Search results for: RLS identification algorithm

Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Orit Baruth, Anat Cohen

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Online courses have become common in many learning programs and various learning environments, particularly in higher education. Social distancing forced in response to the COVID-19 pandemic has increased the demand for these courses. Yet, despite the frequency of use, online learning is not free of limitations and may not suit all learners. Hence, the growth of online learning alongside with learners' diversity raises the question: is online learning, as it currently offered, meets the needs of each learner? Fortunately, today's technology allows to produce tailored learning platforms, namely, personalization. Personality influences learner's satisfaction and therefore has a significant impact on learning effectiveness. A better understanding of personality can lead to a greater appreciation of learning needs, as well to assists educators ensure that an optimal learning environment is provided. In the context of online learning and personality, the research on learning design according to personality traits is lacking. This study explores the relations between personality traits (using the 'Big-five' model) and students' satisfaction with five techno-pedagogical learning solutions (TPLS): discussion groups, digital books, online assignments, surveys/polls, and media, in order to provide an online learning process to students' satisfaction. Satisfaction level and personality identification of 108 students who participated in a fully online learning course at a large, accredited university were measured. Cluster analysis methods (k-mean) were applied to identify learners’ clusters according to their personality traits. Correlation analysis was performed to examine the relations between the obtained clusters and satisfaction with the offered TPLS. Findings suggest that learners associated with the 'Neurotic' cluster showed low satisfaction with all TPLS compared to learners associated with the 'Non-neurotics' cluster. learners associated with the 'Consciences' cluster were satisfied with all TPLS except discussion groups, and those in the 'Open-Extroverts' cluster were satisfied with assignments and media. All clusters except 'Neurotic' were highly satisfied with the online course in general. According to the findings, dividing learners into four clusters based on personality traits may help define tailor learning paths for them, combining various TPLS to increase their satisfaction. As personality has a set of traits, several TPLS may be offered in each learning path. For the neurotics, however, an extended selection may suit more, or alternatively offering them the TPLS they less dislike. Study findings clearly indicate that personality plays a significant role in a learner's satisfaction level. Consequently, personality traits should be considered when designing personalized learning activities. The current research seeks to bridge the theoretical gap in this specific research area. Establishing the assumption that different personalities need different learning solutions may contribute towards a better design of online courses, leaving no learner behind, whether he\ she likes online learning or not, since different personalities need different learning solutions.

Keywords: online learning, personality traits, personalization, techno-pedagogical learning solutions

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Authors: Khadija Al-Hosni, Moon Fai Chan, Mohammed Al-Azri

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Background: Several studies suggest that most school-age adolescents are poorly informed on cancer warning signs and risk factors. Providing adolescents with sufficient knowledge would increase their awareness in adulthood and improve seeking behaviors later. Significant: The results will provide a clear vision in assisting key decision-makers in formulating policies on the students' awareness programs towards cancer. So, the likelihood of avoiding cancer in the future will be increased or even promote early diagnosis. Objectives: to evaluate the effectiveness of an education program designed to increase awareness of cancer signs and symptoms risk factors, improve the behavior of seeking help among school students in Oman, and address the barriers to obtaining medical help. Methods: A randomized controlled trial with two groups was conducted in Oman. A total of 1716 students (n=886/control, n= 830/education), aged 15-17 years, at 10th and 11th grade from 12 governmental schools 3 in governorates from 20-February-2022 to 12-May-2022. Basic demographic data were collected, and the Cancer Awareness Measure (CAM) was used as the primary outcome. Data were collected at baseline (T0) and 4 weeks after (T1). The intervention group received an education program about cancer's cause and its signs and symptoms. In contrast, the control group did not receive any education related to this issue during the study period. Non-parametric tests were used to compare the outcomes between groups. Results: At T0, the lamp was the most recognized cancer warning sign in the control (55.0%) and intervention (55.2%) groups. However, there were no significant changes at T1 for all signs in the control group. In contrast, all sign outcomes were improved significantly (p<0.001) in the intervention group, and the highest response was unexplained pain (93.3%). Smoking was the most recognized risk factor in both groups: (82.8% for control; 84.1% for intervention) at T0. However, there was no significant change in T1 for the control group, but there was for the intervention group (p<0.001), the highest identification was smoking cigarettes (96.5%). Too scared was the largest barrier to seeking medical help by students in the control group at T0 (63.0%) and T1 (62.8%). However, there were no significant changes in all barriers in this group. Otherwise, being too embarrassed (60.2%) was the largest barrier to seeking medical help for students in the intervention group at T0 and too scared (58.6%) at T1. Although there were reductions in all barriers, significant differences were found in six of ten only (p<0.001). Conclusion: The intervention was effective in improving students' awareness of cancer symptoms, warning signs (p<0.001), and risk factors (p<0.001 reduced the most addressed barriers to seeking medical help (p<0.001) in comparison to the control group. The Ministry of Education in Oman could integrate awareness of cancer within the curriculum, and more interventions are needed on the sociological part to overcome the barriers that interfere with seeking medical help.

