Search results for: dimension reducing distribution load flow algorithm

Authors: Marek Dosbaba

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Within the mining sector, SEM-based Automated Mineralogy (AM) has been the standard application for quickly and efficiently handling mineral processing tasks. Over the last decade, the trend has been to analyze larger numbers of samples, often with a higher level of detail. This has necessitated a shift from interactive sample analysis performed by an operator using a SEM, to an increased reliance on offline processing to analyze and report the data. In response to this trend, TESCAN TIMA Mineral Analyzer is designed to quickly create a virtual copy of the studied samples, thereby preserving all the necessary information. Depending on the selected data acquisition mode, TESCAN TIMA can perform hyperspectral mapping and save an X-ray spectrum for each pixel or segment, respectively. This approach allows the user to browse through elemental distribution maps of all elements detectable by means of energy dispersive spectroscopy. Re-evaluation of the existing data for the presence of previously unconsidered elements is possible without the need to repeat the analysis. Additional tiers of data such as a secondary electron or cathodoluminescence images can also be recorded. To take full advantage of these information-rich datasets, TIMA utilizes a new archiving tool introduced by TESCAN. The dataset size can be reduced for long-term storage and all information can be recovered on-demand in case of renewed interest. TESCAN TIMA is optimized for network storage of its datasets because of the larger data storage capacity of servers compared to local drives, which also allows multiple users to access the data remotely. This goes hand in hand with the support of remote control for the entire data acquisition process. TESCAN also brings a newly extended open-source data format that allows other applications to extract, process and report AM data. This offers the ability to link TIMA data to large databases feeding plant performance dashboards or geometallurgical models. The traditional tabular particle-by-particle or grain-by-grain export process is preserved and can be customized with scripts to include user-defined particle/grain properties.

Keywords: Tescan, electron microscopy, mineralogy, SEM, automated mineralogy, database, TESCAN TIMA, open format, archiving, big data

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Authors: H. Ishii, S. Araki, H. Yamamoto

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In recent years, the carbon dioxide (CO2) separation technology is required in terms of the reduction of emission of global warming gases and the efficient use of fossil fuels. Since the emission amount of CO2 gas occupies the large part of greenhouse effect gases, it is considered that CO2 have the most influence on global warming. Therefore, we need to establish the CO2 separation technologies with high efficiency at low cost. In this study, we focused on the membrane separation compared with conventional separation technique such as distillation or cryogenic separation. In this study, we prepared carbonate-ceramic dual-phase membranes to separate CO2 at high temperature. As porous ceramic substrate, the (Pr0.9La0.1)2(Ni0.74Cu0.21Ga0.05)O4+σ, La0.6Sr0.4Ti0.3 Fe0.7O3 and Ca0.8Sr0.2Ti0.7Fe0.3O3-α (PLNCG, LSTF and CSTF) were examined. PLNCG, LSTF and CSTF have the perovskite structure. The perovskite structure has high stability and shows ion-conducting doped by another metal ion. PLNCG, LSTF and CSTF have perovskite structure and has high stability and high oxygen ion diffusivity. PLNCG, LSTF and CSTF powders were prepared by a solid-phase process using the appropriate carbonates or oxides. To prepare porous substrates, these powders mixed with carbon black (20 wt%) and a few drops of polyvinyl alcohol (5 wt%) aqueous solution. The powder mixture were packed into stainless steel mold (13 mm) and uniaxially pressed into disk shape under a pressure of 20 MPa for 1 minute. PLNCG, LSTF and CSTF disks were calcined in air for 6 h at 1473, 1573 and 1473 K, respectively. The carbonate mixture (Li2CO3/Na2CO3/K2CO3: 42.5/32.5/25 in mole percent ratio) was placed inside a crucible and heated to 793 K. Porous substrates were infiltrated with the molten carbonate mixture at 793 K. Crystalline structures of the fresh membranes and after the infiltration with the molten carbonate mixtures were determined by X-ray diffraction (XRD) measurement. We confirmed the crystal structure of PLNCG and CSTF slightly changed after infiltration with the molten carbonate mixture. CO2 permeation experiments with PLNCG-carbonate, LSTF-carbonate and CSTF-carbonate membranes were carried out at 773-1173 K. The gas mixture of CO2 (20 mol%) and He was introduced at the flow rate of 50 ml/min to one side of membrane. The permeated CO2 was swept by N2 (50 ml/min). We confirmed the effect of ceramic materials and temperature on the CO2 permeation at high temperature.

Keywords: membrane, perovskite structure, dual-phase, carbonate

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Rafał Szmajser, Katarzyna Świetla, Mariusz Andrzejewski

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Robotic process automation (RPA) is a technology of repeatable business processes performed using computer programs, robots that simulate the work of a human being. This approach assumes replacing an existing employee with the use of dedicated software (software robots) to support activities, primarily repeated and uncomplicated, characterized by a low number of exceptions. RPA application is widespread in modern business services, particularly in the areas of Finance, Accounting and Human Resources Management. By utilizing this technology, the effectiveness of operations increases while reducing workload, minimizing possible errors in the process, and as a result, bringing measurable decrease in the cost of providing services. Regardless of how the use of modern information technology is assessed, there are also some doubts as to whether we should replace human activities in the implementation of the automation in business processes. After the initial awe for the new technological concept, a reflection arises: to what extent does the implementation of RPA increase the efficiency of operations or is there a Business Case for implementing it? If the business case is beneficial, in which business processes is the greatest potential for RPA? A closer look at these issues was provided by in this research during which the respondents’ view of the perceived advantages resulting from the use of robotization and automation in financial and accounting processes was verified. As a result of an online survey addressed to over 500 respondents from international companies, 162 complete answers were returned from the most important types of organizations in the modern business services industry, i.e. Business or IT Process Outsourcing (BPO/ITO), Shared Service Centers (SSC), Consulting/Advisory and their customers. Answers were provided by representatives of the positions in their organizations: Members of the Board, Directors, Managers and Experts/Specialists. The structure of the survey allowed the respondents to supplement the survey with additional comments and observations. The results formed the basis for the creation of a business case calculating tangible benefits associated with the implementation of automation in the selected financial processes. The results of the statistical analyses carried out with regard to revenue growth confirmed the correctness of the hypothesis that there is a correlation between job position and the perception of the impact of RPA implementation on individual benefits. Second hypothesis (H2) that: There is a relationship between the kind of company in the business services industry and the reception of the impact of RPA on individual benefits was thus not confirmed. Based results of survey authors performed simulation of business case for implementation of RPA in selected Finance and Accounting Processes. Calculated payback period was diametrically different ranging from 2 months for the Account Payables process with 75% savings and in the extreme case for the process Taxes implementation and maintenance costs exceed the savings resulting from the use of the robot.

