Search results for: parking demand forecast

Authors: Lubna Naz, Munir Ahmad, G. M. Arif

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This study analyzes static and dynamic welfare impacts of food price changes for various landholding groups in Pakistan. The study uses three classifications of land ownership, landless, small landowners and large landowners, for analysis. The study uses Panel Survey, Pakistan Rural Household Survey (PRHS) of Pakistan Institute of Development Economics Islamabad, of rural households from two largest provinces (Sindh and Punjab) of Pakistan. The study uses all three waves (2001, 2004 and 2010) of PRHS. This research work makes three important contributions in literature. First, this study uses Quadratic Almost Ideal Demand System (QUAIDS) to estimate demand functions for eight food groups-cereals, meat, milk and milk products, vegetables, cooking oil, pulses and other food. The study estimates food demand functions with Nonlinear Seemingly Unrelated (NLSUR), and employs Lagrange Multiplier and test on the coefficient of squared expenditure term to determine inclusion of squared expenditure term. Test results support the inclusion of squared expenditure term in the food demand model for each of landholding groups (landless, small landowners and large landowners). This study tests for endogeneity and uses control function for its correction. The problem of observed zero expenditure is dealt with a two-step procedure. Second, it creates low price and high price periods, based on literature review. It uses elasticity coefficients from QUAIDS to analyze static and dynamic welfare effects (first and second order Tylor approximation of expenditure function is used) of food price changes across periods. The study estimates compensation variation (CV), money metric loss from food price changes, for landless, small and large landowners. Third, this study compares the findings on welfare implications of food price changes based on QUAIDS with the earlier research in Pakistan, which used other specification of the demand system. The findings indicate that dynamic welfare impacts of food price changes are lower as compared to static welfare impacts for all landholding groups. The static and dynamic welfare impacts of food price changes are highest for landless. The study suggests that government should extend social security nets to landless poor and categorically to vulnerable landless (without livestock) to redress the short-term impact of food price increase. In addition, the government should stabilize food prices and particularly cereal prices in the long- run.

Keywords: QUAIDS, Lagrange multiplier, NLSUR, and Tylor approximation

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Authors: Mohamed Ghorab

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Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: distributed energy resources, network energy system, optimization, microgeneration system

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Authors: S. S. Chong, A. R. Abdul Aziz, S. W. Harun, H. Arof

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A miniaturized non-adiabatic silica microfiber is proposed for biological oxygen demand (BOD) ratio chemical oxygen demand (COD) sensing for the first time. BOD and COD are two main parameters to justify quality of wastewater. A ratio, BOD:COD can usually be established between the two analytical methods once COD and BOD value has been gathered. This ratio plays a vital role to determine appropriate strategy in wastewater treatment. A non-adiabatic microfiber sensor was formed by tapering the SMF to generate evanescent field where sensitive to perturbation of sensing medium. Because difference ratio BOD and COD contain in solution, this may induced changes of effective refractive index between microfiber and sensing medium. Attenuation wavelength shift to right with 0.5 nm and 3.5 nm while BOD:COD equal to 0.09 and 0.18 respectively. Significance difference wavelength shift may relate with the biodegradability of analyte. This proposed sensor is compact, reliable and feasible to determine the BOD:COD. Further research and investigation should be proceeded to enhance sensitivity and precision of the sensor for several of wastewater online monitoring.

Keywords: non-adiabatic fiber sensor, environmental sensing, biodegradability, evanescent field

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Authors: Li-hsing Shih, Wei-Jen Hsu