Keywords: adolescents, awareness, cancer, education, intervention, student

Procedia PDF Downloads 118

Authors: Mahshid Arabi

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In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

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Authors: Tamar Grdzelishvili, Zaza Sinauridze

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Introduction: Preeclampsia is a complication of the second trimester of pregnancy, which is characterized by high morbidity and multiorgan damage. Many complex pathogenic mechanisms are now implicated to be responsible for this disease (1). Preeclampsia is one of the leading causes of maternal mortality worldwide. Statistics are enough to convince you of the seriousness of this pathology: about 100,000 women die of preeclampsia every year. It occurs in 3-14% (varies significantly depending on racial origin or ethnicity and geographical region) of pregnant women, in 75% of cases - in a mild form, and in 25% - in a severe form. During severe pre-eclampsia-eclampsia, perinatal mortality increases by 5 times and stillbirth by 9.6 times. Considering that the only way to treat the disease is to end the pregnancy, the main thing is timely diagnosis and prevention of the disease. Identification of high-risk pregnant women for PE and giving prophylaxis would reduce the incidence of preterm PE. First-trimester screening model developed by the Fetal Medicine Foundation (FMF), which uses the Bayes-theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has been proven to be effective and have superior screening performance to that of traditional risk factor-based approach for the prediction of PE (2) Methods: Retrospective single center screening study. The study population consisted of women from the Tbilisi maternity hospital “Pineo medical ecosystem” who met the following criteria: they spoke Georgian, English, or Russian and agreed to participate in the study after discussing informed consent and answering questions. Prior to the study, the informed consent forms approved by the Institutional Review Board were obtained from the study subjects. Early assessment of preeclampsia was performed between 11-13 weeks of pregnancy. The following were evaluated: anamnesis, dopplerography of the uterine artery, mean arterial blood pressure, and biochemical parameter: Pregnancy-associated plasma protein A (PAPP-A). Individual risk assessment was performed with performed by Fast Screen 3.0 software ThermoFisher scientific. Results: A total of 513 women were recruited and through the study, 51 women were diagnosed with preeclampsia (34.5% in the pregnant women with high risk, 6.5% in the pregnant women with low risk; P<0.000 1). Conclusions: First-trimester screening combining maternal factors with uterine artery Doppler, blood pressure, and pregnancy-associated plasma protein-A is useful to predict PE in a routine care setting. More patient studies are needed for final conclusions. The research is still ongoing.

Keywords: first-trimester, preeclampsia, screening, pregnancy-associated plasma protein

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Authors: Kailash Chandra, Devanshu Gupta

