Search results for: supply and demand prediction

Authors: Fatemeh Faramarzi, Hosein Mahjoob

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Building dams on rivers for utilization of water resources causes problems in hydrodynamic equilibrium and results in leaving all or part of the sediments carried by water in dam reservoir. This phenomenon has also significant impacts on water and sediment flow regime and in the long term can cause morphological changes in the environment surrounding the river, reducing the useful life of the reservoir which threatens sustainable development through inefficient management of water resources. In the past, empirical methods were used to predict the sedimentation amount in dam reservoirs and to estimate its efficient lifetime. But recently the mathematical and computational models are widely used in sedimentation studies in dam reservoirs as a suitable tool. These models usually solve the equations using finite element method. This study compares the results from tow software packages, GSTARS4 & HEC-6, in the prediction of the sedimentation amount in Dez dam, southern Iran. The model provides a one-dimensional, steady-state simulation of sediment deposition and erosion by solving the equations of momentum, flow and sediment continuity and sediment transport. GSTARS4 (Generalized Sediment Transport Model for Alluvial River Simulation) which is based on a one-dimensional mathematical model that simulates bed changes in both longitudinal and transverse directions by using flow tubes in a quasi-two-dimensional scheme to calibrate a period of 47 years and forecast the next 47 years of sedimentation in Dez Dam, Southern Iran. This dam is among the highest dams all over the world (with its 203 m height), and irrigates more than 125000 square hectares of downstream lands and plays a major role in flood control in the region. The input data including geometry, hydraulic and sedimentary data, starts from 1955 to 2003 on a daily basis. To predict future river discharge, in this research, the time series data were assumed to be repeated after 47 years. Finally, the obtained result was very satisfactory in the delta region so that the output from GSTARS4 was almost identical to the hydrographic profile in 2003. In the Dez dam due to the long (65 km) and a large tank, the vertical currents are dominant causing the calculations by the above-mentioned method to be inaccurate. To solve this problem, we used the empirical reduction method to calculate the sedimentation in the downstream area which led to very good answers. Thus, we demonstrated that by combining these two methods a very suitable model for sedimentation in Dez dam for the study period can be obtained. The present study demonstrated successfully that the outputs of both methods are the same.

Keywords: Dez Dam, prediction, sedimentation, water resources, computational models, finite element method, GSTARS4, HEC-6

Procedia PDF Downloads 306

Authors: Sapan Tiwari, Namrata Ghosh

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In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.

Keywords: crew scheduling, duty, optimization of cost, urban mass transit

Procedia PDF Downloads 142

Authors: Chongyang Ye, Rong Liu

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Elastic compression stockings (ECSs) have been widely applied in prophylaxis and treatment of chronic venous insufficiency of lower extremities. The medical function of ECS is to improve venous return and increase muscular pumping action to facilitate blood circulation, which is largely determined by the complex interaction between the ECS and lower limb tissues. Understanding the mechanical transmission of ECS along the skin surface, deeper tissues, and vascular system is essential to assess the effectiveness of the ECSs. In this study, a three-dimensional (3D) finite element (FE) model of the leg-ECS system integrated with a 3D fluid-solid interaction (FSI) model of the leg-vein system was constructed to analyze the biomechanical properties of veins and soft tissues under different ECS compression. The Magnetic Resonance Imaging (MRI) of the human leg was divided into three regions, including soft tissues, bones (tibia and fibula) and veins (peroneal vein, great saphenous vein, and small saphenous vein). The ECSs with pressure ranges from 15 to 26 mmHg (Classes I and II) were adopted in the developed FE-FSI model. The soft tissue was assumed as a Neo-Hookean hyperelastic model with the fixed bones, and the ECSs were regarded as an orthotropic elastic shell. The interfacial pressure and stress transmission were simulated by the FE model, and venous hemodynamics properties were simulated by the FSI model. The experimental validation indicated that the simulated interfacial pressure distributions were in accordance with the pressure measurement results. The developed model can be used to predict interfacial pressure, stress transmission, and venous hemodynamics exerted by ECSs and optimize the structure and materials properties of ECSs design, thus improving the efficiency of compression therapy.

Keywords: elastic compression stockings, fluid-solid interaction, tissue and vein properties, prediction

Procedia PDF Downloads 107

Authors: Maico R. Severino, Laura G. Caixeta, Nadine M. Costa, Raísa L. T. Napoleão, Éverton F. V. Valle, Diego D. Calixto, Danielle Oliveira

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One of the biggest barriers that companies find nowadays is the coordination of production flow in their Supply Chains (SC). In this study, coordination is understood as a mechanism for incorporating the entire production channel, with everyone involved focused on achieving the same goals. Sometimes, this coordination is attempted by the use of logistics practices or production plan and control methods. No papers were found in the literature that presented the combined use of logistics practices and production plan and control methods. The main objective of this paper is to propose solutions for six case studies combining logistics practices and Ordering Systems (OS). The methodology used in this study was a conceptual model of decision making. This model contains six phases: a) the analysis the types and characteristics of relationships in the SC; b) the choice of the OS; c) the choice of the logistics practices; d) the development of alternative proposals of combined use; e) the analysis of the consistency of the chosen alternative; f) the qualitative and quantitative assessment of the impact on the coordination of the production flow and the verification of applicability of the proposal in the real case. This study was conducted on six Brazilian SC of different sectors: footwear, food and beverages, garment, sugarcane, mineral and metal mechanical. The results from this study showed that there was improvement in the coordination of the production flow through the following proposals: a) for the footwear industry the use of Period Bath Control (PBC), Quick Response (QR) and Enterprise Resource Planning (ERP); b) for the food and beverage sector firstly the use of Electronic Data Interchange (EDI), ERP, Continuous Replenishment (CR) and Drum-Buffer-Rope Order (DBR) (for situations in which the plants of both companies are distant), and secondly EDI, ERP, Milk-Run and Review System Continues (for situations in which the plants of both companies are close); c) for the garment industry the use of Collaborative Planning, Forecasting, and Replenishment (CPFR) and Constant Work-In-Process (CONWIP) System; d) for the sugarcane sector the use of EDI, ERP and CONWIP System; e) for the mineral processes industry the use of Vendor Managed Inventory (VMI), EDI and MaxMin Control System; f) for the metal mechanical sector the use of CONWIP System and Continuous Replenishment (CR). It should be emphasized that the proposals are exclusively recommended for the relationship between client and supplier studied. Therefore, it cannot be generalized to other cases. However, what can be generalized is the methodology used to choose the best practices for each case. Based on the study, it can be concluded that the combined use of OS and logistics practices enable a better coordination of flow production on SC.