Keywords: automation, outsourcing, business process automation, process automation, robotic process automation, RPA, RPA business case, RPA benefits

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Authors: Saheed Shittu, Lolwa Alansari, Fahed Nattouf, Tawa Olukade, Naji Abdallah, Tamara Alshdafat, Sarra Amdouni

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Cesarean sections (CS), a highly regarded surgical intervention for improving fetal-maternal outcomes and serving as an integral part of emergency obstetric services, are not without complications. Although CS has many advantages, it poses significant risks to both mother and child and increases healthcare expenditures in the long run. The escalating global prevalence of CS, coupled with variations in rates among immigrant populations, has prompted an inquiry into the correlation between CS rates and the nationalities of women undergoing deliveries at Al-Wakra Hospital (AWH), Qatar's second-largest public maternity hospital. This inquiry is motivated by the notable CS rate of 36%, deemed high in comparison to the 34% recorded across other Hamad Medical Corporation (HMC) maternity divisions This is Qatar's first comprehensive investigation of Caesarean section rates and nationalities. A retrospective cross-sectional study was conducted, and data for all births delivered in 2019 were retrieved from the hospital's electronic medical records. The CS rate, the crude rate, and adjusted risks of Caesarean delivery for mothers from each nationality were determined. The common indications for CS were analysed based on nationality. The association between nationality and Caesarean rates was examined using binomial logistic regression analysis considering Qatari women as a standard reference group. The correlation between the CS rate in the country of nationality and the observed CS rate in Qatar was also examined using Pearson's correlation. This study included 4,816 births from 69 different nationalities. CS was performed in 1767 women, equating to 36.5%. The nationalities with the highest CS rates were Egyptian (49.6%), Lebanese (45.5%), Filipino and Indian (both 42.2%). Qatari women recorded a CS rate of 33.4%. The major indication for elective CS was previous multiple CS (39.9%) and one prior CS, where the patient declined vaginal birth after the cesarean (VBAC) option (26.8%). A distinct pattern was noticed: elective CS was predominantly performed on Arab women, whereas emergency CS was common among women of Asian and Sub-Saharan African nationalities. Moreover, a significant correlation was found between the CS rates in Qatar and the women's countries of origin. Also, a high CS rate was linked to instances of previous CS. As a result of these insights, strategic interventions were successfully implemented at the facility to mitigate unwarranted CS, resulting in a notable reduction in CS rate from 36.5% in 2019 to 34% in 2022. This proves the efficacy of the meticulously researched approach. The focus has now shifted to reducing primary CS rates and facilitating well-informed decisions regarding childbirth methods.

Keywords: maternal nationality, caesarean section rate variation, migrants, high-income country

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Authors: Milton Ixquiac, Erick Montenegro, Francisco Reynoso, Matthew Schmidt, Thomas Mazur, Tianyu Zhao, Hiram Gay, Geoffrey Hugo, Lauren Henke, Jeff Michael Michalski, Angel Velarde, Vicky de Falla, Franky Reyes, Osmar Hernandez, Edgar Aparicio Ruiz, Baozhou Sun

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Purpose: Radiotherapy departments in low- and middle-income countries (LMICs) like Guatemala have recently introduced intensity-modulated radiotherapy (IMRT). IMRT has become the standard of care in high-income countries (HIC) due to reduced toxicity and improved outcomes in some cancers. The purpose of this work is to show the agreement between the dosimetric results shown in the Dose Volume Histograms (DVH) to the objectives proposed in the adopted protocol. This is the initial experience with an O-ring Linac. Methods and Materials: An O-Linac Linac was installed at our clinic in Guatemala in 2019 and has been used to treat approximately 90 patients daily with IMRT. This Linac is a completely Image Guided Device since to deliver each radiotherapy session must take a Mega Voltage Cone Beam Computerized Tomography (MVCBCT). In each MVCBCT, the Linac deliver 9 UM, and they are taken into account while performing the planning. To start the standardization, the TG263 was employed in the nomenclature and adopted a hypofractionated protocol to treat ChestWall, including supraclavicular nodes achieving 40.05Gy in 15 fractions. The planning was developed using 4 semiarcs from 179-305 degrees. The planner must create optimization volumes for targets and Organs at Risk (OARs); the difficulty for the planner was the dose base due to the MVCBCT. To evaluate the planning modality, we used 30 chestwall cases. Results: The plans created manually achieve the protocol objectives. The protocol objectives are the same as the RTOG1005, and the DHV curves look clinically acceptable. Conclusions: Despite the O-ring Linac doesn´t have the capacity to obtain kv images, the cone beam CT was created using MV energy, the dose delivered by the daily image setup process still without affect the dosimetric quality of the plans, and the dose distribution is acceptable achieving the protocol objectives.

Keywords: hypofrationation, VMAT, chestwall, radiotherapy planning

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Authors: Majid Eslami

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Functionally graded materials (FGMs) exhibit heterogeneous microstructures in which the composition and properties gently change in specified directions. The common type of FGMs consist of a metal in which ceramic particles are distributed with a graded concentration. There are many processing routes for FGMs. An important group of these methods is casting techniques (gravity or centrifugal). However, the main problem of casting molten metal slurry with dispersed ceramic particles is a destructive chemical reaction between these two phases which deteriorates the properties of the materials. In order to overcome this problem, in the present investigation a suspension of 6061 aluminum and alumina powders in a liquid polymer was used as the starting material and subjected to centrifugal force for making FGMs. The size rang of these powders was 45-63 and 106-125 μm. The volume percent of alumina in the Al/Al2O3 powder mixture was in the range of 5 to 20%. PMMA (Plexiglas) in different concentrations (20-50 g/lit) was dissolved in toluene and used as the suspension liquid. The glass mold contaning the suspension of Al/Al2O3 powders in the mentioned liquid was rotated at 1700 rpm for different times (4-40 min) while the arm length was kept constant (10 cm) for all the experiments. After curing the polymer, burning out the binder, cold pressing and sintering , cylindrical samples (φ=22 mm h=20 mm) were produced. The density of samples before and after sintering was quantified by Archimedes method. The results indicated that by using the same sized alumina and aluminum powders particles, FGM sample can be produced by rotation times exceeding 7 min. However, by using coarse alumina and fine alumina powders the sample exhibits step concentration. On the other hand, using fine alumina and coarse alumina results in a relatively uniform concentration of Al2O3 along the sample height. These results are attributed to the effects of size and density of different powders on the centrifugal force induced on the powders during rotation. The PMMA concentration and the vol.% of alumina in the suspension did not have any considerable effect on the distribution of alumina particles in the samples. The hardness profiles along the height of samples were affected by both the alumina vol.% and porosity content. The presence of alumina particles increased the hardness while increased porosity reduced the hardness. Therefore, the hardness values did not show the expected gradient in same sample. The sintering resulted in decreased porosity for all the samples investigated.

