromeliads and source height data collected from most infested electric power lines. The seeds terminal velocity, which is an important input data but was not available in the literature, was measured by an experiment with fifty-one seeds of Tillandsia recurvata. Wind is the main dispersal agent acting on plumed seeds whereas atmospheric turbulence is a determinant factor to transport the seeds to distances beyond 200 meters as well as to introduce random variability in the seed dispersal process. Such variability was added to the model through the application of an Inverse Fast Fourier Transform to wind velocity components energy spectra based on boundary-layer meteorology theory and estimated from micrometeorological parameters produced by the WRF model. Seasonal and annual wind means were obtained from the surface wind data simulated by WRF for Ponta Grossa. The mean wind direction is assumed to be the most probable direction of bromeliad seed trajectory. Moreover, the atmospheric turbulence effect and dispersal distances were analyzed in order to identify likely regions of infestation around Ponta Grossa urban area. It is important to mention that this model could be applied to any species and local as long as seed’s biological data and meteorological data for the region of interest are available.

Keywords: atmospheric turbulence, bromeliad, numerical model, seed dispersal, terminal velocity, wind

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Authors: Siraj Beyan Mohamed, Woldia University

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The study is accompanied in northern Ethiopian basement rocks, Finarwa area, and its surrounding areas, south eastern Tigray. From the field observations, the geology of the area haven been described and mapped based on mineral composition, texture, structure, and colour of both fresh and weather rocks. Inductively coupled plasma mass spectrometry (ICP-MS) and atomic absorption spectrometry (AAS) have conducted to analysis gold and base metal mineralization. The ore mineral under microscope are commonly base metal sulphides pyrrhotite, Chalcopyrite, pentilanditeoccurring in variable proportions. Galena, chalcopyrite, pyrite, and gold mineral are hosted in quartz vein. Pyrite occurs both in quartz vein and enclosing rocks as a primary mineral. The base metal sulfides occur as disseminated, vein filling, and replacement. Geochemical analyses result determination of the threshold of geochemical anomalies is directly related to the identification of mineralization information. From samples, stream sediment samples and the soil samples indicated that the most promising mineralization occur in the prospect area are gold(Au), copper (Cu), and zinc (Zn). This is also supported by the abundance of chalcopyrite and sphalerite in some highly altered samples. The stream sediment geochemical survey data shows relatively higher values for zinc compared to Pb and Cu. The moderate concentration of the base metals in some of the samples indicates availability base metal mineralization in the study area requiring further investigation. The rock and soil geochemistry shows the significant concentration of gold with maximum value of 0.33ppm and 0.97 ppm in the south western part of the study area. In Finarwa, artisanal gold mining has become an increasingly widespread economic activity of the local people undertaken by socially differentiated groups with a wide range of education levels and economic backgrounds incorporating a wide variety of ‘labour intensive activities without mechanisation.

Keywords: gold, base metal, anomaly, threshold

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Authors: Salamatu Shaibu, Jan Hernning Sommer

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Integrating biodiversity conservation practices in mining landscapes ensures the continual provision of various ecosystem services to the dependent communities whilst serving as ecological insurance for corporate mining when purchasing reclamation security bonds. Climate hazards such as long dry seasons, erratic rainfall patterns, and extreme weather events contribute to biodiversity loss in addition to the impact due to mining. Both corporate mining and mine-fringe communities perceive the effect of climate on biodiversity from the context of the benefits they accrue, which motivate their conservation practices. In this study, pragmatic approaches including semi-structured interviews, field visual observation, and review were used to collect data on corporate mining employees and households of fringing communities in the southwestern mining hub. The perceived changes in the local climatic conditions and the consequences on environmental management practices that promote biodiversity conservation were examined. Using a thematic content analysis tool, the result shows that best practices such as concurrent land rehabilitation, reclamation ponds, artificial wetlands, land clearance, and topsoil management are directly affected by prolonging long dry seasons and erratic rainfall patterns. Excessive dust and noise generation directly affect both floral and faunal diversity coupled with excessive fire outbreaks in rehabilitated lands and nearby forest reserves. Proposed adaptive measures include engaging national conservation authorities to promote reforestation projects around forest reserves. National government to desist from using permit for mining concessions in forest reserves, engaging local communities through educational campaigns to control forest encroachment and burning, promoting community-based resource management to promote community ownership, and provision of stricter environmental legislation to compel corporate, artisanal, and small scale mining companies to promote biodiversity conservation.