Keywords: supply chain management, production flow coordination, logistics practices, ordering systems

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Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

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Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: T. Tommasi, E. Batuecas, G. Mancini, G. Saracco, D. Fino

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Extra virgin olive-oil (EVO) production is an important economic activity for several countries, especially in the Mediterranean area such as Spain, Italy, Greece and Tunisia. The two major by-products from olive oil production, solid-liquid Olive Pomace (OP) and the Olive Mill Waste Waters (OMWW), are still mainly disposed on soil, in spite of the existence of legislation which already limits this practice. The present study compares the environmental impacts associated with two different scenarios for the management of waste from olive oil production through a comparative Life Cycle Assessment (LCA). The two alternative scenarios are: (I) Anaerobic Digestion and (II) current Disposal on soil. The analysis was performed through SimaPro software and the assessment of the impact categories was based on International Life Cycle Data and Cumulative Energy Demand methods. Both the scenarios are mostly related to the cultivation and harvesting phase and are highly dependent on the irrigation practice and related energy demand. Results from the present study clearly show that as the waste disposal on soil causes the worst environmental performance of all the impact categories here considered. Important environmental benefits have been identified when anaerobic digestion is instead chosen as the final treatment. It was consequently demonstrated that anaerobic digestion should be considered a feasible alternative for olive mills, to produce biogas from common olive oil residues, reducing the environmental burden and adding value to the olive oil production chain.

Keywords: anaerobic digestion, waste management, agro-food waste, biogas

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Authors: Ning Li, Jiacheng Zhang, Zheng Yang, Sylvia Kang

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Introduction: Polycystic ovary syndrome (PCOS) is a common physiological symptom in women of reproductive age. Women with PCOS may have infrequent or prolonged menstrual periods and excess male hormone (androgen) levels. Mira analyzes the cycle profiles and the luteinizing hormone (LH) changes in urine, closely related to the fertility level of healthy women and PCOS women. From the difference between the two groups, Mira helps to understand the physiological state of PCOS women and their hormonal changes in the menstrual cycle. Methods: In this study, data from 1496 cycles and information from 342 women belonging to two groups (181 PCOS and 161 Healthy) were collected and analyzed. Women test their luteinizing hormone (LH) in urine daily with Mira fertility test wand and Mira analyzer, from the day after the menstruation to the starting day of the next menstruation. All the collected data meets Mira’s user agreement and users’ identification was removed. The cycle length, LH peak, and other cycle information of the PCOS group were compared with the Healthy group. Results: The average cycle length of PCOS women is 41 days and of the Healthy women is 33 days. 91.4% of cycle length is within 40 days for the Healthy group, while it decreases to 71.9% for the PCOS group. This means PCOS women have a longer menstrual cycle and more variation during the cycle. With more variation, the ovulation prediction becomes more difficult for the PCOS group. The deviation between the LH surge day and the predicted ovulation day, calculated by the starting day of the next menstruation minus 14 days, is greater in the PCOS group compared with the Healthy group. Also, 46.96% of PCOS women have an irregular cycle, and only 19.25% of healthy women show an irregular cycle. Conclusion: PCOS women have longer menstrual cycles and more variation during the menstrual cycles. The traditional ovulation prediction is not suitable for PCOS women.

Keywords: menstrual cycle, PCOS, urinary luteinizing hormone, Mira

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Authors: Sormeh Sharifi, Wasim Saman, Alemu Alemu, David Whaley

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Although various energy rating schemes and compulsory building codes are using around the world, there are increasing reports on overheating in energy efficient dwellings. Given that the cooling demand of buildings is rising globally because of the climate change, it is more likely that the overheating issue will be observed more. This paper studied the summer indoor temperature in eight air-conditioned multi-level houses in Adelaide which have complied with the Australian Nationwide Houses Energy Rating Scheme (NatHERS) minimum energy performance of 7.5 stars. Through monitored temperature, this study explores that overheating is experienced on 75.5% of top floors during cooling periods while the air-conditioners were running. This paper found that the energy efficiency regulations have significantly improved thermal comfort in low floors, but not on top floors, and the energy-efficient house is not necessarily adapted with the air temperature fluctuations particularly on top floors. Based on the results, this study suggests that the envelope of top floors for multi-level houses in South Australian context need new criteria to make the top floor more heat resistance in order to: preventing the overheating, reducing the summer pick electricity demand and providing thermal comfort. Some methods are used to improve the envelope of the eight case studies. The results demonstrate that improving roofs was the most effective part of the top floors envelope in terms of reducing the overheating.

Keywords: building code, climate change, energy-efficient building, energy rating, overheating, thermal comfort

Procedia PDF Downloads 198

Authors: Anshita Sharma

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India is one of the countries to initiate family planning with intention to control the growing population by reducing fertility. In effort to this, India had introduced the National family planning programme in 1952. The level of unmet need in India shows a reducing trend with increasing effectiveness of family planning services as in NFHS-1 the unmet need for limiting, spacing and total was 46 percent, 14 percent & 9 percent, respectively. The demand for spacing has reduced to at 8 percent, 8 percent for limiting and total unmet need was 16 percent in NFHS-2. The total unmet need has reduced to 13 percent in NFHS-3 for all currently married women and the demand for limiting and spacing is 7 percent and 6 percent respectively. The level of unmet need in India shows a reducing trend with increasing effectiveness of family planning services. Despite the progress, there is chunk of women who are deprived of controlling unintended and unwanted pregnancies. The present paper examines the socio-cultural and economic and demographic correlates of unmet need for contraception in India. It also examines the effect of women’s autonomy and unmet need for contraception on family size among different socio-economic groups of population. It uses data from national family health survey-3 carried out in 2005-06 and employs bi-variate techniques and multivariate techniques for analysis. The multiple regression analysis has done to seek the level and direction of relationship among various socio-economic and demographic factors. The result reveals that women with higher level of education and economic status have low level of unmet need for family planning. Women living in non-nuclear family have high unmet need for spacing and women living in nuclear family have high unmet need for limiting and family size is slightly higher of women of nuclear family. In India, the level of autonomy varies at different life point; usually women with higher age enjoy higher autonomy than their junior female member in the family. The finding shows that women with higher autonomy have large family size counter to women with low autonomy have low family size. Unmet need for family planning decrease with women’s increasing exposure to mass- media. The demographic factors like experience of child loss are directly related to family size. Women who experience higher child loss have low unmet need for spacing and limiting. Thus, It is established with the help that women’s autonomy status play substantial role in fulfilling demand of contraception for limiting and spacing which affect the family size.

