Search results for: optimization of resources

Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Fateme Aysin Anka, Farzad Kiani

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Forced migration is a situation in which people are forced to leave their homes against their will due to political conflicts, wars and conflicts, natural disasters, climate change, economic crises, or other emergencies. This type of migration takes place under conditions where people cannot lead a sustainable life due to reasons such as security, shelter and meeting their basic needs. This type of migration may occur in connection with different factors that affect people's living conditions. In addition to these general and widespread reasons, water security and resources will be one that is starting now and will be encountered more and more in the future. Forced migration may occur due to insufficient or depleted water resources in the areas where people live. In this case, people's living conditions become unsustainable, and they may have to go elsewhere, as they cannot obtain their basic needs, such as drinking water, water used for agriculture and industry. To cope with these situations, it is important to minimize the causes, as international organizations and societies must provide assistance (for example, humanitarian aid, shelter, medical support and education) and protection to address (or mitigate) this problem. From the international perspective, plans such as the Green New Deal (GND) and the European Green Deal (EGD) draw attention to the need for people to live equally in a cleaner and greener world. Especially recently, with the advancement of technology, science and methods have become more efficient. In this regard, in this article, a multidisciplinary case model is presented by reinforcing the water problem with an engineering approach within the framework of the social dimension. It is worth emphasizing that this problem is largely linked to climate change and the lack of a sustainable water management perspective. As a matter of fact, the United Nations Development Agency (UNDA) draws attention to this problem in its universally accepted sustainable development goals. Therefore, an artificial intelligence-based approach has been applied to solve this problem by focusing on the water management problem. The most general but also important aspect in the management of water resources is its correct consumption. In this context, the artificial intelligence-based system undertakes tasks such as water demand forecasting and distribution management, emergency and crisis management, water pollution detection and prevention, and maintenance and repair control and forecasting.

Keywords: water resource management, forced migration, multidisciplinary studies, artificial intelligence

Procedia PDF Downloads 86

Authors: Abu Afree Andalib, M. Mezbah Uddin, M. Rafiur Rahman, M. Abir Hossain, Rajia Sultana Kamol

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This paper deals with the analysis of flow past the marine turbine blade which is designed by using the blade element theory and momentum theory for the purpose of using in the field of renewable energy. The designed blade is analyzed for various parameters using FSI module of Ansys. Computational Fluid Dynamics is used for the study of fluid flow past the blade and other fluidic phenomena such as lift, drag, pressure differentials, energy dissipation in water. Finite Element Analysis (FEA) module of Ansys was used to analyze the structural parameter such as stress and stress density, localization point, deflection, force propagation. Fine mesh is considered in every case for more accuracy in the result according to computational machine power. The relevance of design, search and optimization with respect to complex fluid flow and structural modeling is considered and analyzed. The relevancy of design and optimization with respect to complex fluid for minimum drag force using Ansys Adjoint Solver module is analyzed as well. The graphical comparison of the above-mentioned parameter using CFD and FEA and subsequently FSI technique is illustrated and found the significant conformity between both the results.

Keywords: blade element theory, computational fluid dynamics, finite element analysis, fluid-structure interaction, momentum theory

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Authors: Clifford Otieno Ochieng, Nsenda Lukumwena

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Cities worldwide and most notably those in the global south, including Nairobi City are experiencing accelerated population growth and urban sprawl, accompanied with multiple socioeconomic challenges’ which in turn increase the pressure on already limited infrastructure such as public lighting and on limited financial resources. Based on this premise, through reimaging the value of street lighting infrastructure, the study attempts to highlight the affordance and affordability of streetlights and suggests them as a tool to optimally address limited financial resources that characterize cities in the global south. As a methodology, the paper reviews and analyzes literature available online including Nairobi city budgets; reports from Kenya Power, World Health Organization and United Nations; and articles on enterprise level Internet of Things (IoT) solutions. In conclusion, this study illustrates that streetlights can go well beyond their traditional roles of illuminating cities at night. They can be as suggested in this paper charging stations, communication network terminals and disease prevention nodes.

