Search results for: parking demand forecast

Authors: Timothy Akinwande, Eddie Hui, Karien Dekker

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Housing the urban poor remains a persistent challenge, despite evident research attention over many years. It is, therefore, pertinent to investigate affordable housing provision challenges with novel approaches. For innovative solutions to affordable housing constraints, it is apposite to thoroughly examine housing solutions vis a vis the key elements of the housing supply value chain (HSVC), which are housing finance, housing construction and land acquisition. A pragmatic analysis will examine affordable housing solutions from demand and supply perspectives to arrive at consolidated solutions from bilateral viewpoints. This study thoroughly examined informal housing finance strategies of the urban poor and diligently investigated expert opinion on affordable housing finance solutions. The research questions were: (1) What mutual grounds exist between informal housing finance solutions of the urban poor and housing expert solutions to affordable housing finance constraints in developing economies? (2) What are effective approaches to affordable housing finance in developing economies from an integrated demand - supply perspective? Semi-structured interviews were conducted in the 5 largest slums of Lagos, Nigeria, with 40 informal settlers for demand-oriented solutions, while focus group discussion and in-depth interviews were conducted with 12 housing experts in Nigeria for supply-oriented solutions. Following a rigorous thematic, content and descriptive analyses of data using NVivo and Excel, findings ascertained mutual solutions from both demand and supply standpoints that can be consolidated into more effective affordable housing finance solutions in Nigeria. Deliberate finance models that recognise and include the finance realities of the urban poor was found to be the most significant supply-side housing finance solution, representing 25.4% of total expert responses. Findings also show that 100% of sampled urban poor engage in vocations where they earn little irregular income or zero income, limiting their housing finance capacities and creditworthiness. Survey revealed that the urban poor are involved in community savings and employ microfinance institutions within the informal settlements to tackle their housing finance predicaments. These are informal finance models of the urban poor, revealing common grounds between demand and supply solutions for affordable housing financing. Effective, affordable housing approach will be to modify, institutionalise and incorporate the informal finance strategies of the urban poor into deliberate government policies. This consolidation of solutions from demand and supply perspectives can eliminate the persistent misalliance between affordable housing demand and affordable housing supply. This study provides insights into mutual housing solutions from demand and supply perspectives, and findings are informative for effective, affordable housing provision approaches in developing countries. This study is novel in consolidating affordable housing solutions from demand and supply viewpoints, especially in relation to housing finance as a key component of HSVC. The framework for effective, affordable housing finance in developing economies from a consolidated viewpoint generated in this study is significant for the achievement of sustainable development goals, especially goal 11 for sustainable, resilient and inclusive cities. Findings are vital for future housing studies.

Keywords: affordable housing, affordable housing finance, developing economies, effective affordable housing, housing policy, urban poor, sustainable development goal, sustainable affordable housing

Procedia PDF Downloads 64

Authors: Racha El Kadiri, Mohamed Sultan, Henrique Momm, Zachary Blair, Rachel Schultz, Tamer Al-Bayoumi

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The Mediterranean Basin is a very diverse region of nationalities and climate zones, with a strong dependence on agricultural activities. Predicting long term (with a lead of 1 to 12 months) rainfall, and future droughts could contribute in a sustainable management of water resources and economical activities. In this study, an integrated approach was adopted to construct predictive tools with lead times of 0 to 12 months to forecast rainfall amounts over nine subzones of the Mediterranean Basin region. The following steps were conducted: (1) acquire, assess and intercorrelate temporal remote sensing-based rainfall products (e.g. The CPC Merged Analysis of Precipitation [CMAP]) throughout the investigation period (1979 to 2016), (2) acquire and assess monthly values for all of the climatic indices influencing the regional and global climatic patterns (e.g., Northern Atlantic Oscillation [NOI], Southern Oscillation Index [SOI], and Tropical North Atlantic Index [TNA]); (3) delineate homogenous climatic regions and select nine pilot study zones, (4) apply data mining methods (e.g. neural networks, principal component analyses) to extract relationships between the observed rainfall and the controlling factors (i.e. climatic indices with multiple lead-time periods) and (5) use the constructed predictive tools to forecast monthly rainfall and dry and wet periods. Preliminary results indicate that rainfall and dry/wet periods were successfully predicted with lead zones of 0 to 12 months using the adopted methodology, and that the approach is more accurately applicable in the southern Mediterranean region.