Keywords: family size, socio-economic correlates, unmet need for limiting, unmet need for spacing, women`s autonomy

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Authors: Sunil Arora, Anitya Kumar Jena, S. A. Ravi

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India is at the cusp of major reforms in the hydrocarbon sector. Oil and gas sector is highly liberalised to attract private investment and to increase domestic production. Major hydrocarbon Exploration & Production (E&P) activity here have been undertaken by Government owned companies but with easing up and reworking of hydro carbon exploration licensing policies private players have also joined the fray towards achieving energy security for India. Government of India has come up with policy and administrative reforms including Hydrocarbon Exploration and Licensing Policy (HELP), Sagarmala (port-led development with coastal connectivity), and Development of Small Discovered Fields, etc. with the intention to make industry friendly conditions for investment, ease of doing business and reduce gestation period. To harness the potential resources of Deep water and Ultra deep water, High Pressure – High Temperature (HP-HT) regions, Coal Bed Methane (CBM), Shale Hydrocarbons besides Gas Hydrates, participation shall be required from both domestic and international players. Companies engaged in E&P activities in India have traditionally been managing through their captive supply base, but with crude prices under hammer, the need is being felt to outsource non-core activities. This necessitates establishment of a robust support services to cater to E&P Industry, which is currently non-existent to meet the bourgeon challenges. This paper outlines an agenda for creating an Integrated Services Hub (ISH) under Special Economic Zone (SEZ) to facilitate complete gamut of non-core support activities of E&P industry. This responsive and proficient multi-usage facility becomes viable with better resource utilization, economies of scale to offer cost effective services. The concept envisages companies to bring-in their core technical expertise leaving complete hardware peripherals outsourced to this ISH. The Integrated Services Hub, complying with the best in class global standards, shall typically provide following Services under Single Window Solution, but not limited to: a) Logistics including supply base operations, transport of manpower and material, helicopters, offshore supply vessels, warehousing, inventory management, sourcing and procurement activities, international freight forwarding, domestic trucking, customs clearance service etc. b) Trained/Experienced pool of competent Manpower (Technical, Security etc.) will be available for engagement by companies on either short or long term basis depending upon the requirements with provisions of meeting any training requirements. c) Specialized Services through tie-up with global best companies for Crisis Management, Mud/Cement, Fishing, Floating Dry-dock besides provision of Workshop, Repair and Testing facilities, etc. d) Tools and Tackles including drill strings, etc. A pre-established Integrated Services Hub shall facilitate an early start-up of activities with substantial savings in time lines. This model can be replicated at other parts of the world to expedite E&P activities.

Keywords: integrated service hub, India, oil gas, offshore supply base

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Authors: Som Pal Baliyan

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Dairy enterprise has been a major source of employment and income generation in most of the economies worldwide. Botswana government has also identified dairy as one of the agricultural sectors towards diversification of the mineral dependent economy of the country. The huge gap between local demand and supply of milk and milk products indicated that there are not only constraints but also; opportunities exist in this sub sector of agriculture. Therefore, this study was an attempt to identify constraints and opportunities in dairy production industry in Botswana. The possible ways to mitigate the constraints were also identified. The findings should assist the stakeholders especially, policy makers in the formulation of effective policies for the growth of dairy sector in the country. This quantitative study adopted a survey research design. A final survey followed by a pilot survey was conducted for data collection. The purpose of the pilot survey was to collect basic information on the nature and extent of the constraints, opportunities and ways to mitigate the constraints in dairy production. Based on the information from pilot survey, a four point Likert’s scale type questionnaire was constructed, validated and tested for its reliability. The data for the final survey were collected from purposively selected twenty five dairy farms. The descriptive statistical tools were employed to analyze data. Among the twelve constraints identified; high feed costs, feed shortage and availability, lack of technical support, lack of skilled manpower, high prevalence of pests and diseases and, lack of dairy related technologies were the six major constraints in dairy production. Grain feed production, roughage feed production, manufacturing of dairy feed, establishment of milk processing industry and, development of transportation systems were the five major opportunities among the eight opportunities identified. Increasing production of animal feed locally, increasing roughage feed production locally, provision of subsidy on animal feed, easy access to sufficient financial support, training of the farmers and, effective control of pests and diseases were identified as the six major ways to mitigate the constraints. It was recommended that the identified constraints and opportunities as well as the ways to mitigate the constraints need to be carefully considered by the stakeholders especially, policy makers during the formulation and implementation of the policies for the development of dairy sector in Botswana.

Keywords: dairy enterprise, milk production, opportunities, production constraints

Procedia PDF Downloads 386

Authors: Tami A. Ulhiza, Noor I. M. Puad, Azlin S. Azmi, Mohd. I. A. Malek

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High amount of chemical oxygen demand (COD) in starchy waste can be harmful to the environment. In common practice, starch processing wastewater is discharged to the river without proper treatment. However, starchy waste still contains complex sugars and organic acids. By the right pretreatment method, the complex sugar can be hydrolyzed into more readily digestible sugars which can be utilized to be converted into more valuable products. At the same time, the global demand of energy is inevitable. The continuous usage of fossil fuel as the main source of energy can lead to energy scarcity. Hydrogen is a renewable form of energy which can be an alternative energy in the future. Moreover, hydrogen is clean and carries the highest energy compared to other fuels. Biohydrogen produced from waste has significant advantages over chemical methods. One of the major problems in biohydrogen production is the raw material cost. The carbohydrate-rich starchy wastes such as tapioca, maize, wheat, potato, and sago wastes is a promising candidate to be used as a substrate in producing biohydrogen. The utilization of those wastes for biohydrogen production can provide cheap energy generation with simultaneous waste treatment. Therefore this paper aims to review variety source of starchy wastes that has been widely used to synthesize biohydrogen. The scope includes the source of waste, the performance in yielding hydrogen, the pretreatment method and the type of culture that is suitable for starchy waste.