Keywords: affordance, Nairobi, developing economies, IoT, smart street lights, smart cities

Procedia PDF Downloads 185

Authors: Kaoutar Ben Azzou, Hanaa Talei

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Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

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Authors: Ana Asratashvili

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One of the main issues of state’s economic policy is the environmental problems. The development of society is implementing by the connection with nature. A human being needs different material resources which must be got by the influence on the nature. This relationship between nature and society is complicated and controversial and it was changing from time to time according to human’s evolution. The imprudent and unreasonable usage of natural resources, scientific-technological revolution and the hard pollution of nature related to it caused the disruption of environmental balance between nature and society which has been made for ages and destructively acted on society and environment. Environmental protection is one of the major issues of the European Union all over the world. The aim of EU environmental policy is to improve ecological conditions. Besides, it aims encouraging of careful and rational usage of natural resources. At the same time, the union tries to raise problems related to environmental protection at the international level. After that when scientists concluded anthropogenic impact of human on the nature causes climate changes, the special attention was paid to the environmental protection by developed countries. Global warming will cause floods, storms, draughts and desertification and to solve these results presumably will cost 20% of World GDP by 2050 for developed countries, if, of course, it does not make strict environmental policy. EU member countries have pretty strict environmental standards. Their defense is observed by different state institutions. According to impacts on nature throughout the world the most polluted fumes are made by electricity facilities (44%), transport (20%), industry (18%), domestic and service sector (17%). The special concern to the issues related to the importance of environment by environmentalists is caused by low self-esteem of population about the problems of environment. According to their mind, population is engaged with daily difficulties so that they don’t react much on environmental problems. Correspondingly, the main task for environmental organizations is to inform population and raise self-esteem about environmental issues.

Keywords: economic policy, environment, technological revolution, pollution, environmental, standards, self-esteem

Procedia PDF Downloads 297

Authors: Hari Singh, Abhishek Kamboj, Sudhir Kumar

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This investigation proposes a grey-based Taguchi method to solve the multi-response problems. The grey-based Taguchi method is based on the Taguchi’s design of experimental method, and adopts Grey Relational Analysis (GRA) to transfer multi-response problems into single-response problems. In this investigation, an attempt has been made to optimize the drilling process parameters considering weighted output response characteristics using grey relational analysis. The output response characteristics considered are surface roughness, burr height and hole diameter error under the experimental conditions of cutting speed, feed rate, step angle, and cutting environment. The drilling experiments were conducted using L27 orthogonal array. A combination of orthogonal array, design of experiments and grey relational analysis was used to ascertain best possible drilling process parameters that give minimum surface roughness, burr height and hole diameter error. The results reveal that combination of Taguchi design of experiment and grey relational analysis improves surface quality of drilled hole.

Keywords: metal matrix composite, drilling, optimization, step drill, surface roughness, burr height, hole diameter error

Procedia PDF Downloads 319

Authors: Isra Elfatih Salih Edrees, Mehmet Serdar Ufuk Türeli

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In this paper, an energy-aware method is presented, integrating energy-efficient relay-augmented techniques for correlated data routing with the goal of optimizing bottleneck throughput in wireless sensor networks. The system tackles the dual challenge of throughput optimization while considering sensor network energy consumption. A unique routing metric has been developed to enable throughput maximization while minimizing energy consumption by utilizing data correlation patterns. The paper introduces a game theoretic framework to address the NP-complete optimization problem inherent in throughput-maximizing correlation-aware routing with energy limitations. By creating an algorithm that blends energy-aware route selection strategies with the best reaction dynamics, this framework provides a local solution. The suggested technique considerably raises the bottleneck throughput for each source in the network while reducing energy consumption by choosing the best routes that strike a compromise between throughput enhancement and energy efficiency. Extensive numerical analyses verify the efficiency of the method. The outcomes demonstrate the significant decrease in energy consumption attained by the energy-efficient relay-augmented bottleneck throughput maximization technique, in addition to confirming the anticipated throughput benefits.

