Search results for: road traffic incidents

Authors: Ali Raouli, Amin Chegenizadeh, Hamid Nikraz

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The Perth metropolitan area and its surrounding regions have been expanding rapidly in recent decades and it is expected that this growth will continue in the years to come. With this rapid growth and the resulting increase in population, consideration should be given to strategic planning and modelling for the future expansion of Perth. The accurate estimation of projected traffic volumes has always been a major concern for the transport modelers and planners. Development of a reliable strategic transport model depends significantly on the inputs data into the model and the calibrated parameters of the model to reflect the existing situation. Trip distribution is the second step in four-step modelling (FSM) which is complex due to its behavioral nature. Gravity model is the most common method for trip distribution. The spatial separation between the Origin and Destination (OD) zones will be reflected in gravity model by applying deterrence functions which provide an opportunity to include people’s behavior in choosing their destinations based on distance, time and cost of their journeys. Deterrence functions play an important role for distribution of the trips within a study area and would simulate the trip distances and therefore should be calibrated for any particular strategic transport model to correctly reflect the trip behavior within the modelling area. This paper aims to review the most common deterrence functions and propose a calibrated deterrence function for work trips within the Perth Metropolitan Area based on the information obtained from the latest available Household data and Perth and Region Travel Survey (PARTS) data. As part of this study, a four-step transport model using EMME software has been developed for Perth Metropolitan Area to assist with the analysis and findings.

Keywords: deterrence function, four-step modelling, origin destination, transport model

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Authors: Al-Amin, Huanjun Jiang, Anayat Ali

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Reinforced concrete frames (RC), especially Ordinary RC frames, are prone to structural failures/collapse during seismic events, leading to a large proportion of debris from the structures, which obstructs adjacent areas, including streets. These blocked areas severely impede post-earthquake resilience. This study uses computational simulation (FEM) to investigate the amount of debris generated by the seismic collapse of an ordinary reinforced concrete moment frame building and its effects on the adjacent pedestrian and road network. A three-story ordinary reinforced concrete frame building, primarily designed for gravity load and earthquake resistance, was selected for analysis. Sixteen different ground motions were applied and scaled up until the total collapse of the tested building to evaluate the failure mode under various seismic events. Four types of collapse direction were identified through the analysis, namely aligned (positive and negative) and skewed (positive and negative), with aligned collapse being more predominant than skewed cases. The amount and distribution of debris around the collapsed building were assessed to investigate the interaction between collapsed buildings and adjacent street networks. An interaction was established between a building that collapsed in an aligned direction and the adjacent pedestrian walkway and narrow street located in an unplanned old city. The FEM model was validated against an existing shaking table test. The presented results can be utilized to simulate the interdependency between the debris generated from the collapse of seismic-prone buildings and the resilience of street networks. These findings provide insights for better disaster planning and resilient infrastructure development in earthquake-prone regions.

Keywords: building collapse, earthquake-induced debris, ORC moment resisting frame, street network

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Authors: Dagim Dessalegn Haile

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This study investigated the interaction between the drivers' socio-demographic background information (age, gender, and driving experience) and the risky events score in the i-DREAMS platform. Further, the relationship between the participants' background driving behavior and the i-DREAMS platform behavioral output scores of risky events was also investigated. The i-DREAMS acronym stands for Smart Driver and Road Environment Assessment and Monitoring System. It is a European Union Horizon 2020 funded project consisting of 13 partners, researchers, and industry partners from 8 countries. A total of 25 Belgian car drivers (16 male and nine female) were considered for analysis. Drivers' ages were categorized into ages 18-25, 26-45, 46-65, and 65 and older. Drivers' driving experience was also categorized into four groups: 1-15, 16-30, 31-45, and 46-60 years. Drivers are classified into two clusters based on the recorded score for risky events during phase 1 (baseline) using risky events; acceleration, deceleration, speeding, tailgating, overtaking, and lane discipline. Agglomerative hierarchical clustering using SPSS shows Cluster 1 drivers are safer drivers, and Cluster 2 drivers are identified as risky drivers. The analysis result indicated no significant relationship between age groups, gender, and experience groups except for risky events like acceleration, tailgating, and overtaking in a few phases. This is mainly because the fewer participants create less variability of socio-demographic background groups. Repeated measure ANOVA shows that cluster 2 drivers improved more than cluster 1 drivers for tailgating, lane discipline, and speeding events. A positive relationship between background drivers' behavior and i-DREAMS platform behavioral output scores is observed. It implies that car drivers who in the questionnaire data indicate committing more risky driving behavior demonstrate more risky driver behavior in the i-DREAMS observed driving data.

Keywords: i-dreams, car drivers, socio-demographic background, risky events

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Authors: Borhan Marzougui

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Road and Transport Authority (RTA) is moving ahead with the implementation of the leader’s vision in exploring all avenues that may bring better security and safety services to the community. Smart transport means using smart technologies such as IoT (Internet of Things). This technology continues to affirm its important role in the context of Information and Transportation Systems. In fact, IoT is a network of Internet-connected objects able to collect and exchange different data using embedded sensors. With the growth of IoT, Distributed Denial of Service (DDoS) attacks is also growing exponentially. DDoS attacks are the major and a real threat to various transportation services. Currently, the defense mechanisms are mainly passive in nature, and there is a need to develop a smart technique to handle them. In fact, new IoT devices are being used into a botnet for DDoS attackers to accumulate for attacker purposes. The aim of this paper is to provide a relevant understanding of dangerous types of DDoS attack related to IoT and to provide valuable guidance for the future IoT security method. Our methodology is based on development of the distributed algorithm. This algorithm manipulates dedicated intelligent and cooperative agents to prevent and to mitigate DDOS attacks. The proposed technique ensure a preventive action when a malicious packets start to be distributed through the connected node (Network of IoT devices). In addition, the devices such as camera and radio frequency identification (RFID) are connected within the secured network, and the data generated by it are analyzed in real time by intelligent and cooperative agents. The proposed security system is based on a multi-agent system. The obtained result has shown a significant reduction of a number of infected devices and enhanced the capabilities of different security dispositives.