Keywords: biohydrogen, dark fermentation, renewable energy, starchy waste

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Authors: D. Hephzibah, P. Kumaran, N. M. Saifuddin

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Anaerobic digestion is a well-known technique for sustainable energy recovery from sewage sludge. However, sewage sludge digestion is restricted due to certain factors. Pre-treatment methods have been established in various publications as a promising technique to improve the digestibility of the sewage sludge and to enhance the biogas generated which can be used for energy recovery. In this study, continuous flow microwave (MW) pre-treatment with different intensities were compared by using 5 L semi-continuous digesters at a hydraulic retention time of 27 days. We focused on the effects of MW at different intensities on the sludge solubilization, sludge digestibility, and biogas production of the untreated and MW pre-treated sludge. The MW pre-treatment demonstrated an increase in the ratio of soluble chemical oxygen demand to total chemical oxygen demand (sCOD/tCOD) and volatile fatty acid (VFA) concentration. Besides that, the total volatile solid (TVS) removal efficiency and tCOD removal efficiency also increased during the digestion of the MW pre-treated sewage sludge compared to the untreated sewage sludge. Furthermore, the biogas yield also subsequently increases due to the pre-treatment effect. A higher MW power level and irradiation time generally enhanced the biogas generation which has potential for sustainable energy recovery from sewage treatment plant. However, the net energy balance tabulation shows that the MW pre-treatment leads to negative net energy production.

Keywords: anaerobic digestion, biogas, microwave pre-treatment, sewage sludge

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Authors: Selamawit Dires, Solomon Tesfamariam, Thomas Tannert

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Modern earthquake engineering and design encompass performance-based design philosophy. The main objective in performance-based design is to achieve a system performing precisely to meet the design objectives so to reduce unintended seismic risks and associated losses. Energy-based earthquake-resistant design is one of the design methodologies that can be implemented in performance-based earthquake engineering. In energy-based design, the seismic demand is usually described as the ratio of the hysteretic to input energy. Once the hysteretic energy is known as a percentage of the input energy, it is distributed among energy-dissipating components of a structure. The hysteretic to input energy ratio is highly dependent on the inherent damping of a structural system. In numerical analysis, damping can be modeled as stiffness-proportional, mass-proportional, or a linear combination of stiffness and mass. In this study, the effect of mathematical modeling of damping on the estimation of seismic energy demands is investigated by considering elastic-perfectly-plastic single-degree-of-freedom systems representing short to long period structures. Furthermore, the seismicity of Vancouver, Canada, is used in the nonlinear time history analysis. According to the preliminary results, the input energy demand is not sensitive to the type of damping models deployed. Hence, consistent results are achieved regardless of the damping models utilized in the numerical analyses. On the other hand, the hysteretic to input energy ratios vary significantly for the different damping models.

Keywords: damping, energy-based seismic design, hysteretic energy, input energy

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Authors: Kalyan Sundar Som, Ghanshyam Prasad Jhariya

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Population growth is an important pervasive phenomenon in the world. Its survival depends upon many daily needs and food is one of them. Population factors play a decisive role in the human endeavor to attain food. Nutrition and health status compose integral part of human development and progress of a society. Therefore, the neglect any one of these components may leads to the deterioration of the quality of life. Food is also intimately related with economic growth and social progress as well as with political stability and peace. It refers to the availability of food and its access to it. It can be observed from global to local level. Food scarcity has emerged as a matter of great concern all over the world due to uncontrolled and unregulated growth of population .For this purpose this study try to find out the deficit or surplus production of food availability in terms of their total population in the study area. It also ascertains the population pressure, demand and supply of food stuff and demarcation of insecure areas.The data base of the study under discussion includes government published data regarding agriculture production, yield and cropped area in 2005-06 to 2011-12 available at commissioner land record Madhya Pradesh, Gwalior. It also includes the census of India for population data. For measuring food security or insecurity regions is based on the consumption of net food available in terms caloric value minus the consumption by the weighted total population. This approach has been adopted because the direct estimate of production and consumption is the only reliable way to ascertain food security in a unit area and to compare one area with another (Noor Mohammad, dec. 2002). The scenario in 2005-06 is 57.78 percent district has food insufficient in terms of their population. On the other hand after 5 years, there are only 22 % districts are deficit in term of food availability where Burhanpur is the most deficit (56 percent) district. While 20% district are highly surplus district in the state where Harda and Hoshangabad districts are very high surplus district (5 times and 3.95 times) in term of food availability(2011). The drastic change (agriculture transformation) is happen due government good intervention in the agricultural sector.

