Search results for: community- based approach

Authors: P. Pötters, A. Marquet, B. Leyendecker

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The objective of this paper is to investigate different implementation approaches for the implementation of Lean production in companies. Furthermore, a structured overview of those different approaches is to be made. Therefore, the present work is intended to answer the following research question: What differences and similarities exist between the various systematic approaches and phase models for the implementation of Lean Production? To present various approaches for the implementation of Lean Production discussed in the literature, a qualitative content analysis was conducted. Within the framework of a qualitative survey, a selection of texts dealing with lean production and its introduction was examined. The analysis presents different implementation approaches from the literature, covering the descriptive aspect of the study. The study also provides insights into similarities and differences among the implementation approaches, which are drawn from the analysis of latent text contents and author interpretations. In this study, the focus is on identifying differences and similarities among systemic approaches for implementing Lean Production. The research question takes into account the main object of consideration, objectives pursued, starting point, procedure, and endpoint of the implementation approach. The study defines the concept of Lean Production and presents various approaches described in literature that companies can use to implement Lean Production successfully. The study distinguishes between five systemic implementation approaches and seven phase models to help companies choose the most suitable approach for their implementation project. The findings of this study can contribute to enhancing transparency regarding the existing approaches for implementing Lean Production. This can enable companies to compare and contrast the available implementation approaches and choose the most suitable one for their specific project.

Keywords: implementation, lean production, phase models, systematic approaches

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Authors: Heather Warfield, Brad Genereux

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Military personnel encounter a number of challenges when separating from military service to include career uncertainty, relational/family dynamics, trauma as a result of military experiences, reconceptualization of identity, and existential issues related to purpose, meaning making and framing of the military experience(s). Embedded within military culture are well-defined rites of passage and a significant sense of belonging. Consequently, transition out of the military can result in the loss of such rites of passage and belongingness. However, a pilgrimage journey can provide the time and space to engage in a new rite of passage, to construct a new pilgrim identity, and a to develop deep social relationships that lead to a sense of belongingness to a particular pilgrim community as well as to the global community of pilgrims across numerous types of pilgrimage journeys. The aims of the current paper are to demonstrate the rationale for why pilgrimage journeys are particularly significant for military veterans, provide an overview of an innovative program that facilitates the Camino de Santiago pilgrimage for military veterans, and discusses the lessons learned from the initial pilot project of a recently established program. Veterans on the Camino (VOC) is an emerging nongovernmental organization in the USA. Founded by a military veteran, after leaving his military career, the primary objective of the organization is to facilitate healing for veterans via the Camino de Santiago pilgrimage journey. As part of the program, participants complete a semi-structured interview at three time points – pre, during, and post journey. The interview items are based on ongoing research by the principal investigator and address such constructs as meaning-making, wellbeing, therapeutic benefits and transformation. In addition, program participants complete The Sources of Meaning and Meaning in Life Questionnaire (SoMe). The pilot program occurred in the spring of 2017. Five participants were selected after an extensive application process and review by a three-person selection board. The selection criteria included demonstrated compatibility with the program objectives (i.e., prior military experience, availability for a 40 day journey, and awareness of the need for a transformational intervention). The participants were connected as a group through a private Facebook site and interacted with one another for several months prior to the pilgrimage. Additionally, the participants were interviewed prior to beginning the pilgrimage, at one point during the pilgrimage and immediately following the conclusion of the pilgrimage journey. The interviews yielded themes related to loss, meaning construction, renewed hope in humanity, and a commitment to future goals. The lessons learned from this pilot project included a confirmation of the need for such a program, a need for greater focus on logistical details, and the recognition that the pilgrimage experience needs to continue in some manner once the veterans return home.

Keywords: pilgrimage, healing, military veterans, Camino de Santiago

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Authors: S. Pesina, T. Solonchak

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Lexical invariants, being a sort of stereotypes within the frames of ordinary consciousness, are created by the members of a language community as a result of uniform division of reality. The invariant meaning is formed in person’s mind gradually in the course of different actualizations of secondary meanings in various contexts. We understand lexical the invariant as abstract language essence containing a set of semantic components. In one of its configurations it is the basis or all or a number of the meanings making up the semantic structure of the word.