Keywords: rainfall, neural networks, climatic indices, Mediterranean

Procedia PDF Downloads 310

Authors: B. Chikh, L. Moussa, H. Bechtoula, Y. Mehani, A. Zerzour

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This study presents a new method, applicable to evaluation and design of structures has been developed and illustrated by comparison with the capacity spectrum method (CSM, ATC-40). This method uses inelastic spectra and gives peak responses consistent with those obtained when using the nonlinear time history analysis. Hereafter, the seismic demands assessment method is called in this paper DSM, Ductility Spectrum Method. It is used to estimate the seismic deformation of Single-Degree-Of-Freedom (SDOF) systems based on DDRS, Ductility Demand Response Spectrum, developed by the author.

Keywords: seismic demand, capacity, inelastic spectra, design and structure

Procedia PDF Downloads 391

Authors: Ira Joseph

Abstract:

The LNG paradox addresses the issue of how the most expensive form of gas supply, which is LNG, will grow in an end user market where demand is most competitive, which is power generation. In this case, LNG demand growth is under siege from two entirely different directions. At one end is price; it will be extremely difficult for gas to replace coal in Asia due to the low price of coal and the age of the generation plants. Asia's coal fleet, on average, is less than two decades old and will need significant financial incentives to retire before its state lifespan. While gas would cut emissions in half relative to coal, it would also more than double the price of the fuel source for power generation, which puts it in a precarious position. In most countries in Asia other than China, this cost increase, particularly from imports, is simply not realistic when it is also necessary to focus on economic growth and social welfare. On the other end, renewables are growing at an exponential rate for three reasons. One is that prices are dropping. Two is that policy incentives are driving deployment, and three is that China is forcing renewables infrastructure into the market to take a political seat at the global energy table with Saudi Arabia, the US, and Russia. Plus, more renewables will lower import growth of oil and gas in China, if not end it altogether. Renewables are the predator at the gate of gas demand in power generation and in every year that passes, renewables cut into demand growth projections for gas; in particular, the type of gas that is most expensive, which is LNG. Gas does have a role in the future, particularly within a domestic market. Once it crosses borders in the form of LNG or even pipeline gas, it quickly becomes a premium fuel and must be marketed and used this way. Our research shows that gas will be able to compete with batteries as an intermittency and storage tool and does offer a method to harmonize with renewables as part of the energy transition. As a baseload fuel, however, the role of gas, particularly, will be limited by cost once it needs to cross a border. Gas converted into blue or green hydrogen or ammonia is also an option for storage depending on the location. While this role is much reduced from the primary baseload role that gas once aspired to land, it still offers a credible option for decades to come.

Keywords: natural gas, LNG, demand, price, intermittency, storage, renewables

Procedia PDF Downloads 55

Authors: Dilupa Nakandala, Henry Lau

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Ever increasing demand for cost efficiency and customer satisfaction through reliable delivery have been a mandate for logistics practitioners to continually improve inventory management processes. With the cost optimization objectives, this study considers an extended scenario where sourcing from the same echelon of the supply chain, known as lateral transshipment which is instantaneous but more expensive than purchasing from regular suppliers, is considered by warehouses not only to re-actively fulfill the urgent outstanding retailer demand that could not be fulfilled by stock on hand but also for preventively reduce back-order cost. Such extra lateral trans-shipments as preventive responses are intended to meet the expected demand during the supplier lead time in a periodic review ordering policy setting. We develop decision rules to assist logistics practitioners to make cost optimized selection between back-ordering and combined reactive and proactive lateral transshipment options. A method for determining the optimal quantity of extra lateral transshipment is developed considering the trade-off between purchasing, holding and backorder cost components.

Keywords: lateral transshipment, warehouse inventory management, cost optimization, preventive transshipment

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Authors: Ahmad Samim Ranjbar, Shoshi Mizokami

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Kabul is the heart of political, commercial, cultural, educational and social life in Afghanistan and the Kabul fifth fastest growing city in the world, since 2001 with the establishment of new government Lack of adequate employment opportunities and basic utility services in remote provinces have prompted people to move to Kabul and other urban areas. From 2001 to the present, a rapid increase in population, and also less income of the people most of residence tend to use public transport, especially buses, however there is no proper bus system exist in Kabul city, because of wars, from 1992 to 2001 Kabul suffered damage and destruction of its transportation facilities including pavements, sidewalks, traffic circles, drainage systems, traffic signs and signals, trolleybuses and almost all of the public transit buses (e.g. Millie bus). This research is a primary and very important phase into Kabul city transportation and especially an initial and important step toward using large bus in Kabul city, which the main purpose of this research is to find the demand of Kabul city residence for public transport (Large Bus) and compare it with the actual supply from government. Finding of this research shows that the demand of Kabul city residence for the public transport (Large Bus) exceed the supply from the government, means that current public transportation (Large Bus) is not sufficient to serve people of Kabul city, it is mentionable that according to this research there is no need to build a new road or exclusive way for bus, this research propose to government for investment on the public transportation and exceed the number of large buses to can handle the current demand for public transport.

