Search results for: automated equipment

Authors: Hsin-Yi Lo, Chia-Yu Hsu

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This article is the nursing experience of a multiple trauma case using Swanson's theory of caring, the nursing period is from May 31 to June 4, 2021, collect data through observation, written talks, interviews, listening, direct care and physical assessment, established cases with health problems such as acute pain, impaired tissue integrity, and anxiety. Nursing process including, evaluate the pain index with the pain assessment scale, assist in acupoint massage, use a corset to fix the wound, and give the patient listening to favorite radio programs to divert attention and relieve pain problems; promote wound healing and avoid infection by assessing wound condition and exudation, changing dressings with aseptic technique, and providing appropriate dressings; encourage patients to express their feelings, provide companionship, and assist in self-care and participation in treatment plans, to enable the case to overcome the anxiety caused by being admitted to the intensive care unit for the first time and not knowing about the disease, and assist the case to overcome the injury caused by the accident and return to normal life. There is no video equipment in the intensive care unit during the nursing period. In response to the problem that family visits cannot be opened during the epidemic, it is a limitation this time. It is recommended that the hospital take this into consideration in the future. In the post-epidemic era, it can reduce the risk of various infections for patients and family members. Traveling between home and hospital, improving the quality of high-quality and technological care.

Keywords: swanson's theory of caring, multiple trauma, anxiety, nursing experience

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Authors: Angelis P. Barlampas

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The purpose of this study is to inform the reader, about the various applications of artificial intelligence (AI), in cardiac imaging. AI grows fast and its role is crucial in medical specialties, which use large amounts of digital data, that are very difficult or even impossible to be managed by human beings and especially doctors.Artificial intelligence (AI) refers to the ability of computers to mimic human cognitive function, performing tasks such as learning, problem-solving, and autonomous decision making based on digital data. Whereas AI describes the concept of using computers to mimic human cognitive tasks, machine learning (ML) describes the category of algorithms that enable most current applications described as AI. Some of the current applications of AI in cardiac imaging are the follows: Ultrasound: Automated segmentation of cardiac chambers across five common views and consequently quantify chamber volumes/mass, ascertain ejection fraction and determine longitudinal strain through speckle tracking. Determine the severity of mitral regurgitation (accuracy > 99% for every degree of severity). Identify myocardial infarction. Distinguish between Athlete’s heart and hypertrophic cardiomyopathy, as well as restrictive cardiomyopathy and constrictive pericarditis. Predict all-cause mortality. CT Reduce radiation doses. Calculate the calcium score. Diagnose coronary artery disease (CAD). Predict all-cause 5-year mortality. Predict major cardiovascular events in patients with suspected CAD. MRI Segment of cardiac structures and infarct tissue. Calculate cardiac mass and function parameters. Distinguish between patients with myocardial infarction and control subjects. It could potentially reduce costs since it would preclude the need for gadolinium-enhanced CMR. Predict 4-year survival in patients with pulmonary hypertension. Nuclear Imaging Classify normal and abnormal myocardium in CAD. Detect locations with abnormal myocardium. Predict cardiac death. ML was comparable to or better than two experienced readers in predicting the need for revascularization. AI emerge as a helpful tool in cardiac imaging and for the doctors who can not manage the overall increasing demand, in examinations such as ultrasound, computed tomography, MRI, or nuclear imaging studies.

Keywords: artificial intelligence, cardiac imaging, ultrasound, MRI, CT, nuclear medicine

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Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: Adalberto Gregorio Back

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Historically, the Pinheiros River, which crosses the urban area of the largest South American metropolis, the city of São Paulo, has been the subject of several interventions involving different interests and multiple demands, including the implementation of road axes and industrial occupation in the city, following its floodplains. the dilution of sewers; generation of electricity, with the reversal of its waters to the Billings Dam; and urban drainage. These processes, together with the exclusionary and peripheral urban sprawl with high population density in the peripheries, result in difficulties for the collection and treatment of household sewage, which flow into the tributaries and the Pinheiros River itself. In the last 20 years, two separate projects have been undertaken to clean up its waters. The first one between 2001-2011 was the flotation system, aimed at cleaning the river in its own gutter with equipment installed near the Bilings Dam; and, more recently, from 2019 to 2022, the proposal to connect about 74 thousand dwellings to the sewage collection and treatment system, as well as to install treatment plants in the tributaries of Pinheiros where the connection to the system is impracticable, given the irregular occupations. The purpose of this paper is to make a comparative analysis on the dynamics of conflicts, interests and opportunities of coalitions between the actors involved in the two referred projects of pollution of the Pinheiros River. For this, we use the analysis of documents produced by the state government; as well as documents related to the legal disputes that occurred in the first attempt of decontamination involving the sanitation company; the Billings Dam management company interested in power generation; the city hall and regular and irregular dwellings not linked to the sanitation system.