Keywords: lexical invariant, invariant theories, polysemantic word, cognitive linguistics

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Authors: Shreya Borthakur, Adhar Sharma

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The North-east states of India are well known for their age-old practice of preparing alcoholic beer from rice and millet. They do so in a traditional way by sprinkling starter cake (inoculum) on cooked rice or millet after which the fermentation starts and eventually, forms the beer. This starter cake has a rich composition of different microbes and medicinal herbs along with the powdered rice dough or maize dough with rice bran. The starter cake microbial composition has an important role in determining the microbial succession and metabolic secretions as the fermentation proceeds from the early to its late stage, thus, giving the beer a unique aroma, taste, and other sensory properties of traditionally prepared beer. Here, We have worked on identifying and characterizing the microbial community in the starter cakes prepared by the Monpa and Galo tribes of Arunachal Pradesh. A total of 18 microbial strains have been isolated from the starter cake of Monpa tribe, while 10 microbial isolates in that of Galo tribe. A metagenomic approach was applied to enumerate the cultural and non-cultural microbes present in the starter cakes prepared by the Monpa and Galo tribes of Arunachal Pradesh. The findings of the mini-project lays foundation to understand the role of microbes present in the starter cake in the beer’s fermentation process and will aide in future research on re-formulating the starter cakes to prevent the early spoilage of the ready to consume beer as the traditional rice beer has a short shelf-life. The paper concludes with the way forward being controlled CRISPR-Cas9.

Keywords: fermentation, traditional beer, microbial succession, preservation, CRISPR-Cas, food microbiology

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Authors: Sheila Shamuganathan, Mageswary Karpudewan

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This study investigated the effectiveness of green chemistry integrated with Science Writing Heuristic (SWH) in enhancing matriculation students’ responsible environmental behaviour. For this purpose 207 matriculation students were randomly assigned into experimental (N=118) and control (N=89) group. For the experimental group the chemistry concepts were taught using the instructional approach of green chemistry integrated with Science Writing Heuristic (SWH) while for the control group the same content was taught using green chemistry. The data was analysed using ANCOVA and findings obtained from the quantitative analysis reveals that there is significant changes in responsible environmental behaviour (F 1,204) = 32.13 (ηp² = 0.14) which favours the experimental group. The responses of the qualitative data obtained from an interview with the experimental group also further strengthen and indicated a significant improvement in responsible environmental behaviour. The outcome of the study suggests that using green chemistry integrated with Science Writing Heuristic (SWH) could be an alternative approach to improve students’ responsible environmental behaviour towards the environment.

Keywords: science writing heuristic, green chemistry, pro environmental behaviour, laboratory

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Authors: Serge B. Provost

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Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.

Keywords: density estimation, log-density, polynomial adjustments, sample moments

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Authors: Xiangmei Li

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Domestic violence (DV) victims are at a greater risk of suffering mental health problems; however, not all victims experience the same degree of depression. Women respond differently to gender inequalities based on their gender ideologies. This study explored the moderating role of gender ideology in the relation between exposure to DV and depression. Data were drawn from a sub-sample of women aged 18-60 from the Third WaveSurvey on the Social Status of Women in China (N = 10,701). The survey adopted astratified three-stage sampling design to select a representative sample of respondents from the country. Regression models were used to examine the moderating effects of gender ideology on the relation between DV and depression. Women who reported DV experience had more severe depressive symptoms after controlling for confounding social–demographic factors (β = 0.592, 95% CI: 0.489 – 0.695). Women's gender ideology moderated the association between DV severity and depression (β = -0.049, 95% CI: -0.085 – -0.013), despite being subjected to the same levels of victimization. The experience of domestic violence is a useful indicator for routine screening for depression in clinic and community settings. Interventions that aim to decrease depression caused by DV are more likely to be effective if they promote more egalitarian gender ideology to counter the mindset that a woman's role is confined to the home and a family suffers if the wife participates in the labor force.