Keywords: agriculture transformation, caloric value method, deficit or surplus region, population pressure

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Authors: G. Baranski, A. Majczak, M. Wendeker

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Currently, the most commonly used solution to provide fuel to the diesel engines is the Common Rail system. Compared to previous designs, as a due to relatively simple construction and electronic control systems, these systems allow achieving favourable engine operation parameters with particular emphasis on low emission of toxic compounds into the atmosphere. In this system, the amount of injected fuel dose is strictly dependent on the course of parameters of the electrical impulse sent by the power amplifier power supply system injector from the engine controller. The article presents the construction of a laboratory test bench to examine the course of the injection process and the expense in storage injection systems. The test bench enables testing of injection systems with electromagnetically controlled injectors with the use of scientific engineering tools. The developed system is based on LabView software and CompactRIO family controller using FPGA systems and a real time microcontroller. The results of experimental research on electromagnetic injectors of common rail system, controlled by a dedicated National Instruments card, confirm the effectiveness of the presented approach. The results of the research described in the article present the influence of basic parameters of the electric impulse opening the electromagnetic injector on the value of the injected fuel dose. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A.’ and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: fuel injector, combustion engine, fuel pressure, compression ignition engine, power supply system, controller, LabVIEW

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Authors: Nivedita Sharma

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The global demand for fossil fuels is very high, but their use is not sustainable since its reserves are declining. Additionally, fossil fuels are responsible for the accumulation of greenhouse gases. The emission of greenhouse gases from the transport sector can be reduced by substituting fossil fuels by biofuels. Thus, renewable fuels capable of sequestering carbon dioxide are in high demand. Second‐generation biofuels, which require lignocellulosic biomass as a substrate and ultimately producing ethanol, fall largely in this category. Bioethanol is a favorable and near carbon-neutral renewable biofuel leading to reduction in tailpipe pollutant emission and improving the ambient air quality. Lignocellulose consists of three main components: cellulose, hemicellulose and lignin which can be converted to ethanol with the help of microbial enzymes. Enzymatic hydrolysis of lignocellulosic biomass in 1st step is considered as the most efficient and least polluting methods for generating fermentable hexose and pentose sugars which subsequently are fermented to power alcohol by yeasts in 2nd step of the process. In the present technology, a complete bioconversion process i.e. potential hydrolytic enzymes i.e. cellulase and xylanase producing microorganisms have been isolated from different niches, screened for enzyme production, identified using phenotyping and genotyping, enzyme production, purification and application of enzymes for saccharification of different lignocellulosic biomass followed by fermentation of hydrolysate to ethanol with high yield is to be presented in detail.

Keywords: cellulase, xylanase, lignocellulose, bioethanol, microbial enzymes

Procedia PDF Downloads 87

Authors: Margaret K. Spoo-Chupka

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The Metropolitan Water District of Southern California (MWDSC) manages surface water reservoirs that are a source of drinking water for more than 19 million people in Southern California. These reservoirs experience periodic planktonic cyanobacteria blooms that can impact water quality. MWDSC imports water from two sources – the Colorado River (CR) and the State Water Project (SWP). The SWP brings supplies from the Sacramento-San Joaquin Delta that are characterized as having higher nutrients than CR water. Above average precipitation in 2017 after five years of drought allowed the majority of the reservoirs to fill. Phytoplankton was analyzed during the drought and after the drought at three reservoirs: Diamond Valley Lake (DVL), which receives SWP water exclusively, Lake Skinner, which can receive a blend of SWP and CR water, and Lake Mathews, which generally receives only CR water. DVL experienced a significant increase in water elevation in 2017 due to large SWP inflows, and there were no significant changes to total phytoplankton biomass, Shannon-Wiener diversity of the phytoplankton, or cyanobacteria biomass in 2017 compared to previous drought years despite the higher nutrient loads. The biomass of cyanobacteria that could potentially impact DVL water quality (Microcystis spp., Aphanizomenon flos-aquae, Dolichospermum spp., and Limnoraphis birgei) did not differ significantly between the heavy precipitation year and drought years. Compared to the other reservoirs, DVL generally has the highest concentration of cyanobacteria due to the water supply having greater nutrients. Lake Mathews’ water levels were similar in drought and wet years due to a reliable supply of CR water and there were no significant changes in the total phytoplankton biomass, phytoplankton diversity, or cyanobacteria biomass in 2017 compared to previous drought years. The biomass of cyanobacteria that could potentially impact water quality at Lake Mathews (L. birgei and Microcystis spp.) did not differ significantly between 2017 and previous drought years. Lake Mathews generally had the lowest cyanobacteria biomass due to the water supply having lower nutrients. The CR supplied most of the water to Lake Skinner during drought years, while the SWP was the primary source during 2017. This change in water source resulted in a significant increase in phytoplankton biomass in 2017, no significant change in diversity, and a significant increase in cyanobacteria biomass. Cyanobacteria that could potentially impact water quality at Skinner included: Microcystis spp., Dolichospermum spp., and A.flos-aquae. There was no significant difference in Microcystis spp. biomass in 2017 compared to previous drought years, but biomass of Dolichospermum spp. and A.flos-aquae were significantly greater in 2017 compared to previous drought years. Dolichospermum sp. and A. flos-aquae are two cyanobacteria that are more sensitive to nutrients than Microcystis spp., which are more sensitive to temperature. Patterns in problem cyanobacteria abundance among Southern California reservoirs as a result of above-average precipitation after more than five years of drought were most closely related to nutrient loading.

Keywords: drought, reservoirs, cyanobacteria, and phytoplankton ecology

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Authors: S. M. Islam, Wasi Uddin, Nazmun Nahar

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Dhaka, the capital of Bangladesh, faces two contrasting problems; excess of water during monsoon season and scarcity of water during dry season. The first problem occurs due to rapid urbanization and mismanagement of rainwater whereas the second problem is related to climate change and increasing urban population. Inadequate drainage system also worsens the overall water management scenario in Dhaka city. Dhaka has a population density of 115,000 people per square miles. This results in a 2.5 billion liter water demand every day, 87% of which is fulfilled by groundwater. Over dependency on groundwater has resulted in more than 200 feet drop in the last 50 years and continues to decline at a rate of 9 feet per year. Considering the gravity of the problem, it is high time that practitioners, academicians and policymakers consider different water management practices and look into their cumulative impacts at different scales. The present study assesses different rainwater management options for North South University of Bangladesh and recommends the most feasible and sustainable rainwater management measure. North South University currently accommodates over 20,000 students, faculty members, and administrative staffs. To fulfill the water demand, there are two deep tube wells, which bring up approximately 150,000 liter of water every hour. The annual water demand is approximately 103 million liters. Dhaka receives approximately 1800 mm of rainfall every year. For the current study, two academic buildings and one administrative building consist of 4924 square meters of rooftop area was selected as catchment area. Both rainwater harvesting and groundwater recharge options were analyzed separately. It was estimated that by rainwater harvesting, annually a total of 7.2 million liters of water can be reused which is approximately 7% of the total annual water usage. In the monsoon, rainwater harvesting fulfills 12.2% of the monthly water demand. The approximate cost of the rainwater harvesting system is estimated to be 940975 bdt (USD 11500). For direct groundwater recharge, a system comprises of one de-siltation tank, two recharge tanks and one siltation tank were designed that requires approximately 532788 bdt (USD 6500). The payback period is approximately 7 years and 4 months for the groundwater recharge system whereas the payback period for rainwater harvesting option is approximately 12 years and 4 months. Based on the cost-benefit analysis, the present study finds the groundwater recharge system to be most suitable for North South University. The present study also demonstrates that if only one institution like North South University can add up a substantial amount of water to the aquifer, bringing other institutions in the network has the potential to create significant cumulative impact on replenishing the declining groundwater level of Dhaka city. As an additional benefit, it also prevents large amount of water being discharged into the storm sewers which results in severe flooding in Dhaka city during monsoon.