Keywords: depollution of the Pinheiros River, interests groups, São Paulo, water energy nexus

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Authors: Xianglei Yin, Shen Wang, Baoyi Wang, Laihong Shen

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Chemical looping partial oxidation of methane (CLPOM) is a novel technology to produce high-quality syngas with an auto-thermic process and low equipment investment. The development of oxygen carriers is important for the improvement of the CLPOM performance. In this work, the effect of the nickel-substitution proportion on the performance of LaMn₁₋ᵧNiᵧO₃₊δ perovskites for CLPOM was studied in the aspect of reactivity, syngas selectivity, resistance towards carbon deposition and thermal stability in cyclic redox process. The LaMn₁₋ₓNiₓO₃ perovskite oxides with x = 0, 0.1, 0.2 were prepared by the sol-gel method. The performance of LaMn₁₋ᵧNiᵧO₃₊δ perovskites for CLPOM was investigated through the characterization of XRD, H₂-TPR, XPS, and fixed-bed experiments. The characterization and test results suggest that the doping of nickel enhances the generation rate of syngas, leading to high syngas yield, methane conversion, and syngas selectivity. This is attributed to the that the introduction of nickel provides active sites to promote the methane activation on the surface and causes the addition of oxygen vacancies to accelerate the migration of oxygen anion in the bulk of oxygen carrier particles. On the other hand, the introduction of nickel causes carbon deposition to occur earlier. The best substitution proportion of nickel is y=0.1 and LaMn₀.₉Ni₀.₁O₃₊δ could produce high-quality syngas with a yield of 3.54 mmol·g⁻¹, methane conversion of 80.7%, and CO selectivity of 84.8% at 850℃. In addition, the LaMn₀.₉Ni₀.₁O₃₊δ oxygen carrier exhibits superior and stable performance in the cyclic redox process.

Keywords: chemical looping partial oxidation of methane, LaMnO₃₊δ, Ni doping, syngas, carbon deposition

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Authors: Mahdiyeh Zafaranchi, Ethan S. Cantor, William T. Riddell, Jess W. Everett

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The New Jersey Department of Military and Veteran’s Affairs (NJ DMAVA) operates over 50 facilities throughout the state of New Jersey, U.S. NJDMAVA is under a mandate to move toward decarbonization, which will eventually include eliminating the use of natural gas and other fossil fuels for heating. At the same time, the organization requires increased resiliency regarding electric grid disruption. These competing goals necessitate adopting the use of on-site renewables such as photovoltaic and geothermal power, as well as implementing power control strategies through microgrids. Planning for these changes requires a detailed understanding of current and future electricity use on yearly, monthly, and shorter time scales, as well as a breakdown of consumption by heating, ventilation, and air conditioning (HVAC) equipment. This paper discusses case studies of two buildings that were simulated using the QUick Energy Simulation Tool (eQUEST). Both buildings use electricity from the grid and photovoltaics. One building also uses natural gas. While electricity use data are available in hourly intervals and natural gas data are available in monthly intervals, the simulations were developed using monthly and yearly totals. This approach was chosen to reflect the information available for most NJ DMAVA facilities. Once completed, simulation results are compared to metrics recommended by several organizations to validate energy use simulations. In addition to yearly and monthly totals, the simulated peak demands are compared to actual monthly peak demand values. The simulations resulted in monthly peak demand values that were within 30% of the measured values. These benchmarks will help to assess future energy planning efforts for NJ DMAVA.

Keywords: building energy modeling, eQUEST, peak demand, smart meters

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Authors: Esha Saha, Pradip Kumar Ray

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A hospital inventory comprises of a large number and great variety of items for the proper treatment and care of patients, such as pharmaceuticals, medical equipment, surgical items, etc. Improper management of these items, i.e. stockouts, may lead to delay in treatment or other fatal consequences, even death of the patient. So, generally the hospitals tend to overstock items to avoid the risk of stockout which leads to unnecessary investment of money, difficulty in storing, more expiration and wastage, etc. Thus, in such challenging environment, it is necessary for hospitals to follow an inventory policy considering the stochasticity of demand in a hospital. Statistical analysis captures the correlation of patient condition based on bed occupancy with the patient demand which changes stochastically. Due to the dependency on bed occupancy, the markov model is developed that helps to map the changes in demand of hospital inventory based on the changes in the patient condition represented by the movements of bed occupancy states (acute care state, rehabilitative state and long-care state) during the length-of-stay of patient in a hospital. An inventory policy is developed for a hospital based on the fulfillment of patient demand with the objective of minimizing the frequency and quantity of placement of orders of inventoried items. The analytical structure of the model based on probability calculation is provided to show the optimal inventory-related decisions. A case-study is illustrated in this paper for the development of hospital inventory model based on patient demand for multiple inpatient pharmaceutical items. A sensitivity analysis is conducted to investigate the impact of inventory-related parameters on the developed optimal inventory policy. Therefore, the developed model and solution approach may help the hospital managers and pharmacists in managing the hospital inventory in case of stochastic demand of inpatient pharmaceutical items.