Keywords: IoT, DDoS, attacks, botnet, security, agents

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Authors: Abdulmalik Altuwayjiri, Milad Pirhadi, Mohammed Kalafy, Badr Alharbi, Constantinos Sioutas

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In this study, we investigated the chemical and toxicological characteristics of PM10 in the metropolitan area of Riyadh, Saudi Arabia. PM10 samples were collected on quartz and teflon filters during cold (December 2019–April 2020) and warm (May 2020–August 2020) seasons, including dust and non-dust events. The PM10 constituents were chemically analyzed for their metal, inorganic ions, and elemental and organic carbon (EC/OC) contents. Additionally, the PM10 oxidative potential was measured by means of the dithiothreitol (DTT) assay. Our findings revealed that the oxidative potential of the collected ambient PM10 samples was significantly higher than those measured in many urban areas worldwide. The oxidative potential of the collected ambient PM¹⁰⁻ samples was also higher during dust episodes compared to non-dust events, mainly due to higher concentrations of metals during these events. We performed Pearson correlation analysis, principal component analysis (PCA), and multi-linear regression (MLR) to identify the most significant sources contributing to the toxicity of PM¹⁰⁻ The results of the MLR analyses indicated that the major pollution sources contributing to the oxidative potential of ambient PM10 were soil and resuspended dust emissions (identified by Al, K, Fe, and Li) (31%), followed by secondary organic aerosol (SOA) formation (traced by SO₄-² and NH+₄) (20%), and industrial activities (identified by Se and La) (19%), and traffic emissions (characterized by EC, Zn, and Cu) (17%). Results from this study underscore the impact of transported dust emissions on the oxidative potential of ambient PM10 in Riyadh and can be helpful in adopting appropriate public health policies regarding detrimental outcomes of exposure to PM₁₀-

Keywords: ambient PM10, oxidative potential, source apportionment, Riyadh, dust episodes

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Authors: Hachaichi Mohamed Nour El-Islem, Baouni Tahar

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Environmental sustainability rather than a trans-disciplinary and a scientific issue, is the main problem that characterizes all modern cities nowadays. In developing countries, this concern is expressed in a plethora of critical urban ills: traffic congestion, air pollution, noise, urban decay, increase in energy consumption and CO₂ emissions which blemish cities’ landscape and might threaten citizens’ health and welfare. As in the same manner as developing world cities, the rapid growth of Algiers’ human population and increasing in city scale phenomena lead eventually to increase in daily trips, energy consumption and CO₂ emissions. In addition, the lack of proper and sustainable planning of the city’s infrastructure is one of the most relevant issues from which Algiers suffers. The aim of this contribution is to estimate the carbon deficit of the City of Algiers, Algeria, using the Ecological Footprint Model (carbon footprint). In order to achieve this goal, the amount of CO₂ from fuel combustion has been calculated and aggregated into five sectors (agriculture, industry, residential, tertiary and transportation); as well, Algiers’ biocapacity (CO₂ uptake land) has been calculated to determine the ecological overshoot. This study shows that Algiers’ transport system is not sustainable and is generating more than 50% of Algiers total carbon footprint which cannot be sequestered by the local forest land. The aim of this research is to show that the Carbon Footprint Assessment might be a relevant indicator to design sustainable strategies/policies striving to reduce CO₂ by setting in motion the energy consumption in the transportation sector and reducing the use of fossil fuels as the main energy input.

Keywords: biocapacity, carbon footprint, ecological footprint assessment, energy consumption

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Authors: Seongjun Kim, Jinwooung Kim, Sung-Ah Kim

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The development of information and communication technology also affects human cognition and thinking, especially in the field of design, new techniques are being tried. In architecture, new design methodologies such as machine learning or data-driven design are being applied. In particular, these methodologies are used in analyzing the factors related to the value of real estate or analyzing the feasibility in the early planning stage of the apartment housing. However, since the value of apartment buildings is often determined by external factors such as location and traffic conditions, rather than the interior elements of buildings, data is rarely used in the design process. Therefore, although the technical conditions are provided, the internal elements of the apartment are difficult to apply the data-driven design in the design process of the apartment. As a result, the designers of apartment housing were forced to rely on designer experience or modular design alternatives rather than data-driven design at the design stage, resulting in a uniform arrangement of space in the apartment house. The purpose of this study is to propose a methodology to support the designers to design the apartment unit plan with high consumer preference by deriving the correlation and importance of the floor plan elements of the apartment preferred by the consumers through the machine learning and reflecting this information from the early design process. The data on the pre-sale competition rate and the elements of the floor plan are collected as data, and the correlation between pre-sale competition rate and independent variables is analyzed through machine learning. This analytical model can be used to review the apartment unit plan produced by the designer and to assist the designer. Therefore, it is possible to make a floor plan of apartment housing with high preference because it is possible to feedback apartment unit plan by using trained model when it is used in floor plan design of apartment housing.