Keywords: domestic violence against wives, depression, gender ideology, moderation

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Authors: Farhina Haque, Chanyeop Park

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The high efficiency, high field, and high power density provided by wide bandgap (WBG) semiconductors and advanced power electronic converter (PEC) topologies enabled the dynamic control of power in medium to high voltage systems. Although WBG semiconductors outperform the conventional Silicon based devices in terms of voltage rating, switching speed, and efficiency, the increased voltage handling properties, high dv/dt, and compact device packaging increase local electric fields, which are the main causes of partial discharge (PD) in the advanced medium and high voltage applications. PD, which occurs actively in voids, triple points, and airgaps, is an inevitable dielectric challenge that causes insulation and device aging. The aging process accelerates over time and eventually leads to the complete failure of the applications. Hence, it is critical to mitigating PD. Sharp edges, airgaps, triple points, and bubbles are common defects that exist in any medium to high voltage device. The defects are created during the manufacturing processes of the devices and are prone to high-electric-field-induced PD due to the low permittivity and low breakdown strength of the gaseous medium filling the defects. A contemporary approach of mitigating PD by neutralizing electric fields in high power density applications is introduced in this study. To neutralize the locally enhanced electric fields that occur around the triple points, airgaps, sharp edges, and bubbles, electrets are developed and incorporated into high voltage applications. Electrets are electric fields emitting dielectric materials that are embedded with electrical charges on the surface and in bulk. In this study, electrets are fabricated by electrically charging polyvinylidene difluoride (PVDF) films based on the widely used triode corona discharge method. To investigate the PD mitigation performance of the fabricated electret films, a series of PD experiments are conducted on both the charged and uncharged PVDF films under square voltage stimuli that represent PWM waveform. In addition to the use of single layer electrets, multiple layers of electrets are also experimented with to mitigate PD caused by higher system voltages. The electret-based approach shows great promise in mitigating PD by neutralizing the local electric field. The results of the PD measurements suggest that the development of an ultimate solution to the decades-long dielectric challenge would be possible with further developments in the fabrication process of electrets.

Keywords: electrets, high power density, partial discharge, triode corona discharge

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Authors: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

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Authors: Mina Naeini, Thomas A. Adams II

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Solid Oxide Fuel Cells (SOFCs) feature high electrical efficiency and generate substantial amounts of waste heat that make them suitable for integrated community energy systems (ICEs). By harvesting and distributing the waste heat through hot water pipelines, SOFCs can meet thermal demand of the communities. Therefore, they can replace traditional gas boilers and reduce greenhouse gas (GHG) emissions. Despite these advantages of SOFCs over competing power generation units, this technology has not been successfully commercialized in large-scale to replace traditional generators in ICEs. One reason is that SOFC performance deteriorates over long-term operation, which makes it difficult to find the proper sizing of the cells for a particular ICE system. In order to find the optimal sizing and operating conditions of SOFCs in a community, a proper knowledge of degradation mechanisms and effects of operating conditions on SOFCs long-time performance is required. The simplified SOFC models that exist in the current literature usually do not provide realistic results since they usually underestimate rate of performance drop by making too many assumptions or generalizations. In addition, some of these models have been obtained from experimental data by curve-fitting methods. Although these models are valid for the range of operating conditions in which experiments were conducted, they cannot be generalized to other conditions and so have limited use for most ICEs. In the present study, a general, detailed degradation-based model is proposed that predicts the performance of conventional SOFCs over a long period of time at different operating conditions. Conventional SOFCs are composed of Yttria Stabilized Zirconia (YSZ) as electrolyte, Ni-cermet anodes, and LaSr₁₋ₓMnₓO₃ (LSM) cathodes. The following degradation processes are considered in this model: oxidation and coarsening of nickel particles in the Ni-cermet anodes, changes in the pore radius in anode, electrolyte, and anode electrical conductivity degradation, and sulfur poisoning of the anode compartment. This model helps decision makers discover the optimal sizing and operation of the cells for a stable, efficient performance with the fewest assumptions. It is suitable for a wide variety of applications. Sulfur contamination of the anode compartment is an important cause of performance drop in cells supplied with hydrocarbon-based fuel sources. H₂S, which is often added to hydrocarbon fuels as an odorant, can diminish catalytic behavior of Ni-based anodes by lowering their electrochemical activity and hydrocarbon conversion properties. Therefore, the existing models in the literature for H₂-supplied SOFCs cannot be applied to hydrocarbon-fueled SOFCs as they only account for the electrochemical activity reduction. A regression model is developed in the current work for sulfur contamination of the SOFCs fed with hydrocarbon fuel sources. The model is developed as a function of current density and H₂S concentration in the fuel. To the best of authors' knowledge, it is the first model that accounts for impact of current density on sulfur poisoning of cells supplied with hydrocarbon-based fuels. Proposed model has wide validity over a range of parameters and is consistent across multiple studies by different independent groups. Simulations using the degradation-based model illustrated that SOFCs voltage drops significantly in the first 1500 hours of operation. After that, cells exhibit a slower degradation rate. The present analysis allowed us to discover the reason for various degradation rate values reported in literature for conventional SOFCs. In fact, the reason why literature reports very different degradation rates, is that literature is inconsistent in definition of how degradation rate is calculated. In the literature, the degradation rate has been calculated as the slope of voltage versus time plot with the unit of voltage drop percentage per 1000 hours operation. Due to the nonlinear profile of voltage over time, degradation rate magnitude depends on the magnitude of time steps selected to calculate the curve's slope. To avoid this issue, instantaneous rate of performance drop is used in the present work. According to a sensitivity analysis, the current density has the highest impact on degradation rate compared to other operating factors, while temperature and hydrogen partial pressure affect SOFCs performance less. The findings demonstrated that a cell running at lower current density performs better in long-term in terms of total average energy delivered per year, even though initially it generates less power than if it had a higher current density. This is because of the dominant and devastating impact of large current densities on the long-term performance of SOFCs, as explained by the model.