Keywords: bed occupancy, hospital inventory, markov model, patient condition, pharmaceutical items

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Authors: Parisa Göker, Hilal Kahveci, Özlem Candan Hergül

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Humans are generating culture while being in touch with nature. Along with skills, local knowledge based on experience, and many other subjects developed within this process, 'culture' offers humans a chance to survive. For this reason, culture forms the equipment for humans, which facilitates their survival in all ecosystems. Together with technology, quick consumption of natural sources and overuse culture of humans have brought up the eco-village concept. Ecovillages are ecologically, economically, socio-culturally, and spiritually sustainable settlement models. It is known that the eco-village approach is applying a proper methodology on behalf of integrative and versatile solution generation. Today, the eco-village approach, introducing a radical criticism to the understanding of civilization and consumption culture and deeming urban solutions inadequate as a spatial reflection to civilization and consumption culture, while making a difference about integrative solution offering with multidimensional features, along with the goal of creating self-sufficient communities, is creating solutions on the subject of both reducing the ecological footprint of humans and to provide social order and also to solve the injustice seen in terms of income and life standards. In this study, environmental issues, sustainable development, and environmental sustainability topics are examined within the context of eco-tourism and eco-village. Alongside this, the natural and cultural landscape values of Kurşunlu village which are located in Bilecik province’s Gölpazarı county, and a contextual frame is created for the facilitation of sustainability in the event of dynamizing the Kurşunlu village in terms of tourism-oriented activities.

Keywords: eco village, sustainability, rural landscape, cultural landscape

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Authors: Fangyuan Shao, Wei Liu, Deli Gao

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With the increasing speed of oil and gas exploration, development and production at home and abroad, the demand for drilling speed up technology is becoming more and more critical to reduce the development cost. Highly efficient and personalized PDC bit is important equipment in the bottom hole assembly (BHA). Therefore, improving the rock-breaking efficiency of PDC bits will help reduce drilling time and drilling cost. Advances in PDC bit technology have resulted in a leapfrogging improvement in the rate of penetration (ROP) of PDC bits over roller cone bits in soft to medium-hard formations. Recently, with the development of PDC technology, the diameter of the PDC tooth can be further expanded. The maximum diameter of the PDC cutter used in this paper is 22 mm. According to the theoretical calculation, under the same depth of cut (DOC), the 22mm-PDC cutter increases the exposure of the cutter, and the increase of PDC cutter diameter helps to increase the cutting area of the PDC cutter. In order to evaluate the cutting performance of the 22 mm-PDC cutter and the existing commonly used cutters, the 16 mm, 19 mm and 22 mm PDC cutter was selected put on a vertical turret lathe (VTL) in the laboratory for cutting tests under different DOCs. The DOCs were 0.5mm, 1.0 mm, 1.5 mm and 2.0 mm, 2.5 mm and 3 mm, respectively. The rock sample used in the experiment was limestone. Results of laboratory tests have shown the new 22 mm-PDC cutter technology greatly improved cutting efficiency. On the one hand, as the DOC increases, the mechanical specific energy (MSE) of all cutters decreases, which means that the cutting efficiency increases. On the other hand, under the same DOC condition, the larger the cutter diameter is, the larger the working area of the cutter is, which leads to higher the cutting efficiency. In view of the high performance of the 22 mm-PDC cutters, which was applied to carry out full-scale bit field experiments. The result shows that the bit with 22mm-PDC cutters achieves a breakthrough improvement of ROP than that with conventional 16mm and 19mm cutters in offset well drilling.

Keywords: polycrystalline diamond compact, 22 mm-PDC cutters, cutting efficiency, mechanical specific energy

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Kalpeshkumar L. Gupta, Shivali Rathore

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India is home to over 30 crore rural poor, aware of the criticality of the situation that has made to come with an innovative business idea. Entrepreneurship in India is on the verge of explosive growth and which is actually need of an hour for employment generation, poverty elevation at grass root through developmental intervention. India economic progress has started from the development of its small and medium scale enterprises to ensure that the sectors continues to stay competitive and achieve sustained growth in the era of global economy many incubators centers has been established with the mission to give the encouragement to many innovative ideas. If we define an Incubator, it is simply an enclosed apparatus in which premature small babies are placed and which provides a controlled and protective environment for their care this gives them a chance to adjust to outside environment, and grow stronger before they face the outside world. In a similar way the startup entrepreneur’s business idea is incubated in the incubation centers. Entrepreneurship has been conventionally rated as risky career, to break the myth and to augment the supply of new entrepreneurs through education; research training the incubation centers has been established, their goal is to help create and grow young businesses by providing them with necessary support and financial and technical services. The startup companies spend on an average two years in a business incubator during which numerous benefits like funding, office space, equipment’s etc. is provided by the incubators to the startup business. Present paper will study the background, role, objectives of different incubators set up in Indian Institute of Management (IIMs) and Indian Institute of Technology (IITs) for our study.

Keywords: incubation centres, entrepreneurship, Indian Institute of Management, Indian Institute of Technology

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Authors: Nursigit Bintoro, Abadi Barus, Catur Setyo Dedi Pamungkas

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Indonesia is an agrarian country have almost population work as farmers. One of the popular agriculture commodity in Indonesia is paddy and corn. Production of paddy and corn are increased, but not balanced to the development of appropriate technology to farmers. Methods of drying applied with farmers still using sunshine. Drying by this method has some drawbacks, such as differences moisture content of corn grains, time used to dry around 3 days, and less quality of the products obtained. Beside it, the method of drying by using sunshine can’t do when the rainy season arrives. On this season the product obtained has less quality. One solution to the above problems is to create a dryer with simple technology. That technology is made silo dryer from webbing bamboo and wood. This technology is applicable to be applied to farmers' groups as well as the creation technology is quite cheap. The experiment material used in this research will be obtained from the corn grains. The equipment used are woven bamboo with a height of 3 meters and have capacity of up to 900 kgs as a silo, gas, burner, blower, bucket elevators, thermocouple, Arduino microcontroller 2560. This tools automatically records all the data of temperature and relative humidity. During on drying, each 30 minutes take 9 sample for measuring moisture content with moisture meter. By using this technology, farmers can save time, energy, and cost to the drying their agriculture product. In addition, by using this technology have good quality moisture content of grains and have a longer shelf life because the temperature when the heating process is controlled. Therefore, this technology is applicable to be applied to the public because the materials used to make the dryer easier to find, cheaper, and manufacture of the dryer made simple with good quality.