Keywords: apartment unit plan, data-driven design, design methodology, machine learning

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Authors: Ileen Van den Berg, Reinier J. Daals, Chris E. M. Heuberger, Sven P. Hildering, Bob E. Van Maris, Carla M. Smulders, Rafael Aránguiz

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Chile is located along the subduction zone of the Nazca plate beneath the South American plate, where large earthquakes and tsunamis have taken place throughout history. The last significant earthquake (Mw 8.2) occurred in September 2015 and generated a destructive tsunami, which mainly affected the city of Coquimbo (71.33°W, 29.96°S). The inundation area consisted of a beach, damaged seawall, damaged railway, wetland and old neighborhood; therefore, local authorities started a reconstruction process immediately after the event. Moreover, a seismic gap has been identified in the same area, and another large event could take place in the near future. The present work proposed an integrated tsunami reconstruction plan for the city of Coquimbo that considered several variables such as safety, nature & recreation, neighborhood welfare, visual obstruction, infrastructure, construction process, and durability & maintenance. Possible future tsunami scenarios are simulated by means of the Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE) model with 5 nested grids and a higher grid resolution of ~10 m. Based on the score from a multi-criteria analysis, the costs of the alternatives and a preference for a multifunctional solution, the alternative that includes an elevated coastal road with floodgates to reduce tsunami overtopping and control the return flow of a tsunami was selected as the best solution. It was also observed that the wetlands are significantly restored to their former configuration; moreover, the dynamic behavior of the wetlands is stimulated. The numerical simulation showed that the new coastal protection decreases damage and the probability of loss of life by delaying tsunami arrival time. In addition, new evacuation routes and a smaller inundation zone in the city increase safety for the area.

Keywords: tsunami, Coquimbo, Chile, reconstruction, numerical simulation

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Authors: Hang Yang, Jichao Li, Kewei Yang, Tianyang Lei

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Multivariate time series anomaly detection is a significant research topic in the field of data mining, encompassing a wide range of applications across various industrial sectors such as traffic roads, financial logistics, and corporate production. The inherent spatial dependencies and temporal characteristics present in multivariate time series introduce challenges to the anomaly detection task. Previous studies have typically been based on the assumption that all variables belong to the same spatial hierarchy, neglecting the multi-level spatial relationships. To address this challenge, this paper proposes a multi-scale spatial and unified temporal feature fusion network, denoted as MSUT-Net, for multivariate time series anomaly detection. The proposed model employs a multi-level modeling approach, incorporating both temporal and spatial modules. The spatial module is designed to capture the spatial characteristics of multivariate time series data, utilizing an adaptive graph structure learning model to identify the multi-level spatial relationships between data variables and their attributes. The temporal module consists of a unified temporal processing module, which is tasked with capturing the temporal features of multivariate time series. This module is capable of simultaneously identifying temporal dependencies among different variables. Extensive testing on multiple publicly available datasets confirms that MSUT-Net achieves superior performance on the majority of datasets. Our method is able to model and accurately detect systems data with multi-level spatial relationships from a spatial-temporal perspective, providing a novel perspective for anomaly detection analysis.

Keywords: data mining, industrial system, multivariate time series, anomaly detection

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Authors: Awad Khireldin, Colin Law

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Runways are the major infrastructure of airports around the world. Efficient operations of runways are key to ensure that airports are running smoothly with minimal delays. There are many factors that affect the efficiency of runway operations, such as the aircraft wake separation, runways system configuration, the fleet mix, and the runways separation distance. This paper aims to address how to maximize runway operations using a Discrete Event Simulation model. A case study of Cairo International Airport (CIA) is developed to maximize the utilizing of three parallel runways using a simulation model. Different scenarios have been designed where every runway could be assigned for arrival, departure, or mixed operations. A benchmarking study was also included to compare the actual to the proposed results to spot the potential improvements. The simulation model shows that there is a significant difference in utilization and delays between the actual and the proposed ones, there are several recommendations that can be provided to airport management, in the short and long term, to increase the efficiency and to reduce the delays. By including the recommendation with different operations scenarios, such as upgrading the airport slot Coordination from Level 1 to Level 2 in the short term. In the long run, discuss the possibilities to increase the International Air Transport association (IATA) slot coordination to Level 3 as more flights are expected to be handled by the airport. Technological advancements such as radar in the approach full airside simulation model could improve the airport performance where the airport is recommended to review the standard operations procedures with the appropriate authorities. Also, the airport can adopt a future operational plan to accommodate the forecasted additional traffic density in case of adding a fourth terminal building to increase the airport capacity.

Keywords: airport performance, runway, discrete event simulation, capacity, airside

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Authors: Hui Wang

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Traditional collection building approaches are limited in breadth and scope and are not necessarily suitable for multidisciplinary fields development in the institutes of the Chinese Academy of Sciences. The increasing of multidisciplinary fields researches require a viable approach to collection development in these libraries. This study uses qualitative and quantitative analysis to assess collection. The quantitative analysis consists of three levels of evaluation, which including realistic demand, potential demand and trend demand analysis. For one institute, three samples were separately selected from the object institute, more than one international top institutes in highly relative research fields and future research hotspots. Each sample contains an appropriate number of papers published in recent five years. Several keywords and the organization names were reasonably combined to search in commercial databases and the institutional repositories. The publishing information and citations in the bibliographies of these papers were selected to build the dataset. One weighted evaluation model and citation analysis were used to calculate the demand intensity index of every journal and book. Principal Investigator selector and database traffic provide a qualitative evidence to describe the demand frequency. The demand intensity, demand frequency and academic committee recommendations were comprehensively considered to recommend collection development. The collection gaps or weaknesses were ascertained by comparing the current collection and the recommend collection. This approach was applied in more than 80 institutes’ libraries in Chinese Academy of Sciences in the past three years. The evaluation results provided an important evidence for collections building in the second year. The latest user survey results showed that the updated collection’s capacity to support research in a multidisciplinary subject area have increased significantly.