Keywords: biodiversity conservation, climate hazards, corporate mining, mining landscapes

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Authors: Raúl García de la Cruz

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In the state of Hidalgo and to the vicinity to the state of Mexico, there is a network of people who also share a valley bordered by hills with agave landscape of cacti and shared a bond of building traditions inherited from pre-Hispanic times and according to their material resources, habits and needs have been adapted in time. Weather has played an important role in the way buildings and roofs are constructed. Throughout the centuries, the population has developed very sophisticated building techniques like the flat roof, made out of a layer of earth; that is usually identified as belonging to architecture of the desert, but it can also be found in other climates, such as semi-arid and even template climates. It is an example of a constructive logic applied efficiently to various cultures proving its thermal isolation. So far it has done a review and analysis of the use of the roof in different areas, from pre-Hispanic architecture to traditional Moroccan architecture , finding great similarities in the elements of the system to be incorporated into the contemporary architecture. The rescue of a lore that dissolves with the changing environment, depends in principle on the links created towards the use of environmental resources as the anchor of the people to retain and preserve a building tradition which has viability deep league with the possibility of obtaining the raw material from the immediate environment. The objective of the research is the documentation of existing earth flat roofs in the state of Hidalgo and Mexico, as evidence of the importance of constructive system and its historical value in the area, considering its environmental, social aspects, also understanding the process of transformation of public housing at the time replaced the traditional techniques for industrial materials on a path towards urbanization. So far it has done a review and analysis of the use of the roof in different areas, from pre-Hispanic architecture to traditional Moroccan architecture, finding great similarities in the elements of the system to be incorporated into the contemporary architecture. The rescue of a lore that dissolves with the changing environment, depends in principle on the links created towards the use of environmental resources as the anchor of the people to retain and preserve a building tradition which has viability deep league with the possibility of obtaining the raw material from the immediate environment.

Keywords: earth roof, low impact building system, sustainable architecture, vernacular architecture

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Authors: Athanasios A. Gavrilidis, Mihai R. Nita, Larissa N. Stoia, Diana A. Onose

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Contemporary global environmental challenges must be primarily addressed at local levels. Cities are under continuous pressure as they must ensure high quality of life levels for their citizens and at the same time to adapt and address specific environmental issues. Innovative solutions using natural features or mimicking natural systems are endorsed by the scientific community as efficient approaches for both mitigating climate change effects and the decrease of environmental quality and for maintaining high standards of living for urban dwellers. The aim of this study was to assess whether Romanian cities’ authorities are considering nature-based innovation as solutions for their planning, management, and environmental issues. Data were gathered by applying 140 questionnaires to urban authorities throughout the country. The questionnaire was designed for assessinglocal policy makers’ perspective over the efficiency of nature-based innovations as a tool to address specific challenges. It also focused on extracting data about financing sources and challenges they must overcome for adopting nature-based approaches. The gather results from the municipalities participating in our study were statistically processed, and they revealed that Romanian city managers acknowledge the benefits of nature-based innovations, but investments in this sector are not on top of their priorities. More than 90% of the selected cities have agreed that in the last 10 years, their major concern was to expand the grey infrastructure (roads and public amenities) using traditional approaches. When asked how they would react if faced with different socio-economic and environmental challenges, local urban managers indicated investments nature-based solutions as a priority only in case of biodiversity loss and extreme weather, while for other 14 proposed scenarios, they would embrace the business-as-usual approach. Our study indicates that while new concepts of sustainable urban planning emerge within the scientific community, local authorities need more time to understand and implement them. Without the proper knowledge, personnel, policies, or dedicated budgets, local administrators will not embrace nature-based innovations as solutions for their challenges.