Keywords: degradation rate, long-term performance, optimal operation, solid oxide fuel cells, SOFCs

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Authors: Morteza Raminnia

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In this study, dynamic analysis of functionally graded nano-composite pipe reinforced by single-walled carbon nano-tubes (SWCNTs) with simply supported boundary condition subjected to moving mechanical loads is investigated. The material properties of functionally graded carbon nano tube-reinforced composites (FG-CNTRCs) are assumed to be graded in the thickness direction and are estimated through a micro-mechanical model. In this paper polymeric matrix considered as isotropic material and for the CNTRC, uniform distribution (UD) and three types of FG distribution patterns of SWCNT reinforcements are considered. The system equation of motion is derived by using Hamilton's principle under the assumptions of first order shear deformation theory (FSDT).The thin piezoelectric layers embedded on inner and outer surfaces of FG-CNTRC layer are acted as distributed sensor and actuator to control dynamic characteristics of the FG-CNTRC laminated pipe. The modal analysis technique and Newmark's integration method are used to calculate the displacement and dynamic stress of the pipe subjected to moving loads. The effects of various material distribution and velocity of moving loads on dynamic behavior of the pipe is presented. This present approach is validated by comparing the numerical results with the published numerical results in literature. The results show that the above-mentioned effects play very important role on dynamic behavior of the pipe .This present work shows that some meaningful results that which are interest to scientific and engineering community in the field of FGM nano-structures.

Keywords: nano-composite, functionally garded material, moving load, active control, PZT layers

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Authors: Ramin Rostamkhani, Thurasamy Ramayah

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One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.

Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components

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Authors: Anastasia P. Samaras, Allison Ward-Parsons, Beth Dalbec, Paula Cristina Azevedo, Anya Evmenova, Arvinder Johri, Lynne Scott Constantine, Lesley Smith

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Two cycles of qualitative data were collected. Cycle One sources included participant survey results, participant postings on Blackboard forums, facilitator memos, and meeting notes as well as reflections and notes from whole-group meetings.

Keywords: adjunct faculty, professional development, self-study methodology, teaching

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Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

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Authors: Punit Gandhi, J. C. Brezet, Tim Gorter, Uchechi Obinna