Keywords: FGM, powder metallurgy, centrifugal method, polymeric suspension

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Authors: Danny Alexander R. Moreno, Gustavo L. Sartorello, Yuli Andrea P. Bermudez, Richard R. Lobo, Ives Claudio S. Bueno, Augusto H. Gameiro

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Meat production is a significant sector for Brazil's economy; however, the agricultural segment has suffered censure regarding the negative impacts on the environment, which consequently results in climate change. Therefore, it is essential the implementation of nutritional strategies that can improve the environmental performance of livestock. This research aimed to estimate the environmental impact and profitability of the use of yerba mate extract (Ilex paraguariensis) as an additive in the feeding of feedlot lamb. Thirty-six castrated male lambs (average weight of 23.90 ± 3.67 kg and average age of 75 days) were randomly assigned to four experimental diets with different levels of inclusion of yerba mate extract (0, 1, 2, and 4 %) based on dry matter. The animals were confined for fifty-three days and fed with 60:40 corn silage to concentrate ratio. As an indicator of environmental impact, the carbon footprint (CF) was measured as kg of CO₂ equivalent (CO₂-eq) per kg of body weight produced (BWP). The greenhouse gas (GHG) emissions such as methane (CH₄) generated from enteric fermentation, were calculated using the sulfur hexafluoride gas tracer (SF₆) technique; while the CH₄, nitrous oxide (N₂O - emissions generated by feces and urine), and carbon dioxide (CO₂ - emissions generated by concentrate and silage processing) were estimated using the Intergovernmental Panel on Climate Change (IPCC) methodology. To estimate profitability, the gross margin was used, which is the total revenue minus the total cost; the latter is composed of the purchase of animals and food. The boundaries of this study considered only the lamb fattening system. The enteric CH₄ emission from the lamb was the largest source of on-farm GHG emissions (47%-50%), followed by CH₄ and N₂O emissions from manure (10%-20%) and CO₂ emission from the concentrate, silage, and fossil energy (17%-5%). The treatment that generated the least environmental impact was the group with 4% of yerba mate extract (YME), which showed a 3% reduction in total GHG emissions in relation to the control (1462.5 and 1505.5 kg CO₂-eq, respectively). However, the scenario with 1% YME showed an increase in emissions of 7% compared to the control group. In relation to CF, the treatment with 4% YME had the lowest value (4.1 kg CO₂-eq/kg LW) compared with the other groups. Nevertheless, although the 4% YME inclusion scenario showed the lowest CF, the gross margin decreased by 36% compared to the control group (0% YME), due to the cost of YME as a food additive. The results showed that the extract has the potential for use in reducing GHG. However, the cost of implementing this input as a mitigation strategy increased the production cost. Therefore, it is important to develop political strategies that help reduce the acquisition costs of input that contribute to the search for the environmental and economic benefit of the livestock sector.

Keywords: meat production, natural additives, profitability, sheep

Procedia PDF Downloads 139

Authors: Fatima Muhammad Abdulkadir, D. B. Maikaje, Y. A. Umar

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A study conducted to determine cercariae diversity and prevalence of trematode infection in freshwater snails from six freshwater bodies selected by systematic random sampling in Kaduna State was carried from January 2013 to December 2013. Freshwater snails and cercariae harvested from the study sites were morphologically identified. A total of 23,823 freshwater snails were collected from the six freshwater bodies: Bagoma dam, Gimbawa dam, Kangimi dam, Kubacha dam, Manchok water intake and Saminaka water intake. The observed freshwater snail species were: Melanoides tuberculata, Biomphalaria pfeifferi, Bulinus globosus, Lymnaea natalensis, Physa sp., Cleopatra bulimoides, Bellamya unicolor and Lanistes varicus. The freshwater snails were exposed to artificial bright light from a 100 Watt electric bulb in the laboratory to induce cercarial shedding. Of the total freshwater snails collected, 10.55% released one or more types of cercariae. Seven morphological types of cercariae were shed by six freshwater snail species namely: Brevifurcate-apharyngeate distome, Amphistome, Gymnocephalus, Longifurcate-pharyngeate monostome, Longifurcate-pharyngeate distome, Echinostome and Xiphidio cercariae. Infection was monotype in most of the freshwater snails collected; however, Physa species presented a mixed infection with Gymnocephalus and Longifurcate-pharyngeate distome cercariae. B. globosus and B. pfeifferi were the most preferred intermediate hosts with the prevalence of 13.48% and 13.46%, respectively. The diversity and prevalence of cercariae varied among the six freshwater bodies with Manchok water intake having the highest infestation (14.3%) and the least recorded in Kangimi dam (3.9%). There was a correlation trend between the number of freshwater snails and trematode infection with Manchok exhibiting the highest and Bagoma none. The highest cercarial diversity was observed in B. pfeifferi and B. globosus with four morphotypes each, and the lowest was in M. tuberculata with one morphotype. The general distribution of freshwater snails and the trematode cercariae they shed suggests the risk of human and animals to trematodiasis in Manchok community. Public health education to raise awareness on individual and communal action that may control snail breeding sites, prevent transmission and provide access to treatment should be intensified.

Keywords: Cercariae, diversity, freshwater snails, prevalence, trematodiasis

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Authors: Chandanee Wasana Kalansooriya

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Dietary behaviour is a crucial factor affecting diabetes control. With increasing rates of diabetes prevalence in Asian countries, examining their dietary patterns, which are largely based on rice, is timely required. It has been identified that higher consumption of some rice varieties is associated with increased risk of type 2 diabetes. Although diabetes patients are advised to consume healthier rice varieties, which contains low glycemic, several conditions, one of which food insecurity, make them difficult to preserve those healthy dietary guidelines. Hence this study tries to investigate how food security affects on making right decisions of rice consumption within diabetes affected households using a sample from Sri Lanka, a country which rice considered as the staple food and records the highest diabetes prevalence rate in South Asia. The study uses data from the Household Income and Expenditure Survey 2016, a nationally representative sample conducted by the Department of Census and Statistics, Sri Lanka. The survey used a two-stage stratified sampling method to cover different sectors and districts of the country and collected micro-data on demographics, health, income and expenditures of different categories. The study uses data from 2547 households which consist of one or more diabetes patients, based on the self-recorded health status. The Household Dietary Diversity Score (HDDS), which constructed based on twelve food groups, is used to measure the level of food security. Rice is categorized into three groups according to their Glycemic Index (GI), high GI, medium GI and low GI, and the likelihood and impact made by food security on each rice consumption categories are estimated using a Two-part Model. The shares of each rice categories out of total rice consumption is considered as the dependent variable to exclude the endogeneity issue between rice consumption and the HDDS. The results indicate that the consumption of medium GI rice is likely to increase with the increasing household food security, but low GI varieties are not. Households in rural and estate sectors are less likely and Tamil ethnic group is more likely to consume low GI rice varieties. Further, an increase in food security significantly decreases the consumption share of low GI rice, while it increases the share of medium GI varieties. The consumption share of low GI rice is largely affected by the ethnic variability. The effects of food security on the likelihood of consuming high GI rice varieties and changing its shares are statistically insignificant. Accordingly, the study concludes that a higher level of food security does not ensure diabetes patients are consuming healthy rice varieties or reducing consumption of unhealthy varieties. Hence policy attention must be directed towards educating people for making healthy dietary choices. Further, the study provides a room for further studies as it reveals considerable ethnic and sectorial differences in making healthy dietary decisions.

