Search results for: process block

Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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Authors: M. Elham Ghabouli

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Intermediate cities which also called medium size cities have an important role in the process of globalization. It is argued that, in some cases this type of cities may be depopulated or in otherwise may be transformed as the periphery of metropolitans so that the personal identity of the city and its local cultural heritage could suffer from its neighbor metropolitan. Over the last decades, the role of tourism in development process and the cultural heritage is increased. The effect of tourism in socio-economic growth makes motivation for study on tourism development in regional and urban planning process. Tourism potentially has a specific role in promoting sustainable development especially by its economic and socio-cultural effects. The positive role of tourism in local development and in cultural heritage should be empowered by urban and regional planning. Damavand is an intermediate city located in Tehran province, Iran. Considering its local specific characteristic like social structure, antiquities and natural monuments made a suitable case study for studying on urban tourism planning method. Focusing on recognition of historical and cultural heritage of Damavand, this paper tried to peruse cultural-historical heritage protecting issue through “base plan methodology” which is introduced as a first step of urban planning for intermediate cities.

Keywords: urban planning, tourism, cultural heritage, intermediate cities

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Authors: Flavio Campos

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This paper describes an implementation of a STEM curriculum program using robotics as a technological resource at a private school in Brazil. Emphasized the pedagogic and didactic aspects and brings a discussion about STEM curriculum and the perspective of using robotics and the relation between curriculum, science and technologies into the learning process. The results indicate that STEM curriculum integration with robotics as a technological resource in K-12 students learning process has complex aspects, such as relation between time/space, the development of educators and the relation between robotics and other subjects. Therefore, the comprehension of these aspects could indicate some steps that we should consider when integrating STEM basis and robotics into curriculum, which can improve education for science and technology significantly.

Keywords: STEM curriculum, educational robotics, constructionist approach, education and technology

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Authors: Mekdes Lulu

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This study assessed the effect of the interactions of biochar (BC), farmyard manure (FYM) and lime on soil chemical properties and on different wheat attributes in Southern Ethiopia. The experimental design was a randomized complete block in three replications. The site significantly (p ≤ 0.05) influenced soil and wheat attributes. Biochar showed a large significant effect (p ≤ 0.05) on soil organic carbon, cation exchange capacity, and exchangeable potassium (K), while lime showed a substantially significant (p ≤ 0.05) effect on exchangeable Calcium (Ca) and acidity. Farmyard manure (10 tonnes ha−1 ) had a significant effect on soil total nitrogen (TN). Biochar and lime showed a large significant effect on soil pH and available phosphorus (P) depending on the site. All amendments showed a significant (p ≤ 0.001) effect on most wheat attributes, but the highest effect was from BC. Biochar produced highly significant (p ≤ 0.001) effects on plant height, total number of tillers and productive tillers, number of seeds per spike, aboveground biomass, grain yield, and P and K content in wheat grain and straw. We accredited the greater effect of BC on wheat attributes to its influence on soil chemical properties. We recommend long-term studies on the impact of BC alone or in combination with FYM on acid soil types.

Keywords: grain yield, soil amendments, soil nutrients, soil organic carbon, Triticum aestivum

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Authors: Ermelinda Bloise, Giuseppe Mele

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In recent years, Cashew Nut Shell Liquid (CNSL) has received great attention from researchers because it is an abundant waste material from the agri-food industry that fits perfectly into the idea of reusing waste from renewable resources for the production of new functional materials. The different components of this waste showed a certain chemical versatility and, above all, various biological activities. Take advantage of their surface-active capacity in particular conditions, various amphiphilic nanostructures have been prepared through sustainable chemical processes using cardanol (CA) and anacardic acid (AA) as two main components of the CNSL. In-batch solvent-free method has been developed to obtain new versatile green nanovesicles capable of effectively incorporating and stabilizing both hydrophobic and hydrophilic bioactive molecules. Furthermore, these nanosystems have shown antioxidant and cytotoxic properties and, in vitroinvestigations, established that they efficiently taken-up some human cells. With the idea of meeting the principles of green chemistry, even more, some improvements of the synthetic procedure have been implemented in terms of milder temperature and pH conditions, producing one-component nanovesicles, in which the AA and CA-derivatives are the sole building block of the green nanosystems. Finally, a new experimental approach has been carried out by a microfluidic route, with the advantage to operate at continuous flows, with a reduced amount of reagents, waste, and at lower temperatures, ensuring the achievement of size-monodisperse amphiphilic nanostructures that do not need further purification steps.