Keywords: transportation, planning, public transport, large bus, Kabul, Afghanistan

Procedia PDF Downloads 293

Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

Procedia PDF Downloads 71

Authors: Federico Valenzuela-Beltran, Sonia E. Ruiz, Alfredo Reyes-Salazar, Juan Bojorquez

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A reliability-based methodology which uses structural demand hazard curves to consider the increment of the ductility demands of structures with tilting is proposed. The approach considers the effect of two orthogonal components of the ground motions as well as the influence of soil-structure interaction. The approach involves the calculation of ductility demand hazard curves for symmetric systems and, alternatively, for systems with different degrees of asymmetry. To get this objective, demand hazard curves corresponding to different global ductility demands of the systems are calculated. Next, Uniform Exceedance Rate Spectra (UERS) are developed for a specific mean annual rate of exceedance value. Ratios between UERS corresponding to asymmetric and to symmetric systems located in soft soil of the valley of Mexico are obtained. Results indicate that the ductility demands corresponding to tilted structures may be several times higher than those corresponding to symmetric structures, depending on several factors such as tilting angle and vibration period of structure and soil.

Keywords: asymmetric yielding, seismic performance, structural reliability, tilted structures

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Authors: Aydin Sipahioglu, Gokhan Celik

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Helicopter routing problem (HRP) is finding good tours for helicopter so as to pick up and deliver personnel or material among specified nodes, mutually. It can be encountered in case of being lots of supply and demand points for different commodities and requiring delivering commodities with helicopter. For instance, to deliver personnel or material from shore to oil rig is a good example. In fact, HRP is a branch of vehicle routing problem with pickup and delivery (VRPPD). However, it has additional constraints such that fuel capacity, performance of helicopter in different altitude and temperature, and the number of maximum takeoff and landing allowed. This kind of pickup and delivery problems can be classified into 3 groups, basically. 1-1 (one to one), M-M (many to many) and 1-M-1 (one to many to one). 1-1 means each commodity has only one supply and one demand point. M-M means there can be more than one supply and demand points for each kind of commodity. 1-M-1 means commodities at depot are delivered to demand points and commodities at customers are delivered to depot. In this case helicopter takes off from its own base, complete its tour and return to its own base. In this study, we define 1-M-M-1 type HRP. That means helicopter takes off from its home base, deliver commodities among the nodes as well as between depot and customers and return to its home base. These problems have NP-hard nature. Therefore, obtaining a good solution in a reasonable time is not easy. In this study, a model is offered for 1-M-M-1 type HRP. It is shown on small scale test instances that the model can find the optimal solution.

Keywords: helicopter routing problem, vehicle routing with pickup and delivery, integer programming

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Authors: Zouari Ezzeddine, Ghraieb Ikram

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From the results of the academic literature which evokes the limitations of previous studies, this article shows the reasons for multidimensionality Prediction of financial bubbles. A new framework for modeling study predicting financial bubbles by linking a set of variable presented on several dimensions dictating its multidimensional character. It takes into account the preferences of financial actors. A multicriteria anticipation of the appearance of bubbles in international financial markets helps to fight against a possible crisis.

Keywords: classical measures, predictions, financial bubbles, multidimensional, artificial neural networks

Procedia PDF Downloads 571

Authors: Henri El Zakhem, Dona Shalhoub, Elias Atallah, Jessica Koura

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Due to the increase of demand on dietetic food and the need for more types of diet food, the production of dietetic food is increasing and improving. This demand on dietetic food has triggered us to study the market in which we found that Kishk (Lebanese dairy product) diet is not available. Production of a low fat product which is diet Kishk was our concern. A strategy was followed to choose the right idea that will satisfy the need of the market. The whole process was studied and explained thoroughly. The percentage of fat was found to be 32.52 % in regular Kishk and 3.84 % in the diet Kishk produced. The new product has the advantage to be high in protein, low in fat.

Keywords: design and industrialization, dietetic, diet Kishk, fat

Procedia PDF Downloads 370

Authors: Li Qiaoming

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The outbreak of Coronavirus disease 2019 (COVID-19) in early 2020 brought new opportunities to the development of the digital creative industry in China. Based on the realistic foundation of the development of the digital creative industry in China, an analysis was conducted on the mechanism of action of the pandemic on this industry from both sides of supply and demand by sorting out its concept, connotation, and related theories. To be specific, the demand side experienced changes due to the changes in the consumption habits of residents, the sharp increase in gross domestic time (GDT), the satisfaction of the psychological needs of users, search for substitutes for offline consumption, and other factors. An analysis was carried out on the mechanism of action of the pandemic on the digital creative industry from the production link, supply subjects, product characteristics, and transmission link of the supply side. Then, a detailed discussion was held on the manifestation forms of the impact of the pandemic from the dimensions of time and space. Finally, this paper discussed the main development focuses of the digital creative industry in the post-pandemic era from the aspects of the government, industries, and enterprises.