Keywords: diabetes, food security, glycemic index, rice consumption

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Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

Procedia PDF Downloads 238

Authors: Alvaro Figueira, Bruno Cabral

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Nowadays, students are used to be assessed through an online platform. Educators have stepped up from a period in which they endured the transition from paper to digital. The use of a diversified set of question types that range from quizzes to open questions is currently common in most university courses. In many courses, today, the evaluation methodology also fosters the students’ online participation in forums, the download, and upload of modified files, or even the participation in group activities. At the same time, new pedagogy theories that promote the active participation of students in the learning process, and the systematic use of problem-based learning, are being adopted using an eLearning system for that purpose. However, although there can be a lot of feedback from these activities to student’s, usually it is restricted to the assessments of online well-defined tasks. In this article, we propose an automatic system that informs students of abnormal deviations of a 'correct' learning path in the course. Our approach is based on the fact that by obtaining this information earlier in the semester, may provide students and educators an opportunity to resolve an eventual problem regarding the student’s current online actions towards the course. Our goal is to prevent situations that have a significant probability to lead to a poor grade and, eventually, to failing. In the major learning management systems (LMS) currently available, the interaction between the students and the system itself is registered in log files in the form of registers that mark beginning of actions performed by the user. Our proposed system uses that logged information to derive new one: the time each student spends on each activity, the time and order of the resources used by the student and, finally, the online resource usage pattern. Then, using the grades assigned to the students in previous years, we built a learning dataset that is used to feed a machine learning meta classifier. The produced classification model is then used to predict the grades a learning path is heading to, in the current year. Not only this approach serves the teacher, but also the student to receive automatic feedback on her current situation, having past years as a perspective. Our system can be applied to online courses that integrate the use of an online platform that stores user actions in a log file, and that has access to other student’s evaluations. The system is based on a data mining process on the log files and on a self-feedback machine learning algorithm that works paired with the Moodle LMS.

Keywords: data mining, e-learning, grade prediction, machine learning, student learning path

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Authors: João Pedro Zanella, Michel J. O. Fagundes

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Introduction: Drug use has been practised by humans universally for millennia, not excluding any population from these habits, however, the rampant drug use is a global concern due to the harm that affects the health of the world population. In this sense, it is observed the reduction of lasting and effective public policies for the resolution, increasing the demand for treatment services. With this comes ibogaine, an alkaloid derived from the root of an African bush (Tabernanthe Iboga), found mostly in Gabon and used widely by the native Bwiti population in rituals, and also other social groups, which demonstrates efficacy against chemical dependence, psychic and emotional disorders, opioid withdrawal was first confirmed by a study in rats done by Michailo Dzoljic and associates in 1988 and again in 1994. Methods: A brief description of the plant, its neurohumoral potential and the effects caused by ingested doses, in a simplified and objective way, will be discussed in the course of this abstract. Results: Ibogaine is not registered or passed by Anvisa, regarding safety and efficacy, and cannot be sold in Brazil. Its illegal trade reaches R$ 5 thousand for a session with the proceeds of the root, and its effect can last up to 72 hours, attributing Iboga's psychoactive effects to the alkaloid called ibogaine. The shrub where Ibogaine is located has pink and yellow flowers, and its fruit produced does not have psychoactive substances, but its root bark contains 6 to 7% indolic alkaloids. Besides extraction from the iboga plant, ibogaine hydrochloride can be semisynthesized from voacangine, another plant alkaloid that acts as a precursor. Its potential has the ability to perform multiple interactions with the neurotransmitter system, which are closely associated with addiction, including nicotinic, opioid and serotoninergic systems. Studies carried out by Edwards found that the doses administered of Iboga should be determined by a health professional when its purpose is to treat individuals for dependence on other drugs. Its use in small doses may cause an increase in sensibility, impaired vision and motor alterations; in moderate quantities, hallucinations, motor and neurological alterations and impaired vision; in high quantities it may cause hallucinations with personal events at a deeper level lasting up to 24 hours or more, followed by motor and visual alterations. Conclusion: The product extracted from the Iboga plant is of great importance in controlling addiction, reducing the need for the use of narcotics by patients, thus gaining a space of extreme importance in the treatment of users of psychoactive substances. It is remarkable the progress of the latest’s research about the usefulness of Ibogaine, and its benefits for certain treatments, even with the restriction of its sale in Brazil. Besides this, Ibogaine has an additional benefit of helping the patient to gain self-control over their destructive behaviours.

Keywords: alkaloids, dependence, Gabon, ibogaine

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Aziz Ghoufi, Ayman Kanaan

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Clean water is ubiquitous from drinking to agriculture and from energy supply to industrial manufacturing. Since the conventional water sources are becoming increasingly rare, the development of new technologies for water supply is crucial to address the world’s clean water needs in the 21st century. Desalination is in many regards the most promising approach to long-term water supply since it potentially delivers an unlimited source of fresh water. Seawater desalination using reverse osmosis (RO) membranes has become over the past decade a standard approach to produce fresh water. While this technology has proven to be efficient, it remains however relatively costly in terms of energy input due to the use of high-pressure pumps resulting of the low water permeation through polymeric RO membranes. Recently, water channels incorporated in lipidic and polymeric membranes were demonstrated to provide a selective water translocation that enables to break permeability- selectivity trade-off. Biomimetic Artificial Water channels (AWCs) are becoming highly attractive systems to achieve a selective transport of water. The first developed AWCs formed from imidazole quartet (I-quartet) embedded in lipidic membranes exhibited an ion selectivity higher than AQPs however associated with a lower water flow performance. Recently it has been conducted pioneer work in this field with the fabrication of the first AWC@Polyamide(PA) composite membrane with outstanding desalination performance. However, the microscopic desalination mechanism in play is still unknown and its understanding represents the shortest way for a long-term conception and design of AWC@PA composite membranes with better performance. In this work we gain an unprecedented fundamental understanding and rationalization of the nanostructuration of the AWC@PA membranes and the microscopic mechanism at the origin of their water transport performance from advanced molecular simulations. Using osmotic molecular dynamics simulations and a non-equilibrium method with water slab control, we demonstrate an increase in porosity near the AWC@PA interfaces, enhancing water transport without compromising the rejection rate. Indeed, the water transport pathways exhibit a single-file structure connected by hydrogen bonds. Finally, by comparing AWC@PA and PA membranes, we show that the difference in water flux aligns well with experimental results, validating the model used.