Keywords: Dhaka, groundwater, harvesting, rainwater, recharge

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Authors: Agnieszka Dubiel, Artur Grabowski, Tomasz Przerywacz, Mateusz Roganowicz, Patrycja Zioty

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Food waste is one of the most significant challenges humanity is facing nowadays. Every year, reports from global organizations show the scale of the phenomenon, although society's awareness is still insufficient. One-third of the food produced in the world is wasted at various points in the food supply chain. Wastes are present from the delivery through the food preparation and distribution to the end of the sale and consumption. The first step in understanding and resisting the phenomenon is a thorough analysis of the everyday behaviors of humanity. This concept is understood as finding the correlation between the type of food and the reason for throwing it out and wasting it. Those actions were identified as a critical step in the start of work to develop technology to prevent food waste. In this paper, the problem mentioned above was analyzed by focusing on the inhabitants of Central Europe, especially Poland, aged 20-30. This paper provides an insight into collecting data through dedicated software and an organized database. The proposed database contains information on the amount, type, and reasons for wasting food in households. A literature review supported the work to answer research questions, compare the situation in Poland with the problem analyzed in other countries, and find research gaps. The proposed article examines the cause of food waste and its quantity in detail. This review complements previous reviews by emphasizing social and economic innovation in Poland's food waste management. The paper recommends a course of action for future research on food waste management and prevention related to the handling and disposal of food, emphasizing households, i.e., the last link in the supply chain.

Keywords: food waste, food waste reduction, consumer food waste, human-food interaction

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Authors: Prashant Verma, Prafulla K. Swain, K. K. Singh, Mukti Khetan

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Objective: In India, around 20,000 women die every year due to abortion-related complications. In the modelling of count variables, there is sometimes a preponderance of zero counts. This article concerns the estimation of various count regression models to predict the average number of spontaneous abortion among women in the Punjab state of India. It also assesses the factors associated with the number of spontaneous abortions. Materials and methods: The study included 27,173 married women of Punjab obtained from the DLHS-4 survey (2012-13). Poisson regression (PR), Negative binomial (NB) regression, zero hurdle negative binomial (ZHNB), and zero-inflated negative binomial (ZINB) models were employed to predict the average number of spontaneous abortions and to identify the determinants affecting the number of spontaneous abortions. Results: Statistical comparisons among four estimation methods revealed that the ZINB model provides the best prediction for the number of spontaneous abortions. Antenatal care (ANC) place, place of residence, total children born to a woman, woman's education and economic status were found to be the most significant factors affecting the occurrence of spontaneous abortion. Conclusions: The study offers a practical demonstration of techniques designed to handle count variables. Statistical comparisons among four estimation models revealed that the ZINB model provided the best prediction for the number of spontaneous abortions and is recommended to be used to predict the number of spontaneous abortions. The study suggests that women receive institutional Antenatal care to attain limited parity. It also advocates promoting higher education among women in Punjab, India.

Keywords: count data, spontaneous abortion, Poisson model, negative binomial model, zero hurdle negative binomial, zero-inflated negative binomial, regression

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Authors: Kunihisa Kakumoto

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Purpose: The global environmental problem is now raised in the global dimension. The sprawl phenomenon over the natural limitation is to be made a forecast beforehand in an algorithmic way so that the condition of our social life can hopefully be protected under the natural limitation. The sustainable condition in the globe is now to be found to keep the balance between the capacity of nature and the possibility of our social lives. The amount of water on the earth is limited. Therefore, on the reason, sustainable conditions are strongly dependent on the capacity of water. The amount of water can be considered in relation to the area of the green planting because a certain volume of the water can be obtained in the forest, where the green planting can be preserved. We can find the sustainable conditions of the water in relation to the green planting area. The reduction of CO₂ by green planting is also possible. Possible Measure and the Methods: Until now, by the opportunity of many international conferences, the concept of the solar community as one prototype has been introduced by technical papers. The algorithmic trial calculation on the basic concept of the solar community can be taken into consideration. The concept of the solar community is based on the collected data of the solar model house. According to the algorithmic results of the prototype, the simulation work in the globe can be performed as the algorithmic conversion results. This algorithmic study can be simulated by the amount of water, also in relation to the green planting area. Additionally, the submission of CO₂ in the solar community and the reduction of CO₂ by green planting can be calculated. On the base of these calculations in the solar community, the sustainable conditions on the globe can be simulated as the conversion results in an algorithmic way. The digital formation in the solar community can also be taken into consideration by this opportunity. Conclusion: For the finding of sustainable conditions around the globe, the solar community as one prototype has been taken into consideration. The role of the water is very important because the capacity of the water supply is very limited. But, at present, the cycle of the social community is not composed by the point of the natural mechanism. The simulative calculation of this study can be shown by the limitation of the total water supply. According to this process, the total capacity of the water supply and the capable residential number of the population and the areas can be taken into consideration by the algorithmic calculation. For keeping enough water, the green planting areas are very important. The planting area is also very important to keep the balance of CO₂. The simulative calculation can be performed by the relation between the submission and the reduction of CO₂ in the solar community. For the finding of this total balance and the sustainable conditions, the green planting area and the total amount of water can be recognized by the algorithmic simulative calculation. The study for the finding of sustainable conditions can be performed by the simulative calculations on the algorithmic model in the solar community as one prototype. The example of one prototype can be in balance. The activity of the social life must be in the capacity of the natural mechanism. The capable capacity of the natural environment in our world is very limited.