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Recently, the sale of electrical vehicles (EVs) has increased dramatically due to maturing technology development and decreasing cost. Governments of many countries have made regulations and policies in favor of EVs due to their long-term commitment to net zero carbon emissions. However, due to uncertain factors such as the future price of EVs, forecasting the future market share of EVs is a challenging subject for both the auto industry and local government. This study tries to forecast the market share of EVs using conjoint models and Monte Carlo simulation. The research is conducted in three phases. (1) A conjoint model is established to represent the customer preference structure on purchasing vehicles while five product attributes of both EV and internal combustion engine vehicles (ICEV) are selected. A questionnaire survey is conducted to collect responses from Taiwanese consumers and estimate the part-worth utility functions of all respondents. The resulting part-worth utility functions can be used to estimate the market share, assuming each respondent will purchase the product with the highest total utility. For example, attribute values of an ICEV and a competing EV are given respectively, two total utilities of the two vehicles of a respondent are calculated and then knowing his/her choice. Once the choices of all respondents are known, an estimate of market share can be obtained. (2) Among the attributes, future price is the key attribute that dominates consumers’ choice. This study adopts the assumption of a learning curve to predict the future price of EVs. Based on the learning curve method and past price data of EVs, a regression model is established and the probability distribution function of the price of EVs in 2030 is obtained. (3) Since the future price is a random variable from the results of phase 2, a Monte Carlo simulation is then conducted to simulate the choices of all respondents by using their part-worth utility functions. For instance, using one thousand generated future prices of an EV together with other forecasted attribute values of the EV and an ICEV, one thousand market shares can be obtained with a Monte Carlo simulation. The resulting probability distribution of the market share of EVs provides more information than a fixed number forecast, reflecting the uncertain nature of the future development of EVs. The research results can help the auto industry and local government make more appropriate decisions and future action plans.

Keywords: conjoint model, electrical vehicle, learning curve, Monte Carlo simulation

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Authors: Hasik Lee, Seung-Young Kho

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Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

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Authors: Yuxiao Jiang, Lingjun Meng, Mengyu Zhan, Lichunyi Zhang, Yingxia Yun

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On August 8th of 2015, a serious explosion occurred in Binhai New Area of Tianjin. This explosion led to the suspension of Tianjin-Binhai Light Rail Line 9 which was an important transportation mean connecting the old and new urban areas and the suspension causes inconvenience to commuters traveling from Tianjin to Binhai or Binhai to Tianjin and residents living by Line 9. On this regard, this paper intends to give suggestions on how to develop multi-mode transportation system rapidly and effectively after a disaster and tackle with the problems in terms of transportation infrastructure facilities. The paper proposes the idea of traffic resilience which refers to the city’s ability to restore its transportation system and reduce risks when the transportation system is destroyed by a disaster. By doing questionnaire research, on the spot study and collecting data from the internet, a GIS model is established so as to analyze the alternative traffic means used by different types of residents and study the transportation supply and demand. The result shows that along the Line 9, there is a larger demand for alternative traffic means in the place which is nearer to the downtown area. Also, the distribution of bus stations is more reasonable in the place nearer to downtown area, however, the traffic speed in the area is slower. Based on traffic resilience, the paper raises strategies to develop post-disaster multi-mode transportation system such as establishing traffic management mechanism timely and effectively, building multi-mode traffic networks, improving intelligent traffic systems and so on.

Keywords: traffic resilience, multi-mode transportation system, public traffic, transportation demand

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Authors: Lali Khurtsia, Vano Tsertsvadze

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Georgian drug policy is directed to reduce the supply of drugs. Retrospective analysis has shown that law enforcement activities have been followed by the expulsion of particular injecting drugs. The demand remains unchanged and drugs are substituted by the hand-made, even more dangerous homemade drugs entered the market. To find out expected new trends on the Georgian drug market, qualitative study was conducted with Georgian drug users to determine drug supply routes. It turned out that drug suppliers and consumers for safety reasons and to protect their anonymity, use Skype to make deals. IT in illegal drug trade is even more sophisticated in the worldwide. Trading with Bitcoins in the Darknet ensures high confidentiality of money transactions and the safe circulation of drugs. In 2014 largest Bitcoin mining enterprise in the world was built in Georgia. We argue that the use of Bitcoins and Darknet by Georgian drug consumers and suppliers will be an incentive to response adequately to the government's policy of restricting supply in order to satisfy market demand for drugs.