Keywords: water desalination, biomimetic membranes, molecular simulation, nanochannels

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Authors: Fei Wang, Jie Meng, Qingxiang Meng

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China is rich in straw and by-product resources, whose utilization has always been a hot topic. The objective of this study was to investigate the effect of feeding soybean straw and wine distiller’s grain as a replacement for corn stover on performance of beef cattle. Sixty Simmental×local crossbred bulls averaging 12 months old and 335.7 ± 39.1 kg of body weight (BW) were randomly assigned into four groups (15 animals per group) and allocated to a diet with 40% maize stover (MSD), a diet with 40% wrapping package maize silage (PMSD), a diet with 12% soybean straw plus 28% maize stover (SSD) and a diet with 12% wine distiller’s grain plus 28% maize stover (WDD). Bulls were fed ad libitum an TMR consisting of 36.0% maize, 12.5% of DDGS, 5.0% of cottonseed meal, 4.0% of soybean meal and 40.0% of by-product as described above. Treatment period lasted for 22 weeks, consisting of 1 week of dietary adaptation. The results showed that dry matter intake (DMI) was significantly higher (P < 0.01) for PMSD group than MSD and SSD groups during 0-7 week and 8-14week, and PMSD and WDD groups had higher (P < 0.05) DMI values than MSD and SSD groups during the whole period. Average daily gain (ADG) values were 1.56, 1.72, 1.68 and 1.58 kg for MSD, PMSD, SSD and WDD groups respectively, although the differences were not significant (P > 0.05). The value of blood sugar concentration was significantly higher (P < 0.01) for MSD group than WDD group, and the blood urea nitrogen concentration of SSD group was lower (P < 0.05) than MSD and WDD groups. No significant difference (P > 0.05) of serum total cholesterol, triglycerides or total protein content was observed among the different groups. Ten bulls with similar body weight were selected at the end of feeding trial and slaughtered for measurement of slaughtering performance, carcass quality and meat chemical composition. SSD group had significantly lower (P < 0.05) shear force value and cooking loss than MSD and PMSD groups. The pH values of MSD and SSD groups were lower (P < 0.05) than PMSD and WDD groups. WDD group had a higher fat color brightness (L*) value than PMSD and SSD groups. There were no significant differences in dressing percentage, meat percentage, top grade meat weight, ribeye area, marbling score, meat color and meat chemical compositions among different dietary treatments. Based on these results, the packed maize stover silage showed a potential of improving the average daily gain and feed intake of beef cattle. Soybean straw had a significant effect on improving the tenderness and reducing cooking loss of beef. In general, soybean straw and packed maize stover silage would be beneficial to nitrogen deposition and showed a potential to substitute maize stover in beef cattle diets.

Keywords: beef cattle, by-products, carcass quality, growth performance

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Authors: Thomas Arink, Isam Janajreh

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The petroleum industry generates significant amounts of waste in the form of drill cuttings, contaminated soil and oily sludge. Drill cuttings are a product of the off-shore drilling rigs, containing wet soil and total petroleum hydrocarbons (TPH). Contaminated soil comes from different on-shore sites and also contains TPH. The oily sludge is mainly residue or tank bottom sludge from storage tanks. The two main treatment methods currently used are incineration and thermal desorption (TD). Thermal desorption is a method where the waste material is heated to 450ºC in an anaerobic environment to release volatiles, the condensed volatiles can be used as a liquid fuel. For the thermal desorption unit dry contaminated soil is mixed with moist drill cuttings to generate a suitable mixture. By thermo gravimetric analysis (TGA) of the TD feedstock it was found that less than 50% of the TPH are released, the discharged material is stored in landfill. This study proposes co-gasification of petroleum waste with waste tires as an alternative to thermal desorption. Co-gasification with a high-calorific material is necessary since the petroleum waste consists of more than 60 wt% ash (soil/sand), causing its calorific value to be too low for gasification. Since the gasification process occurs at 900ºC and higher, close to 100% of the TPH can be released, according to the TGA. This work consists of three parts: 1. a mathematical gasification model, 2. a reactive flow CFD model and 3. experimental work on a drop tube reactor. Extensive material characterization was done by means of proximate analysis (TGA), ultimate analysis (CHNOS flash analysis) and calorific value measurements (Bomb calorimeter) for the input parameters of the mathematical and CFD model. The mathematical model is a zero dimensional model based on Gibbs energy minimization together with Lagrange multiplier; it is used to find the product species composition (molar fractions of CO, H2, CH4 etc.) for different tire/petroleum feedstock mixtures and equivalence ratios. The results of the mathematical model act as a reference for the CFD model of the drop-tube reactor. With the CFD model the efficiency and product species composition can be predicted for different mixtures and particle sizes. Finally both models are verified by experiments on a drop tube reactor (1540 mm long, 66 mm inner diameter, 1400 K maximum temperature).

Keywords: computational fluid dynamics (CFD), drop tube reactor, gasification, Gibbs energy minimization, petroleum waste, waste tires

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Authors: Lindsay Foreman

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Introduction: Goals have become synonymous with the quest for the good life and the pursuit of happiness, with coaching and positive psychology gaining popularity as an approach in recent decades. And yet mental health is on the rise and the leading cause of disability, wellbeing is on the decline, stress is leading to 50-60% of workday absences and the need for action is indisputable and urgent. Purpose: The purpose of this study is to better understand two things we cannot see, but that play the most significant role in these outcomes - what we think and how we feel. With many working on the assumption that positive thinking and an optimistic outlook are necessary or valuable components of goal pursuit, this study uncovers the reality of the ‘inner-game’ from the coachee's perspective. Method: With a mixed methods design using a Q Method study of subjectivity to ‘make the unseen seen’. First, a wide-ranging universe of subjective thoughts and feelings experienced during goal pursuit are explored. These are generated from literature and a Qualtrics survey to create a Q-Set of 40 statements. Then 19 participants in professional and organisational settings offer their perspectives on these 40 Q-Set statements. Each rank them in a semi-forced distribution from ‘most like me’ to ‘least like me’ using Q-Sort software. From these individual perspectives, clusters of perspectives are identified using factor analysis and four distinct viewpoints have emerged. Findings: These Goal Pursuit Viewpoints offer insight into the states and self-talk experienced by coachees and may not reflect the assumption of positive thinking associated with achieving goals. The four Viewpoints are 1) the Optimistic View, 2) the Realistic View 3) The Dreamer View and 4) The Conflicted View. With only a quarter of the Dreamer View, and a third of the Optimistic view going on to achieve their goals, these assumptions need review. And with all the Realistic Views going on to achieve their goals, the role of self-doubt, overwhelm and anxiousness in goal achievement cannot be overlooked. Contribution: This study offers greater insight and understanding of people's inner experiences as they pursue goals and highlights the necessary and normal negative states associated with goal achievement. It also offers a practical tool of the Q-set statements to help coaches and coachees explore the current state and help navigate the journey towards goal achievement. It calls into question whether goals should always be part of coaching and if values, identity, and purpose may play a greater role than goals.