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This paper introduces how weather forecasting could help in more efficient energy management for smart homes with the use of Home Energy Management Systems (HEMS). The paper also focuses on educating consumers and helping them make more informed decisions while using the HEMS. A combined approach of technical and user perspective has been selected to develop a novel HEMS-product-service combination in a more comprehensive manner. The current HEMS switches on/off the energy intensive appliances based on the fluctuating electricity tariffs, but with weather forecasting, it is possible to shift the time of use of energy intensive appliances to maximum electricity production from the renewable energy system installed in the house. Also, it is possible to estimate the heating/cooling load of the house for the day ahead demand. Hence, relevant insight is gained in the expected energy production and consumption load for the next day, facilitating better (more efficient, peak shaved, cheaper, etc.) energy management practices for smart homes. In literature, on the user perspective, it has been observed that consumers lose interest in using HEMS after three to four months. Therefore, to further help in better energy management practices, the new system had to be designed in a way that consumers would sustain their interaction with the system on a structural basis. It is hypothesized that, if consumers feel more comfortable with using such system, it would lead to a prolonged usage, including more energy savings and hence financial savings. To test the hypothesis, a survey for the HEMS is conducted, to which 59 valid responses were recorded. Analysis of the survey helped in designing a system which imparts better information about the energy production and consumption to the consumers. It is also found from the survey that, consumers like a variety of options and they do not like a constant reminder of what they should do. Hence, the final system is designed to encourage consumers to make an informed decision about their energy usage with a wide variety of behavioral options available. It is envisaged that the new system will be tested in several pioneering smart energy grid projects in both the Netherlands and India, with a continued ‘design thinking’ approach, combining the technical and user perspective, as the basis for further improvements.

Keywords: weather forecasting, smart grid, renewable energy forecasting, user defined HEMS

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Authors: Zeynep Sener, Mehtap Dursun

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Supplier evaluation and selection is one of the most important components of an effective supply chain management system. Due to the expanding competition in healthcare, selecting the right medical device suppliers offers great potential for increasing quality while decreasing costs. This paper proposes a fuzzy decision making approach for medical supplier selection. A real-world medical device supplier selection problem is presented to illustrate the application of the proposed decision methodology.

Keywords: fuzzy decision making, fuzzy multiple objective programming, medical supply chain, supplier selection

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Authors: Abdurrauf M. Gusbi, Mahmud H. Arhima, Abdurrahim A. Elouzi, Ebtisam A. Benomran, Salsabeela Elmezwghi, Aram Elhatan, Nafesa Elgusbi

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Mass poisonings with methanol are rare but occur regularly both in developed and in non-developing countries. As a result of the tragedy that happened in the city of Tripoli Libya in March during year 2013 a number of patients were admitted to Tripoli Medical Center and Tripoli Central Hospital suffering from poisoning following ingestion of methanol by mistake. Our aims have been formulated to collect Information about those cases as much as we can from the archiving departments from the two hospitals including the number of cases that had been admitted, recovered patients and died victims. This retrospective study was planned to find out the reasons which allow those patients to drink methanol in our Muslim community and also the role of pharmacist to prevent such a disaster that claimed the lives of many people. During this tragedy 291 ospitalized patients their ages between 16-32 years old were admitted to both hospitals, total number of died 189 (121 at Tripoli medical center) and (68 at Tripoli central hospital), demographic data also shows that most of them are male (97%) and (3% female), about 4% of the patients foreigners and 96% were Libyans. There were a lot of obstacles and poor facilities at the time of patient admission as recognized in many cases including lack of first line of treatment. The morbidity was high due to the lack of antidote and availability of dialysis machines at this two main hospitals in Tripoli also according to survey done to the medical staff and also a random number of medical students shows about 28% have no idea about the first aid procedure used for methanol poisoning cases and this due to the absence of continuing education for all medical staff through the establishment of training courses on first aid, rapid diagnosis of poisoning and follow the written procedures to dealing with such cases.

Keywords: ethanol, fomepizole, methanol, poisoning

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Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: K. Thakkar, C. Ghenai

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An integrated modeling approach was used in this study to (1) track energy consumption, production, and resource extraction, (2) track greenhouse gases emissions and (3) analyze emissions for local and regional air pollutions. The model was used in this study for short and long term energy and GHG emissions reduction analysis for the state of Florida. The integrated modeling methodology will help to evaluate the alternative energy scenarios and examine emissions-reduction strategies. The mitigation scenarios have been designed to describe the future energy strategies. They consist of various demand and supply side scenarios. One of the GHG mitigation scenarios is crafted by taking into account the available renewable resources potential for power generation in the state of Florida to compare and analyze the GHG reduction measure against ‘Business As Usual’ and ‘Florida State Policy’ scenario. Two more ‘integrated’ scenarios, (‘Electrification’ and ‘Efficiency and Lifestyle’) are crafted through combination of various mitigation scenarios to assess the cumulative impact of the reduction measures such as technological changes and energy efficiency and conservation.