Keywords: correlated data aggregation, energy efficiency, game theory, relay-augmented routing, throughput maximization, wireless sensor networks

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Authors: Oluwatosin Olofintoye, Josiah Adeyemo, Gbemileke Shomade

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The relationship between rainfall and runoff is an important issue in surface water hydrology therefore the understanding and development of accurate rainfall-runoff models and their applications in water resources planning, management and operation are of paramount importance in hydrological studies. This paper reviews some of the previous works on the rainfall-runoff process modeling. The hydrologic applications of conceptual models and artificial neural networks (ANNs) for the precipitation-runoff process modeling were studied. Gradient training methods such as error back-propagation (BP) and evolutionary algorithms (EAs) are discussed in relation to the training of artificial neural networks and it is shown that application of EAs to artificial neural networks training could be an alternative to other training methods. Therefore, further research interest to exploit the abundant expert knowledge in the area of artificial intelligence for the solution of hydrologic and water resources planning and management problems is needed.

Keywords: artificial intelligence, artificial neural networks, evolutionary algorithms, gradient training method, rainfall-runoff model

Procedia PDF Downloads 454

Authors: Muhammd Usman Sardar, Mazhar Hussain Baloch, Muhammad Shahbaz Ahmad, Zahir Javed Paracha

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Likewise other developing countries in the world, Pakistan is furthermore suffering from electrical energy deficiency as adverse well-being nominated. Its generation of electricity has become reliant onto a great range of conventional sources since the last ten of years. The foreseeable exhaustion of petroleum and conventional resources will be alarming in continued growth and development for future in Pakistan so renewable energy interchange have to be employed by interesting the majority of power grid network. Energy adding-up through solar photovoltaic based systems and projects can offset the shortfall to such an extent with this sustainable natural resources and most promising technologies. An assessment of solar energy potential for electricity generation is being presented for fulfilling the energy demands with higher level of reliability. This research study estimates the present and future approaching renewable energy resource for power generation to off-grid independent setup or energizing the existed conventional power grids of Pakistan to becoming self-sustained for its entire outfit.

Keywords: powergrid network, solar photovoltaic setups, solar power generation, solar energy technology

Procedia PDF Downloads 434

Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Effort M. Magoso

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This study analyses urban institutional arrangements and their implications on allocation of wetlands for development purposes in Zimbabwe using a case study of Harare. It was driven by the need to get to the root of the current urban assault on wetlands. The study sought to analyse institutions that influence wetlands governance in Harare, to ascertain level of wetlands loss and to determine the adequacy of the legal and regulatory framework for governing wetlands. Theories of common property resources and of institutions are the paradigms that undergird this study. A qualitative research methodology was employed, while in-depth interviews, observations and document review were used to gather data. The study found out that unchecked infrastructure developments are taking place in the city’s wetlands. Urban institutional arrangements in Harare were exposed as having negative implications on the protection of wetlands. It is the key argument of this study that good institutional arrangements are priceless in the protection of commons such as wetlands. This study also recommends a new framework that has environmentalists and technocrats as the final decision maker in land allocation as the solution to protect wetlands from undue anthropogenic activities.

Keywords: institutional arrangements, common property resources, wetlands, institutions

Procedia PDF Downloads 388

Authors: Maris Eugênia Dela Rosa, Ana Luiza Menegatti Pavan, Marcela De Oliveira, Diana Rodrigues De Pina, Luis Carlos Vulcano