Keywords: bioactive nanosystems, bio-based renewables, cashew oil, green nanoformulations

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Authors: Amit Kumar, Rajdeep Chakrabarty, Ganesh Gupta

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This paper illustrates the detailed accreditation process of Accreditation Board of Engineering and Technology (ABET) for accrediting engineering and Technology programs. ABET is a non-governmental agency that accredits engineering and technology, applied and natural sciences, and computing sciences programs. ABET was founded on 10th May 1932 and was founded by Institute of Electrical and Electronics Engineering. International industries accept ABET accredited institutes having the highest standards in their academic programs. In this accreditation, there are eight criteria in general; criterion 1 describes the student outcome evaluations, criteria 2 measures the program's educational objectives, criteria 3 is the student outcome calculated from the marks obtained by students, criteria 4 establishes continuous improvement, criteria 5 focus on curriculum of the institute, criteria 6 is about faculties of this institute, criteria 7 measures the facilities provided by the institute and finally, criteria 8 focus on institutional support towards staff of the institute. In this paper, we focused on the calculative part of each criterion with equations and suitable examples, the files and documentation required for each criterion, and the total workflow of the process. The references and the values used to illustrate the calculations are all taken from the samples provided at ABET's official website. In the final section, we also discuss the criterion-wise score weightage followed by evaluation with timeframe and deadlines.

Keywords: Engineering Accreditation Committee, Computing Accreditation Committee, performance indicator, Program Educational Objective, ABET Criterion 1 to 7, IEEE, National Board of Accreditation, MOOCS, Board of Studies, stakeholders, course objective, program outcome, articulation, attainment, CO-PO mapping, CO-PO-SO mapping, PDCA cycle, degree certificates, course files, course catalogue

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Authors: Hyeon-Kyo Lim, Hyunjung Kim, Kune-Woo Lee

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Decommissioning process of nuclear facilities can be said to consist of a sequence of problem solving activities, partly because there may exist working environments contaminated by radiological exposure, and partly because there may also exist industrial hazards such as fire, explosions, toxic materials, and electrical and physical hazards. As for an individual hazard factor, risk assessment techniques are getting known to industrial workers with advance of safety technology, but the way how to integrate those results is not. Furthermore, there are few workers who experienced decommissioning operations a lot in the past. Therefore, not a few countries in the world have been trying to develop appropriate counter techniques in order to guarantee safety and efficiency of the process. In spite of that, there still exists neither domestic nor international standard since nuclear facilities are too diverse and unique. In the consequence, it is quite inevitable to imagine and assess the whole risk in the situation anticipated one by one. This paper aimed to find out an appropriate technique to integrate individual risk assessment results from the viewpoint of experts. Thus, on one hand the whole risk assessment activity for decommissioning operations was modeled as a sequence of individual risk assessment steps, and on the other, a hierarchical risk structure was developed. Then, risk assessment procedure that can elicit individual hazard factors one by one were introduced with reference to the standard operation procedure (SOP) and hierarchical task analysis (HTA). With an assumption of quantification and normalization of individual risks, a technique to estimate relative weight factors was tried by using the conventional Analytic Hierarchical Process (AHP) and its result was reviewed with reference to judgment of experts. Besides, taking the ambiguity of human judgment into consideration, debates based upon fuzzy inference was added with a mathematical case study.

Keywords: decommissioning, risk assessment, analytic hierarchical process (AHP), fuzzy inference

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Authors: M. A. Mulatu, L. C. Chang, Y. S. Han

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Energy harvesting tags with cooperative communication capabilities are emerging as possible infrastructure for internet of things (IoT) applications. This paper studies about the \ cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of EnHANT-equipped objects to communicate with the destination either directly or by cooperating with neighboring objects. We formulate the the problem as a Markov decision process (MDP) under synchronised On/Off keying (S-OOK) pulse modulation format. The simulation results are provided to show the the performance of the cooperative transmission policy and compared against the greedy and conservative policies of single-link transmission.

Keywords: cooperative communication, transmission strategy, energy harvesting, Markov decision process, value iteration

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Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: Evgeni Baratashvili, Nino Pailodze, Ana Bolkvadze, Giorgi Sulashvili

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At the present stage in our country intensifies cooperation with different business cultures, actively developing the process of implementation of Georgia in the global business system that requires us to develop a specific concept, including in the field of management. With the entry of Georgia into the international community, exchange of experience will only intensify. It is clear that the achievement of goals such as the doubling of the National Product increase the competitiveness of Georgian enterprises can’t be recorded without foreign management experience. On the other hand, knowledge of the areas of comparative management can be used in the process of choosing the path of socio-economic development of Georgia.