Keywords: energy planning, climate change mitigation assessment, integrated modeling approach, energy alternatives, and GHG emission reductions

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Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies

Keywords: crop yield, roughness coefficient, PAR, WRM model

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Authors: Shi-Bo Feng, Sheng-Jie Zhang, Jin Zhou

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The relationship between microbial diversity and algal bloom has received considerable attention for decades. Microbes undoubtedly affect annual bloom events and impact the physiology of both partners, as well as shape ecosystem diversity. However, knowledge about interactions and network correlations among broader-spectrum microbes that lead to the dynamics in a complete bloom cycle are limited. In this study, pyrosequencing and network approaches simultaneously assessed the associate patterns among bacteria, archaea, and microeukaryotes in surface water and sediments in response to a natural dinoflagellate (Alexandrium sp.) bloom. In surface water, among the bacterial community, Gamma-Proteobacteria and Bacteroidetes dominated in the initial bloom stage, while Alpha-Proteobacteria, Cyanobacteria, and Actinobacteria become the most abundant taxa during the post-stage. In the archaea biosphere, it clustered predominantly with Methanogenic members in the early pre-bloom period while the majority of species identified in the later-bloom stage were ammonia-oxidizing archaea and Halobacteriales. In eukaryotes, dinoflagellate (Alexandrium sp.) was dominated in the onset stage, whereas multiply species (such as microzooplankton, diatom, green algae, and rotifera) coexistence in bloom collapse stag. In sediments, the microbial species biomass and richness are much higher than the water body. Only Flavobacteriales and Rhodobacterales showed a slight response to bloom stages. Unlike the bacteria, there are small fluctuations of archaeal and eukaryotic structure in the sediment. The network analyses among the inter-specific associations show that bacteria (Alteromonadaceae, Oceanospirillaceae, Cryomorphaceae, and Piscirickettsiaceae) and some zooplankton (Mediophyceae, Mamiellophyceae, Dictyochophyceae and Trebouxiophyceae) have a stronger impact on the structuring of phytoplankton communities than archaeal effects. The changes in population were also significantly shaped by water temperature and substrate availability (N & P resources). The results suggest that clades are specialized at different time-periods and that the pre-bloom succession was mainly a bottom-up controlled, and late-bloom period was controlled by top-down patterns. Additionally, phytoplankton and prokaryotic communities correlated better with each other, which indicate interactions among microorganisms are critical in controlling plankton dynamics and fates. Our results supplied a wider view (temporal and spatial scales) to understand the microbial ecological responses and their network association during algal blooming. It gives us a potential multidisciplinary explanation for algal-microbe interaction and helps us beyond the traditional view linked to patterns of algal bloom initiation, development, decline, and biogeochemistry.

Keywords: microbial community, harmful algal bloom, ecological process, network

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Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

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Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization

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Authors: M. A. Rubio, A. Urquia

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Genetic algorithms (GA) are applied to the solution of high-dimensional optimization problems. Additionally, sensitivity analysis (SA) is usually carried out to determine the effect on optimal solutions of changes in parameter values of the objective function. These two analyses (i.e., optimization and sensitivity analysis) are computationally intensive when applied to high-dimensional functions. The approach presented in this paper consists in performing the SA during the GA execution, by statistically analyzing the data obtained of running the GA. The advantage is that in this case SA does not involve making additional evaluations of the objective function and, consequently, this proposed approach requires less computational effort than conducting optimization and SA in two consecutive steps.

Keywords: optimization, sensitivity, genetic algorithms, model calibration

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Authors: Hernández Eva Selene, Reyna Mary Carmen, Rivera Héctor, Barragán Irving

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We propose an approach that jointly addresses the layout of a facility and the scheduling of a sequence of jobs. In real production, these two problems are interrelated. However, they are treated separately in the literature. Our approach is an extension of the job shop problem with transportation delay, where the location of the machines is selected among possible sites. The model minimizes the makespan, using the short processing times rule with two algorithms; the first one considers all the permutations for the location of machines, and the second only a heuristic to select some specific permutations that reduces computational time. Some instances are proved and compared with literature.