Keywords: nature based innovations, perception analysis, policy making, urban planning

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Authors: Zhongzhong Zeng, Zichen Liang

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In recent years, Beijing courtyards have been facing the problem of renewal and renovation, and the residents are faced with the problems of small house areas, large household sizes, old and dangerous houses, etc. Among the many renovation methods, the authors note two more common practices of using the front porch to expand the floor area and adding a loft. Residents and architects, however, did not give the ventilation performance of the significant interior consideration before beginning the remodeling. The aim of this article is to explore the good or negative impacts of both front porch and loft structures on the manner of interior ventilation in the courtyard. Ventilation, in turn, is crucial to the indoor environmental quality of a home. The major method utilized in this study is the comparative analysis method, in which the authors create four alternative house models with or without a front porch and an attic as two variables and examine internal ventilation using the CFD(Computational Fluid Dynamics) technique. The authors compare the indoor ventilation of four different architectural models with or without front porches and lofts as two variables. The results obtained from the analysis of the sectional airflow and the plane 1.5m height cloud are the existence of the loft, to a certain extent, disrupts the airflow organization of the building and makes the rear wall high windows of the building less effective. Occupying the front porch to become the area of the house has no significant effect on ventilation, but try not to occupy the front porch and add the loft at the same time in the building renovation. The findings of this study led to the following recommendations: strive to preserve the courtyard building's original architectural design and make adjustments to only the inappropriate elements or constructions. The ventilation in the loft portion is inadequate, and the inhabitants typically use the loft as a living area. This may lead to the building relying more on air conditioning in the summer, which would raise energy demand. The front porch serves as a transition place as well as a source of shade, weather protection, and inside ventilation. In conclusion, the examination of interior environments in upcoming studies should concentrate on cross-disciplinary, multi-angle, and multi-level research topics.

Keywords: Beijing courtyard renewal, CFD, indoor environment, ventilation analysis

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Authors: Vinko Lešić, Mario Vašak, Anita Martinčević, Marko Gulin, Antonio Starčić, Hrvoje Novak

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With 40% of total world energy consumption, building systems are developing into technically complex large energy consumers suitable for application of sophisticated power management approaches to largely increase the energy efficiency and even make them active energy market participants. Centralized control system of building heating and cooling managed by economically-optimal model predictive control shows promising results with estimated 30% of energy efficiency increase. The research is focused on implementation of such a method on a case study performed on two floors of our faculty building with corresponding sensors wireless data acquisition, remote heating/cooling units and central climate controller. Building walls are mathematically modeled with corresponding material types, surface shapes and sizes. Models are then exploited to predict thermal characteristics and changes in different building zones. Exterior influences such as environmental conditions and weather forecast, people behavior and comfort demands are all taken into account for deriving price-optimal climate control. Finally, a DC microgrid with photovoltaics, wind turbine, supercapacitor, batteries and fuel cell stacks is added to make the building a unit capable of active participation in a price-varying energy market. Computational burden of applying model predictive control on such a complex system is relaxed through a hierarchical decomposition of the microgrid and climate control, where the former is designed as higher hierarchical level with pre-calculated price-optimal power flows control, and latter is designed as lower level control responsible to ensure thermal comfort and exploit the optimal supply conditions enabled by microgrid energy flows management. Such an approach is expected to enable the inclusion of more complex building subsystems into consideration in order to further increase the energy efficiency.