Keywords: business cultures, comparative management, corporate culture, Georgian business, Anglo-Saxon model, Georgian civilization, anti-capitalist mentality, culture management

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Authors: Hyunsun Lee, Yi Zhu

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Wireless ad-hoc network is a decentralized type of temporary machine-to-machine connection that is spontaneous or impromptu so that it does not rely on any fixed infrastructure and centralized administration. As unmanned aerial vehicles (UAVs), also called drones, have recently become more accessible and widely utilized in military and civilian domains such as surveillance, search and detection missions, traffic monitoring, remote filming, product delivery, to name a few. The communication between these UAVs become possible and materialized through Flying Ad-hoc Networks (FANETs). However, due to the high mobility of UAVs that may cause different types of transmission interference, it is vital to design robust routing protocols for FANETs. In this talk, the multicast routing method based on a modified stochastic branching process is proposed. The stochastic branching process is often used to describe an early stage of an infectious disease outbreak, and the reproductive number in the process is used to classify the outbreak into a major or minor outbreak. The reproductive number to regulate the local transmission rate is adapted and modified for flying ad-hoc network communication. The performance of the proposed routing method is compared with other well-known methods such as flooding method and gossip method based on three measures; average reachability, average node usage and average branching factor. The proposed routing method achieves average reachability very closer to flooding method, average node usage closer to gossip method, and outstanding average branching factor among methods. It can be concluded that the proposed multicast routing scheme is more efficient than well-known routing schemes such as flooding and gossip while it maintains high performance.

Keywords: Flying Ad-hoc Networks, Multicast Routing, Stochastic Branching Process, Unmanned Aerial Vehicles

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Authors: Abigaba Sophia

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Artificial intelligence (AI) has transformed the education sector by revolutionizing educational frameworks by providing new opportunities and innovative advanced platforms for language translation during the teaching and learning process. In today's education sector, the primary key to scholarly communication is language; therefore, translation between different languages becomes vital in the process of communication. KIU-T being an International University, admits students from different nations speaking different languages, and English is the official language; some students find it hard to grasp a word during teaching and learning. This paper explores the practical aspect of using artificial intelligence technologies in an advanced language translation manner during teaching and learning. The impact of this technology is reflected in the education strategies to equip students with the necessary knowledge and skills for professional activity in the best way they understand. The researcher evaluated the demand for this practice since students have to apply the knowledge they acquire in their native language to their countries in the best way they understand. The main objective is to improve student's language competence and lay a solid foundation for their future professional development. A descriptive-analytic approach was deemed best for the study to investigate the phenomena of language translation intelligence alongside Microsoft Office during the teaching and learning process. The study analysed the responses of 345 students from different academic programs. Based on the findings, the researcher recommends using the artificial intelligence language translation technique during teaching, and this requires the wisdom of human content designers and educational experts. Lecturers and students will be trained in the basic knowledge of this technique to improve the effectiveness of teaching and learning to meet the student’s needs.

Keywords: artificial intelligence, language translation technique, teaching and learning process, Microsoft Office

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Authors: Maitree Thamma, Witchupong Wiboonjaroen, Thanat Suknuan, Karan Homchat

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First order plus dead time (FOPDT) is a high dynamic system. Therefore, the controller must be intelligent. This paper presents the development and implementation of self-tuning Fuzzy-PID controller for controlling the FOPDT system. The water level process used represented FOPDT system and the mathematical model of the system was approximated by using System Identification toolbox in Matlab. The control programming and Fuzzy-PID algorithm used Matlab/Simulink and run on Microcontroller STM32.

Keywords: real-time control, self-tuning fuzzy-PID, FOPDT system, the water lever process

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Authors: Ola Jon Mork, Lars Andre Giske, Emil Bjørlykhaug