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The Himalayan Mountains of India fall under two biogeographic zones Trans Himalaya (TH) and Himalaya and seven biotic provinces (TH-Ladakh Mountains, TH-Tibetan Plateau, TH-Sikkim, North-West Himalaya, West Himalaya, Central Himalaya, and East Himalaya). Because of the extreme environment and altitudinal variations, unique physiography, varied ecological conditions, and different vegetations, the Himalaya exhibit a rich assemblage of life, both flora, and fauna, further subjected to the impacts of climate change. To the authors’ best knowledge, there is no comprehensive account except for sporadic faunal investigations, to assess or interpret the insect diversity and their biogeographic distribution in Indian Himalaya (IH), one of the biodiversity hotspots. Therefore, in this paper, a compelling review of the extensive knowledge of insect diversity of IH is presented for the first time to the best of our knowledge. The inventory of the known insect species of IH was compiled from the exploration cum faunal-study data ready with the zoological survey of India, Kolkata as well as from the information published in the scientific literature till date. The species were listed with their valid names with their distribution in seven biotic provinces of IH. The insect fauna of IH represents about 38% of the identified insect diversity of India. The interpretation of data provided significant information in detecting possible gap areas in the taxonomic representation of different insect orders. Archaeognatha, Zygentoma, Ephemeroptera, Phasmida, Embioptera, Psocoptera, Phthiraptera, Strepsiptera, Megaloptera, Raphidioptera, Siphonaptera, and Mecoptera need revisions, and it is required to collect more samples from remote areas of the region. Scope for finding new taxa even in the most diverse orders, Coleoptera, Lepidoptera, Hymenoptera, Diptera, and Hemiptera cannot be overlooked. Exploration of cold deserts of Trans Himalaya and East Himalaya (Arunachal Pradesh) may result in a good number of new species from these regions. The most notable data was that many of the species recorded from Himalaya are still known from their type localities only, so there is an urgency to revisit and resurvey those collection localities for the evaluation of the status of those species. It is also required to assess and monitor the impact of climate change on the diversity of insects inhabiting in the fragile Himalayan ecosystem. DNA barcoding especially pests and biological control agents to solve the problems of identification in species complexes is also the need of the hour. In a nutshell, it can be concluded that the inventory of insects of this region is extensive but is far from final as every year hundreds of new species are described.

Keywords: catalog, climate change, diversity, DNA barcoding

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Authors: Janice Keener, Christine Houlihan

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Over the last several years, there has been an increase in children identified as having Autism Spectrum Disorder (ASD). Specialists across several disciplines: mental health and medical professionals have been tasked with ensuring accurate and timely evaluations for children with suspected ASD. Due to the nature of the ASD symptom presentation, an interdisciplinary assessment and treatment approach best addresses the needs of the whole child. During the unprecedented COVID-19 Pandemic, clinicians were faced with how to continue with interdisciplinary assessments in a telehealth arena. Instruments that were previously used to assess ASD in-person were no longer appropriate measures to use due to the safety restrictions. For example, The Autism Diagnostic Observation Schedule requires examiners and children to be in very close proximity of each other and if masks or face shields are worn, they render the evaluation invalid. Similar issues arose with the various cognitive measures that are used to assess children such as the Weschler Tests of Intelligence and the Differential Ability Scale. Thus the need arose to identify measures that are able to be safely and accurately administered using safety guidelines. The incidence of ASD continues to rise over time. Currently, the Center for Disease Control estimates that 1 in 59 children meet the criteria for a diagnosis of ASD. The reasons for this increase are likely multifold, including changes in diagnostic criteria, public awareness of the condition, and other environmental and genetic factors. The rise in the incidence of ASD has led to a greater need for diagnostic and treatment services across the United States. The uncertainty of the diagnostic process can lead to an increased level of stress for families of children with suspected ASD. Along with this increase, there is a need for diagnostic clarity to avoid both under and over-identification of this condition. Interdisciplinary assessment is ideal for children with suspected ASD, as it allows for an assessment of the whole child over the course of time and across multiple settings. Clinicians such as Psychologists and Developmental Pediatricians play important roles in the initial evaluation of autism spectrum disorder. An ASD assessment may consist of several types of measures such as standardized checklists, structured interviews, and direct assessments such as the ADOS-2 are just a few examples. With the advent of telehealth clinicians were asked to continue to provide meaningful interdisciplinary assessments via an electronic platform and, in a sense, going to the family home and evaluating the clinical symptom presentation remotely and confidently making an accurate diagnosis. This poster presentation will review the benefits, limitations, and interpretation of these various instruments. The role of other medical professionals will also be addressed, including medical providers, speech pathology, and occupational therapy.

Keywords: Autism Spectrum Disorder Assessments, Interdisciplinary Evaluations , Tele-Assessment with Autism Spectrum Disorder, Diagnosis of Autism Spectrum Disorder

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Authors: Diana Cunha, Catarina Coelho, Ana Paula Relvas, Elisabeth Kastenholz