Keywords: citation analysis, collection assessment, collection development, quantitative analysis

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Authors: Rimon Rafiah

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This paper will present a combination of two seemingly unrelated models, which are the one for estimating economic development impacts as a result of transportation investment and the other for increasing CAV penetration in order to reduce congestion. Measuring economic development impacts resulting from transportation investments is becoming more recognized around the world. Examples include the UK’s Wider Economic Benefits (WEB) model, Economic Impact Assessments in the USA, various input-output models, and additional models around the world. The economic impact model is based on WEB and is based on the following premise: investments in transportation will reduce the cost of personal travel, enabling firms to be more competitive, creating additional throughput (the same road allows more people to travel), and reducing the cost of travel of workers to a new workplace. This reduction in travel costs was estimated in out-of-pocket terms in a given localized area and was then translated into additional employment based on regional labor supply elasticity. This additional employment was conservatively assumed to be at minimum wage levels, translated into GDP terms, and from there into direct taxation (i.e., an increase in tax taken by the government). The CAV model is based on economic principles such as CAV usage, supply, and demand. Usage of CAVs can increase capacity using a variety of means – increased automation (known as Level I thru Level IV) and also by increased penetration and usage, which has been predicted to go up to 50% by 2030 according to several forecasts, with possible full conversion by 2045-2050. Several countries have passed policies and/or legislation on sales of gasoline-powered vehicles (none) starting in 2030 and later. Supply was measured via increased capacity on given infrastructure as a function of both CAV penetration and implemented technologies. The CAV model, as implemented in the USA, has shown significant savings in travel time and also in vehicle operating costs, which can be translated into economic development impacts in terms of job creation, GDP growth and salaries as well. The models have policy implications as well and can be adapted for use in Japan as well.

Keywords: CAV, economic development, WEB, transport economics

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Authors: Vladimir Klepikov

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Countries of Central and Southern Europe have a typical feature: oil consumption in the region exceeds own commodity production capacity by far. So crude oil import prevails in the region’s crude oil consumption structure. Transportation using marine and pipeline transport is a common method of the imported oil delivery in the region. For certain refineries, in addition to possible transportation by oil pipelines from seaports, oil is delivered from Russian oil fields. With the view to these specific features and geographic location of the region’s refineries, three ways of imported oil delivery can be singled out: oil delivery by tankers to the port and subsequent transportation by pipeline transport of the port and the refinery; oil delivery by tanker fleet to the port and subsequent transportation by oil trunk pipeline transport; oil delivery from the fields by oil trunk pipelines to refineries. Oil is also delivered by road, internal water, and rail transport. However, the volumes transported this way are negligible in comparison to the three above transportation means. Multimodal oil transportation to refineries using the pipeline and marine transport is one of the biggest cargo flows worldwide. However, in scientific publications this problem is considered mainly for certain modes of transport. Therefore, this study is topical. To elaborate an efficient transportation policy of crude oil supply to Central and Southern Europe, in this paper the geographic concentration of oil refineries was determined and the capacities of the region’s refineries were assessed. The quantitative analysis method is used as a tool. The port infrastructure and the oil trunk pipeline system capacity were assessed in terms of delivery of raw materials to the refineries. The main groups of oil consuming countries were determined. The trends of crude oil production in the region were reviewed. The changes in production capacities and volumes at refineries in the last decade were shown. Based on the revealed refining trends, the scope of possible crude oil supplies to the refineries of the region under review was forecast. The existing transport infrastructure is able to handle the increased oil flow.

Keywords: European region, infrastructure, oil terminal capacity, pipeline capacity, refinery capacity, tanker draft

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Authors: Raheb Mirzanamadi, João Patrício

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Asphalt rubber (AR) was initially developed in Sweden in the 1960s by replacing crumb rubber (CR) as aggregates in asphalt pavement. The AR produced by this method had better mechanical properties than conventional asphalt pavement but was very expensive. Since then, different technologies and methods have been developed to use CR in asphalt pavements, including blending CR with bitumen at a high temperature in the mixture, called the wet method, and blending CR with bitumen in the refinery, called the terminal blending method. In 2006, the wet method was imported from the USA to Sweden to evaluate the potential of using AR on Swedish roads. 154 km AR roads were constructed by the wet method in Sweden. The evaluation showed that the AR had, in most cases, better mechanical performance than conventional asphalt pavements. However, the terrible smoke and smell led the Swedish Transport Administration (STA) to stop using AR in Sweden. Today, there are few focuses on AR, despite its good mechanical properties and environmental aspects. Hence, there is a need to study the drives and barriers of using AR mixture in Sweden. The aims of this paper are: (i) to study drivers and barriers of using AR pavements in Sweden and (ii) to discover knowledge gaps for further research in this area. The study was done using a literature review and completed by interviews with experts, including three researchers from Swedish National Road and Transport Research Institute (VTI) and two experts from STA. The results showed that AR can be an alternative not only for conventional asphalt pavement but also for polymer modified asphalt (PMA) due to the same mechanical properties but the lower cost for production. New technologies such as terminal blending and using warm mix asphalt (WMA) methods can lead to reducing the energy and temperature during production processes. From this study, it is found that there is not enough experience and knowledge about AR in Sweden, and more research is needed, including the lifespan of AR, mechanical properties of AR using new technologies, and the impact of AR on spreading and leaching substances into nature. More studies can lead to standardization of using AR in Sweden, a potential solution for the use of end-of-life tyres, with better mechanical properties and lower costs, in comparison with conventional asphalt pavements and PMA.