Keywords: bitcoin, darknet, drugs, policy

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Authors: Brahmia Nadjet

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The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient. They rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible for the advance reservation, planning and organization, and studying the different ODT criteria (organizational, technical, geographical, etc.). As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This paper presents the study of an ODT implementation in the west of Algeria, by developing the geomatics side of the study. This part requires the use of specific systems such as Geographic Information System (GIS), Road Database Management System (RDBMS). So, we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: ODT, geomatics, GIS, transport systems

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Authors: Mandeep Kaur, Fatehgarh Sahib

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The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system.

Keywords: economic load dispatch, genetic algorithm, generating units, multiobjective optimization, weighting method

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Authors: Omolara Lade, David Oloke

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Ibadan City suffers serious water supply problems; cases of dry taps are common in virtually every part of the City. The scarcity of piped water has made communities find alternative water sources; groundwater sources being a ready source. These wells are prone to pollution due to the close proximity of septic tanks to wells, disposal of solid or liquid wastes in pits, abandoned boreholes or even stream channels and landfills. Storms and floods in Ibadan have increased with consequent devastating effects claiming over 120 lives and displacing 600 people on August 2011 alone. In this study, an analysis of the water demand and sources of supply for the city was carried out through questionnaire survey and collection of data from City’s main water supply - Water Corporation of Oyo State (WCOS), groundwater sources were explored and 30 years rainfall data were collected from Meteorological station in Ibadan. 1067 questionnaire were administered at household level with a response rate of 86.7 %. A descriptive analysis of the survey revealed that 77.1 % of the respondents did not receive water at all from WCOS while 83.8 % depend on groundwater sources. Analysis of data from WCOS revealed that main water supply is inadequate as < 10 % of the population water demand was met. Rainfall intensity is highest in June with a mean value of 188 mm, which can be harvested at community—based level and used to complement the population water demand. Rainwater harvesting if planned, and managed properly will become a valuable alternative source of managing urban flood and alleviating water scarcity in the city.

Keywords: Ibadan, rainwater harvesting, sustainable water, urban flooding

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Authors: Almahd Alshereef, Ahmed Alkilany, Hammad Said, Azuraliza Abu Bakar

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From time to time, electrical power grid is directed by the National Electricity Operator to conduct load shedding, which involves hours' power outages on the area of this study, Southern Electrical Grid of Libya (SEGL). Load shedding is conducted in order to alleviate pressure on the National Electricity Grid at times of peak demand. This approach has chosen a set of categories to study load-shedding problem considering the effect of the demand priorities on the operation of the power system during emergencies. Classification of category region for load shedding problem is solved by a new algorithm (the harmony algorithm) based on the "random generation list of category region", which is a possible solution with a proximity degree to the optimum. The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on SEGL.

Keywords: optimization, harmony algorithm, load shedding, classification

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Authors: Aswathi Thrivikraman, S. Advaith

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The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

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Authors: Jingjue Bao, Ye Li, Yujie Qi

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The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

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Authors: M. Erol Genevois, D. Celik, H. Z. Ulukan

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Automated teller machines (ATMs) can be considered among one of the most important service facilities in the banking industry. The investment in ATMs and the impact on the banking industry is growing steadily in every part of the world. The banks take into consideration many factors like safety, convenience, visibility, cost in order to determine the optimum locations of ATMs. Today, ATMs are not only available in bank branches but also at retail locations. Another important factor is the cash management in ATMs. A cash demand model for every ATM is needed in order to have an efficient cash management system. This forecasting model is based on historical cash demand data which is highly related to the ATMs location. So, the location and the cash management problem should be considered together. Although the literature survey on facility location models is quite large, it is surprising that there are only few studies which handle together ATMs location and cash management problem. In order to fulfill the gap, this paper provides a general review on studies, efforts and development in ATMs location and cash management problem.

Keywords: ATM location problem, cash management problem, ATM cash replenishment problem, literature review in ATMs

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Authors: Maria C. Mariani, Md Al Masum Bhuiyan, Osei K. Tweneboah, Hector G. Huizar

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This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties.