Keywords: COVID-19, demand and supply relationship, digital creative industries, industry shocks

Procedia PDF Downloads 148

Authors: Frezer Okubay Weldegebriel

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The tourism sector in Ethiopia plays a significant role in the national economy. The government is granting its pledge and readiness to develop this sector through various initiatives since to eradicate poverty and encourage economic development of the country is one of the Millennium Development plans. The tourism sector has been identified as one of the priority economic sectors by many countries, and the Government of Ethiopia has planned to make Ethiopia among the top five African destinations by 2020. Nevertheless, the international tourism demand for Ethiopia currently lags behind other African countries such as South Africa, Egypt, Morocco, Tanzania, and Kenya. Meanwhile, the number of international tourists’ arrival in Ethiopia is recently increasing even if it cannot be competitive with other African countries. Therefore, to offer demand-driven tourism products, the Ethiopian government, Tourism planners, Tour & Travel operators need to understand the important factors, which affect international tourists’ decision to visit Ethiopian destinations. This study was intended to analyze Italian Tourists Demand towards Ethiopian destination. The researcher aimed to identify the demand for Italian tourists’ preference to Ethiopian destinations comparing to the top East African countries. This study uses both qualitative and quantitative research methodology, and the data is manipulating through primary data collection method using questionnaires, interviews, and secondary data by reviewing books, journals, magazines, past researches, and websites. An active and potential Italian tourist cohort, five well-functioning tour operators based in Ethiopia for Italian tourists and professionals from Ethiopian Ministry of Tourism and Culture participated. Based on the analysis of the data collected through the questionnaire, interviews, and reviews of different materials, the study disclosed that the majority of Italian tourists have a high demand on Ethiopian Tourist destination. Historical and cultural interest, safety and security, the hospitality of the people and affordable accommodation coast are the main reason for them. However, some Italian tourists prefer to visit Kenya, Tanzania, and Uganda due to the fact that they are fascinated by adventure, safari and beaches, while Ethiopia cannot provide these attractions. Most Italian tourists have little information and practical experiences on Ethiopian tourism possibilities via a tour and travel companies. Moreover, the insufficient marketing campaign and promotion by Ethiopian Government and Ministry of Tourism could also contribute to the failure of Ethiopian tourism.

Keywords: The demand of Italian tourists, Ethiopia economy, Ethiopia tourism destination, promoting Ethiopia tourism

Procedia PDF Downloads 202

Authors: Carlos Fontanillas

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Brazil is going through a real revolution in the logistics area. It is increasingly common to find articles and news in this context, as companies begin to become aware that a good management of the areas that make up the logistics can bring excellent results in reducing costs and increasing productivity. With this, companies are investing more emphasis on reduced spending on storage and transport of their products to ensure competitiveness. The scope of this work is the analysis of the logistics of a restaurant and materials will be presented the best way to serve the customer, avoiding the interruption of production due to lack of materials; for it will be analyzed the supply chain in terms of acquisition costs, maintenance and service demand.

Keywords: ABC curve, logistic, productivity, supply chain

Procedia PDF Downloads 307

Authors: Diyono Harun

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Indonesia aims to reduce carbon emissions from energy generation by reaching 23% and 31% of the national energy supply from renewable energy sources (RES) in 2025 and 2030. The potential for RES in Indonesia is enormous, but not all province has the same potential for RES. Yogyakarta, one of the most travel-destinated provinces in Indonesia, has less potential than its neighbour, Central Java. Consequently, Yogyakarta must meet its electricity demand by importing electricity from Central Java if this province only wants to use electricity from RES. Thus, achieving the objective is balancing the electricity supply between an importer (Yogyakarta) and an exporter province (Central Java). This research aims to explore the RES potential and the current capacity of RES for electricity generation in both provinces. The results show that the present capacity of RES meets the annual domestic electricity demand in both provinces only with an extension of the RES potential. The renewable energy mixes in this research also can lower CO2 emissions compared to gas-fired power plants. This research eventually provides insights into exploring and using the domestic RES potentials between two areas with different RES capacities.