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Context: Tourist experiences have a recognized impact on the well-being of individuals. However, studies on the specific benefits of tourist experiences for families are scattered across different disciplines. This study aims to systematically review the literature to synthesize the evidence on the benefits of tourist experiences for families. Research Aim: The main objective is to systematize the evidence in the literature regarding the benefits of tourist experiences for families. Methodology: A systematic literature review was conducted using Nvivo, analyzing 33 scientific studies obtained from various databases. The search terms used were "family"/ "couple" and "tourist experience". The studies included quantitative, qualitative, mixed methods, and literature reviews. All works prior to the year 2000 were excluded, and the search was restricted to full text. A language filter was also used, considering articles in Portuguese, English, and Spanish. For NVivo analysis, information was coded based on both deductive and inductive perspectives. To minimize the subjectivity of the selection and coding process, two of the authors discussed the process and agreed on criteria that would make the coding more objective. Once the coding process in NVivo was completed, the data relating to the identification/characterization of the works were exported to the Statistical Package for the Social Sciences (SPPS), to characterize the sample. Findings: The results highlight that tourist experiences have several benefits for family systems, including the strengthening of family and marital bonds, the creation of family memories, and overall well-being and life satisfaction. These benefits contribute to both immediate relationship quality improvement and long-term family identity construction and transgenerational transmission. Theoretical Importance: This study emphasizes the systemic nature of the effects and relationships within family systems. It also shows that no harm was reported within these experiences, with only some challenges related to positive outcomes. Data Collection and Analysis Procedures: The study collected data from 33 scientific studies published predominantly after 2013. The data were analyzed using Nvivo, employing a systematic review approach. Question Addressed: The study addresses the question of the benefits of tourist experiences for families and how these experiences contribute to family functioning and individual well-being. Conclusion: Tourist experiences provide opportunities for families to enhance their interpersonal relationships and create lasting memories. The findings suggest that formal interventions based on evidence could further enhance the potential benefits of these experiences and be a valuable preventive tool in therapeutic interventions.

Keywords: family systems, individual and family well-being, marital satisfaction, tourist experiences

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Authors: G. V. Manzane, S. J. Modise

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Uterine fibroids, also known as leiomyomas or myomas, are non-cancerous growths that develop in the muscular wall of the uterus during the reproductive years. The cause of uterine fibroids includes hormonal, genetic, growth factors, and extracellular matrix factors. Common symptoms of uterine fibroids include heavy and prolonged menstrual bleeding which can lead to a high risk of anemia, lower abdominal pains, pelvic pressure, infertility, and pregnancy loss. The growth of this tumor is a concern because of its negative impact on women’s health and the increase in their economic burden. Traditional medicinal plants have long been used in Africa for their potential therapeutic effects against various ailments. In this study, we aimed to identify and characterize bioactive compounds from selected African medicinal plants with potential anti-fibrotic properties using Fourier-transform infrared spectroscopy (FTIR) and gas chromatography-mass spectrometry (GCMS) analysis. Two medicinal plant species known for their traditional use in fibrosis-related conditions were selected for investigation. Aqueous extracts were prepared from the plant materials, and FTIR analysis was conducted to determine the functional groups present in the extracts. GCMS analysis was performed to identify the chemical constituents of the extracts. The FTIR analysis revealed the presence of various functional groups, such as phenols, flavonoids, terpenoids, and alkaloids, known for their potential therapeutic activities. These functional groups are associated with antioxidant, anti-inflammatory, and anti-fibrotic properties. The GCMS analysis identified several bioactive compounds, including flavonoids, alkaloids, terpenoids, and phenolic compounds, which are known for their pharmacological activities. The discovery of bioactive compounds in African medicinal plants that exhibit anti-fibrotic effects, opens up promising avenues for further research and development of potential treatments for fibrosis. This suggests the potential of these plants as a valuable source of novel therapeutic agents for treating fibrosis-related conditions. In conclusion, our study identified and characterized bioactive compounds from selected African medicinal plants using FTIR and GCMS analysis. The presence of compounds with known antifibrotic properties suggests that these plants hold promise as a potential source of natural products for the development of novel anti-fibrotic therapies.

Keywords: uterine fibroids, african medicinal plants, bioactive compounds, identify and characterized

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Authors: Bartosz Kedra, Robert Malkowski