Keywords: Augmented Dickey Fuller Test, geophysical time series, maximum likelihood estimation, stochastic volatility model

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Authors: Thelma Maria Melo Pinheiro, Guilherme Raposo Diniz Vieira, Sidney Matos da Silva, Leonardo Mendonça de Oliveira Queiroz, Mateus Sousa Pinheiro, Danyllo Wenceslau de Oliveira Lopes

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The present article has the objective to describe the regulatory impact analysis (RIA) of the contracting efficiency of the Brazilian transmission system usage. This contracting is made by users connected to the main transmission network and is used to guide necessary investments to supply the electrical energy demand. Therefore, an inefficient contracting of this energy amount distorts the real need for grid capacity, affecting the sector planning accuracy and resources optimization. In order to provide this efficiency, the Brazilian Electricity Regulatory Agency (ANEEL) homologated the Normative Resolution (NR) No. 666, from July 23th of 2015, which consolidated the procedures for the contracting of transmission system usage and the contracting efficiency verification. Aiming for a more efficient and rational transmission system contracting, the resolution established economic incentives denominated as Inefficiency installment for excess (IIE) and inefficiency installment for over-contracting (IIOC). The first one, IIE, is verified when the contracted demand exceeds the established regulatory limit; it is applied to consumer units, generators, and distribution companies. The second one, IIOC, is verified when the distributors over-contract their demand. Thus, the establishment of the inefficiency installments IIE and IIOC intends to avoid the agent contract less energy than necessary or more than it is needed. Knowing that RIA evaluates a regulatory intervention to verify if its goals were achieved, the results from the application of the above-mentioned normative resolution to the Brazilian transmission sector were analyzed through indicators that were created for this RIA to evaluate the contracting efficiency transmission system usage, using real data from before and after the homologation of the normative resolution in 2015. For this, indicators were used as the efficiency contracting indicator (ECI), excess of demand indicator (EDI), and over-contracting of demand indicator (ODI). The results demonstrated, through the ECI analysis, a decrease of the contracting efficiency, a behaviour that was happening even before the normative resolution of 2015. On the other side, the EDI showed a considerable decrease in the amount of excess for the distributors and a small reduction for the generators; moreover, the ODI notable decreased, which optimizes the usage of the transmission installations. Hence, with the complete evaluation from the data and indicators, it was possible to conclude that IIE is a relevant incentive for a more efficient contracting, indicating to the agents that their contracting values are not adequate to keep their service provisions for their users. The IIOC also has its relevance, to the point that it shows to the distributors that their contracting values are overestimated.

Keywords: contracting, electricity regulation, evaluation, regulatory impact analysis, transmission power system

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Authors: Hong Geng, Zaiyu Fan

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With the acceleration of urbanization and motorization in China, the scale of cities and the travel distance of residents are constantly expanding, and the number of cars is continuously increasing, so the urban traffic problem is more and more serious. Traffic congestion, environmental pollution, energy consumption, travel safety and direct interference between traffic and other urban activities are increasingly prominent problems brought about by motorized development. This not only has a serious impact on the lives of the residents but also has a major impact on the healthy development of the city. The paper found that, in order to solve the development of motorization, a number of problems will arise; urban planning and traffic planning and design in residential planning often take into account the development of motorized traffic but neglects the demand for street life. This kind of planning has resulted in the destruction of the traditional communication space of the residential area, the pollution of noise and exhaust gas, and the potential safety risks of the residential area, which has disturbed the previously quiet and comfortable life of the residential area, resulting in the inconvenience of residents' life and the loss of street vitality. Based on these facts, this paper takes a residential area in Wuhan as the research object, through the actual investigation and research, from the perspective of micro-transformation analysis, combined with the concept of traffic micro-reconstruction governance. And research puts forward the residential traffic optimization strategies such as strengthening the interaction and connection between the residential area and the urban street system, street traffic classification and organization.