Keywords: energy mix, renewable energy sources, domestic electricity, electricity generation

Procedia PDF Downloads 83

Authors: Pappu Kumar, Ajai Singh, Anshuman Singh

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There are different water user sectors such as rural, urban, mining, subsistence and commercial irrigated agriculture, commercial forestry, industry, power generation which are present in the catchment in Subarnarekha River Basin and Ranchi city. There is an inequity issue in the access to water. The development of the rural area, construction of new power generation plants, along with the population growth, the requirement of unmet water demand and the consideration of environmental flows, the revitalization of small-scale irrigation schemes is going to increase the water demands in almost all the water-stressed catchment. The WEAP Model was developed by the Stockholm Environment Institute (SEI) to enable evaluation of planning and management issues associated with water resources development. The WEAP model can be used for both urban and rural areas and can address a wide range of issues including sectoral demand analyses, water conservation, water rights and allocation priorities, river flow simulation, reservoir operation, ecosystem requirements and project cost-benefit analyses. This model is a tool for integrated water resource management and planning like, forecasting water demand, supply, inflows, outflows, water use, reuse, water quality, priority areas and Hydropower generation, In the present study, efforts have been made to access the utility of the WEAP model for water supply and demand analysis for Ranchi city. A detailed works have been carried out and it was tried to ascertain that the WEAP model used for generating different scenario of water requirement, which could help for the future planning of water. The water supplied to Ranchi city was mostly contributed by our study river, Hatiya reservoir and ground water. Data was collected from various agencies like PHE Ranchi, census data of 2011, Doranda reservoir and meteorology department etc. This collected and generated data was given as input to the WEAP model. The model generated the trends for discharge of our study river up to next 2050 and same time also generated scenarios calculating our demand and supplies for feature. The results generated from the model outputs predicting the water require 12 million litter. The results will help in drafting policies for future regarding water supplies and demands under changing climatic scenarios.

Keywords: WEAP model, water demand analysis, Ranchi, scenarios

Procedia PDF Downloads 416

Authors: Esmeralda Hysenbelliu

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Over the last years, the demand for high bandwidth services, such as live (IPTV Service) and on-demand video streaming, steadily and rapidly increased. It has been predicted that video traffic (IPTV, VoD, and WEB TV) will account more than 90% of global Internet Protocol traffic that will cross the globe in 2016. Consequently, the importance and consideration on requirements and challenges of service providers faced today in supporting user’s requests for entertainment video across the various IPTV services through virtualization over Software Defined Networks (SDN), is tremendous in the highest stage of attention. What is necessarily required, is to deliver optimized live and on-demand services like Internet Protocol Service (IPTV Service) with low cost and good quality by strictly fulfill the essential requirements of Clients and ISP’s (Internet Service Provider’s) in the same time. The aim of this study is to present an overview of the important requirements and challenges of IPTV service with two network trends on solving challenges through virtualization (SDN and Network Function Virtualization). This paper provides an overview of researches published in the last five years.

Keywords: challenges, IPTV service, requirements, software defined networking (SDN)

Procedia PDF Downloads 268

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 121

Authors: Kristine Nore, Alexander Severnisen, Petter Arnestad, Dimitris Kraniotis, Roy Rossebø

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Natural materials like wood, absorb and release moisture. Thus wood can buffer indoor climate. When used wisely, this buffer potential can be used to counteract the outer climate influence on the building. The mass of moisture used in the buffer is defined as the potential hygrothermal mass, which can be an energy storage in a building. This works like a natural heat pump, where the moisture is active in damping the diurnal changes. In Norway, the ability of wood as a material used for climate buffering is tested in several buildings with the extensive use of wood, including supermarkets. This paper defines the potential of hygrothermal mass in a supermarket building. This includes the chosen ventilation strategy, and how the climate impact of the building is reduced. The building is located above the arctic circle, 50m from the coastline, in Valnesfjord. It was built in 2015, has a shopping area, including toilet and entrance, of 975 m². The climate of the area is polar according to the Köppen classification, but the supermarket still needs cooling on hot summer days. In order to contribute to the total energy balance, wood needs dynamic influence to activate its hygrothermal mass. Drying and moistening of the wood are energy intensive, and this energy potential can be exploited. Examples are to use solar heat for drying instead of heating the indoor air, and raw air with high enthalpy that allow dry wooden surfaces to absorb moisture and release latent heat. Weather forecasts are used to define the need for future cooling or heating. Thus, the potential energy buffering of the wood can be optimized with intelligent ventilation control. The ventilation control in Valnesfjord includes the weather forecast and historical data. That is a five-day forecast and a two-day history. This is to prevent adjustments to smaller weather changes. The ventilation control has three zones. During summer, the moisture is retained to dampen for solar radiation through drying. In the winter time, moist air let into the shopping area to contribute to the heating. When letting the temperature down during the night, the moisture absorbed in the wood slow down the cooling. The ventilation system is shut down during closing hours of the supermarket in this period. During the autumn and spring, a regime of either storing the moisture or drying out to according to the weather prognoses is defined. To ensure indoor climate quality, measurements of CO₂ and VOC overrule the low energy control if needed. Verified simulations of the Valnesfjord building will build a basic model for investigating wood as a climate regulating material also in other climates. Future knowledge on hygrothermal mass potential in materials is promising. When including the time-dependent buffer capacity of materials, building operators can achieve optimal efficiency of their ventilation systems. The use of wood as a climate regulating material, through its potential hygrothermal mass and connected to weather prognoses, may provide up to 25% energy savings related to heating, cooling, and ventilation of a building.