Keywords: asphalt rubber, crumb rubber, terminal blending method, wet method

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Authors: Claudio L. M. Souza, Milton Erthal, Aldo Shimoya, Elias R. Goncalves, Igor C. Rangel, Allysson R. T. Tavares, Elias G. Figueira

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The process of choosing a region for the implementation of wind farms involves factors such as the wind regime, economic viability, land value, topography, and accessibility. This work presents results obtained by multi-criteria decision analysis, and it establishes a hierarchy, regarding the installation of wind farms, among geopolicy regions in the state of ‘Rio de Janeiro’, Brazil: ‘Regiao Norte-RN’, ‘Regiao dos Lagos-RL’ and ‘Regiao Serrana-RS’. The wind regime map indicates only these three possible regions with an average annual wind speed of above of 6.0 m/s. The method applied was the Analytical Hierarchy Process-AHP, designed to prioritize and rank the three regions based on four criteria as follows: 1) potential of the site and average wind speeds of above 6.0 ms-¹, 2) average land value, 3) distribution and interconnection to electric network with the highest number of electricity stations, and 4) accessibility with proximity and quality of highways and flat topography. The values of energy generation were calculated for wind turbines 50, 75, and 100 meters high, considering the production of site (GWh/Km²) and annual production (GWh). The weight of each criterion was attributed by six engineers and by analysis of Road Map, the Map of the Electric System, the Map of Wind Regime and the Annual Land Value Report. The results indicated that in 'RS', the demand was estimated at 2,000 GWh, so a wind farm can operate efficiently in 50 m turbines. This region is mainly mountainous with difficult access and lower land value. With respect to ‘RL’, the wind turbines have to be installed at a height of 75 m high to reach a demand of 6,300 GWh. This region is very flat, with easy access, and low land value. Finally, the ‘NR’ was evaluated as very flat and with expensive lands. In this case, wind turbines with 100 m can reach an annual production of 19,000 GWh. In this Region, the coast area was classified as of greater logistic, productivity and economic potential.

Keywords: AHP, renewable energy, wind energy

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Authors: Xianping Du, Runlu Miao, Guanjun Zhang, Libo Cao, Feng Zhu

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Current vehicle safety standards and human body injury criteria were established based on the biomechanical response of Euro-American human body, without considering the difference in the body anthropometry and injury characteristics among different races, particularly the East Asian people with smaller body size. Absence of such race specific design considerations will negatively influence the protective performance of safety products for these populations, and weaken the accuracy of injury thresholds derived. To resolve these issues, in this study, we aim to develop a race specific finite element model to simulate the impact response of the lower extremity of a 50th percentile East Asian (Chinese) male. The model was built based on medical images for the leg of an average size Chinese male and slightly adjusted based on the statistical data. The model includes detailed anatomic features and is able to simulate the muscle active force. Thirteen biomechanical tests available in the literature were used to validate its biofidelity. Using the validated model, a pedestrian-car impact accident taking place in China was re-constructed computationally. The results show that the newly developed lower leg model has a good performance in predicting dynamic response and tibia fracture pattern. An additional comparison on the fracture tolerance of the East Asian and Euro-American lower limb suggests that the current injury criterion underestimates the degree of injury of East Asian human body.

Keywords: lower limb, East Asian body characteristics, traffic accident reconstruction, finite element analysis, injury tolerance

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Bingying Liu, Dandong Ge, Xinlan Zhang, Haoyang Liang

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Over the past two years, a new generation of No-Pile Bike sharing, represented by the Ofo, Mobike and HelloBike, has sprung up in various cities in China, and spread rapidly in countries such as Britain, Japan, the United States and Singapore. As a new green public transportation mode, bike sharing can bring a series of benefits to urban space. At first, this paper analyzes the specific impact of bike sharing on urban space in China. Based on the market research and data analyzing, it is found that bike sharing can improve the quality of urban space in three aspects: expanding the radius of public transportation service, filling service blind spots, alleviating urban traffic congestion, and enhancing the vitality of urban space. On the other hand, due to the immature market and the imperfect system, bike sharing has gradually revealed some difficulties, such as parking chaos, malicious damage, safety problems, imbalance between supply and demand, and so on. Then the paper investigates the characteristics of shared bikes, business model, operating mechanism on Chinese market currently. Finally, in order to make bike sharing serve urban construction better, this paper puts forward some specific countermeasures from four aspects. In terms of market operations, it is necessary to establish a public-private partnership model and set up a unified bike-sharing integrated management platform. From technical methods level, the paper proposes to develop an intelligent parking system for regulating parking. From policy formulation level, establishing a bike-sharing assessment mechanism would strengthen supervision. As to urban planning, sharing data and redesigning slow roadway is beneficial for transportation and spatial planning.

Keywords: bike sharing, impact analysis, improvement strategy, urban space

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Authors: Yu-Cheng Chen, Tzu-Ping Lin, Feng-Yi Lin, Chih-Yu Chen

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Due to the urban heat island effect caused by highly development of city, the heat stress increased in recent year rapidly. Resulting in a sharp raise of the energy used in urban area. The heat stress during summer time exacerbated the usage of air conditioning and electric equipment, which caused more energy consumption and anthropogenic heat. Therefore, an accurate and simple method to measure energy used in urban area can be helpful for the architectures and urban planners to develop better energy efficiency goals. This research applies the combination of airborne LiDAR data and thermal imager to provide an innovate method to estimate energy consumption. Owing to the high resolution of remote sensing data, the accurate current volume and total floor area and the surface temperature of building derived from LiDAR and thermal imager can be herein obtained to predict energy used. In the estimate process, the LiDAR data will be divided into four type of land cover which including building, road, vegetation, and other obstacles. In this study, the points belong to building were selected to overlay with the land use information; therefore, the energy consumption can be estimated precisely with the real value of total floor area and energy use index for different use of building. After validating with the real energy used data from the government, the result shows the higher building in high development area like commercial district will present in higher energy consumption, caused by the large quantity of total floor area and more anthropogenic heat. Furthermore, because of the surface temperature can be warm up by electric equipment used, this study also applies the thermal image of building to find the hot spots of energy used and make the estimation method more complete.