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Stabilization of critical processes in order to have the right quality of the products, more efficient production and smoother flow is a key issue in lean production. This paper presents how simulation of key welding processes can stabilize complicated welding processes in small scale production, and how simulation can impact the entire production concept seen from the perspective of lean production. First, a field study was made to learn the production processes in the factory, and subsequently the field study was transformed into a value stream map to get insight into each operation, the quality issues, operation times, lead times and flow of materials. Valuable practical knowledge of how the welding operations were done by operators, appropriate tools and jigs, and type of robots that could be used, was collected. All available information was then implemented into a simulation environment for further elaboration and development. Three researchers, the management of the company and skilled operators at the work floor where working on the project over a period of eight months, and a detailed description of the process was made by the researchers. The simulation showed that simulation could solve a number of technical challenges, the robot program can be tuned in off line mode, and the design and testing of the robot cell could be made in the simulator. Further on the design of the product could be optimized for robot welding and the jigs could be designed and tested in simulation environment. This means that a key issue of lean production can be solved; the welding operation will work with almost 100% performance when it is put into real production. Stabilizing of one key process is critical to gain control of the entire value chain, then a Takt Time can be established and the focus can be directed towards the next process in the production which should be stabilized. Results show that industrial parameters like welding time, welding cost and welding quality can be defined on the simulation stage. Further on, this gives valuable information for calculation of the factories business performance, like manufacturing volume and manufacturing efficiency. Industrial impact from simulation is more efficient implementation of lean manufacturing, since the welding process can be stabilized. More research should be done to gain more knowledge about simulation as a tool for implementation of lean, especially where there complex processes.

Keywords: simulation, lean, stabilization, welding process

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Authors: Javed Iqbal

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The growing need for energy by the human society and depletion of conventional energy sources demands a renewable, safe, infinite, low-cost and omnipresent energy source. One of the most suitable ways to solve the foreseeable world’s energy crisis is to use the power of the sun. Photovoltaic devices are especially of wide interest as they can convert solar energy to electricity. Recently the best performing solar cells are silicon-based cells. However, silicon cells are expensive, rigid in structure and have a large timeline for the payback of cost and electricity. Organic photovoltaic cells are cheap, flexible and can be manufactured in a continuous process. Therefore, organic photovoltaic cells are an extremely favorable replacement. Organic photovoltaic cells utilize sunlight as energy and convert it into electricity through the use of conductive polymers/ small molecules to separate electrons and electron holes. A major challenge for these new organic photovoltaic cells is the efficiency, which is low compared with the traditional silicon solar cells. To overcome this challenge, usually two straightforward strategies have been considered: (1) reducing the band-gap of molecular donors to broaden the absorption range, which results in higher short circuit current density (JSC) of devices, and (2) lowering the highest occupied molecular orbital (HOMO) energy of molecular donors so as to increase the open-circuit voltage (VOC) of applications devices.8 Keeping in mind the cost of chemicals it is hard to try many materials on test basis. The best way is to find the suitable material in the bulk. For this purpose, we use computational approach to design molecules based on our organic chemistry knowledge and determine their physical and electronic properties. In this study, we did DFT calculations with different options to get high open circuit voltage and after getting suitable data from calculation we finally did synthesis of a novel D–π–A–π–D type low band-gap small molecular donor material (ZOPTAN-TPA). The Aarylene vinylene based bis(arylhalide) unit containing a cyanostilbene unit acts as a low-band- gap electron-accepting block, and is coupled with triphenylamine as electron-donating blocks groups. The motivation for choosing triphenylamine (TPA) as capped donor was attributed to its important role in stabilizing the separated hole from an exciton and thus improving the hole-transporting properties of the hole carrier.3 A π-bridge (thiophene) is inserted between the donor and acceptor unit to reduce the steric hindrance between the donor and acceptor units and to improve the planarity of the molecule. The ZOPTAN-TPA molecule features a low HOMO level of 5.2 eV and an optical energy gap of 2.1 eV. Champion OSCs based on a solution-processed and non-annealed active-material blend of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) and ZOPTAN-TPA in a mass ratio of 2:1 exhibits a power conversion efficiency of 1.9 % and a high open-circuit voltage of over 1.0 V.

Keywords: high open circuit voltage, donor, triphenylamine, organic solar cells

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Authors: Celeste E. van Rinsum, Sanne M. P. L. Gerards, Geert M. Rutten, Ien A. M. van de Goor, Stef P. J. Kremers