Keywords: climate buffer, energy, hygrothermal mass, ventilation, wood, weather forecast

Procedia PDF Downloads 210

Authors: Elad Harison

Abstract:

The paper identifies the complex links between post-COVID-19 inflationary pressures and global supply chains. Throughout the COVID-19 lockdowns and long periods after the termination of social distancing policies, consumers, notably in the U.S., have confronted and still face disruptions in the supply of goods. The study analyzes the monetary policy in the U.S. that led to the significant shift in consumer demand during a limited supply period, hence resulting in shortages and emphasizing inflationary dynamics. We argue that the monetary guidelines applied by the U.S. government further elevated the scope of supply chain disruptions.

Keywords: consumer demand, COVID-19, inflation, monetary policy, supply chain

Procedia PDF Downloads 89

Authors: Taha Benarbia, Kay W. Axhausen, Anugrah Ilahi

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Electric car sharing system as ecologic transportation increasing in the world. The complexity of managing electric car sharing systems, especially one-way trips and battery autonomy have direct influence to on supply and demand of system. One must be able to precisely model the demand and supply of these systems to better operate electric car sharing and estimate its effect on mobility management and the accessibility that it provides in urban areas. In this context, our work focus to develop performances optimization model of the system based on discrete event simulation and stochastic Petri net. The objective is to search optimal decisions and management parameters of the system in order to fulfil at best demand while minimizing undesirable situations. In this paper, we present new model of electric cars sharing with relocation based on monitoring system. The proposed approach also help to precise the influence of battery charging level on the behaviour of system as important decision parameter of this complex and dynamical system.

Keywords: electric car-sharing systems, smart mobility, Petri nets modelling, discrete event simulation

Procedia PDF Downloads 176

Authors: Su Sin Chong, Abdul Aziz Abdul Raman, Sulaiman Wadi Harun, Hamzah Arof

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Chemical Oxygen Demand (COD) plays a vital role determination of an appropriate strategy for wastewater treatment including the control of the quality of an effluent. In this study, a new sensing method was introduced for the first time and developed to investigate chemical oxygen demand (COD) using a Mach-Zehner Interferometer (MZI)-based dye sensor. The sensor is constructed by bridging two single mode fibres (SMF1 and SMF2) with a short section (~20 mm) of multimode fibre (MMF) and was formed by tapering the MMF to generate evanescent field which is sensitive to perturbation of sensing medium. When the COD concentration increase takes effect will induce changes in output intensity and effective refractive index between the microfiber and the sensing medium. The adequacy of decisions based on COD values relies on the quality of the measurements. Therefore, the dual output response can be applied to the analytical procedure enhance measurement quality. This work presents a detailed assessment of the determination of COD values in synthetic wastewaters. Detailed models of the measurement performance, including sensitivity, reversibility, stability, and uncertainty were successfully validated by proficiency tests where supported on sound and objective criteria. Comparison of the standard method with the new proposed method was also conducted. This proposed sensor is compact, reliable and feasible to investigate the COD value.

Keywords: chemical oxygen demand, environmental sensing, Mach-Zehnder interferometer sensor, online monitoring

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Authors: Muhammed Ordu, Eren Demir, Chris Tofallis

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The number of inpatient admissions in the UK has been significantly increasing over the past decade. These increases cause bed occupancy rates to exceed the target level (85%) set by the Department of Health in England. Therefore, hospital service managers are struggling to better manage key resource such as beds. On the other hand, this severe demand pressure might lead to confusion in wards. For example, patients can be admitted to the ward of another inpatient specialty due to lack of resources (i.e., bed). This study aims to develop a simulation-optimization model to reallocate the available number of beds in a mid-sized hospital in the UK. A hospital simulation model was developed to capture the stochastic behaviours of the hospital by taking into account the accident and emergency department, all outpatient and inpatient services, and the interactions between each other. A couple of outputs of the simulation model (e.g., average length of stay and revenue) were generated as inputs to be used in the optimization model. An integer linear programming was developed under a number of constraints (financial, demand, target level of bed occupancy rate and staffing level) with the aims of maximizing number of admitted patients. In addition, a sensitivity analysis was carried out by taking into account unexpected increases on inpatient demand over the next 12 months. As a result, the major findings of the approach proposed in this study optimally reallocate the available number of beds for each inpatient speciality and reveal that 74 beds are idle. In addition, the findings of the study indicate that the hospital wards will be able to cope with 14% demand increase at most in the projected year. In conclusion, this paper sheds a new light on how best to reallocate beds in order to cope with current and future demand for healthcare services.