Keywords: coaching, goals, positive psychology, mindset, leadership, mental health, beliefs, cognition, emotional intelligence

Procedia PDF Downloads 113

Authors: Jacques M. Berner, Monja Gerber, Gillian L. Maggs-Kolling, Stuart J. Piketh

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The enigmatic melon species, Acanthosicyos horridus Welw. ex Hook. f., locally known as !nara, is endemic to the hyper-arid Namib Desert, where it thrives in sandy dune areas and dry river banks. The Namib Desert is characterized by extreme weather conditions which include high temperatures, very low rainfall, and extremely dry air. Plant and animals that have made the Namib Dessert their home are dependent on non-rainfall water inputs, like fog, dew and water vapor, for survival. Fog is believed to be the most important non-rainfall water input for most of the coastal Namib Desert and is a life line to many Namib plants and animals. It is commonly assumed that the !nara plant is adapted and dependent upon coastal fog events. The !nara plant shares many comparable adaptive features with other organisms that are known to exploit fog as a source of moisture. These include groove-like structures on the stems and the cone-like structures of thorns. These structures are believed to be the driving forces behind directional water flow that allow plants to take advantage of fog events. The !nara-fog interaction was investigated in this study to determine the dependence of !nara on these fog events, as it would illustrate strategies to benefit from non-rainfall water inputs. The direct water uptake capacity of !nara shoots was investigated through absorption tests. Furthermore, the movement and behavior of fluorescent water droplets on a !nara stem were investigated through time-lapse macrophotography. The shoot water potential was measured to investigate the effect of fog on the water status of !nara stems. These tests were used to determine whether the morphology of !nara has evolved to exploit fog as a non-rainfall water input and whether the !nara plant has adapted physiologically in response to fog. Chlorophyll a fluorescence was used to compare the photochemical efficiency of !nara plants on days with fog events to that on non-foggy days. The results indicate that !nara plants do have the ability to take advantage of fog events as commonly believed. However, the !nara plant did not exhibit visible signs of drought stress and this, together with the strong shoot water potential, indicates that these plants are reliant on permanent underground water sources. Chlorophyll a fluorescence data indicated that temperature stress and wind were some of the main abiotic factors influencing the plants’ overall vitality.

Keywords: Acanthosicyos horridus, chlorophyll a fluorescence, fog, foliar absorption, !nara

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman

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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: categorical data, log linear modeling, neural network, shifting cultivation

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Authors: Lucas Derks, Christine Beenhakker, Michiel Brandt, Gert Arts, Ruud van Langeveld

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Background: The method Depression in Awareness Space (DAS) is a psychotherapeutic intervention technique based on the principles of spatial cognition and imagination therapy with spatial components. The basic assumptions are: mental space is the primary organizing principle in the mind, and all psychological issues can be treated by first locating and by next relocating the conceptualizations involved. The most clinical experience was gathered over the last 20 years in the area of social issues (with the social panorama model). The latter work led to the conclusion that a mental object (image) gains emotional impact when it is placed more central, closer and higher in the visual field – and vice versa. Changing the locations of mental objects in space thus alters the (socio-) emotional meaning of the relationships. The experience of depression seems always associated with darkness. Psychologists tend to see the link between depression and darkness as a metaphor. However, clinical practice hints to the existence of more literal forms of darkness. Aims: The aim of the method Depression in Awareness Space is to reduce the distress of clients with depression in the clinical counseling practice, as a reliable alternative method of psychological therapy for the treatment of depression. The method Depression in Awareness Space aims at making dark areas smaller, lighter and more transparent in order to identify the problem or the cause of the depression which lies behind the darkness. It was hypothesized that the darkness is a subjective side-effect of the neurological process of repression. After reducing the dark clouds the real problem behind the depression becomes more visible, allowing the client to work on it and in that way reduce their feelings of depression. This makes repression of the issue obsolete. Results: Clients could easily get into their 'sadness' when asked to do so and finding the location of the dark zones proved pretty easy as well. In a recent pilot study with five participants with mild depressive symptoms (measured on two different scales and tested against an untreated control group with similar symptoms), the first results were also very promising. If the mental spatial approach to depression can be proven to be really effective, this would be very good news. The Society of Mental Space Psychology is now looking for sponsoring of an up scaled experiment. Conclusions: For spatial cognition and the research into spatial psychological phenomena, the discovery of dark areas can be a step forward. Beside out of pure scientific interest, it is great to know that this discovery has a clinical implication: when darkness can be connected to depression. Also, darkness seems to be more than metaphorical expression. Progress can be monitored over measurement tools that quantify the level of depressive symptoms and by reviewing the areas of darkness.

Keywords: depression, spatial cognition, spatial imagery, social panorama

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Authors: Nilda Tri Putri, Muhammad Taufik

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Tools and agricultural machinery (Alsintan) is a tool used in agribusiness activities. Alsintan used to change the traditional farming systems generally use manual equipment into modern agriculture with mechanization. CV Nugraha Chakti Consultant make an action plan for industrial development Alsintan West Sumatra in 2012 to develop medium industries of Alsintan become a major industry of Alsintan, one of efforts made is increase the production capacity of the industry Alsintan. Production capacity for superior products as hydrotiller and threshers set each for 2.000 units per year. CV Citra Dragon as one of the medium industry alsintan in West Sumatra has a plan to relocate the existing plant to meet growing consumer demand each year. Increased production capacity and plant relocation plan has led to a change in the layout; therefore need to design the layout of the plant facility CV Citra Dragon. First step the to design of plant layout is design the layout of the production floor. The design of the production floor layout is done by applying group technology layout. The initial step is to do a machine grouping and part family using the Average Linkage Clustering (ALC) and Rank Order Clustering (ROC). Furthermore done independent work station design and layout design using the Modified Spanning Tree (MST). Alternative selection layout is done to select the best production floor layout between ALC and ROC cell grouping. Furthermore, to design the layout of warehouses, offices and other production support facilities. Activity Relationship Chart methods used to organize the placement of factory facilities has been designed. After structuring plan facilities, calculated cost manufacturing facility plant establishment. Type of layout is used on the production floor layout technology group. The production floor is composed of four cell machinery, assembly area and painting area. The total distance of the displacement of material in a single production amounted to 1120.16 m which means need 18,7minutes of transportation time for one time production. Alsintan Factory has designed a circular flow pattern with 11 facilities. The facilities were designed consisting of 10 rooms and 1 parking space. The measure of factory building is 84 m x 52 m.

Keywords: Average Linkage Clustering (ALC), Rank Order Clustering (ROC), Modified Spanning Tree (MST), Activity Relationship Chart (ARC)

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Authors: Bing Zhang, Jingyi Zhang, Mudan Chen

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Fibre-reinforced polymer (FRP) composites have been extensively utilised in various industries due to their high specific strength, e.g., aerospace, renewable energy, automotive, and marine. However, they have relatively low electrical conductivity than metals, especially in the out-of-plane direction. Conductive metal strips or meshes are typically employed to protect composites when designing lightweight structures that may be subjected to lightning strikes, such as composite wings. Unfortunately, this approach downplays the lightweight advantages of FRP composites, thereby limiting their potential applications. Extensive studies have been undertaken to improve the electrical conductivity of FRP composites. The authors are amongst the pioneers who use through-thickness reinforcement (TTR) to tailor the electrical conductivity of composites. Compared to the conventional approaches using conductive fillers, the through-thickness reinforcement approach has been proven to be able to offer a much larger improvement to the through-thickness conductivity of composites. In this study, an advanced high-fidelity numerical modelling strategy is presented to investigate the effects of through-thickness reinforcement on both the in-plane and out-of-plane electrical conductivities of FRP composites. The critical micro-structural features of through-thickness reinforced composites incorporated in the modelling framework are 1) the fibre waviness formed due to TTR insertion; 2) the resin-rich pockets formed due to resin flow in the curing process following TTR insertion; 3) the fibre crimp, i.e., fibre distortion in the thickness direction of composites caused by TTR insertion forces. In addition, each interlaminar interface is described separately. An IMA/M21 composite laminate with a quasi-isotropic stacking sequence is employed to calibrate and verify the modelling framework. The modelling results agree well with experimental measurements for bothering in-plane and out-plane conductivities. It has been found that the presence of conductive TTR can increase the out-of-plane conductivity by around one order, but there is less improvement in the in-plane conductivity, even at the TTR areal density of 0.1%. This numerical tool provides valuable references as a design tool for through-thickness reinforced composites when exploring their electrical applications. Parametric studies are undertaken using the numerical tool to investigate critical parameters that affect the electrical conductivities of composites, including TTR material, TTR areal density, stacking sequence, and interlaminar conductivity. Suggestions regarding the design of electrical through-thickness reinforced composites are derived from the numerical modelling campaign.