Keywords: micro-transformation, residential traffic, residents demand, traffic microcirculation

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Authors: Mehmet Savsar

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One of the most important factors affecting power plant performance is the reliability of the turbine units operated under different conditions. Reliability directly affects plant availability and performance. Therefore, it is very important to be able to analyze turbine units, as well as power plant system reliability and availability under various operational conditions. In this paper, data related to power station failures are collected and analyzed in detail for all power stations in the state of Kuwait. Failures are characterized and categorized. Reliabilities of various power plants are analyzed and availabilities are quantified. Based on calculated availabilities of all installed power plants, actual power output is estimated. Furthermore, based on the past 15 years of data, power consumption trend is determined and the demand for power in the future is forecasted. Estimated power output is compared to the forecasted demand in order to determine the need for future capacity expansion.

Keywords: power plants, reliability, availability, capacity, preventive maintenance, forecasting

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Authors: Draou Azeddine, Mazin Alahmadi, Abdulrahmane Alkassem, Alamri Abdullah

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The demand for electric power in Saudi Arabia is steadily increasing with economic growth. More power plants should be installed to increase generation capacity and meet demand. Electricity in Saudi Arabia is mainly dependent on fossil fuels, which are a major problem as they deplete natural resources and increase CO₂ emissions. In this research work, performance and techno-economic analyzes are conducted to evaluate a microgrid system based on hybrid PV/wind diesel power sources as a stand-alone system for rural electrification in Saudi Arabia. The total power flow, maximum power point tracking (MPPT) efficiency, effectiveness of the proposed control strategy, and total harmonic distortion (THD) are analyzed in MATLAB/Simulink environment. Various simulation studies have been carried out under different irradiation conditions. The sizing, optimization, and economic feasibility analysis were performed using Homer energy software.

Keywords: WIND, solar, microgrid, energy

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Authors: P. S. Surya Meghana, K. Lingeshwaran, C. Kannan, V. Raghavendran, C. Priya

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One of the most basic and powerful tools in all of science and medicine is the light microscope, the fundamental device for laboratory as well as research purposes. With the improving technology, the need for portable, economic and user-friendly instruments is in high demand. The conventional microscope fails to live up to the emerging trend. Also, adequate access to healthcare is not widely available, especially in developing countries. The most basic step towards the curing of a malady is the diagnosis of the disease itself. The main aim of this paper is to diagnose Malaria with the most common device, cell phones, which prove to be the immediate solution for most of the modern day needs with the development of wireless infrastructure allowing to compute and communicate on the move. This opened up the opportunity to develop novel imaging, sensing, and diagnostics platforms using mobile phones as an underlying platform to address the global demand for accurate, sensitive, cost-effective, and field-portable measurement devices for use in remote and resource-limited settings around the world.

Keywords: cellular, hand-held, health care, image processing, malarial parasites, microscope

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Authors: Claus N. Holm, Oliver F. Grooss, Robert A. Alphinas

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This research strives to predict the remaining product life cycle of a song on radio after it has been played for one or two months. The best results were achieved using a k-d tree to calculate the most similar songs to the test songs and use a Random Forest model to forecast radio plays. An 82.78% and 83.44% accuracy is achieved for the two time periods, respectively. This explorative research leads to over 4500 test metrics to find the best combination of models and pre-processing techniques. Other algorithms tested are KNN, MLP and CNN. The features only consist of daily radio plays and use no musical features.