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Combined lifestyle interventions have shown to be effective in changing and maintaining behavioral lifestyle changes and reducing overweight and obesity. A lifestyle coach is expected to promote lifestyle changes in adults related to physical activity and diet. The present Coaching on Lifestyle (CooL) study examined participants’ physical activity level, dietary behavioral, and motivational changes immediately after the intervention and at 1.5 years after baseline. In CooL intervention a lifestyle coach coaches individuals from eighteen years and older with (a high risk of) obesity in group and individual sessions. In addition a process evaluation was conducted in order to examine the implementation process and to be able to interpret the changes within the participants. This action-oriented research has a pre-post design. Participants of the CooL intervention (N = 200) completed three questionnaires: at baseline, immediately after the intervention (on average after 44 weeks), and at 1.5 years after baseline. T-tests and linear regressions were conducted to test self-reported changes in physical activity (IPAQ), dietary behaviors, their quality of motivation for physical activity (BREQ-3) and for diet (REBS), body mass index (BMI), and quality of life (EQ-5D-3L). For the process evaluation, we used individual and group interviews, observations and document analyses to gain insight in the implementation process (e.g. the recruitment) and how the intervention was valued by the participants, lifestyle coaches, and referrers. The study is currently ongoing and therefore the results presented here are preliminary. On average, the participants that finished the intervention and those that have completed the long-term measurement improved their level of vigorous-intense physical activity, sedentary behavior, sugar-sweetened beverage consumption and BMI. Mixed results were observed in motivational regulation for physical activity and nutrition. Moreover, an improvement on the quality of life dimension anxiety/depression was found, also in the long-term. All the other constructs did not show significant change over time. The results of the process evaluation have shown that recruitment of clients was difficult. Participants evaluated the intervention positively and the lifestyle coaches have continuously adapted the structure and contents of the intervention throughout the study period, based on their experiences and feedback from research. Preliminary results indicate that the CooL-intervention may have beneficial effects on overweight and obese participants in terms of energy balance-related behaviors, weight reduction, and quality of life. Recruitment of participants and embedding the position of the lifestyle coach in traditional care structures is challenging.

Keywords: combined lifestyle intervention, effect evaluation, lifestyle coaching, process evaluation, overweight, the Netherlands

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Authors: Samir Ranjbar, Nasrullah Istanekzai

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According to a report published in The Guardian, Kabul, the capital city of Afghanistan is the fifth fastest growing city in the world, whose population has increased fourfold since 2001 from 1.2 million to 4.8 million people. The main reason for this increment is identified as the return of Afghans migrated during the civil war. In addition to the return of immigrants, a steep economic growth due to foreign assistance in last decade creating lots of job opportunities in Kabul resulted in the attraction of individuals from the neighboring provinces as well. However, the development of urban facilities such as water supply system, housing transportation and waste management systems has yet to catch up with this rapid increase in population. Since Kabul city has developed traditionally and municipal governance had very limited capacity to implement municipal bylaws. As an unwanted consequence of this growth 70% of Kabul citizens contributed to developing informal settlement for which we can say that around three million people living in informally settled areas, lacking the very vital social and physical infrastructures of livelihood. This research focuses on a region with 30 ha area and 2100 people residents in the center of Kabul city. A comprehensive land readjustment concept plan has been formulated for this area. Through this concept plan, physical and social infrastructure has been demonstrated and analyzed. Findings of this paper propose a solution for the problems of this unplanned area in Kabul which is readjusting of unplanned area by a self-supporting process. This process does not need governmental budget and can be applied by government, private sectors and landowner associations. Furthermore, by implementing the Land Readjustment process, conceptual plans can be built for unplanned areas, maximum facilities can be brought to the residents’ urban life, improve the environment for the users’ benefit, promote the culture and sense of cooperation, participation and coexistence in the mind of people, improving the transport system, improvement in economic status (the value of land increases due to infrastructure availability and land legalization). In addition to all these benefits for the public, we can raise the revenue of government by collecting the taxes from landowners. This process is implemented in most of countries of the world, it was implemented for the first time in Germany and after that in most cities of Japan as well, and is known as one of the effective processes for infrastructural development. To sum up, the notable characteristic of the Land readjustment process is that it works on the concept of mutual interest in which both landowners and the government take advantage. However, in this process, the engagement of community is very important and without public cooperation, this process can face the failure.

Keywords: land readjustment, informal settlement, Kabul, Afghanistan

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Authors: Lucia Antonela Mitidieri

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This research analyzes the application of a model of settlements management based on networks of territorial integration that advocates planning as a cyclical and participatory process that engages early on with civic society, the private sector and the state. Through qualitative methods such as participant observation, interviews with snowball technique and an active research on territories, concrete results of community empowerment are obtained from the promotion of productive enterprises and community spaces of encounter and exchange. Studying the cultural and organizational dimensions of empowerment allows building indicators such as increase of capacities or community cohesion that can lead to support local governments in achieving sustainable urban development for a reduction of urban poverty.