Keywords: grains, dryer, moisture content, appropriate technology

Procedia PDF Downloads 356

Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Gerald Gwamba, Bo Zhou, Yajun Song, Dong Changyin

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The challenges that sand production presents to the oil and gas industry, particularly while working in poorly consolidated reservoirs, cannot be overstated. From restricting production to blocking production tubing, sand production increases the costs associated with production as it elevates the cost of servicing production equipment over time. Production in reservoirs that present with high viscosities, flow rate, cementation, clay content as well as fine sand contents is even more complex and challenging. As opposed to the one-factor at a-time testing, investigating the interactive effects arising from a combination of several factors offers increased reliability of results as well as representation of actual field conditions. It is thus paramount to investigate the conditions leading to the onset of sanding during production to ensure the future sustainability of hydrocarbon production operations under viscous conditions. We adopt the Design of Experiments (DOE) to analyse, using Taguchi factorial designs, the most significant interactive effects of sanding. We propose an optimized regression model to predict the drawdown time at sand production. The results obtained underscore that reservoirs characterized by varying (high and low) levels of viscosity, flow rate, cementation, clay, and fine sand content have a resulting impact on sand production. The only significant interactive effect recorded arises from the interaction between BD (fine sand content and flow rate), while the main effects included fluid viscosity and cementation, with percentage significances recorded as 31.3%, 37.76%, and 30.94%, respectively. The drawdown time model presented could be useful for predicting the time to reach the maximum drawdown pressure under viscous conditions during the onset of sand production.

Keywords: factorial designs, DOE optimization, sand production prediction, drawdown time, regression model

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Authors: Linda Boussaid, Farid Brahim Belaribi

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The physico-chemical properties of liquid materials in the industrial field, in general, and in that of the chemical industries, in particular, constitutes a prerequisite for the design of equipment, for the resolution of specific problems (related to the techniques of purification and separation, at risk in the transport of certain materials, etc.) and, therefore, at the production stage. Chloroalkanes, ethers constitute three chemical families having an industrial, theoretical and environmental interest. For example, these compounds are used in various applications in the chemical and pharmaceutical industries. In addition, they contribute to the particular thermodynamic behavior (deviation from ideality, association, etc.) of certain mixtures which constitute a severe test for predictive theoretical models. Finally, due to the degradation of the environment in the world, a renewed interest is observed for ethers, because some of their physicochemical properties could contribute to lower pollution (ethers would be used as additives in aqueous fuels.). This work is a thermodynamic, experimental and theoretical study of the volumetric properties of liquid binary systems formed from compounds belonging to the chemical families of chloroalkanes, ethers, having an industrial, theoretical and environmental interest. Experimental determination of the densities and excess volumes of the systems studied, at different temperatures in the interval [278.15-333.15] K and at atmospheric pressure, using an AntonPaar vibrating tube densitometer of the DMA5000 type. This contribution of experimental data, on the volumetric properties of the binary liquid mixtures of 1,2-dichloroethane with an ether, supplemented by an application of the theoretical model of Prigogine-Flory-Patterson PFP, will probably contribute to the enrichment of the thermodynamic database and the further development of the theory of Flory in its Prigogine-Flory-Patterson (PFP) version, for a better understanding of the thermodynamic behavior of these liquid binary mixtures

Keywords: prigogine-flory-patterson (pfp), propriétés volumétrique , volume d’excés, ethers

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Authors: Armen Grigoryan, Milena Arakelyan

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The idea of smart logistics is still quite a complicated one. It can be used to market products to a large number of customers or to acquire raw materials of the highest quality at the lowest cost in geographically dispersed areas. The use of smart contracts in logistics and supply chain management has the potential to revolutionize the way that goods are tracked, transported, and managed. Smart contracts are simply computer programs written in one of the blockchain programming languages (Solidity, Rust, Vyper), which are capable of self-execution once the predetermined conditions are met. They can be used to automate and streamline many of the traditional manual processes that are currently used in logistics and supply chain management, including the tracking and movement of goods, the management of inventory, and the facilitation of payments and settlements between different parties in the supply chain. Currently, logistics is a core area for companies which is concerned with transporting products between parties. Still, the problem of this sector is that its scale may lead to detainments and defaults in the delivery of goods, as well as other issues. Moreover, large distributors require a large number of workers to meet all the needs of their stores. All this may contribute to big detainments in order processing and increases the potentiality of losing orders. In an attempt to break this problem, companies have automated all their procedures, contributing to a significant augmentation in the number of businesses and distributors in the logistics sector. Hence, blockchain technology and smart contracted legal agreements seem to be suitable concepts to redesign and optimize collaborative business processes and supply chains. The main purpose of this paper is to examine the scope of blockchain technology and smart contracts in the field of logistics and supply chain management. This study discusses the research question of how and to which extent smart contracts and blockchain technology can facilitate and improve the implementation of collaborative business structures for sustainable entrepreneurial activities in smart supply chains. The intention is to provide a comprehensive overview of the existing research on the use of smart contracts in logistics and supply chain management and to identify any gaps or limitations in the current knowledge on this topic. This review aims to provide a summary and evaluation of the key findings and themes that emerge from the research, as well as to suggest potential directions for future research on the use of smart contracts in logistics and supply chain management.