Keywords: urban heat island, urban planning, LiDAR, thermal imager, energy consumption

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Authors: Mahmoud F. Mohamadin, Ahmed Abdel Malek, Wessam Said

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Achieving energy efficient architecture in general, and in emerging countries in particular, is a challenging process that requires the contribution of various governmental, institutional, and individual entities. The rule of architectural design is essential in this process as it is considered as one of the earliest steps on the road to sustainability. Architectural firms have a moral and professional responsibility to respond to these challenges and deliver buildings that consume less energy. This study aims to evaluate the design processes and tools in practice of Egyptian architectural firms based on a limited survey to investigate if their processes and methods can lead to projects that meet the Egyptian Code of Energy Efficiency Improvement. A case study of twenty architectural firms in Cairo was selected and categorized according to their scale; large-scale, medium-scale, and small-scale. A questionnaire was designed and distributed to the firms, and personal meetings with the firms’ representatives took place. The questionnaire answered three main points; the design processes adopted, the usage of performance-based simulation tools, and the usage of BIM tools for energy efficiency purposes. The results of the study revealed that only little percentage of the large-scale firms have clear strategies for building energy efficiency in their building design, however the application is limited to certain project types, or according to the client request. On the other hand, the percentage of medium-scale firms is much less, and it is almost absent in the small-scale ones. This demonstrates the urgent need of enhancing the awareness of the Egyptian architectural design community of the great importance of implementing these methods starting from the early stages of the building design. Finally, the study proposed recommendations for such firms to be able to create a healthy built environment and improve the quality of life in emerging countries.

Keywords: architectural firms, emerging countries, energy efficiency, performance-based simulation tools

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Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Nima Safaei, Arezoo Masoud, Babak Safaei

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In recent years, there has been a growing emphasis on the role of urban planning in walking capability and the effects of individual and socioeconomic factors on the physical activity levels of city dwellers. Although considerable number of studies are conducted about walkability and for identifying the effective factors in walking mode choice in developed countries, to our best knowledge, literature lacks in the study of factors affecting choice of walking mode in developing countries. Due to the high importance of health aspects of human societies and in order to make insights and incentives for reducing traffic during rush hours, many researchers and policy makers in the field of transportation planning have devoted much attention to walkability studies; they have tried to improve the effective factors in the choice of walking mode in city neighborhoods. In this study, effective factors in walkability that have proven to have significant impact on the choice of walking mode, are studied at the same time in work trips. The data for the study is collected from the employees in their workplaces by well-instructed people using questionnaires; the statistical population of the study consists of 117 employed people who commute daily from work to home in Rasht city of Iran during the beginning of spring 2015. Results of the study which are found through the linear regression modeling, show that people who do not have freedom of choice for choosing their living locations and need to be present at their workplaces in certain hours have lower levels of walking. Additionally, unlike some of the previous studies which were conducted in developed countries, coincidental effects of Body Mass Index (BMI) and the income level of employees, do not have a significant effect on the walking level in work travels.

Keywords: BMI, linear regression, transportation, walking, work trips

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Authors: Anjana R. Menon, Anjana Bhasi

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Development of highways and railways play crucial role in a nation’s economic growth. While rigid concrete pavements are durable with high load bearing characteristics, growing economies mostly rely on flexible pavements which are easier in construction and more economical. The strength of flexible pavement is based on the strength of subgrade and load distribution characteristics of intermediate granular layers. In this scenario, to simultaneously meet economy and strength criteria, it is imperative to strengthen and stabilize the load transferring layers, namely subbase and base. Geosynthetic reinforcement in planar and cellular forms have been proven effective in improving soil stiffness and providing a stable load transfer platform. Studies have proven the relative superiority of cellular form-geocells over planar geosynthetic forms like geogrid, owing to the additional confinement of infill material and pocket effect arising from vertical deformation. Hence, the present study investigates the efficiency of geocells over single/multiple layer geogrid reinforcements by a series of three-dimensional model analyses of a flexible pavement section under a standard repetitive wheel load. The stress transfer mechanism and deformation profiles under various reinforcement configurations are also studied. Geocell reinforcement is observed to take up a higher proportion of stress caused by the traffic loads compared to single and double-layer geogrid reinforcements. The efficiency of single geogrid reinforcement reduces with an increase in embedment depth. The contribution of lower geogrid is insignificant in the case of the double-geogrid reinforced system.

Keywords: Geocell, Geogrid, Flexible Pavement, Repetitive Wheel Load, Numerical Analysis

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Authors: Daria Pashneva, Julija Pauraite, Agne Minderyte, Vadimas Dudoitis, Lina Davuliene, Kristina Plauskaite, Inga Garbariene, Steigvile Bycenkiene