Keywords: community spaces, empowerment, network urbanism, participatory process

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Authors: Shane David van Zyl, A. J. Burger

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The global green energy shift has placed significant value on the production of green hydrogen and its derivatives. The study examines the impact on capital expenditure (CAPEX), operational expenditure (OPEX), levelized cost, and environmental impact, depending on the relationship between various production capacities of potable water, green hydrogen, and green ammonia. A model-based sensitivity analysis approach was used to determine the relevance of various process parameters in the production of potable water combined with green hydrogen or green ammonia production. The effects of changes on CAPEX, OPEX and levelized costs of the products were determined. Furthermore, a qualitative environmental impact analysis was done to determine the effect on the environment. The findings indicated the individual process unit contribution to the overall CAPEX and OPEX while also determining the major contributors to changes in the levelized costs of products. The results emphasize the difference in costs associated with potable water, green hydrogen, and green ammonia production, indicating the extent to which potable water production costs become insignificant in the complete process, which, therefore, can have a large social benefit through increased potable water production resulting in decreased water scarcity in the south-west African region.

Keywords: CAPEX and OPEX, desalination, green hydrogen and green ammonia, sensitivity analysis

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Authors: Abdullah Almlaki, Anamaria Berea

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Social media platforms, such as Twitter, reflect public opinion well on various topics. However, current methods demonstrate limited accuracy in automated processes reflecting aggregate crowd beliefs. For example, many tweets, especially in the Arabic region, include spam. We propose a revised methodology using machine learning techniques by applying two filters, removing news and spam, from Arabic tweets before the sentiment analysis process. Afterwards, during the classification process, we propose incrementing the polarity score by the retweets and favorites. We show our revision methodology improves the accuracy of automated real opinion detection.

Keywords: computing methodologies, artificial intelligence, natural language processing, social media analysis

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Authors: Geetakshi Arora, Danish Malhotra

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Diabetic wounds are serious health issues and often fail to heal, leading to limb amputation that makes the life of the patient miserable. Delayed wound healing has been characterized by an increase in matrix metalloproteinase-9 (MMP-9). Thus research throughout the world has been going on to develop selective MMP-9 inhibitors for aiding diabetic wound healing. Bioactive constituents from natural sources always served as potential leads in drug development with high rates of success. Considering the need for novel selective MMP-9 inhibitors and the importance of natural bioactive compounds in drug development, we have screened a library of bioactive constituents from plant sources that were effective in diabetic wound healing on human MMP-9 (hMMP-9) using molecular docking studies. Screened constituents are ranked according to their dock score, ∆G value (binding affinity), and Ligand efficiency evaluated from FleXX docking and Hyde scoring modules available with drug designing platform LeadIT. Rhamnocitrin showed the highest correlation between dock score, ∆G value (binding affinity), and Ligand efficiency was further explored for binding interactions with hMMP-9. The overall study suggest that Rhamnocitrin is sufficiently decorated with both hydrophilic and hydrophobic substitutions that perfectly block hMMP-9 and act as a potential lead in the design and development of selective hMMP-9 inhibitors.

Keywords: MMP-9, diabetic wound, molecular docking, phytoconstituents

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Authors: Ali Karrech, Alberto Puccini, Ben Galvin, Davide Galli

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This paper summarises the laboratory tests, numerical models and statistical approach developed to investigate the behaviour of concrete blocks loaded in shear through metallic anchors. This research is proposed to bridge a gap in the state of the art and practice related to anchors loaded against partially confined concrete surfaces. Eight concrete blocks (420 mm x 500 mm x 1000 mm) with 150 and/or 250 deep anchors were tested. The stainless-steel anchors of diameter 16 mm were bonded with HIT-RE 500 V4 injection epoxy resin and were subjected to shear loading against partially supported edges. In addition, finite element models were constructed to validate the laboratory tests and explore the influence of key parameters such as anchor depth, anchor distance from the edge, and compressive strength on the stability of the block. Upon their validation experimentally, the numerical results were used to populate, develop and interpret a systematic parametric study based on the Design of Experiment approach through the Box-Behnken design and Response Surface Methodology. An empirical model has been derived based on this approach, which predicts the load capacity with the desirable intervals of confidence.