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In medical veterinary as well as in human medicine, radiological study is essential for a safe diagnosis in clinical practice. Thus, the quality of radiographic image is crucial. In last year’s there has been an increasing substitution of image acquisition screen-film systems for computed radiology equipment (CR) without technical charts adequacy. Furthermore, to carry out a radiographic examination in veterinary patient is required human assistance for restraint this, which can compromise image quality by generating dose increasing to the animal, for Occupationally Exposed and also the increased cost to the institution. The image optimization procedure and construction of radiographic techniques are performed with the use of homogeneous phantoms. In this study, we sought to develop a homogeneous phantom of canine chest to be applied to the optimization of these images for the CR system. In carrying out the simulator was created a database with retrospectives chest images of computed tomography (CT) of the Veterinary Hospital of the Faculty of Veterinary Medicine and Animal Science - UNESP (FMVZ / Botucatu). Images were divided into four groups according to the animal weight employing classification by sizes proposed by Hoskins & Goldston. The thickness of biological tissues were quantified in a 80 animals, separated in groups of 20 animals according to their weights: (S) Small - equal to or less than 9.0 kg, (M) Medium - between 9.0 and 23.0 kg, (L) Large – between 23.1 and 40.0kg and (G) Giant – over 40.1 kg. Mean weight for group (S) was 6.5±2.0 kg, (M) 15.0±5.0 kg, (L) 32.0±5.5 kg and (G) 50.0 ±12.0 kg. An algorithm was developed in Matlab in order to classify and quantify biological tissues present in CT images and convert them in simulator materials. To classify tissues presents, the membership functions were created from the retrospective CT scans according to the type of tissue (adipose, muscle, bone trabecular or cortical and lung tissue). After conversion of the biologic tissue thickness in equivalent material thicknesses (acrylic simulating soft tissues, bone tissues simulated by aluminum and air to the lung) were obtained four different homogeneous phantoms, with (S) 5 cm of acrylic, 0,14 cm of aluminum and 1,8 cm of air; (M) 8,7 cm of acrylic, 0,2 cm of aluminum and 2,4 cm of air; (L) 10,6 cm of acrylic, 0,27 cm of aluminum and 3,1 cm of air and (G) 14,8 cm of acrylic, 0,33 cm of aluminum and 3,8 cm of air. The developed canine homogeneous phantom is a practical tool, which will be employed in future, works to optimize veterinary X-ray procedures.

Keywords: radiation protection, phantom, veterinary radiology, computed radiography

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Authors: RAJ KUMAR G.C.

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There are tremendous opportunities to maximize smallholder farmers’ income from small-scale water resource development through micro irrigation and multiple-use water systems (MUS). MUS are an improved water management approach, developed and tested successfully by iDE that pipes water to a community both for domestic use and for agriculture using efficient micro irrigation. Different MUS models address different landscape constraints, water demand, and users’ preferences. MUS are complemented by micro irrigation kits, which were developed by iDE to enable farmers to grow high-value crops year-round and to use limited water resources efficiently. Over the last 15 years, iDE’s promotion of the MUS approach has encouraged government and other key stakeholders to invest in MUS for better planning of scarce water resources. Currently, about 60% of the cost of MUS construction is covered by the government and community. Based on iDE’s experience, a gravity-fed MUS costs approximately $125 USD per household to construct, and it can increase household income by $300 USD per year. A key element of the MUS approach is keeping farmers well linked to input supply systems and local produce collection centers, which helps to ensure that the farmers can produce a sufficient quantity of high-quality produce that earns a fair price. This process in turn creates an enabling environment for smallholders to invest in MUS and micro irrigation. Therefore, MUS should be seen as an integrated package of interventions –the end users, water sources, technologies, and the marketplace– that together enhance technical, financial, and institutional sustainability. Communities are trained to participate in sustainable water resource management as a part of the MUS planning and construction process. The MUS approach is cost-effective, improves community governance of scarce water resources, helps smallholder farmers to improve rural health and livelihoods, and promotes gender equity. MUS systems are simple to maintain and communities are trained to ensure that they can undertake minor maintenance procedures themselves. All in all, the iDE Nepal MUS offers multiple benefits and represents a practical and sustainable model of the MUS approach. Moreover, there is a growing national consensus that rural water supply systems should be designed for multiple uses, acknowledging that substantial work remains in developing national-level and local capacity and policies for scale-up.