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Black carbon (BC) has received particular attention around the world, not only for its impact on regional and global climate change but also for its impact on air quality and public health. In order to study the relationship between indoor and outdoor BC concentrations, studies were carried out in Vilnius, Lithuania. The studies are aimed at determining the relationship of concentrations, identifying dependencies during the day and week with a further opportunity to analyze the key factors affecting the indoor concentration of BC. In this context, indoor and outdoor continuous real-time measurements of optical BC-related light absorption by aerosol particles were carried out during the cold season (from October to December 2020). The measurement venue was an office located in an urban background environment. Equivalent black carbon (eBC) mass concentration was measured by an Aethalometer (Magee Scientific, model AE-31). The optical transmission of carbonaceous aerosol particles was measured sequentially at seven wavelengths (λ= 370, 470, 520, 590, 660, 880, and 950 nm), where the eBC mass concentration was derived from the light absorption coefficient (σab) at 880 nm wavelength. The diurnal indoor eBC mass concentration was found to vary in the range from 0.02 to 0.08 µgm⁻³, while the outdoor eBC mass concentration - from 0.34 to 0.99 µgm⁻³. Diurnal variations of eBC mass concentration outdoor vs. indoor showed an increased contribution during 10:00 and 12:00 AM (GMT+2), with the highest indoor eBC mass concentration of 0.14µgm⁻³. An indoor/outdoor eBC ratio (I/O) was below one throughout the entire measurement period. The weekend levels of eBC mass concentration were lower than in weekdays for indoor and outdoor for 33% and 28% respectively. Hourly mean mass concentrations of eBC for weekdays and weekends show diurnal cycles, which could be explained by the periodicity of traffic intensity and heating activities. The results show a moderate influence of outdoor eBC emissions on the indoor eBC level.

Keywords: black carbon, climate change, indoor air quality, I/O ratio

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Authors: Ballari Bagchi

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The dynamism ingrained in the process of urban-rural integration is manifested in the emergence of rurban settlements, referring to areas that combine the characteristics of agricultural activities found in rural zones with those of suburban living areas and industrialised zones. The concept of rurbanisation refers to the idea of introducing urban conveniences and opportunities, to rural areas in an attempt to stem rural urban migration. In the backdrop of the worldwide problem of disharmonised urban-rural dependence and the associated problems in urban and rural areas, the present study seeks to explore the potentialities of few settlements having a blend of rural and urban characteristics in the urban field of Koch Bihar. The prime concern of the present paper is three-fold: (i) to identify the rurban centres, (ii) to analyse the spatial integration of these identified centres with the rural areas situated in the urban periphery, and (iii) to suggest the necessities to be introduced in these settlements. The methodology applied here includes rurban index, gravity model, and functional classification of rurban centres, correlation and regression analysis and cartographic representation of data collected through primary and secondary sources. The investigation has identified a number of settlements potentially viable to be termed as rurban centres which may render services to the other less equipped rural areas in all aspects of life and thereby would lessen the burden on Koch Bihar urban centre. The levels of infrastructure of these settlements should be such that it might even attract the urban population in a reverse direction. The villages belonging to the lower rung of these service settlements would require metalled road connection with these intermediate settlements in addition to their connection with the core town. That is to say, a proper policy needs to be adopted in this regard to furnish these settlements with required infrastructures for serving their own population as well as the population of other villages. As a consequence of that, the idea of a well-coordinated settlement hierarchy may emerge in future.

Keywords: Hinterland, rurban, settlement hierarchy, urban-rural integration

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Authors: S. Cafiso, B. Capace, A. Di Graziano, C. D’Agostino

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Systematic monitoring of the trackbed is necessary to assure safety and quality of service in the railway system. Moreover, to produce effective management of the maintenance treatments, the assessment of bearing capacity of the railway trackbed must include ballast, sub-ballast and subgrade layers at different depths. Consequently, there is an increasing interest in obtaining a consistent measure of ballast bearing capacity with no destructive tests (NDTs) able to work in the physical and time restrictions of railway tracks in operation. Moreover, in the case of the local railway with reduced gauge, the use of the traditional high-speed track monitoring systems is not feasible. In that framework, this paper presents results from in site investigation carried out on ballast and sleepers with Ground Penetrating Radar (GPR) and Light Falling Weight Deflectometer (LWD). These equipment are currently used in road pavement maintenance where they have shown their reliability and effectiveness. Application of such Non-Destructive Tests in railway maintenance is promising but in the early stage of the investigation. More specifically, LWD was used to estimate the stiffness of ballast and sleeper support, as well. LWD, despite the limited load (6 kN in the trial test) applied directly on the sleeper, was able to detect defects in the bearing capacity at the Sleeper/Ballast interface. A dual frequency GPR was applied to detect the presence of layers’ discontinuities at different depths due to fouling phenomena that are the main causes of changing in the layer dielectric proprieties within the ballast thickness. The frequency of 2000Mhz provided high-resolution data to approximately 0.4m depth, while frequency of 600Mhz showed greater depth penetration up to 1.5 m. In the paper literature review and trial in site experience are used to identify Strengths, Weaknesses, Opportunities, and Threats (SWOT analysis) of the application of GPR and LWD for the assessment of bearing capacity of railway track-bed.

Keywords: bearing capacity, GPR, LWD, no destructive test, railway track

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Authors: Diya Sarkar, Prafulla C. Mishra

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In a parliamentary system, party discipline is the impulse; when it falls short, the government usually falls. Conceivably, the platform of Indian politics suffers with innumerous practical disorders. The politics of defection is one such specie entailing gross miscarriage of fair conduct turning politics into a game of thrones (powers). This practice of political nomaditude can trace its seed in the womb of British House of Commons. Therein, if a legislator was found to cross the floor, the party considered him disloyal. In other words, the legislator lost his allegiance to his former party by joining another party. This very phenomenon, in practice has a two way traffic i.e. ruling party to the opposition party or vice versa. The democracies like USA, Australia and Canada were also aware of this fashion of swapping loyalties. There have been several instances of great politicians changing party allegiance, for example Winston Churchill, Ramsay McDonald, William Gladstone etc. Nevertheless, it is interesting to cite that irrespective of such practice of changing party allegiance, none of the democracies in the west ever desired or felt the need to legislatively ban defections. But, exceptionally India can be traced to have passed anti-defection laws. The politics of defection had been a unique popular phenomenon on the floor of Indian Parliamentary system gradually gulping the democratic essence and synchronization of the Federation. This study is both analytical and doctrinal, which tries to examine whether representative democracy has lost its essence due to political nomadism. The present study also analyzes the classical as well as contemporary pulse of floor crossing amidst dynastic politics in a representative democracy. It will briefly discuss the panorama of defections under the Indian federal structure in the light of the anti-defection law and an attempt has been made to add valuable suggestions to streamline remedy for the still prevalent political defections.