Keywords: the solar community, the sustainable condition, the natural limitation, the algorithmic calculation

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Authors: Cheng-Chi Yu, Chi-Shiun Chiou

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This study developed a plug-in hybrid powertrain system which consisted of two continuous variable transmissions. By matching between the engine, motor, generator, and dual continuous variable transmissions, this integrated power system can take advantages of the components. The hybrid vehicle can be driven by the internal combustion engine, or electric motor alone, or by these two power sources together when the vehicle is driven in hard acceleration or high load. The energy management of this integrated hybrid system controls the power systems based on rule-based control strategy to achieve better fuel economy. When the vehicle driving power demand is low, the internal combustion engine is operating in the low efficiency region, so the internal combustion engine is shut down, and the vehicle is driven by motor only. When the vehicle driving power demand is high, internal combustion engine would operate in the high efficiency region; then the vehicle could be driven by internal combustion engine. This strategy would operate internal combustion engine only in optimal efficiency region to improve the fuel economy. In this research, the vehicle simulation model was built in MATLAB/ Simulink environment. The analysis results showed that the power coupled efficiency of the hybrid powertrain system with dual continuous variable transmissions was better than that of the Honda hybrid system on the market.

Keywords: plug-in hybrid power system, fuel economy, performance, continuously variable transmission

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Authors: Aschalew Cherie Workneh, K. S. Hari Prasad, Chandra Shekhar Prasad Ojha

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Due to the increase in water scarcity, the crop water stress index (CWSI) is receiving significant attention these days, especially in arid and semiarid regions, for quantifying water stress and effective irrigation scheduling. Nowadays, machine learning techniques such as neural networks are being widely used to determine CWSI. In the present study, the performance of two artificial neural networks, namely, Self-Organizing Maps (SOM) and Feed Forward-Back Propagation Artificial Neural Networks (FF-BP-ANN), are compared while determining the CWSI of rice crop. Irrigation field experiments with varying degrees of irrigation were conducted at the irrigation field laboratory of the Indian Institute of Technology, Roorkee, during the growing season of the rice crop. The CWSI of rice was computed empirically by measuring key meteorological variables (relative humidity, air temperature, wind speed, and canopy temperature) and crop parameters (crop height and root depth). The empirically computed CWSI was compared with SOM and FF-BP-ANN predicted CWSI. The upper and lower CWSI baselines are computed using multiple regression analysis. The regression analysis showed that the lower CWSI baseline for rice is a function of crop height (h), air vapor pressure deficit (AVPD), and wind speed (u), whereas the upper CWSI baseline is a function of crop height (h) and wind speed (u). The performance of SOM and FF-BP-ANN were compared by computing Nash-Sutcliffe efficiency (NSE), index of agreement (d), root mean squared error (RMSE), and coefficient of correlation (R²). It is found that FF-BP-ANN performs better than SOM while predicting the CWSI of rice crops.

Keywords: artificial neural networks; crop water stress index; canopy temperature, prediction capability

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Authors: C. Bala Prashanth Reddy, B. Abhinay, C. Sreekar, D. V. Shobhana Priscilla

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The project aims in designing an emergency pacemaker which is capable of giving shocks to a human heart which has stopped working suddenly. A pacemaker is a machine commonly used by cardiologists. This machine is used in order to shock a human’s heart back into usage. The way the heart works is that there are small cells called pacemakers sending electrical pulses to cardiac muscles that tell the heart when to pump blood. When these electrical pulses stop, the heart stops beating. When this happens, a pacemaker is used to shock the heart muscles and the pacemakers back into action. The way this is achieved is by rubbing the two panels of the pacemaker together to create an adequate electrical current, and then the heart gets back to the normal state. The project aims in designing a system which is capable of continuously displaying the heart beat and blood pressure of a person on LCD. The concerned doctor gets the heart beat and also the blood pressure details continuously through the GSM Modem in the form of SMS alerts. In case of abnormal condition, the doctor sends message format regarding the amount of electric shock needed. Automatically the microcontroller gives the input to the pacemaker which in turn gives the shock to the patient. Heart beat monitor and display system is a portable and a best replacement for the old model stethoscope which is less efficient. The heart beat rate is calculated manually using stethoscope where the probability of error is high because the heart beat rate lies in the range of 70 to 90 per minute whose occurrence is less than 1 sec, so this device can be considered as a very good alternative instead of a stethoscope.

Keywords: missing R wave, PWM, demand pacemaker, heart

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Authors: Rashid S. Mohammad, Shicheng Zhang, Xinzhe Zhao

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In tight oil reservoirs, wettability alteration has generally been considered as an effective way to remove fracturing fluid retention on the surface of the fracture and consequently improved oil production. However, there is a lack of a reliable productivity prediction model to show the relationship between the wettability and oil production in tight oil well. In this paper, a new oil productivity prediction model of immiscible oil-water flow and miscible CO₂-oil flow accounting for wettability is developed. This mathematical model is established by considering two different length scales: nonporous network and propped fractures. CO₂ flow diffuses in the nonporous network and high velocity non-Darcy flow in propped fractures are considered by taking into account the effect of wettability alteration on capillary pressure and relative permeability. A laboratory experiment is also conducted here to validate this model. Laboratory experiments have been designed to compare the water saturation profiles for different contact angle, revealing the fluid retention in rock pores that affects capillary force and relative permeability. Four kinds of brines with different concentrations are selected here to create different contact angles. In water-wet porous media, as the system becomes more oil-wet, water saturation decreases. As a result, oil relative permeability increases. On the other hand, capillary pressure which is the resistance for the oil flow increases as well. The oil production change due to wettability alteration is the result of the comprehensive changes of oil relative permeability and capillary pressure. The results indicate that wettability is a key factor for fracturing fluid retention removal and oil enhancement in tight reservoirs. By incorporating laboratory test into a mathematical model, this work shows the relationship between wettability and oil production is not a simple linear pattern but a parabolic one. Additionally, it can be used for a better understanding of optimization design of fracturing fluids.