Keywords: smart contracts, smart logistics, smart supply chain management, blockchain and smart contracts in logistics, smart contracts for controlling supply chain management

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Authors: Mohanad Moustafa, Julia Sieberer, Rhys Davies

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Background: Orbital compartment syndrome (OCS) is a sight-threatening Ophthalmologic emergency caused by rapidly increasing intraorbital pressure. It is usually caused by a retrobulbar hemorrhage as a result of trauma. If not treated in a timely manner, permanent vision loss can occur. Lateral canthotomy and cantholysis are minor procedures that can be performed bedside with equipment available in the emergency department. The aim of the procedure is to release the attachments between the suspensory ligaments of the eye and the bony orbital wall, leading to a decrease in intraorbital pressure and preventing irreversible loss of vision. As most Ophthalmologists across the UK provide non-resident on-call service, this may lead to a delay in the treatment of OCS and stresses the need for Emergency medical staff to be able to provide this sight-saving procedure independently. Aim: To survey current training, experience, and confidence levels among Emergency Medicine doctors in performing emergency lateral canthotomy and to establish whether these variables change the following teaching from experienced ophthalmologists. RESULTS: Most EM registrars had little to no experience in performing lateral canthotomy and cantholysis. The majority of them showed a significant increase in their confidence to perform the procedure following ophthalmic-led teaching. The survey also showed that the registrars felt such training should be added to/part of the EM curriculum. Conclusion: The involvement of Ophthalmologists in the teaching of EM doctors to recognise and treat OCS independently may prevent delays in treatment and reduce the risk of permanent sight loss. This project showed potential in improving patient care and will lead to a National Survey of EM doctors across the UK.

Keywords: lateral canthotomy, retrobulbar hemorrhage, Ophthalmology, orbital compartment syndrome, sight loss, blindness

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Authors: Wajeeha Shahid

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The study was designed to assess the impact of transformational and transactional leadership styles on work motivation and organizational commitment among faculty members of universities of Punjab. 713 faculty members were selected as sample through convenient random sampling technique. Three self-constructed questionnaires namely Leadership Styles Questionnaire (LSQ), Work Motivation Questionnaire (WMQ) and Organizational Commitment Questionnaire (OCMQ) were used as research instruments. Major objectives of the study included assessing the effect and impact of transformational and transactional leadership styles on work motivation and organizational commitment. Theoretical frame work of the study included Idealized Influence, Inspirational Motivation, Intellectual Stimulation, Individualized Consideration, Contingent Rewards and Management by Exception as independent variables and Extrinsic motivation, Intrinsic motivation, Affective commitment, Continuance commitment and Normative commitment as dependent variables. SPSS Version 21 was used to analyze and tabulate data. Cronbach's Alpha reliability, Pearson Correlation and Multiple regression analysis were applied as statistical treatments for the analysis. Results revealed that Idealized Influence correlated significantly with intrinsic motivation and Affective commitment whereas Contingent rewards had a strong positive correlation with extrinsic motivation and affective commitment. Multiple regression models revealed a variance of 85% for transformational leadership style over work motivation and organizational commitment. Whereas transactional style as a predictor manifested a variance of 79% for work motivation and 76% for organizational commitment. It was suggested that changing organizational cultures are demanding more from their leadership. All organizations need to consider transformational leadership style as an important part of their equipment in leveraging both soft and hard organizational targets.

Keywords: leadership styles, work motivation, organizational commitment, faculty member

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Authors: Angelis P. Barlampas, Ghita Bianca-Andreea

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A case of a prostatic midline cyst is presented, which was found during a routine general ultrasound examination in an otherwise healthy young man. The incidence of prostatic cysts discovered in suprapubic ultrasound examination has constantly been rising over the previous decades. Despite the fact that the majority of them are benign, a significant amount is related to symptoms, such as pain, dysuria, infertility, and even cancer. The wide use of ultrasound examination and the increasing availability of high-resolution ultrasound systems have rendered new diagnostic challenges. Once upon a time a suprapubic ultrasound was only useful for measuring only the size and the dimensions of the prostatic gland. It did not have the ability to analyze and resolve structures such as cystic or solid nodules. The current machine equipment has managed to depict the imaging characteristics of lesions with high acuity that compares of an intrarectal ultrasound. But the last one is a specialized examination, which demands expertise and good knowledge. Maybe the time has come for the general radiologist and, especially the one who uses suprapubic ultrasound, to pay more attention to the examination of the prostate gland and to take advantage of the superb abilities and the high resolution of the new ultrasound systems. That is exactly, what this case is emphasizing. The incidental discovery of prostatic cysts, and the relatively little available literature about managing them turns them into an interesting theme for exploring and studying. The prostatic cysts are further divided into midline and paramidline cysts, with the first being usually utricle cysts. A more precise categorization is as follows: A midline cystic lesion usually regards a Mullerian duct cyst, a prostatic utricle cyst, an ejaculatory duct cyst, a prostatic cystadenoma, a ductus deferens cyst, and a TURP. On the other hand, a lateral cystic lesion usually refers to a cystic degeneration of benign prostatic hyperplasia, a prostatic retention cyst, a seminal vesicle cyst, diverticular prostatitis, a prostatic abscess, cavitatory prostatitis from chronic prostatitis, a parasitic prostatic cyst, a cystic prostatic carcinoma, e.t.c.