Keywords: multiple-use water systems , small scale water resources, rural livelihoods, practical and sustainable model

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Authors: Huanhuan Qiang, Sijia Jin

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Population aging has become a global trend, and China has entered an aging society, implementing an active aging system focused on home and community-based care. However, most urban communities where elderly people live face issues such as monotonous planning, unappealing landscapes, and inadequate aging infrastructure, which do not meet the requirements for active aging. Intergenerational friendliness and mutual assistance are key components in China's active aging policy framework. Therefore, residential development should prioritize enhancing intergenerational friendliness. Residential and public spaces are central to community life and well-being, offering new and challenging venues to improve relationships among residents of different ages. They are crucial for developing intergenerational communities with diverse generations and non-blood relationships. This paper takes the Maigaoqiao community in Nanjing, China, as a case study, examining intergenerational interactions in public spaces. Based on Maslow's hierarchy of needs and using time geography analysis, it identifies the spatiotemporal behavior characteristics of intergenerational groups in outdoor activities. Then construct an intergenerational-friendly evaluation system and an IPA quadrant model for public spaces in residential areas. Lastly, it explores optimization strategies for public spaces to promote intergenerational friendly interactions, focusing on five aspects: accessibility, safety, functionality, a sense of belonging, and interactivity.

Keywords: intergenerational friendliness, demand theory, spatiotemporal behavior, IPA analysis, existing residential public space

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Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

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Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

Procedia PDF Downloads 365

Authors: Debasis Sengupta, Sudipta Das

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The class of life distributions with decreasing mean residual life (DMRL) is well known in the field of reliability modeling. It contains the IFR class of distributions and is contained in the NBUE class of distributions. While upper and lower bounds of the reliability distribution function of aging classes such as IFR, IFRA, NBU, NBUE, and HNBUE have discussed in the literature for a long time, there is no analogous result available for the DMRL class. We obtain the upper and lower bounds for the reliability function of the DMRL class in terms of first order finite moment. The lower bound is obtained by showing that for any fixed time, the minimization of the reliability function over the class of all DMRL distributions with a fixed mean is equivalent to its minimization over a smaller class of distribution with a special form. Optimization over this restricted set can be made algebraically. Likewise, the maximization of the reliability function over the class of all DMRL distributions with a fixed mean turns out to be a parametric optimization problem over the class of DMRL distributions of a special form. The constructive proofs also establish that both the upper and lower bounds are sharp. Further, the DMRL upper bound coincides with the HNBUE upper bound and the lower bound coincides with the IFR lower bound. We also prove that a pair of sharp upper and lower bounds for the reliability function when the distribution is increasing mean residual life (IMRL) with a fixed mean. This result is proved in a similar way. These inequalities fill a long-standing void in the literature of the life distribution modeling.

Keywords: DMRL, IMRL, reliability bounds, hazard functions

Procedia PDF Downloads 397

Authors: Ana Alvarenga De Castro

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Food sovereignty has been brought by the international peasants’ movement, La Via Campesina, as a precondition to food security, speaking about the right of each nation to keep its own supply of foods respecting cultural, sustainable practices and productive diversity. The political conceptualization nowadays goes beyond saying that this term is about achieving the rights of farmers to control the food systems according to local specificities, and about equality in the access to natural resources and quality food. The current feminization of agroecosystems and of food insecurity identified by researchers and recognized by international agencies like the UN and FAO has enhanced the feminist discourse into the food sovereignty movement, considering the historical inequalities that place women farmers in subaltern positions inside the families and rural communities. The current tendency in many rural areas of more women taking responsibility for food production and still facing the lack of access to natural resources meets particular aspects in Latin America due to the global economic logic which places the Global South in the position of raw material supplier for the industrialized North, combined with regional characteristics. In this context, Latin American countries play the role of commodities exporters in the international labor division, including among exported items grains, soybean paste, and ores, to the expense of local food chains which provide domestic quality food supply under more sustainable practices. The connections between gender inequalities and global territorial inequalities related to the access and control of food and natural resources are pointed out by feminist political ecology - FPE - authors, and are linked in this article to the potentialities and limitations of women farmers to reproduce diversified agroecosystems in the tropical environments. The work brings the importance of local practices held by women farmers which are crucial to maintaining sustainable agricultural systems and their results on seeds, soil, biodiversity and water conservation. This work presents an analysis of documents, releases, videos and other publicized experiences launched by some peasants’ organizations in Latin America which evidence the different technical and political answers that meet food sovereignty from peasants’ groups that are attributed to women farmers. They are associated with articles presenting the empirical analysis of women farmers' practices in Latin America. The combination drove to discuss the benefits of peasants' conceptions about food systems and their connections with local realities and the gender issues linked to the food sovereignty conceptualization. Conclusion meets that reality on the field cannot reach food sovereignty's ideal homogeneously and that agricultural sustainable practices are dependent on rights' achievement and social inequalities' eradication.