Keywords: price-optimal building climate control, Microgrid power flow optimisation, hierarchical model predictive control, energy efficient buildings, energy market participation

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Authors: Mina Rouhollahi, J. Boland

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Changes in cities’ heat balance due to rapid urbanization and the urban heat island (UHI) have increased energy demands for space cooling and have resulted in uncomfortable living conditions for urban residents. Climate resilience and comfortable living spaces can be addressed through well-designed urban development. The sustainable housing can be more effective in controlling high levels of urban heat. In Australia, to mitigate the effects of UHIs and summer heat waves, one solution to sustainable housing has been the trend to compact housing design and the construction of energy efficient dwellings. This paper analyses whether current housing configurations and orientations are effective in avoiding increased demands for air conditioning and having an energy efficient residential neighborhood. A significant amount of energy is consumed to ensure thermal comfort in houses. This paper reports on the modelling of heat transfer within the homes using the measurements of radiation, convection and conduction between exterior/interior wall surfaces and outdoor/indoor environment respectively. The simulation was tested on selected 7.5-star energy efficient houses constructed of typical material elements and insulation in Adelaide, Australia. The chosen design dwellings were analyzed in extremely hot weather through one year. The data were obtained via a thermal circuit to accurately model the fundamental heat transfer mechanisms on both boundaries of the house and through the multi-layered wall configurations. The formulation of the Lumped capacitance model was considered in discrete time steps by adopting a non-linear model method. The simulation results focused on the effects of orientation of the solar radiation on the dynamic thermal characteristics of the houses orientations. A high star rating did not necessarily coincide with a decrease in peak demands for cooling. A more effective approach to avoid increasing the demands for air conditioning and energy may be to integrate solar–climatic data to evaluate the performance of energy efficient houses.

Keywords: energy-efficient residential building, heat transfer, neighborhood orientation, solar–climatic data

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Authors: Emilienne Lardy, Mariam Lafkihi, Eric Ballot

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Efficient city logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modeling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed to describe extensively the kinetic and dynamic aspects of driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore it investigates how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Generalized Linear Model has been established to link kinetic parameters with independent categorical contextual variables. The results include the analysis of the regression’s accuracy, as well as the utilization of the regression’s results in freight distribution scenario elaboration and analysis for Supply Chain Management purposes.

Keywords: driving context, generalized linear model, kinetic behaviour, real world driving data

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Authors: Carlos Roberto De Rolt, Julio da Silva Dias, Rafael Tezza, Luca Foschini, Matteo Mura

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The seasonal population fluctuation presents a challenge to touristic cities since the number of inhabitants can double according to the season. The aim of this work is to develop a model that correlates the waste collected with the population of the city and also allow cooperation between the inhabitants and the local government. The model allows public managers to evaluate the impact of the seasonal population fluctuation on waste generation and also to improve planning resource utilization throughout the year. The study uses data from the company that collects the garbage in Florianópolis, a Brazilian city that presents the profile of a city that attracts tourists due to numerous beaches and warm weather. The fluctuations are caused by the number of people that come to the city throughout the year for holidays, summer time vacations or business events. Crowdsensing will be accomplished through smartphones with access to an app for data collection, with voluntary participation of the population. Crowdsensing participants can access information collected in waves for this portal. Crowdsensing represents an innovative and participatory approach which involves the population in gathering information to improve the quality of life. The management of crowdsensing solutions plays an essential role given the complexity to foster collaboration, establish available sensors and collect and process the collected data. Practical implications of this tool described in this paper refer, for example, to the management of seasonal tourism in a large municipality, whose public services are impacted by the floating of the population. Crowdsensing and big data support managers in predicting the arrival, permanence, and movement of people in a given urban area. Also, by linking crowdsourced data to databases from other public service providers - e.g., water, garbage collection, electricity, public transport, telecommunications - it is possible to estimate the floating of the population of an urban area affected by seasonal tourism. This approach supports the municipality in increasing the effectiveness of resource allocation while, at the same time, increasing the quality of the service as perceived by citizens and tourists.

Keywords: big data, dashboards, floating population, smart city, urban management solutions

Procedia PDF Downloads 258