Keywords: constitutional law, defection, democracy, polarization, political anti-trust

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Authors: Lokman Gozcu, Sule Deniz Gozcu

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This study aims to analyze the skills of speaking in the acquisition of Turkish as a foreign language. One of the most important things for the individual who learns a foreign language is to be successful in the oral communication (speaking) skills and to interact in an understandable way. Speech skill requires much more time and effort than other language skills. In this direction, it is necessary to make an analysis of these oral communication skills, which is important in Turkish language acquisition as a foreign language and to draw out a road map according to the result. The aim of this study is to determine the competence and attitudes of speaking competence according to the individuals who learn Turkish as a foreign language and to be considered as speaking skill elements; Grammar, emphasis, intonation, body language, speed, ranking, accuracy, fluency, pronunciation, etc. and the results and suggestions based on these determinations. A mixed method has been chosen for data collection and analysis. A Likert scale (for competence and attitude) was applied to 190 individuals who were interviewed face-to-face (for speech skills) with a semi-structured interview form about 22 participants randomly selected. In addition, the observation form related to the 22 participants interviewed were completed by the researcher during the interview, and after the completion of the collection of all the voice recordings, analyses of voice recordings with the speech skills evaluation scale was made. The results of the research revealed that the speech skills of the individuals who learned Turkish as a foreign language have various perspectives. According to the results, the most inadequate aspects of the participants' ability to speak in Turkish include vocabulary, using humorous elements while speaking Turkish, being able to include items such as idioms and proverbs while speaking Turkish, Turkish fluency respectively. In addition, the participants were found not to feel comfortable while speaking Turkish, to feel ridiculous and to be nervous while speaking in formal settings. There are conclusions and suggestions for the situations that arise after the have been analyses made.

Keywords: learning Turkish as a foreign language, proficiency criteria, phonetic (modalities), speaking skills

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Authors: Umashankar Morya, Somnath Basu

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Metalloids like arsenic are often present as contaminants in industrial effluents. Removal of the same is essential before the safe discharge of the wastewater into the environment. Otherwise, these pollutants tend to percolate into aquifers over a period of time and contaminate drinking water sources. Several adsorbents, including metal powders, carbon nanotubes and zeolites, are being used for this purpose, with varying degrees of success. However, most of these solutions are not only costly but also not always readily available. This restricts their use, especially among financially weaker communities. Slag generated globally from primary steelmaking operations exceeds 200 billion kg every year. Some of it is utilized for applications like road construction, filler in reinforced concrete, railway track ballast and recycled into iron ore agglomeration processes. However, these usually involve low-value addition, and a significant amount of the slag still ends up in a landfill. However, there is a strong possibility that the constituents in the steelmaking slag may immobilize metalloid contaminants present in wastewater through a combination of adsorption and precipitation of insoluble product(s). Preliminary experiments have already indicated that exposure to basic oxygen steelmaking slag does reduce pollutant concentration in wastewater. In addition, the slag is relatively inexpensive and available in large quantities and in several countries across the world. Investigations on the mechanism of interactions at the water-solid interfaces have been in progress for some time. However, at the same time, there are concerns about the possibility of leaching of metal ions from the slag particles in concentrations greater than what exists in the water bodies where the “treated” wastewater would eventually be discharged. The effect of such leached ions on the aquatic flora and fauna is yet uncertain. This has prompted the present investigation, which focuses on the leaching of metal ions from steelmaking slag particles in contact with wastewater, and the influence of these ions on the removal of contaminant species. Experiments were carried out to quantify the leaching behavior of different ionic species upon exposure of the slag particles to simulated wastewater, both with and without specific metalloid contaminants.

Keywords: slag, water, metalloid, heavy metal, wastewater

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Authors: Awais Ahmed, Javed Iqbal

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Pakistan has been for many years facing extreme challenges in energy deficit due to the shortage of power generation compared to increasing demand. A part of this energy deficit is also contributed by the power lost in transmission and distribution network. Unfortunately, distribution companies are not equipped with modern technologies and methods to identify and eliminate these losses. According to estimate, total energy lost in early 2000 was between 20 to 26 percent. To address this issue the present research study was designed with the objectives of developing a standalone GIS application for distribution companies having the capability of loss calculation as well as identification of overloaded transformers. For this purpose, Hilal Road feeder in Faisalabad Electric Supply Company (FESCO) was selected as study area. An extensive GPS survey was conducted to identify each consumer, linking it to the secondary pole of the transformer, geo-referencing equipment and documenting conductor sizes. To identify overloaded transformer, accumulative kWH reading of consumer on transformer was compared with threshold kWH. Technical losses of 11kV and 220V lines were calculated using the data from substation and resistance of the network calculated from the geo-database. To automate the process a standalone GIS application was developed using ArcObjects with engineering analysis capabilities. The application uses GIS database developed for 11kV and 220V lines to display and query spatial data and present results in the form of graphs. The result shows that about 14% of the technical loss on both high tension (HT) and low tension (LT) network while about 4 out of 15 general duty transformers were found overloaded. The study shows that GIS can be a very effective tool for distribution companies in management and planning of their distribution network.

Keywords: geographical information system, GIS, power distribution, distribution transformers, technical losses, GPS, SDSS, spatial decision support system

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