Keywords: prostatic cyst, radiology, benign prostatic lesions, prostatic cancer, suprapubic prostatic ultrasound

Procedia PDF Downloads 53

Authors: S. M. Mahdi Niktabara, K. Seshagiri Raob, Amit Kumar Shrivastavac, Jiří Ščučkaa

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The presence of the discontinuity in the form of joints is one of the most significant factors causing instability in the rock mass. On the other hand, dynamic loads, including earthquake and blasting induce cyclic shear loads along the joints in rock masses; therefore, failure of rock mass exacerbates along the joints due to changing shear resistance. Joints are under constant normal load (CNL) and constant normal stiffness (CNS) conditions. Normal stiffness increases on the joints with increasing depth, and it can affect shear resistance. For correct assessment of joint shear resistance under varying normal stiffness and number of cycles, advanced laboratory shear machine is essential for the shear test. Conventional direct shear equipment has limitations such as boundary conditions, working under monotonic movements only, or cyclic shear loads with constant frequency and amplitude of shear loads. Hence, a large-scale servo-controlled direct shear testing machine was designed and fabricated to perform shear test under the both CNL and CNS conditions with varying normal stiffness at different frequencies and amplitudes of shear loads. In this study, laboratory cyclic shear tests were conducted on non-planar joints under varying normal stiffness. In addition, the effects of different frequencies and amplitudes of shear loads were investigated. The test results indicate that shear resistance increases with increasing normal stiffness at the first cycle, but the influence of normal stiffness significantly decreases with an increase in the number of shear cycles. The frequency of shear load influences on shear resistance, i.e. shear resistance increases with increasing frequency. However, at low shear amplitude the number of cycles does not affect shear resistance on the joints, but it decreases with higher amplitude.

Keywords: cyclic shear load, frequency of load, amplitude of displacement, normal stiffness

Procedia PDF Downloads 147

Authors: Laura Florez

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The construction industry is labour intensive, and the behaviour and management of workers have a direct impact on the performance of construction projects. One of the issues it currently faces is how to recruit and maintain its workers. Construction is known as an industry where workers face the problem of short employment durations, frequent layoffs, and periods of unemployment between jobs. These challenges not only creates pressures on the workers but also project managers have to constantly train new workers, face skills shortage, and uncertainty on the quality of the workers it will attract. To consider worker’s needs and project managers expectations, one practice that can be implemented is to schedule construction projects to maintain a stable workforce. This paper proposes a mixed integer programming (MIP) model to schedule projects with the objective of maximising social sustainability of construction projects, that is, maximise labour stability. Aside from the social objective, the model accounts for equipment and financial resources required by the projects during the construction phase. To illustrate how the solution strategy works, a construction programme comprised of ten projects is considered. The projects are scheduled to maximise labour stability while simultaneously minimising time and minimising cost. The tradeoff between the values in terms of time, cost, and labour stability allows project managers to consider their preferences and identify which solution best suits their needs. Additionally, the model determines the optimal starting times for each of the projects, working patterns for the workers, and labour costs. This model shows that construction projects can be scheduled to not only benefit the project manager, but also benefit current workers and help attract new workers to the industry. Due to its practicality, it can be a valuable tool to support decision making and assist construction stakeholders when developing schedules that include social sustainability factors.

Keywords: labour stability, mixed-integer programming (MIP), scheduling, workforce management

Procedia PDF Downloads 251

Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

Procedia PDF Downloads 340

Authors: Shamim Ahsan

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Abstract Global digital advances associated with consumer’s strong inclination for the state of art digital technologies is causing overwhelming social and environmental challenges for global community. During recent years not only economic advances of electronic industries has taken place at steadfast rate, also the generation of e-waste outshined the growth of any other types of wastes. The estimated global e-waste volume is expected to reach 65.4 million tons annually by 2017. Formal recycling practices in developed countries are stemming economic liability, opening paths for illegal trafficking to developing countries. Informal crude management of large volume of e-waste is transforming into an emergent environmental and health challenge in. Contrariwise, in several studies formal and informal recycling of e-waste has also exhibited potentials for economic returns both in developed and developing countries. Some research on China illustrated that from large volume of e-wastes generation there are recycling potential in evolving from ∼16 (10−22) billion US$ in 2010, to an anticipated ∼73.4 (44.5−103.4) billion US$ by 2030. While in another study, researcher found from an economic analysis of 14 common categories of waste electric and electronic equipment (WEEE) the overall worth is calculated as €2.15 billion to European markets, with a potential rise to €3.67 billion as volumes increase. These economic returns and environmental protection approaches are feasible only when sustainable policy options are embraced with stricter regulatory mechanism. This study will critically review current researches to stipulate how global e-waste generation and sustainable e-waste recycling practices demonstrate future economic development potential in terms of both quantity and processing capacity, also triggering complex some environmental challenges.