Keywords: food sovereignty, gender, diversified agricultural systems, access to natural resources

Procedia PDF Downloads 248

Authors: Yuhang Zou, Zhu Wang

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Most of the western part of China is mountainous and hilly region, with abundant resources of mountainous space. However, the resources are complex, and the ecological factors are diverse. As urbanization expands rapidly today, the landscape of the mountain residence needs to be changed. This paper, starting with the ecological environment and visual landscape of the mountain living space, analyzes the basic conditions of the Eling Peak, ‘Mirror of the Sky’, in Chongqing, China before its landscape renovation. Then, it analyzes some parts of the project, including the overall planning, ecological coordination, space expansion and local conditions in mountain environment. After that, this paper concludes the intention of designer and 4 methods, appropriate demolition, space reconstruction, landscape modeling and reasonable road system, to transform the master’s mountain residential works. Finally, through the analysis and understanding of the project, it sums up that the most beautiful landscape is not only the outdoor space, but also borrowing scene from the city and the sky, making them a part of the mountainous residential buildings. Only in this way can people, landscape, building, sky, and city become integrated and coexist harmoniously.

Keywords: landscape design, mountainous architecture, renovation, residence

Procedia PDF Downloads 157

Authors: Adel A. Ghoneim

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Desalination using solar energy is an interesting option specifically at regions with abundant solar radiation since such areas normally have scarcity of clean water resources. Desalination is the procedure of eliminating dissolved minerals from seawater or brackish water to generate fresh water. In this work, a simulation program is developed to determine the performance of reverse osmosis (RO) water desalination plant powered by high concentrated photovoltaic (HCPV) panels in Kuwait climate conditions. The objective of such a photovoltaic thermal system is to accomplish a double output, i.e., co-generation of both electricity and fresh water that is applicable for rural regions with high solar irradiation. The suggested plan enables to design an RO plant that does not depend on costly batteries or additional land and significantly reduce the government costs to subsidize the water generation cost. Typical weather conditions for Kuwait is employed as input to the simulation program. The simulation program is utilized to optimize the system efficiency as well as the distillate water production. The areas and slopes of HCPV modules are varied to attain maximum yearly power production. Maximum yearly distillate production and HCPV energy generation are found to correspond to HCPV facing south with tilt of 27° (Kuwait latitude-3°). The power needed to produce 1 l of clean drinking water ranged from 2 to 8 kW h/m³, based on the salinity of the feed water and the system operating conditions. Moreover, adapting HCPV systems achieve an avoided greenhouse gases emission by about 1128 ton CO₂ annually. Present outcomes certainly illustrate environmental advantages of water desalination system powered by high concentrated photovoltaic systems in Kuwait climate conditions.

Keywords: desalination, high concentrated photovoltaic systems, reverse osmosis, solar radiation

Procedia PDF Downloads 142

Authors: Ekin Nurbaş

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One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

Procedia PDF Downloads 147

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

Procedia PDF Downloads 156

Authors: Reyhan Özdoğan, Özgür Ceylan, Mehmet Arif Kaya, Mithat Çelebi

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Food packaging is important for the food industry. Bioplastics have been used as food packaging materials. According to the European Bioplastics organization, bioplastics can be defined as plastics based on renewable resources (bio-based) or as plastics which are biodegradable and/or compostable. Poly(lactic acid) (PLA) has an industrially importance of bioplastic polymers. PLA is a family of biodegradable thermoplastic polyester made from renewable resources. It is produced by conversion of corn, or other carbohydrate sources, into dextrose, followed by fermentation into lactic acid through direct polycondensation of lactic acid monomers or through ring-opening polymerization of lactide. The processing possibilities of this transparent material are very wide, ranging from injection molding and extrusion over cast film extrusion to blow molding and thermoforming. In this study, PLA films were prepared by solution casting method. PLAs which are different molecular weights were plasticized with glycerol and the morphology of films was monitored by optical microscopy. Properties of mechanical and film of PLA were researched with the mechanical testing machine.