Keywords: hit song science, product life cycle, machine learning, radio

Procedia PDF Downloads 142

Authors: Pascal Mwenge, Tumisang Seodigeng

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The increase in urbanisation in South Africa has led to an increase in water demand and a decline in freshwater supply. Despite this, poor water usage is still a major challenge in South Africa, for instance, freshwater is still used for non-drinking applications. The freshwater shortage can be alleviated by using other sources of water for non-portable purposes such as greywater treated with activated biochar produced from agricultural waste. The success of activated biochar produced from agricultural waste to treat greywater can be both economically and environmentally beneficial. Greywater treated with activated biochar produced from agricultural waste is considered a cost-effective wastewater treatment.  This work was aimed at determining the ability of activated biochar to remove Total Suspended Solids (TSS), Ammonium (NH₄-N), Nitrate (NO₃-N), and Chemical Oxygen Demand (COD) from greywater. The experiments were carried out in 800 ml laboratory plastic cylinders used as filter columns. 2.5 cm layer of gravel was used at the bottom and top of the column to sandwich the activated biochar material. Activated biochar (200 g and 400 g) was loaded in a column and used as a filter medium for greywater. Samples were collected after a week and sent for analysis. Four types of greywater were treated: Kitchen, floor cleaning water, shower and laundry water. The findings showed: 95% removal of TSS, 76% of NO₃-N and 63% of COD on kitchen greywater and 85% removal of NH₄-N on bathroom greywater, as highest removal of efficiency of the studied pollutants. The results showed that activated biochar produced from agricultural waste reduces a certain amount of pollutants from greywater. The results also indicated the ability of activated biochar to treat greywater for onsite non-potable reuse purposes.

Keywords: activated biochar produced from agriculture waste, ammonium, NH₄-N, chemical oxygen demand, COD, greywater, nitrate, NO₃-N, total suspended solids, TSS

Procedia PDF Downloads 191

Authors: Supakij Saisopon

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The process of economic development incurs spatial transformation. This spatial alternation also causes environmental impacts, leading to higher pollution. In the case of Thailand, there is still a lack of price-endogenous quantitative analysis incorporating relationships among economic growth, land-use change, and environmental impact. Therefore, this paper aimed at developing the Computable General Equilibrium (CGE) model with the capability of stimulating such mutual effects. The developed CGE model has also incorporated the nested constant elasticity of transformation (CET) structure that describes the spatial redistribution mechanism between agricultural land and urban area. The simulation results showed that the 1% decrease in the availability of agricultural land lowers the value-added of agricultural by 0.036%. Similarly, the 1% reduction of availability of urban areas can decrease the value-added of manufacturing and service sectors by 0.05% and 0.047%, respectively. Moreover, the outcomes indicate that the increasing farming and urban areas induce higher volumes of solid waste, wastewater, and air pollution. Specifically, the 1% increase in the urban area can increase pollution as follows: (1) the solid waste increase by 0.049%, (2) water pollution ̶ indicated by biochemical oxygen demand (BOD) value ̶ increase by 0.051% and (3) air pollution ̶ indicated by the volumes of CO₂, N₂O, NOₓ, CH₄, and SO₂ ̶ increase within the range of 0.045%–0.051%. With the simulation for exploring the sustainable development path, a 1% increase in agricultural land use efficiency leads to the shrinking demand for agricultural land. But this is not happening in urban, a 1% scale increase in urban utilization results in still increasing demand for land. Therefore, advanced clean production technology is necessary to align the increasing land-use efficiency with the lowered pollution density.

Keywords: CGE model, CET structure, environmental impact, land use

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Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

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Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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Authors: Mahmoud M. Othman, Almoataz Y. Abdelaziz, Yasser G. Hegazy

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This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm.

Keywords: big bang big crunch, distributed generation, load control, optimization, planning