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This paper provides description and presentation of laboratory test unit built basing on 150 kVA power frequency converter and Simulink RealTime platform. Assumptions, based on criteria which load and generator types may be simulated using discussed device, are presented, as well as control algorithm structure. As laboratory setup contains transformer with thyristor controlled tap changer, a wider scope of setup capabilities is presented. Information about used communication interface, data maintenance, and storage solution as well as used Simulink real-time features is presented. List and description of all measurements are provided. Potential of laboratory setup modifications is evaluated. For purposes of Rapid Control Prototyping, a dedicated environment was used Simulink RealTime. Therefore, load model Functional Unit Controller is based on a PC computer with I/O cards and Simulink RealTime software. Simulink RealTime was used to create real-time applications directly from Simulink models. In the next step, applications were loaded on a target computer connected to physical devices that provided opportunity to perform Hardware in the Loop (HIL) tests, as well as the mentioned Rapid Control Prototyping process. With Simulink RealTime, Simulink models were extended with I/O cards driver blocks that made automatic generation of real-time applications and performing interactive or automated runs on a dedicated target computer equipped with a real-time kernel, multicore CPU, and I/O cards possible. Results of performed laboratory tests are presented. Different load configurations are described and experimental results are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area and arbitrary active and reactive power regulation basing on defined schedule.

Keywords: MATLAB, power converter, Simulink Real-Time, thyristor-controlled tap changer

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Authors: Shaikah Alsubayae, Gianluigi Casse, Carlos Chavez, Jon Taylor, Alan Taylor, Mohammad Alsulimane

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Achieving precise radiotherapy through carbon therapy necessitates the accurate monitoring of radiation dose distribution within the patient's body. This process is pivotal for targeted tumor treatment, minimizing harm to healthy tissues, and enhancing overall treatment effectiveness while reducing the risk of side effects. In our investigation, we adopted a methodological approach to monitor secondary proton doses in carbon therapy using Monte Carlo (MC) simulations. Initially, Geant4 simulations were employed to extract the initial positions of secondary particles generated during interactions between carbon ions and water, including protons, gamma rays, alpha particles, neutrons, and tritons. Subsequently, we explored the relationship between the carbon ion beam and these secondary particles. Interaction vertex imaging (IVI) proves valuable for monitoring dose distribution during carbon therapy, providing information about secondary particle locations and abundances, particularly protons. The IVI method relies on charged particles produced during ion fragmentation to gather range information by reconstructing particle trajectories back to their point of origin, known as the vertex. In the context of carbon ion therapy, our simulation results indicated a strong correlation between some secondary particles and the range of carbon ions. However, challenges arose due to the unique elongated geometry of the target, hindering the straightforward transmission of forward-generated protons. Consequently, the limited protons that did emerge predominantly originated from points close to the target entrance. Fragment (protons) trajectories were approximated as straight lines, and a beam back-projection algorithm, utilizing interaction positions recorded in Si detectors, was developed to reconstruct vertices. The analysis revealed a correlation between the reconstructed and actual positions.

Keywords: radiotherapy, carbon therapy, monitor secondary proton doses, interaction vertex imaging

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Authors: I. Berger, N. Machour, F. Portet-Koltalo

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Polycyclic aromatic hydrocarbons (PAHs) are toxic and carcinogenic pollutants produced in majority by incomplete combustion processes in industrialized and urbanized areas. After being emitted in atmosphere, these persistent contaminants are deposited to soils or sediments. Even if persistent, some can be partially degraded (photodegradation, biodegradation, chemical oxidation) and they lead to oxygenated metabolites (oxy-PAHs) which can be more toxic than their parent PAH. Oxy-PAHs are less measured than PAHs in sediments and this study aims to compare different analytical tools in order to extract and quantify a mixture of four hydroxylated PAHs (OH-PAHs) and four carbonyl PAHs (quinones) in sediments. Methodologies: Two analytical systems – HPLC with on-line UV and fluorescence detectors (HPLC-UV-FLD) and GC coupled to a mass spectrometer (GC-MS) – were compared to separate and quantify oxy-PAHs. Microwave assisted extraction (MAE) was optimized to extract oxy-PAHs from sediments. Results: First OH-PAHs and quinones were analyzed in HPLC with on-line UV and fluorimetric detectors. OH-PAHs were detected with the sensitive FLD, but the non-fluorescent quinones were detected with UV. The limits of detection (LOD)s obtained were in the range (2-3)×10-4 mg/L for OH-PAHs and (2-3)×10-3 mg/L for quinones. Second, even if GC-MS is not well adapted to the analysis of the thermodegradable OH-PAHs and quinones without any derivatization step, it was used because of the advantages of the detector in terms of identification and of GC in terms of efficiency. Without derivatization, only two of the four quinones were detected in the range 1-10 mg/L (LODs=0.3-1.2 mg/L) and LODs were neither very satisfying for the four OH-PAHs (0.18-0.6 mg/L). So two derivatization processes were optimized, comparing to literature: one for silylation of OH-PAHs, one for acetylation of quinones. Silylation using BSTFA/TCMS 99/1 was enhanced using a mixture of catalyst solvents (pyridine/ethyle acetate) and finding the appropriate reaction duration (5-60 minutes). Acetylation was optimized at different steps of the process, including the initial volume of compounds to derivatize, the added amounts of Zn (0.1-0.25 g), the nature of the derivatization product (acetic anhydride, heptafluorobutyric acid…) and the liquid/liquid extraction at the end of the process. After derivatization, LODs were decreased by a factor 3 for OH-PAHs and by a factor 4 for quinones, all the quinones being now detected. Thereafter, quinones and OH-PAHs were extracted from spiked sediments using microwave assisted extraction (MAE) followed by GC-MS analysis. Several mixtures of solvents of different volumes (10-25 mL) and using different extraction temperatures (80-120°C) were tested to obtain the best recovery yields. Satisfactory recoveries could be obtained for quinones (70-96%) and for OH-PAHs (70-104%). Temperature was a critical factor which had to be controlled to avoid oxy-PAHs degradation during the MAE extraction process. Conclusion: Even if MAE-GC-MS was satisfactory to analyze these oxy-PAHs, MAE optimization has to be carried on to obtain a most appropriate extraction solvent mixture, allowing a direct injection in the HPLC-UV-FLD system, which is more sensitive than GC-MS and does not necessitate a previous long derivatization step.