Keywords: composite structures, design, electrical conductivity, numerical modelling, through-thickness reinforcement

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Authors: Katherine Del Carmen Camacho Zorogastua, Victor Hugo Gallo Ramos, Jhon Walter Gomez Lora

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Marine hydrocarbon exploration (oil and natural gas) activities are developed using 2D, 3D and 4D seismic prospecting techniques where sound waves are directed from a seismic vessel emitted every few seconds depending on the variety of air compressors, which cross the layers of rock at the bottom of the sea and are reflected to the surface of the water. Hydrophones receive and record the reflected energy signals for cross-sectional mapping of the lithological profile in order to identify possible areas where hydrocarbon deposits can be formed. However, they produce several significant negative environmental impacts on the marine ecosystem and in the social and economic sectors. Therefore, the objective of the research is to publicize the negative impacts and environmental measures that must be carried out during the development of these activities to prevent and mitigate water quality, the population involved (fishermen) and the marine biota (e.g., Cetaceans, fish) that are the most vulnerable. The research contains technical environmental aspects based on bibliographic sources of environmental studies approved by the Peruvian authority, research articles, undergraduate and postgraduate theses, books, guides, and manuals from Spain, Australia, Canada, Brazil, and Mexico. It describes the negative impacts on the environment and population (fishing sector), environmental prevention, mitigation, recovery and compensation measures that must be properly implemented and the cases of global sea species stranding, for which international experiences from Spain, Madagascar, Mexico, Ecuador, Uruguay, and Peru were referenced. Negative impacts on marine fauna, seawater quality, and the socioeconomic sector (fishermen) were identified. Omission or inadequate biological monitoring in mammals could alter their ability to communicate, feed, and displacement resulting in their stranding and death. In fish, they cause deadly damage to physical-physiological type and in their behavior. Inadequate wastewater treatment and waste management could increase the organic load and oily waste on seawater quality in violation of marine flora and fauna. The possible estrangement of marine resources (fish) affects the economic sector as they carry out their fishing activity for consumption or sale. Finally, it is concluded from the experiences gathered from Spain, Madagascar, Mexico, Ecuador, Uruguay, and Peru that there is a cause and effect relationship between the inadequate development of seismic exploration activities (cause) and marine species strandings (effect) since over the years, stranded or dead marine mammals have been detected on the shores of the sea in areas of seismic acquisition of hydrocarbons. In this regard, it is recommended to establish technical procedures, guidelines, and protocols for the monitoring of marine species in order to contribute to the conservation of hydrobiological resources.

Keywords: 3D seismic prospecting, cetaceans, significant environmental impacts, prevention, mitigation, recovery, environmental compensation

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Authors: Antonio Casero Martínez, María de Lluch Rayo Llinas

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This work is part of an investigation into the relationship between romantic love and self-esteem in college students, performed by the students of matter "methods and techniques of social research", of the Master Gender at the University of Balearic Islands, during 2014-2015. In particular, we have investigated the relationships that may exist between self-esteem, gender and field of study. They are known as gender differences in self-esteem, and the relationship between gender and branch of study observed annually by the distribution of enrolment in universities. Therefore, in this part of the study, we focused the spotlight on the differences in self-esteem between the sexes through the various branches of study. The study sample consists of 726 individuals (304 men and 422 women) from 30 undergraduate degrees that the University of the Balearic Islands offers on its campus in 2014-2015, academic year. The average age of men was 21.9 years and 21.7 years for women. The sampling procedure used was random sampling stratified by degree, simple affixation, giving a sampling error of 3.6% for the whole sample, with a confidence level of 95% under the most unfavorable situation (p = q). The Spanish translation of the Rosenberg Self-Esteen Scale (RSE), by Atienza, Moreno and Balaguer was applied. The psychometric properties of translation reach a test-retest reliability of 0.80 and an internal consistency between 0.76 and 0.87. In this paper we have obtained an internal consistency of 0.82. The results confirm the expected differences in self-esteem by gender, although not in all branches of study. Mean levels of self-esteem in women are lower in all branches of study, reaching statistical significance in the field of Science, Social Sciences and Law, and Engineering and Architecture. However, analysed the variability of self-esteem by the branch of study within each gender, the results show independence in the case of men, whereas in the case of women find statistically significant differences, arising from lower self-esteem of Arts and Humanities students vs. the Social and legal Sciences students. These findings confirm the results of numerous investigations in which the levels of female self-esteem appears always below the male, suggesting that perhaps we should consider separately the two populations rather than continually emphasize the difference. The branch of study, for its part has not appeared as an explanatory factor of relevance, beyond detected the largest absolute difference between gender in the technical branch, one in which women are historically a minority, ergo, are no disciplinary or academic characteristics which would explain the differences, but the differentiated social context that occurs within it.

Keywords: study branch, gender, self-esteem, applied psychology

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Authors: Barbara Farinon, Maurizio E. Picarella, Lorenzo Mancini, Andrea Mazzucato

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Italy is notoriously a secondary center of diversification for cultivated tomatoes (Solanum lycopersicum L.). The study of phenotypic and genetic diversity in landrace collections is important for germplasm conservation and biodiversity protection. Here, we set up to study the germplasm collected in the region of Lazio in Central Italy with a focus on the distinctiveness among landraces and the attribution of membership to unnamed accessions. Our regional collection included 30 accessions belonging to six different locally recognized landraces and 21 unnamed accessions. All accessions were gathered in Lazio and belonged to the collection held at the Regional Agency for the Development and Innovation of Agriculture in Lazio (ARSIAL, in the application of the Regional Act n. 15/2000, funded by Lazio Rural Development Plan 2014 – 2020 Agro-environmental Measure, Action 10.2.1) and at the University of Tuscia. We included 13 control genotypes as references. The collection showed wide phenotypic variability for several traits, such as fruit weight (range 14-277 g), locule number (2-12), shape index (0.54-2.65), yield (0.24-3.08 kg/plant), and soluble solids (3.4-7.5 °B). A few landraces showed uncommon phenotypes, such as potato leaf, colorless fruit epidermis, or delayed ripening. Multivariate analysis of 25 cardinal phenotypic variables grouped the named varieties and allowed to assign of some of the unnamed to recognized groups. A case study for distinctiveness is presented for the flattened-ribbed types that presented overlapping distribution according to the phenotypic data. Molecular markers retrieved by previous studies revealed differences compared to the phenotyping clustering, indicating that the named varieties “Scatolone di Bolsena” and “Pantano Romanesco” belong to the Marmande group, together with the reference landrace from Tuscany “Costoluto Fiorentino”. Differently, the landrace “Spagnoletta di Formia e Gaeta” was clearly distinct from the former at the molecular level. Therefore, a genotypic analysis of the analyzed collection appears needed to better define the molecular distinctiveness among the flattened-ribbed accessions, as well as to properly attribute the membership group of the unnamed accessions.