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Authors: Szymon Kuczynski

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Poland is characterized by the presence of numerous sedimentary basins and hydrocarbon provinces. Since 2006 exploration for hydrocarbons in Poland become gradually more focus on new unconventional targets, particularly on the shale gas potential of the Upper Ordovician and Lower Silurian in the Baltic-Podlasie-Lublin Basin. The first forecast prepared by US Energy Information Administration in 2011 indicated to 5.3 Tcm of natural gas. In 2012, Polish Geological Institute presented its own forecast which estimated maximum reserves on 1.92 Tcm. The difference in the estimates was caused by problems with calculations of the initial amount of adsorbed, as well as free, gas trapped in shale rocks (GIIP - Gas Initially in Place). This value is dependent from sorption capacity, gas saturation and mutual interactions between gas, water, and rock. Determination of the reservoir type in the initial exploration phase brings essential knowledge, which has an impact on decisions related to the production. The study of porosity impact for phase envelope shift eliminates errors and improves production profitability. Confinement phenomenon affects flow characteristics, fluid properties, and phase equilibrium. The thermodynamic behavior of confined fluids in porous media is subject to the basic considerations for industrial applications such as hydrocarbons production. In particular the knowledge of the phase equilibrium and the critical properties of the contained fluid is essential for the design and optimization of such process. In pores with a small diameter (nanopores), the effect of the wall interaction with the fluid particles becomes significant and occurs in shale formations. Nano pore size is similar to the fluid particles’ diameter and the area of particles which flow without interaction with pore wall is almost equal to the area where this phenomenon occurs. The molecular simulation studies have shown an effect of confinement to the pseudo critical properties. Therefore, the critical parameters pressure and temperature and the flow characteristics of hydrocarbons in terms of nano-scale are under the strong influence of fluid particles with the pore wall. It can be concluded that the impact of a single pore size is crucial when it comes to the nanoscale because there is possible the above-described effect. Nano- porosity makes it difficult to predict the flow of reservoir fluid. Research are conducted to explain the mechanisms of fluid flow in the nanopores and gas extraction from porous media by desorption.

Keywords: adsorption, capillary condensation, phase envelope, nanopores, unconventional natural gas

Procedia PDF Downloads 325

Authors: Jamal Radaideh

Abstract:

Al-Asfar Lake is located about 14 km east of Al-Ahsa and is one of the most important wetland lakes in the Al Ahsa/Eastern Province of Saudi Arabia. Al-Ahsa is may be the largest oasis in the world, having an area of 20,000 hectares, in addition, it is of the largest and oldest agricultural centers in the region. The surplus farm irrigation water beside additional water supplied by treated wastewater from Al-Hofuf sewage station is collected by a drainage network and discharged into Al-Asfar Lake. The lake has good wetlands, sand dunes as well as large expanses of open and shallow water. Salt tolerant vegetation is present in some of the shallow areas around the lake, and huge stands of Phragmites reeds occur around the lake. The lake presents an important habitat for wildlife and birds, something not expected to find in a large desert. Although high evaporation rates in the range of 3250 mm are common, the water remains in the evaporation lakes during all seasons of the year is used to supply cattle with drinking water and for aquifer recharge. Investigations showed that high concentrations of nitrogen (N), phosphorus (P), biological oxygen demand (BOD), chemical oxygen demand (COD) and salinity discharge to Al Asfar Lake from the D2 drain exist. It is expected that the majority of BOD, COD and N originates from wastewater discharge and leachate from surplus irrigation water which also contribute to the majority of P and salinity. The significant content of nutrients and biological oxygen demand reduces available oxygen in the water. The present project aimed to improve the water quality of the lake using constructed wetland trains which will be built around the lake. Phragmites reeds, which already occur around the lake, will be used.

Keywords: Al Asfar lake, constructed wetland, water quality, water treatment

Procedia PDF Downloads 428

Authors: Guo Bingkun

Abstract:

With the rapid development of China's social economy and the continuous improvement of urbanization level, people's living standards have undergone tremendous changes, and more and more people are gathering in cities. The demand for urban residents' housing has been greatly released in the past decade. The demand for housing and related construction land required for urban development has brought huge pressure to urban operations, and land prices have also risen rapidly in the short term. On the other hand, from the comparison of the eastern and western regions of China, there are also great differences in urban socioeconomics and land prices in the eastern, central and western regions. Although judging from the current overall market development, after more than ten years of housing market reform and development, the quality of housing and land use efficiency in Chinese cities have been greatly improved. However, the current contradiction between land demand for urban socio-economic development and land supply, especially the contradiction between land supply and demand for urban residential land, has not been effectively alleviated. Since land is closely linked to all aspects of society, changes in land prices will be affected by many complex factors. Therefore, this paper studies the factors that may affect urban residential land prices and compares them among eastern, central and western cities, and finds the main factors that determine the level of urban residential land prices. This paper provides guidance for urban managers in formulating land policies and alleviating land supply and demand. It provides distinct ideas for improving urban planning and improving urban planning and promotes the improvement of urban management level. The research in this paper focuses on residential land prices. Generally, the indicators for measuring land prices mainly include benchmark land prices, land price level values, parcel land prices, etc. However, considering the requirements of research data continuity and representativeness, this paper chooses to use residential land price level values. Reflects the status of urban residential land prices. First of all, based on the existing research at home and abroad, the paper considers the two aspects of land supply and demand and, based on basic theoretical analysis, determines some factors that may affect urban housing, such as urban expansion, taxation, land reserves, population, and land benefits. Factors of land price and correspondingly selected certain representative indicators. Secondly, using conventional econometric analysis methods, we established a model of factors affecting urban residential land prices, quantitatively analyzed the relationship and intensity of influencing factors and residential land prices, and compared the differences in the impact of urban residential land prices between the eastern, central and western regions. Compare similarities. Research results show that the main factors affecting China's urban residential land prices are urban expansion, land use efficiency, taxation, population size, and residents' consumption. Then, the main reason for the difference in residential land prices between the eastern, central and western regions is the differences in urban expansion patterns, industrial structures, urban carrying capacity and real estate development investment.

Keywords: urban housing, urban planning, housing prices, comparative study

Procedia PDF Downloads 38

Authors: Carolina Aparicio-Fernández, Alejandro Vilar Abad, Mar Cañada Soriano, Jose-Luis Vivancos

Abstract:

The building sector is responsible for 40% of the total energy consumption in the European Union (EU). Thus, implementation of strategies for quantifying and reducing buildings energy consumption is indispensable for reaching the EU’s carbon neutrality and energy efficiency goals. Each Member State has transposed the European Directives according to its own peculiarities: existing technical legislation, constructive solutions, climatic zones, etc. Therefore, in accordance with the Energy Performance of Buildings Directive, Member States have developed different Energy Performance Certificate schemes, using proposed energy simulation software-tool for each national or regional area. Energy Performance Certificates provide a powerful and comprehensive information to predict, analyze and improve the energy demand of new and existing buildings. Energy simulation software and databases allow a better understanding of the current constructive reality of the European building stock. However, Energy Performance Certificates still have to face several issues to consider them as a reliable and global source of information since different calculation tools are used that do not allow the connection between them. In this document, TRNSYS (TRaNsient System Simulation program) software is used to calculate the energy demand of a building, and it is compared with the energy labeling obtained with Spanish Official software-tools. We demonstrate the possibility of using not official software-tools to calculate the Energy Performance Certificate. Thus, this approach could be used throughout the EU and compare the results in all possible cases proposed by the EU Member States. To implement the simulations, an isolated single-family house with different construction solutions is considered. The results are obtained for every climatic zone of the Spanish Technical Building Code.

Keywords: energy demand, energy performance certificate EPBD, trnsys, buildings

Procedia PDF Downloads 114

Authors: Mujtaba Roshan, John A. Schormans

Abstract:

Quality of Experience (QoE) drives churn in the broadband networks industry, and good QoE plays a large part in the retention of customers. QoE is known to be affected by the Quality of Service (QoS) factors packet loss probability (PLP), delay and delay jitter caused by the network. Earlier results have shown that the relationship between these QoS factors and QoE is non-linear, and may vary from application to application. We use the network emulator Netem as the basis for experimentation, and evaluate how QoE varies as we change the emulated QoS metrics. Focusing on Video-on-Demand, we discovered that the reported QoE may differ widely for users of different age groups, and that the most demanding age group (the youngest) can require an order of magnitude lower PLP to achieve the same QoE than is required by the most widely studied age group of users. We then used a bottleneck TCP model to evaluate the capacity cost of achieving an order of magnitude decrease in PLP, and found it be (almost always) a 3-fold increase in link capacity that was required.

Keywords: network capacity, packet loss probability, quality of experience, quality of service

Procedia PDF Downloads 264