Keywords: derivatizations for GC-MS, microwave assisted extraction, on-line HPLC-UV-FLD, oxygenated PAHs, polluted sediments

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Authors: Joy Cao, Min Zhou

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Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

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Authors: Sinem Bulkan

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This study introduces the construct of psychopathic manager behaviour and aims for the development of psychopathic manager behaviour (Psycho-Man B) measure. The study also aims for the understanding of the relationship between psychopathic manager behaviour and workplace deviance while investigating the mediating role of a revenge motive and the moderating roles of the core self-evaluations and the attitude importance. Data were collected from 519 employees from a wide variety of jobs and industries who currently work for or previously worked for a manager in a collectivist culture, Turkey. Psycho-Man B Measure was developed resulting in five dimensions as opposed to the proposed ten dimensions. Simple linear and hierarchical regression analyses were conducted to test the hypotheses. The results of simple linear regression analyses showed that psychopathic manager behaviour was positively significantly related to supervisor-directed and organisation-directed deviance. Revenge motive towards the manager partially mediated the relationship between psychopathic manager behaviour and supervisor-directed deviance. Similarly, revenge motive towards the organisation partially mediated the relationship between psychopathic manager behaviour and organisation-directed deviance. Furthermore, no support was found for the expected moderating role of core self-evaluations in the revenge motive towards the manager-supervisor-directed deviance and revenge motive towards the organisation-organisation-directed deviance relationships. Attitude importance moderated the relationship between revenge motive towards the manager and supervisor-directed deviance; revenge motive towards the organisation and organisation-directed deviance. Moderated-mediation hypotheses were not supported for core self-evaluations but were supported for the attitude importance. Additional analyses for sub-dimensions were conducted to further examine the hypotheses. Demographic variables were examined through independent samples t-tests, and one way ANOVA. Finally, findings are discussed; limitations, suggestions and implications are presented. The major contribution of this study is that ‘psychopathic manager behaviour’ construct was introduced to the literature and a scale for the reliable identification of psychopathic manager behaviour was developed in to evaluate managers’ level of sub-clinical psychopathy in the workforce. The study introduced that employees engage in different forms of supervisor-directed deviance and organisation-directed deviance depending on the level of the emotions and personal goals. Supervisor-directed deviant behaviours and organisation-directed deviant behaviours became distinct in a way as impulsive and premeditated, active or passive, direct and indirect actions. Accordingly, it is important for organisations to notice that employees’ level of affective state and attitude importance for psychopathic manager behaviours predetermine the certain type of employee deviant behaviours.