Keywords: biodegradable, bioplastics, morphology, solution casting, poly(lactic acid)

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Authors: Pradipta Risang Ratna Sambawa, Driya Herseta, Mahendra Fajri Nugraha

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In 2020, PT Petrokimia Gresik implemented a program to increase the ROP (Run Of Pile) production rate at the Phosphate Fertilizer 1 plant, causing an increase in scrubbing water consumption in the 100/200 area unit. This increase in water consumption causes a higher discharge of wastewater, which can further cause local flooding, especially during the rainy season. The 100/200 area of the Phosphate Fertilizer 1 plant is close to the warehouse and is often a passing area for trucks transporting raw materials. This causes the pH in the wastewater to become acidic (the worst point is up to pH 1). The problem of flooding and exposure to acidic wastewater in the 100/200 area of Phosphate Fertilizer Plant 1 was then resolved by PT Petrokimia Gresik through wastewater optimization steps called the 3R program (Reduce, Reuse, and Recycle). The 3R (Reduce, reuse, and recycle) program consists of an air consumption reduction program by considering the liquid/gas ratio in scrubbing unit of 100/200 Phosphate Fertilizer 1 plant, creating a wastewater interconnection line so that wastewater from unit 100/200 can be used as scrubbing water in the Phonska 1, Phonska 2, Phonska 3 and unit 300 Phosphate Fertilizer 1 plant and increasing scrubbing effectiveness through scrubbing effectiveness simulations. Through a series of wastewater optimization programs, PT Petrokimia Gresik has succeeded in reducing NaOH consumption for neutralization up to 2,880 kg/day or equivalent in saving up to 314,359.76 dollars/year and reducing process water consumption up to 600 m3/day or equivalent in saving up to 63,739.62 dollars/year.

Keywords: fertilizer, phosphate fertilizer, wastewater, wastewater treatment, water management

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Authors: Hosein Ghahremani, MohammadReza Khoshchehre, Pejman Hakemi

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This study involves numerical simulations of a vertical plate-type photo-bioreactor to investigate the performance of Microalgae Spirulina and Control and optimization of parameters for the digital controller by Taguchi method that MATLAB software and Qualitek-4 has been made. Since the addition of parameters such as temperature, dissolved carbon dioxide, biomass, and ... Some new physical parameters such as light intensity and physiological conditions like photosynthetic efficiency and light inhibitors are involved in biological processes, control is facing many challenges. Not only facilitate the commercial production photo-bioreactor Microalgae as feed for aquaculture and food supplements are efficient systems but also as a possible platform for the production of active molecules such as antibiotics or innovative anti-tumor agents, carbon dioxide removal and removal of heavy metals from wastewater is used. Digital controller is designed for controlling the light bioreactor until Microalgae growth rate and carbon dioxide concentration inside the bioreactor is investigated. The optimal values of the controller parameters of the S/N and ANOVA analysis software Qualitek-4 obtained With Reaction curve, Cohen-Con and Ziegler-Nichols method were compared. The sum of the squared error obtained for each of the control methods mentioned, the Taguchi method as the best method for controlling the light intensity was selected photo-bioreactor. This method compared to control methods listed the higher stability and a shorter interval to be answered.