Keywords: bed occupancy rate, bed reallocation, discrete event simulation, inpatient admissions, integer linear programming, projected usage

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Authors: Mustafa Rezazada, Takuya Maruyama

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Cars have a strong integration with the human being since its introduction, and this interaction is more evident in the urban context. Therefore, shifting city residents from driving private vehicles to public transits has been a big challenge. Accordingly, carsharing as an innovative, environmentally friendly transport alternative had a significant contribution to this transition so far. It helped to reduce the numbers of household car ownership, declining demand for on-street parking, dropping the numbers of kilometers traveled by car, and affects the future of mobility by decreasing the Green House Gases (GHS) emissions’ and the numbers of new cars to be purchased otherwise. However, majorities of carsharing researches were conducted in highly developed cities, and less attention has been paid to the cities of developing countries. This study is conducted in the Capital of Afghanistan, Kabul to investigate the current transport pattern, user behavior, and to examine the possibility of introducing the carsharing system. This study established a new survey method called Onboard Carsharing Survey OCS. In this survey, the carpooling passengers aboard are interviewed following the Onboard Transit Survey OTS guideline with a few refinements. The survey focuses on respondents’ daily travel behavior and hypothetical stated choice of carsharing opportunities. Moreover, it followed by an aggregate analysis at the end. The survey results indicate the following: two-thirds of the respondents 62% have been carpooling every day since 5 years or more, more than half of the respondents are not satisfied with current modes, besides other attributes the Traffic Congestion, Environment and Insufficient Public Transport were ranked the most critical in daily transportation by survey participants. Moreover, 68.24% of the respondent chose Carsharing over carpooling under different choice game scenarios. Overall, the findings in this research show that Kabul City is a potential underground for the introduction of Carsharing in the future. Taken together, insufficient public transit, dissatisfaction with current modes, and their stated interest will affect the future of carsharing positively in Kabul City. The modal choice in this study is limited to carpooling and carsharing; more choice sets, including bus, cycling, and walking, will have to be added to evaluate further.

Keywords: carsharing, developing countries, Kabul Afghanistan, onboard carsharing survey, transportation, urban planning

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Authors: Jui Afrin, Akhtarul Islam

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In this paper, the solution of glucose, yeast and glucose yeast mixture are being used as sample solution for determining the chemical oxygen demand (COD). In general COD determination method used to determine the different rang of oxidative potential. But in this work has shown to determine the definite oxidative potential for different concentration for known COD value and wanted to see the difference between experimental value and the theoretical value for evaluating the method drawbacks. In this study, made the values of oxidative potential like 400 mg/L, 500 mg/L, 600 mg/L, 700 mg/L and 800mg/L for various sample solutions and determined the oxidative potential according to our developed method. Plotting the experimental COD values vs. sample solutions of various concentrations in mg/L to draw the curve. From these curves see that the curves for glucose solution is not linear; its deviate from linearity for the lower concentration and the reason for this deviation is unknown. If these drawback can be removed this method can be effectively used to determine Oxidative Potential of Industrial wastewater (such as: Leather industry wastewater, Municipal wastewater, Food industry wastewater, Textile wastewater, Pharmaceuticals waste water) that’s why more experiment and study required.

Keywords: bod (biological oxygen demand), cod (chemical oxygen demand), oxidative potential, titration, waste water, development

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Authors: Tzen-Ying Ling

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Recently, the resilience of dwellings in urban areas has been deliberated, as to accommodate the growing demand for changing the demography and rapid urbanization. The need to incorporate sustainability and cleaner production thinking have intensified to mitigate climate risks and satisfy the demand for housing. The modular thinking satisfies both the pressing call for fast-tracked housing stocks; while meeting the goal of more sustainable production. In the other side, the importance of the dwelling as a podium for well-being and social connectedness are sought to explore the key human/environment design thinking for the modular system in dwelling. We argue the best practice incorporates the concept of systemic components thinking. The fieldwork reported in this paper illustrates the process of the case study in a modular dwelling unit prototype development; focusing on the systemic frame system design process and adjustment recommendation hereafter. Using a case study method, the study identified that: (1) inclusive human dimensional factoring through systemic design thinking results in affordable implementations possibilities. (2) The environmental dimension encourages the place-based solution suited for the locality and the increasing demand for dwelling in the urban system. (3) Prototype design consideration avails module system component as dwelling construction alternative. (4) Building code often acts as an inhibitor for such dwelling units by the restriction in lot sizes and units placement. The demand for fast-track dwelling construction and cleaner production decisively outweighs the code inhibition; we further underscored the sustainability implication of the alternative prototype as the core of this study. The research suggests that modular thinking results in a resilient solution suited for the locality and the increasing demand for dwelling in the urban system.