Keywords: attitude importance, core self evaluations, psychopathic manager behaviour, revenge motive, workplace deviance

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Othman E. Othman, Amira M. Nowier, Medhat El-Denary

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Camels play an important socio-economic role within the pastoral and agricultural system in the dry and semidry zones of Asia and Africa. Camels are economically important animals in Egypt where they are dual purpose animals (meat and milk). The analysis of chemical composition of camel milk showed that the total protein contents ranged from 2.4% to 5.3% and it is divided into casein and whey proteins. The casein fraction constitutes 52% to 89% of total camel milk protein and it divided into 4 fractions namely αs1, αs2, β and κ-caseins which are encoded by four tightly genes. In spite of the important role of casein genes and the effects of their genetic polymorphisms on quantitative traits and technological properties of milk, the studies for the detection of genetic polymorphism of camel milk genes are still limited. Due to this fact, this work focused - using PCR-RFP and sequencing analysis - on the identification of genetic polymorphisms and SNPs of two casein genes in Maghrabi camel breed which is a dual purpose camel breed in Egypt. The amplified fragments at 488-bp of the camel κ-CN gene were digested with AluI endonuclease. The results showed the appearance of three different genotypes in the tested animals; CC with three digested fragments at 203-, 127- and 120-bp, TT with three digested fragments at 203-, 158- and 127-bp and CT with four digested fragments at 203-, 158-, 127- and 120-bp. The frequencies of three detected genotypes were 11.0% for CC, 48.0% for TT and 41.0% for CT genotypes. The sequencing analysis of the two different alleles declared the presence of a single nucleotide polymorphism (C→T) at position 121 in the amplified fragments which is responsible for the destruction of a restriction site (AG/CT) in allele T and resulted in the presence of two different alleles C and T in tested animals. The nucleotide sequences of κ-CN alleles C and T were submitted to GenBank with the accession numbers; KU055605 and KU055606, respectively. The primers used in this study amplified 942-bp fragments spanning from exon 4 to exon 6 of camel αS1-Casein gene. The amplified fragments were digested with two different restriction enzymes; SmlI and AluI. The results of SmlI digestion did not show any restriction site whereas the digestion with AluI endonuclease revealed the presence of two restriction sites AG^CT at positions 68^69 and 631^632 yielding the presence of three digested fragments with sizes 68-, 563- and 293-bp.The nucleotide sequences of this fragment from camel αS1-Casein gene were submitted to GenBank with the accession number KU145820. In conclusion, the genetic characterization of quantitative traits genes which are associated with the production traits like milk yield and composition is considered an important step towards the genetic improvement of livestock species through the selection of superior animals depending on the favorable alleles and genotypes; marker assisted selection (MAS).

Keywords: genetic polymorphism, SNP polymorphism, Maghrabi camels, κ-Casein gene, αS1-Casein gene

Procedia PDF Downloads 613

Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

Procedia PDF Downloads 296

Authors: Patcharaporn Sakulpong, Wiriya Phokhwang

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Background: Banpunrug (Love Sharing House) established in 2013 provides a community-based palliative care for patients with cancer from 7 provinces in southern Thailand. These patients come to receive outpatient chemotherapy and radiotherapy at Suratthani Cancer Hospital. They are poor and uneducated; they need an accommodation during their 30-45 day course of therapy. Methods: A community-participatory action research (PAR) was employed to establish a model of palliative care for patients with cancer. The participants included health care providers, community, and patients and families. The PAR process includes problem identification and need assessment, community and team establishment, field survey, organization founding, model of care planning, action and inquiry (PDCA), outcome evaluation, and model distribution. Results: The model of care at Banpunrug involves the concepts of HHHS model, in that Banpunrug is a Home for patients; patients live in a house comfortable like in a Hotel resource; the patients are given care and living facilities similarly to those in a Hospital; the house is a School for patients to learn how to take care themselves, how to live well with cancer, and most importantly how to prepare themselves for a good death. The house is also a humanized care school for health care providers. Banpunrug’s philosophy of care is based on friendship therapy, social and spiritual support, community partnership, patient-family centeredness, Live & Love sharing house, and holistic and humanized care. With this philosophy, the house is managed as a home of the patients and everyone involved; everything is costless for all eligible patients and their family members; all facilities and living expense are donated from benevolent people, friends, and community. Everyone, including patients and family, has a sense of belonging to the house and there is no authority between health care providers and the patients in the house. The house is situated in a temple and a community and supported by many local nonprofit organizations and healthcare facilities such as a health promotion hospital at sub-disctrict level and Suratthani Cancer Hospital. Village health volunteers and multi-professional health care volunteers have contributed not only appropriate care, but also knowledge and experience to develop a distinguishing HHHS community-based palliative care model for patients with cancer. Since its opening the house has been a home for more than 400 patients and 300 family members. It is also a model for many national and international healthcare organizations and providers, who come to visit and learn about palliative care in and by community. Conclusions: The success of this palliative care model comes from community involvement, multi-professional volunteers and distributions, and concepts of HHHS model. Banpunrug promotes a consistent care across the cancer trajectory independent of prognosis in order to strengthen a full integration of palliative