Keywords: photo-bioreactor, control and optimization, Light intensity, Taguchi method

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Authors: Zeev Wiesman, Paula Berman, Nitzan Meiri, Charles Linder

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Supramolecular chemistry refers to the domain of chemistry beyond that of molecules and focuses on the chemical systems made up of a discrete number of assembled molecular sub units or components. Biodiesel components self arrangements is closely related/affect their physical properties in combustion systems and emission. Due to technological difficulties, knowledge regarding the molecular packing of FAMEs (biodiesel) in the liquid phase is limited. Spectral tools such as X-ray and NMR are known to provide evidences related to molecular structure organization. Recently, it was reported by our research group that using 1H Time Domain NMR methodology based on relaxation time and self diffusion coefficients, FAMEs clusters with different motilities can be accurately studied in the liquid phase. Head to head dimarization with quasi-smectic clusters organization, based on molecular motion analysis, was clearly demonstrated. These findings about the assembly/packing of the FAME components are directly associated with fluidity/viscosity of the biodiesel. Furthermore, these findings may provide information of micro/nano-particles that are formed in the delivery and injection system of various combustion systems (affected by thermodynamic conditions). Various relevant parameters to combustion such as: distillation/Liquid Gas phase transition, cetane number/ignition delay, shoot, oxidation/NOX emission maybe predicted. These data may open the window for further optimization of FAME/diesel mixture in terms of combustion and emission.

Keywords: supermolecular chemistry, FAMEs, liquid phase, fluidity, LF-NMR

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Authors: Emil Aliyev

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The main focus of this conference paper is on the aspects of the environmental sustainability of onshore hydrocarbon pipelines. The latter is notorious for being a source of major environmental contamination and a consumer of vast amounts of natural resources such as water, land, steel, etc. Therefore, the environmentally sustainable operation of pipelines is a concern that requires attention and research. The geographical scope of the paper is confined to onshore hydrocarbon pipelines operated in the Middle East region. The research contains elements of originality as it draws on the author’s field experience and practical implementation of environmental and sustainability solutions in a major Middle East-based pipeline organization. The authors describe some of the most common significant environmental aspects of pipeline operations and provide examples of various approaches and technologies that can be successfully utilized to make pipelines more environmentally sustainable. The author concludes that the operation of onshore hydrocarbon pipelines can be made environmentally sustainable. This can be achieved by adopting a systematic framework, focusing limited resources on significant aspects, integrating a circular economy into day-to-day activities, and having strong management support.

Keywords: pipelines, onshore hydrocarbon pipelines, environmental sustainability, significant environmental aspects

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Authors: Bandar A. Alkhayyal

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Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

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Authors: Iulia E. Falcan

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The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.

Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization

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Authors: U. Isyaku, C. Upton, J. Dickinson

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Critical institutional approach for understanding pathways to shared prosperity among forest communities enabled questioning the underlying rational choice assumptions that have dominated traditional institutional thinking in natural resources management. Common pool resources framing assumes that communities as social groups share collective interests and values towards achieving greater development. Hence, policies related to natural resources management in the global South prioritise economic prosperity by focusing on how to maximise material benefits and improve the livelihood options of resource dependent communities. Recent trends in commodification and marketization of ecosystem goods and services into tradable natural capital and incentivising conservation are structured in this paradigm. Several researchers however, have problematized this emerging market-based model because it undermines cultural basis for protecting natural ecosystems. By exploring how forest people’s motivations for conservation differ within the context of reducing emissions from deforestation and forest degradation (REDD+) project in Nigeria, we aim to provide an alternative approach to conceptualising prosperity beyond the traditional economic thinking. Through in depth empirical work over seven months with five communities in Nigeria’s Cross River State, Q methodology was used to uncover communities’ perspectives and meanings of forest values that underpin contemporary and historic conservation practices, expected benefits, and willingness to participate in the REDD+ process. Our study finds six discourses about forest and conservation values that transcend wealth creation, poverty reduction and livelihoods. We argue that communities’ decisions about forest conservation consist of a complex mixture of economic, emotional, moral, and ecological justice concerns that constitute new meanings and dimensions of prosperity. Prosperity is thus reconfigured as having socio-cultural and psychological pathways that could be derived through place identity and attachment, connectedness to nature, family ties, and ability to participate in everyday social life. We therefore suggest that natural resources policy making and development interventions should consider institutional arrangements that also include the psycho-cultural dimensions of prosperity among diverse community groups.

Keywords: critical institutionalism, Q methodology, REDD+, shared prosperity

Procedia PDF Downloads 345