Keywords: wettability, relative permeability, fluid retention, oil production, unconventional and tight reservoirs

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Authors: Ginger Egberts, Marianne Schaaphok, Fred Vermolen, Paul van Zuijlen

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A few years ago, a promising morphoelastic model was developed for the simulation of contraction formation after burn injuries. Contraction can lead to a serious reduction in physical mobility, like a reduction in the range-of-motion of joints. If this is the case in a healing burn wound, then this is referred to as a contracture that needs medical intervention. The morphoelastic model consists of a set of partial differential equations describing both a chemical part and a mechanical part in dermal wound healing. These equations are solved with the numerical finite element method (FEM). In this method, many calculations are required on each of the chosen elements. In general, the more elements, the more accurate the solution. However, the number of elements increases rapidly if simulations are performed in 2D and 3D. In that case, it not only takes longer before a prediction is available, the computation also becomes more expensive. It is therefore important to investigate alternative possibilities to generate the same results, based on the input parameters only. In this study, a surrogate neural network has been designed to mimic the results of the one-dimensional morphoelastic model. The neural network generates predictions quickly, is easy to implement, and there is freedom in the choice of input and output. Because a neural network requires extensive training and a data set, it is ideal that the one-dimensional FEM code generates output quickly. These feed-forward-type neural network results are very promising. Not only can the network give faster predictions, but it also has a performance of over 99%. It reports on the relative surface area of the wound/scar, the total strain energy density, and the evolutions of the densities of the chemicals and mechanics. It is, therefore, interesting to investigate the applicability of a neural network for the two- and three-dimensional morphoelastic model for contraction after burn injuries.

Keywords: biomechanics, burns, feasibility, feed-forward NN, morphoelasticity, neural network, relative surface area wound

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Authors: Chao Xu

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Selecting ground motion intensity measures reasonably is one of the very important issues to affect the input ground motions selecting and the reliability of vulnerability analysis results. In this paper, inelastic spectral displacement is used as an alternative intensity measure to characterize the ground motion damage potential. The inelastic spectral displacement is calculated based modal pushover analysis and inelastic spectral displacement based incremental dynamic analysis is developed. Probability seismic demand analysis of a six story and an eleven story RC frame are carried out through cloud analysis and advanced incremental dynamic analysis. The sufficiency and efficiency of inelastic spectral displacement are investigated by means of regression and residual analysis, and compared with elastic spectral displacement. Vulnerability curves are developed based on inelastic spectral displacement. The study shows that inelastic spectral displacement reflects the impact of different frequency components with periods larger than fundamental period on inelastic structural response. The damage potential of ground motion on structures with fundamental period prolonging caused by structural soften can be caught by inelastic spectral displacement. To be compared with elastic spectral displacement, inelastic spectral displacement is a more sufficient and efficient intensity measure, which reduces the uncertainty of vulnerability analysis and the impact of input ground motion selection on vulnerability analysis result.

Keywords: vulnerability, probability seismic demand analysis, ground motion intensity measure, sufficiency, efficiency, inelastic time history analysis

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Authors: Parul Jindal, Shubhi Singh, Priya Ramakrishnan, Shailender Raghuvanshi

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Background: Knowledge of the influence of the age of the child on laryngeal dimensions is essential for all practitioners who are dealing with paediatric airway. Choosing the correct endotracheal tube (ETT) size is a crucial step in pediatric patients because a large-sized tube may cause complications like post-extubation stridor and subglottic stenosis. On the other hand with a smaller tube, there will be increased gas flow resistance, aspiration risk, poor ventilation, inaccurate monitoring of end-tidal gases and reintubation may also be required with a different size of the tracheal tube. Recent advancement in ultrasonography (USG) techniques should now allow for accurate and descriptive evaluation of pediatric airway. Aims and objectives: This study was planned to determine the accuracy of Ultrasonography (USG) to assess the appropriate ETT size and compare it with physical indices based formulae. Methods: After obtaining approval from Institute’s Ethical and Research committee, and parental written and informed consent, the study was conducted on 100 subjects of either sex between 12-60 months of age, undergoing various elective surgeries under general anesthesia requiring endotracheal intubation. The same experienced radiologist performed ultrasonography. The transverse diameter was measured at the level of cricoids cartilage by USG. After USG, general anesthesia was administered using standard techniques followed by the institute. An experienced anesthesiologist performed the endotracheal intubations with uncuffed endotracheal tube (Portex Tracheal Tube Smiths Medical India Pvt. Ltd.) with Murphy’s eye. He was unaware of the finding of the ultrasonography. The tracheal tube was considered best fit if air leak was satisfactory at 15-20 cm H₂O of airway pressure. The obtained values were compared with the values of endotracheal tube size calculated by ultrasonography, various age, height, weight-based formulas and diameter of right and left little finger. The correlation of the size of the endotracheal tube by different modalities was done and Pearson's correlation coefficient was obtained. The comparison of the mean size of the endotracheal tube by ultrasonography and by traditional formula was done by the Friedman’s test and Wilcoxon sign-rank test. Results: The predicted tube size was equal to best fit and best determined by ultrasonography (100%) followed by comparison to left little finger (98%) and right little finger (97%) and age-based formula (95%) followed by multivariate formula (83%) and body length (81%) formula. According to Pearson`s correlation, there was a moderate correlation of best fit endotracheal tube with endotracheal tube size by age-based formula (r=0.743), body length based formula (r=0.683), right little finger based formula (r=0.587), left little finger based formula (r=0.587) and multivariate formula (r=0.741). There was a strong correlation with ultrasonography (r=0.943). Ultrasonography was the most sensitive (100%) method of prediction followed by comparison to left (98%) and right (97%) little finger and age-based formula (95%), the multivariate formula had an even lesser sensitivity (83%) whereas body length based formula was least sensitive with a sensitivity of 78%. Conclusion: USG is a reliable method of estimation of subglottic diameter and for prediction of ETT size in children.

Keywords: endotracheal intubation, pediatric airway, subglottic diameter, traditional formulas, ultrasonography

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