Keywords: E-Waste, , Generation, , Economic Potential, Recycling

Procedia PDF Downloads 302

Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

Procedia PDF Downloads 191

Authors: Felix Eyben, Simon Schaffrath, Markus Feldmann

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A building should maximize the potential for use through its design. Therefore, flexible use is always important when designing a steel structure. To create flexibility, steel beams with web openings are increasingly used, because these offer the advantage that cables, pipes and other technical equipment can easily be routed through without detours, allowing for more space-saving and aesthetically pleasing construction. This can also significantly reduce the height of ceiling systems. Until now, beams with web openings were not explicitly considered in the European standard. However, this is to be done with the new EN 1993-1-13, in which design rules for different opening forms are defined. In order to further develop the design concepts, beams with web openings under bending are therefore to be investigated in terms of damage mechanics as part of a German national research project aiming to optimize the verifications for steel structures based on a wider database and a validated damage prediction. For this purpose, first, fundamental factors influencing the load-bearing behavior of girders with web openings under bending load were investigated numerically without taking material damage into account. Various parameter studies were carried out for this purpose. For example, the factors under study were the opening shape, size and position as well as structural aspects as the span length, arrangement of stiffeners and loading situation. The load-bearing behavior is evaluated using resulting load-deformation curves. These results are compared with the design rules and critically analyzed. Experimental tests are also planned based on these results. Moreover, the implementation of damage mechanics in the form of the modified Bai-Wierzbicki model was examined. After the experimental tests will have been carried out, the numerical models are validated and further influencing factors will be investigated on the basis of parametric studies.

Keywords: damage mechanics, finite element, steel structures, web openings

Procedia PDF Downloads 169

Authors: Ximena Calle, Plinio Cantero-López, Felipe Muñoz-Córdova, Mayarling-Francisca Troncoso, Sergio Lavandero, Valentina Parra

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MUL1, a mitochondrial E3 ubiquitin ligase anchored to the outer mitochondrial membrane, is highly expressed in the heart. MUL1 is involved in multiple biological pathways associated with mitochondrial dynamics. Increased MUL1 affects the balance between fission and fusion, affecting mitochondrial function, which plays a crucial role in myocardial function. Therefore, it is interesting to evaluate the effect of cardiac-specific overexpression of MUL1 on myocardial function. Aim: To determine heart functionality in a mouse model with cardio-specific overexpression MUL1 protein. Methods and Results: Male C57BL/Tg transgenic mice with cardiomyocyte-specific overexpression of MUL1 (n=10) and control (n=4) were evaluated at 12, 27, and 35 weeks of age. Glucose tolerance curve determination was performed after a 6-hours fast to assess metabolic capacity, treadmill test, and systolic, and diastolic pressure was evaluated by the mouse tail-cuff blood pressure system equipment. The result showed no glucose tolerance curve, and the treadmill test demonstrated no significant changes between groups. However, substantial changes in diastolic function were observed by ultrasound and determination of cardiac hypertrophy proteins by western blot. Conclusions: Cardio-specific overexpression of MUL1 in mice without any treatment affects diastolic cardiac function, thus showing the important role contributed by MUL1 in the heart. Future research should evaluate the effect of cardiomyocyte-specific overexpression of MUL1 in pathological conditions such as a high-fat diet is one of the main risk factors for cardiovascular disease.

Keywords: diastolic dysfunction, hypertrophy cardiac, mitochondrial E3 ubiquitin ligase 1, MUL1

Procedia PDF Downloads 66

Authors: Bintou Jobe

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Musculo-skeletal disorders (MSDs) are injuries or disorders of the spine disc, muscle strains, and low back injuries. It remains a major cause of occupational illness. Findings: Due to poor grips during handling, it is possible for neck, shoulder, arm, knees, ankle, fingers, waist, lower back injuries, and other muscle joints to be affected. Pregnant women are more prone to physical and hormonal changes, which lead to the relaxation of supporting ligaments. MSD continues to pose a global concern due to its impact on workers worldwide. The prevalence of the disorder is high, according to research into the workforce in Europe and developing countries. The causes are characterized by long working hours, insufficient rest breaks, poor posture, repetitive motion, poor manual handling techniques, psychological stress, and poor nutrition. To prevent MSD, the design mainly involves avoiding and assessing the risk. However, clinical solutions, policy governance, and minimizing manual labour are also an alternative. In addition, eating a balanced diet and teamwork force are key to elements in minimising the risk. This review aims to raise awareness and promote cost effectiveness prevention and understanding of MSD through research and identify proposed solutions to recognise the underlying causes of MSDs in the construction sectors. The methodology involves a literature review approach, engaging with the policy landscape of MSD, synthesising publications on MSD and a wider range of academic publications. In conclusion, training on effective manual handling techniques should be considered, and Personal Protective Equipment should be a last resort. The implementation of training guidelines has yielded significant benefits.