Keywords: system prototype, urban resilience, human/environment dimension, modular thinking, dwelling alternative

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Authors: Ayanori Sugiyama, Takahisa Hanei, Yasuhide Higo

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Domestic demand for the construction of tunnels has been increasing in recent years in Japan. To meet this demand, various construction materials and construction methods have been developed to attain higher strength, reduction of negative impact on the environment and improvement for working conditions. In this report, we would like to introduce the newly developed shotcrete with superior hardening properties which were tested through the actual machine scale and its workability and strength development were evaluated. As a result, this new tunnel construction method was found to achieve higher workability and quicker strength development in only a couple of minutes.

Keywords: accelerator, shotcrete, tunnel, high-strength

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Authors: Clifford Irikefe Gbeyonron

Abstract:

The Nigerian educational system, which has English language as a major medium of instruction, has been designed in such a way that the cognitive, psychomotor and affective endowments of the Nigerian learner could be explored. However, the human resources that would impart the desired knowledge, skills and values in the learners seem to be in short supply. This paucity is more manifest in the area of teachers of English. As a result, this research was conducted on the demand and supply of teachers of English at the junior secondary schools in Gashua, Yobe State. The results indicate that there was dearth of teachers of English the domain under review. This thus presents a challenge that should propel English language teacher education industries to produce more teachers of English. As a result, this paper recommends that the teacher production process should make use of qualified and enthusiastic teacher trainers that would be able to inculcate in-depth linguistic and communicative competence of English language and English language teaching skills in the potential teachers of English. In addition, English language education service providers should attract and retain the trained teachers of English in the business of English language teaching in such a way that all the states of Nigeria could experience educational development.

Keywords: demand, supply, teachers of English, Yobe State

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Authors: Hana Janáčková

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Housing can be sorted as basic needs of households. Purchase of acceptable ownership housing is important investments for most them. For rental housing households must consider the part of rent expenditure paid in the total household income. For this reason, financial considerations of households in this area depend on the government innervations (public administration) in housing - on housing policy. Market system of housing allocation, whether ownership or tenancy, is based on the fact that housing is a scarce good. The allocation of housing is based on demand and supply. The market system of housing can sometimes have a negative impact on some households, the market is unable to satisfy certain groups of the population that are not able or willing to accept market price. For these reasons, there is a more or less regulation of the market. Regulation is both on the demand and supply side, and the state determines the rules of behaviour for all economic entities of the housing market. This article submits results of analysis of selected regulatory interference of the state in the housing market and assesses their implications deforming the market in the selected region of the Czech Republic. The first part describes tools of supports and the second part discusses deformations and analyses their consequences on the demand side of housing market and on supply side.

Keywords: housing, housing market, microeconomic consequences, deformation

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Authors: Akhtar Nawaz, Sahar Noor, Iftikhar Hussain

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This paper considers advanced hybrid manufacturing planning both push and pull system in which each customer order has a due date by demand forecast and customer orders. We present a tool for model for tool development that requires an absolute due dates and customer orders in a manufacturing supply chain. It is vital for the manufacturing companies to face the problem of variations in demands, increase in varieties by maintaining safety stock and to minimize components obsolescence and uselessness. High inventory cost and low delivery lead time is expected in push type of system and on contrary high delivery lead time and low inventory cost is predicted in the pull type. For this tool for model we need an MRP system for the push and pull environment and control of inventories in push parts and lead time in the pull part. To retain process data quickly, completely and to improve responsiveness and minimize inventory cost, a tool is required to deal with the high product variance and short cycle parts. In practice, planning and scheduling are interrelated and should be solved simultaneously with supply chain to ensure that the due dates of customer orders are met. The proposed tool for model considers alternative process plans for job types, with precedence constraints for job operations. Such a tool for model has not been treated in the literature. To solve the model, tool was developed, so a new technique was required to deal with the issue of high product variance and short life cycles in assemble to order.

Keywords: hybrid manufacturing system, supply chain system, make to order, make to stock, assemble to order

Procedia PDF Downloads 559