Keywords: finite element modelling, design of experiment, response surface methodology, Box-Behnken design, empirical model, interval of confidence, load capacity

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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Authors: Golnoosh Torabian, P. Valtchev, F. Dehghani

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The need for efficient nutraceutical products has been dramatically changing the approach of the industrial processes. The development of novel mild processes is highly demanded for the production of such products; especially when both quality and safety need to be guaranteed during their long shelf life. Within this research, for the first time, we investigated the effect of supercritical carbon dioxide treatment for the inactivation of microbes and enzymes in a berry juice possessing therapeutic effect. We demonstrated that a complete inactivation of microbes can be achieved at optimized conditions of treatment. However, the bottle neck of the process was represented by the unpromising inactivation of the degradative enzyme by supercritical carbon dioxide treatment. However, complete enzyme inactivation was achieved by applying two strategies: the first was optimizing juicing method by adding a mechanical step and the second strategy was addition of natural inhibitors to the juice. Overall these results demonstrate that our hybrid process has a significant effect on the inactivation of microorganism and enzymes in the fresh juice. The developed process opens the possibility for the evolution of new products with optimal nutritional and sensorial characteristics, as well as offering a competitive cost and an environmentally friendly alternative for pasteurization and extension of shelf life in a wide range of natural therapeutic products.

Keywords: hybrid method, berry juice, pasteurization, enzymes inactivation

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Authors: Tolulope Aremu

Abstract:

This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

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Authors: Narendra Akhadkar, Silvestre Cano, Christophe Gourru

Abstract:

Injection-molded parts are widely used in power system protection products. One of the biggest challenges in an injection molding process is shrinkage and warpage of the molded parts. All these geometrical variations may have an adverse effect on the quality of the product, functionality, cost, and time-to-market. The situation becomes more challenging in the case of intricate shapes and in mass production using multi-cavity tools. To control the effects of shrinkage and warpage, it is very important to correctly find out the input parameters that could affect the product performance. With the advances in the computer-aided engineering (CAE), different tools are available to simulate the injection molding process. For our case study, we used the MoldFlow insight tool. Our aim is to predict the spread of the functional dimensions and geometrical variations on the part due to variations in the input parameters such as material viscosity, packing pressure, mold temperature, melt temperature, and injection speed. The input parameters may vary during batch production or due to variations in the machine process settings. To perform the accurate product assembly variation simulation, the first step is to perform an individual part variation simulation to render realistic tolerance ranges. In this article, we present a method to simulate part variations coming from the input parameters variation during batch production. The method is based on computer simulations and experimental validation using the full factorial design of experiments (DoE). The robustness of the simulation model is verified through input parameter wise sensitivity analysis study performed using simulations and experiments; all the results show a very good correlation in the material flow direction. There exists a non-linear interaction between material and the input process variables. It is observed that the parameters such as packing pressure, material, and mold temperature play an important role in spread on functional dimensions and geometrical variations. This method will allow us in the future to develop accurate/realistic virtual prototypes based on trusted simulated process variation and, therefore, increase the product quality and potentially decrease the time to market.

Keywords: correlation, molding process, tolerance, sensitivity analysis, variation simulation

Procedia PDF Downloads 184

Authors: Oscar F. Toro, Alexia Pardo Figueroa, Brigitte M. Larico

Abstract:

The development of new processes in the textile industry entails designing methodologies to select adequate supplies that fit these new processes requirements. This paper presents a methodology to select chemicals that fulfill a new process technical specifications. The proposed methodology involves three major phases: (1) Data collection of chemical products, (2) Qualitative pre-selection and (3) Laboratory tests. We have applied this methodology to the selection of a binder which will form a protective film above the textile fibers and bond them. Our findings were that, there exist five possible products that can be used in our new process: Arkofil, Elvanol, Size plus A, Size plus AC and Starch. This new methodology has both qualitative and experimental variables, and can be used to select supplies for new textile processes.

Keywords: binder, chemical products, selection methodology, textile supplies, textile fiber

Procedia PDF Downloads 302

Authors: A. Armin, R. Fotouhi, W. Szyszkowski

Abstract:

This paper is part of a study to develop robots for farming. As such power requirement to operate equipment attach to such robots become an important factor. Soil-tool interaction play major role in power consumption, thus predicting accurately the forces which act on the blade during the farming is prime importance for optimal designing of farm equipment. In this paper a finite element investigation for tillage tools and soil interaction is described by using an inelastic constitutive material law for agriculture application. A 3-dimentional (3D) nonlinear finite element analysis (FEA) is developed to examine behavior of a blade with different rake angles moving in a block of soil, and to estimate the blade force. The soil model considered is an elastic-plastic with non-associated Drucker-Prager material model. Special use of contact elements are employed to consider connection between soil-blade and soil-soil surfaces. The FEA results are compared with experiment ones, which show good agreement in accurately predicting draft forces developed on the blade when it moves through the soil. Also, a very good correlation was obtained between FEA results and analytical results from classical soil mechanics theories for straight blades. These comparisons verified the FEA model developed. For analyzing complicated soil-tool interactions and for optimum design of blades, this method will be useful.