Keywords: distinctiveness, flattened-ribbed fruits, regional landraces, tomato

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Authors: Laura Simmer, Maria Kalt, Oliver Schauer

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Freight transport is growing fast, but many vehicles are empty or just partially loaded. The vision and concepts of the Physical Internet (PI) proposes to eliminate these inefficiencies. Aiming for a radical sustainability improvement, the PI – inspired by the Digital Internet – is a hyperconnected global logistic system, enabling seamless asset sharing and flow consolidation. The implementation of a PI in its full expression will be a huge challenge: the industry needs innovation and implementation support including change management approaches, awareness creation and good practices diffusion, legislative actions to remove antitrust and international commerce barriers, standardization and public incentives policies. In order to take a step closer to this future the project ‘Atropine - Fast Track to the Physical Internet’ funded under the Strategic Economic and Research Program ‘Innovative Upper Austria 2020’ was set up. The two-year research project unites several research partners in this field, but also industrial partners and logistics service providers. With Atropine, the consortium wants to actively shape the mobility landscape in Upper Austria and make an innovative contribution to an energy-efficient, environmentally sound and sustainable development in the transport area. This paper should, on the one hand, clarify the questions what the project Atropine is about and, on the other hand, how a proof of concept will be reached. Awareness building plays an important role in the project as the PI requires a reorganization of the supply chain and the design of completely new forms of inter-company co-operation. New business models have to be developed and should be verified by simulation. After the simulation process one of these business models will be chosen and tested in real life with the partner companies. The developed results - simulation model and demonstrator - are used to determine how the concept of the PI can be applied in Upper Austria. Atropine shall pave the way for a full-scale development of the PI vision in the next few decades and provide the basis for pushing the industry toward a new level of co-operation with more shared resources and increased standardization.

Keywords: Atropine, inter-company co-operation, Physical Internet, shared resources, sustainable logistics

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Authors: Arzu K. Harmanci Seren, Burcu Alacam, Serap Altuntas, Ulku Baykal

Abstract:

Organizational justice has been evaluated as a concept related to rules developed with regards to distributing gains and making decisions of distribution such as duty, goods, service, reward, punishment, fee, organizational position, opportunity or role among those working in that organization, and to social norms on which these rules are based. Studies of organizational justice are crucial for analyzing the organizational life. It is considered that organization justice will be positively influential upon organizational behaviours such as employees’ level of work satisfaction, their performance, and behaviours of organization citizenship, management by values perception, tendency towards cooperation, and towards quitting their jobs. However, when the literature related to health and nurse management is examined, authors could not reach enough findings related to the influence of nurses’ perception of organizational justice upon the perception of management and the intention of quitting in accordance with the values. For that reason, this study has been carried out with the purpose of determining the influence of nurses’ perception of organizational justice upon the perception of management and the intention of quitting in accordance with the values. The study has been carried out with 176 nurses working in a university hospital in Istanbul and a private hospital who accepted to take part in the study, and it is definitive and relation-seeking. Before the data has been collected, ethics committee approval and institutional permissions have been taken, Organizational Justice Scale, Management by Values, Intention to Leave Scale with a questionnaire including 8 questions that aims at defining the personal and professional characteristics of the nurses have been used as a means of data collection. The data collected between 1 May and 20 June 2016 have been evaluated by the researchers in a computer via definitive, relation-seeking and psychometric statistic. As a result of the study, it has been determined that most of the nurses are working in a university hospital (70.5%), that they are 30 and over (49.4%), women (91.5%), single (52.8%) and have a Bachelor’s Degree (48.3%), working in a surgery unit (17.6), have 5 year or less institutional experience (44.9%), 11 year or more professional experience. Cronbach alpha values of the scales used in this study are .94, .95 and .56. Nurses’ average scores of Organizational Justice Scale is M= 3.35±.96, Management by Values Scale is M=3.30±.74, Intention to Leave Scale is M=8.36±3.14. As a result of the analysis carried out in order to determine the influence of nurses’ perception of organizational justice upon the perception of management and the intention of quitting in accordance with the values, it has been pointed out that the Perception of Organizational Justice influenced the perception of Management by Values positively, Intention to Leave negatively.

Keywords: intention to leave, management by values, nursing, organizational justice

Procedia PDF Downloads 267

Authors: Takaaki Miyabe, Hideharu Takahashi, Hiroshige Kikura

Abstract:

The Government of Japan and Tokyo Electric Power Company Holdings, Incorporated (TEPCO) are struggling with the decommissioning of Fukushima Daiichi Nuclear Power Plants, especially fuel debris retrieval. In fuel debris retrieval, amount of fuel debris, location, characteristics, and distribution information are important. Recently, a survey was conducted using a robot with a small camera. Progress report in remote robot and camera research has speculated that fuel debris is present both at the bottom of the Pressure Containment Vessel (PCV) and inside the Reactor Pressure Vessel (RPV). The investigation found a 'tie plate' at the bottom of the containment, this is handles on the fuel rod. As a result, it is assumed that a hole large enough to allow the tie plate to fall is opened at the bottom of the reactor pressure vessel. Therefore, exploring the existence of holes that lead to inside the RCV is also an issue. Investigations of the lower part of the RPV are currently underway, but no investigations have been made inside or above the PCV. Therefore, a survey must be conducted for future fuel debris retrieval. The environment inside of the RPV cannot be imagined due to the effect of the melted fuel. To do this, we need a way to accurately check the internal situation. What we propose here is the adaptation of a technology called 'Structure from Motion' that reconstructs a 3D image from multiple photos taken by a single camera. The plan is to mount a monocular camera on the tip of long-arm robot, reach it to the upper part of the PCV, and to taking video. Now, we are making long-arm robot that has long-arm and used at high level radiation environment. However, the environment above the pressure vessel is not known exactly. Also, fog may be generated by the cooling water of fuel debris, and the radiation level in the environment may be high. Since camera alone cannot provide sufficient sensing in these environments, we will further propose using ultrasonic measurement technology in addition to cameras. Ultrasonic sensor can be resistant to environmental changes such as fog, and environments with high radiation dose. these systems can be used for a long time. The purpose is to develop a system adapted to the inside of the containment vessel by combining a camera and an ultrasound. Therefore, in this research, we performed a basic experiment on 3D image reconstruction using a camera and ultrasound. In this report, we select the good and bad condition of each sensing, and propose the reconstruction and detection method. The results revealed the strengths and weaknesses of each approach.

Keywords: camera, image processing, reconstruction, ultrasound

Procedia PDF Downloads 104