Keywords: layout problem, job shop scheduling problem, concurrent scheduling and layout problem, metaheuristic

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Authors: Yin Yuanling

Abstract:

A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Latha Subbiah, Dhanalakshmi Samiappan

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In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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Authors: Malte Schilling, Mahmoud M. Rabah, Sven Liebisch

Abstract:

Wave run-up and overtopping are the relevant parameters for the dimensioning of the crest height of dikes. Various experimental as well as numerical studies have investigated these parameters under different boundary conditions (e.g. wave conditions, structure type). Particularly for the dike design in Europe, a common approach is formulated where wave and structure properties are parameterized. However, this approach assumes equal run-up heights and overtopping discharges along the longitudinal axis. However, convex dikes have a heterogeneous crest by definition. Hence, local differences in a convex dike line are expected to cause wave-structure interactions different to a straight dike. This study aims to assess both run-up and overtopping at convexly curved dikes. To cast light on the relevance of curved dikes for the design approach mentioned above, physical model tests were conducted in a 3D wave basin of the Ludwig-Franzius-Institute Hannover. A dike of a slope of 1:6 (height over length) was tested under both regular waves and TMA wave spectra. Significant wave heights ranged from 7 to 10 cm and peak periods from 1.06 to 1.79 s. Both run-up and overtopping was assessed behind the curved and straight sections of the dike. Both measurements were compared to a dike with a straight line. It was observed that convex curvatures in the longitudinal dike line cause a redirection of incident waves leading to a concentration around the center point. Measurements prove that both run-up heights and overtopping rates are higher than on the straight dike. It can be concluded that deviations from a straight longitudinal dike line have an impact on design parameters and imply uncertainties within the design approach in force. Therefore, it is recommended to consider these influencing factors for such cases.

Keywords: convex dike, longitudinal curvature, overtopping, run-up

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Authors: Made Kurnia Widiastuti Giri, Nyoman Kanca, Arie Swastini, Bambang Purwanto

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Aim: Waria transgenders are a phenomenon whose existence is undeniable. The sexual behaviours of waria transgenders belong to the groups of high-risk STDs infections, especially HIV/AIDS. The present study was aimed at finding out the general idea of the existence of waria transgenders in Singaraja, their sexual transactions, their sexual behaviours, and at exploring the factors affecting their sexual behaviours along with their participation in regular reproduction health control. Methods: The subjects of the present research were male-to-female transgenders living in the town of Singaraja. The research applied a qualitative approach. Data collection in this research was conducted through in-depth interview and observation. Results: The results of the study exposed 1) the existence of waria transgender community in Singaraja observed from their active participation in social events such as taking the roles of counsellors in the campaign of prevention and control of HIV/AIDS with the Local Commission of AIDS Control and other foundations; 2) the sexual services provided by waria transgenders which were performed in squeeze method, oral and anal sex which could be categorized as HIV/AIDS high-risk sexual behaviours, while the consistency in doing safe sex among the trangenders in Singaraja showed that most of the waria transgenders (80%) were aware of the urgency of using condoms during sexual intercourse; and 3) the low participation of the waria transgenders in Singaraja in regular reproduction health check up at the local Centre of Public Health Service was caused by their negative perception about being examined by female doctors. Conclucions: Waria in singaraja categorized as HIV/AIDS high-risk sexual behaviours but they do have consistency in doing safe sex by using condoms. They have a negative psychological perception about being examined by female doctors.

Keywords: waria transgenders, sexual behaviours, reproduction health, hiv/aids

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Authors: Ravinder Bahl, Jamini Sharma

Abstract:

The paper demonstrates analysis of the cervical cancer based on a probabilistic model. It involves technique for classification and prediction by recognizing typical and diagnostically most important test features relating to cervical cancer. The main contributions of the research include predicting the probability of recurrences in no recurrence (first time detection) cases. The combination of the conventional statistical and machine learning tools is applied for the analysis. Experimental study with real data demonstrates the feasibility and potential of the proposed approach for the said cause.

Keywords: cervical cancer, recurrence, no recurrence, probabilistic, classification, prediction, machine learning

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Authors: Alexander A. Tokmakov

Abstract:

Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

Procedia PDF Downloads 402