Keywords: musculoskeletal disorder work related, MSD, manual handling, work hazards

Procedia PDF Downloads 55

Authors: Lyka Selene Magnayi, Marcos Vinas, Roseanne Ramos

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As the real estate industry continually grows in the Philippines, Geographic Information Systems (GIS) provide advantages in generating spatial databases for efficient delivery of information and services. The real estate sector is not only providing qualitative data about real estate properties but also utilizes various spatial aspects of these properties for different applications such as hazard mapping and assessment. In this study, a three-dimensional (3D) model and a spatial database of real estate properties in Fort Bonifacio, Taguig City are developed using GIS and SketchUp. Spatial datasets include political boundaries, buildings, road network, digital terrain model (DTM) derived from Interferometric Synthetic Aperture Radar (IFSAR) image, Google Earth satellite imageries, and hazard maps. Multiple model layers were created based on property listings by a partner real estate company, including existing and future property buildings. Actual building dimensions, building facade, and building floorplans are incorporated in these 3D models for geovisualization. Hazard model layers are determined through spatial overlays, and different scenarios of hazards are also presented in the models. Animated maps and walkthrough videos were created for company presentation and evaluation. Model evaluation is conducted through client surveys requiring scores in terms of the appropriateness, information content, and design of the 3D models. Survey results show very satisfactory ratings, with the highest average evaluation score equivalent to 9.21 out of 10. The output maps and videos obtained passing rates based on the criteria and standards set by the intended users of the partner real estate company. The methodologies presented in this study were found useful and have remarkable advantages in the real estate industry. This work may be extended to automated mapping and creation of online spatial databases for better storage, access of real property listings and interactive platform using web-based GIS.

Keywords: geovisualization, geographic information systems, GIS, real estate, spatial database, three-dimensional model

Procedia PDF Downloads 157

Authors: Paul R Armstrong

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Doubled haploids (DHs) have become an important breeding tool for creating maize inbred lines, although several bottlenecks in the DH production process limit wider development, application, and adoption of the technique. DH kernels are typically sorted manually and represent about 10% of the seeds in a much larger pool where the remaining 90% are hybrid siblings. This introduces time constraints on DH production and manual sorting is often not accurate. Automated sorting based on the chemical composition of the kernel can be effective, but devices, namely NMR, have not achieved the sorting speed to be a cost-effective replacement to manual sorting. This study evaluated a single kernel near-infrared reflectance spectroscopy (skNIR) platform to accurately identify DH kernels based on oil content. The skNIR platform is a higher-throughput device, approximately 3 seeds/s, that uses spectra to predict oil content of each kernel from maize crosses intentionally developed to create larger than normal oil differences, 1.5%-2%, between DH and hybrid kernels. Spectra from the skNIR were used to construct a partial least squares regression (PLS) model for oil and for a categorical reference model of 1 (DH kernel) or 2 (hybrid kernel) and then used to sort several crosses to evaluate performance. Two approaches were used for sorting. The first used a general PLS model developed from all crosses to predict oil content and then used for sorting each induction cross, the second was the development of a specific model from a single induction cross where approximately fifty DH and one hundred hybrid kernels used. This second approach used a categorical reference value of 1 and 2, instead of oil content, for the PLS model and kernels selected for the calibration set were manually referenced based on traditional commercial methods using coloration of the tip cap and germ areas. The generalized PLS oil model statistics were R2 = 0.94 and RMSE = .93% for kernels spanning an oil content of 2.7% to 19.3%. Sorting by this model resulted in extracting 55% to 85% of haploid kernels from the four induction crosses. Using the second method of generating a model for each cross yielded model statistics ranging from R2s = 0.96 to 0.98 and RMSEs from 0.08 to 0.10. Sorting in this case resulted in 100% correct classification but required models that were cross. In summary, the first generalized model oil method could be used to sort a significant number of kernels from a kernel pool but was not close to the accuracy of developing a sorting model from a single cross. The penalty for the second method is that a PLS model would need to be developed for each individual cross. In conclusion both methods could find useful application in the sorting of DH from hybrid kernels.

Keywords: NIR, haploids, maize, sorting

Procedia PDF Downloads 299

Authors: Gabriel Wainer

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Modeling and Simulation methods have been used to better analyze the behavior of complex physical systems, and it is now common to use simulation as a part of the scientific and technological discovery process. M&S advanced thanks to the improvements in computer technology, which, in many cases, resulted in the development of simulation software using ad-hoc techniques. Formal M&S appeared in order to try to improve the development task of very complex simulation systems. Some of these techniques proved to be successful in providing a sound base for the development of discrete-event simulation models, improving the ease of model definition and enhancing the application development tasks; reducing costs and favoring reuse. The DEVS formalism is one of these techniques, which proved to be successful in providing means for modeling while reducing development complexity and costs. DEVS model development is based on a sound theoretical framework. The independence of M&S tasks made possible to run DEVS models on different environments (personal computers, parallel computers, real-time equipment, and distributed simulators) and middleware. We will present a historical perspective of discrete-event M&S methodologies, showing different modeling techniques. We will introduce DEVS origins and general ideas, and compare it with some of these techniques. We will then show the current status of DEVS M&S, and we will discuss a technological perspective to solve current M&S problems (including real-time simulation, interoperability, and model-centered development techniques). We will show some examples of the current use of DEVS, including applications in different fields. We will finally show current open topics in the area, which include advanced methods for centralized, parallel or distributed simulation, the need for real-time modeling techniques, and our view in these fields.

Keywords: modeling and simulation, discrete-event simulation, hybrid systems modeling, parallel and distributed simulation

Procedia PDF Downloads 318