Keywords: finite element analysis, soil-blade contact modeling, blade force, mechanical engineering

Procedia PDF Downloads 300

Authors: Huseyin Sinan Gunesli

Abstract:

Process Safety Management is a disciplined framework for managing the integrity of systems and processes that handle hazardous substances. It relies on good design principles, well-implemented automation systems, and operating and maintenance practices. Alarm Management Systems play a critically important role in the safe and efficient operation of modern industrial plants. In that respect, Alarm Management is one of the critical factors feeding the safe operations of the plants in the manner of applying effective process safety principles. Trans Anatolian Natural Gas Pipeline (TANAP) is part of the Southern Gas Corridor, which extends from the Caspian Sea to Italy. TANAP transports Natural Gas from the Shah Deniz gas field of Azerbaijan, and possibly from other neighboring countries, to Turkey and through Trans Adriatic Pipeline (TAP) Pipeline to Europe. TANAP plays a crucial role in maintaining Energy Security for the region and Europe. In that respect, the application of Process Safety principles is vital to deliver safe, reliable and efficient Natural Gas delivery to Shippers both in the region and Europe. Effective Alarm Management is one of those Process Safety principles which feeds safe operations of the TANAP pipeline. Alarm Philosophy was designed and implemented in TANAP Pipeline according to the relevant standards. However, it is essential to manage the alarms received in the control room effectively to maintain safe operations. In that respect, TANAP has commenced Alarm Management & Rationalization program as of February 2022 after transferring to Plateau Regime, reaching the design parameters. While Alarm Rationalization started, there were more than circa 2300 alarms received per hour from one of the compressor stations. After applying alarm management principles such as reviewing and removal of bad actors, standing, stale, chattering, fleeting alarms, comprehensive review and revision of alarm set points through a change management principle, conducting alarm audits/design verification and etc., it has been achieved to reduce down to circa 40 alarms per hour. After the successful implementation of alarm management principles as specified above, the number of alarms has been reduced to industry standards. That significantly improved operator vigilance to focus on mainly important and critical alarms to avoid any excursion beyond safe operating limits leading to any potential process safety events. Following the ‟What Gets Measured, Gets Managed” principle, TANAP has identified key Performance Indicators (KPIs) to manage Process Safety principles effectively, where Alarm Management has formed one of the key parameters of those KPIs. However, review and analysis of the alarms were performed manually. Without utilizing Alarm Management Software, achieving full compliance with international standards is almost infeasible. In that respect, TANAP has started using one of the industry-wide known Alarm Management Applications to maintain full review and analysis of alarms and define actions as required. That actually significantly empowered TANAP’s process safety principles in terms of Alarm Management.

Keywords: process safety principles, energy security, natural gas pipeline operations, alarm rationalization, alarm management, alarm management application

Procedia PDF Downloads 108

Authors: Jeaha Yang, Ahmed Khan, Donna L. Rodela, Mohammed A. Qaudeer

Abstract:

Traditional supply chain silos still exist today due to the difficulty of establishing trust between various partners and technological barriers across industries. Companies lose opportunities and revenue and inadvertently make poor business decisions resulting in further challenges. Blockchain technology can bring a new level of transparency through sharing information with a distributed ledger in a decentralized manner that creates a basis of trust for business. Blockchain is a loosely coupled, hub-style communication network in which trading partners can work indirectly with each other for simpler integration, but they work together through the orchestration of their supply chain operations under a coherent process that is developed jointly. A Blockchain increases efficiencies, lowers costs, and improves interoperability to strengthen and automate the supply chain management process while all partners share the risk. Blockchain ledger is built to track inventory lifecycle for supply chain transparency and keeps a journal of inventory movement for real-time reconciliation. State design patterns are used to capture the life cycle (behavior) of inventory management as a state machine for a common, transparent and coherent process which creates an opportunity for trading partners to become more responsive in terms of changes or improvements in process, reconcile discrepancies, and comply with internal governance and external regulations. It enables end-to-end, inter-company visibility at the unit level for more accurate demand planning with better insight into order fulfillment and replenishment.

Keywords: supply chain management, inventory trace-ability, perpetual inventory system, inventory lifecycle, blockchain, inventory consignment, supply chain transparency, digital thread, demand planning, hyper ledger fabric

Procedia PDF Downloads 92