Keywords: community-based palliative care, model, participatory action research, patients with cancer

Procedia PDF Downloads 268

Authors: Heribert R. Kaijage, Samuel N. A. Codjoe, Simon H. D. Mamuya, Mangi J. Ezekiel

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There is strong evidence that climate has changed significantly affecting various sectors including public health. The recommended feasible solution is adopting development trajectories which combine both mitigation and adaptation measures for improving resilience pathways. This approach demands a consideration for complex interactions between climate and social-ecological systems. While other sectors such as agriculture and water have developed climate resilience indices, the public health sector in Tanzania is still lagging behind. The aim of this study was to find out how can we use Demographic and Health Surveys (DHS) linked with Remote Sensing (RS) technology and metrological information as tools to inform climate change resilient development and evaluation for the health sector. Methodological review was conducted whereby a number of studies were content analyzed to find appropriate indicators and indices for climate resilience household and their integration approach. These indicators were critically reviewed, listed, filtered and their sources determined. Preliminary identification and ranking of indicators were conducted using participatory approach of pairwise weighting by selected national stakeholders from meeting/conferences on human health and climate change sciences in Tanzania. DHS datasets were retrieved from Measure Evaluation project, processed and critically analyzed for possible climate change indicators. Other sources for indicators of climate change exposure were also identified. For the purpose of preliminary reporting, operationalization of selected indicators was discussed to produce methodological approach to be used in resilience comparative analysis study. It was found that household climate resilient index depends on the combination of three indices namely Household Adaptive and Mitigation Capacity (HC), Household Health Sensitivity (HHS) and Household Exposure Status (HES). It was also found that, DHS alone cannot complement resilient evaluation unless integrated with other data sources notably flooding data as a measure of vulnerability, remote sensing image of Normalized Vegetation Index (NDVI) and Metrological data (deviation from rainfall pattern). It can be concluded that if these indices retrieved from DHS data sets are computed and scientifically integrated can produce single climate resilience index and resilience maps could be generated at different spatial and time scales to enhance targeted interventions for climate resilient development and evaluations. However, further studies are need to test for the sensitivity of index in resilience comparative analysis among selected regions.

Keywords: climate change, resilience, remote sensing, demographic and health surveys

Procedia PDF Downloads 165

Authors: Revathi S. Rajan, Pratibha Malik, Nupur Garg, Smitha Avula, Kamini A. Rao

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This study aimed to analyse the pregnancy outcomes in patients with TPO positivity after appropriate L-Thyroxin supplementation with close surveillance. All pregnant women attending the antenatal clinic at Milann-The Fertility Center, Bangalore, India- from Aug 2013 to Oct 2014 whose booking TSH was more than 2.5 mIU/L were included along with those pregnant women with prior hypothyroidism who were TPO positive. Those with TPO positive status were vigorously managed with appropriate thyroxin supplementation and the doses were readjusted every 3 to 4 weeks until delivery. Women with recurrent pregnancy loss were also tested for TPO positivity and if tested positive, were monitored serially with TSH and fT4 levels every 3 to 4 weeks and appropriately supplemented with thyroxin when the levels fluctuated. The testing was done after an informed consent in all these women. The statistical software namely SAS 9.2, SPSS 15.0, Stata 10.1, MedCalc 9.0.1, Systat 12.0 and R environment ver.2.11.1 were used for the analysis of the data. 460 pregnant women were screened for thyroid dysfunction at booking of which 52% were hypothyroid. Majority of them (31.08%) were subclinically hypothyroid and the remaining were overt. 25% of the total no. of patients screened were TPO positive. The various pregnancy complications that were observed in the TPO positive women were gestational glucose intolerance [60%], threatened abortion [21%], midtrimester abortion [4.3%], premature rupture of membranes [4.3%], cervical funneling [4.3%] and fetal growth restriction [3.5%]. 95.6% of the patients who followed up till the end delivered beyond 30 weeks. 42.6% of these patients had previous history of recurrent abortions or adverse obstetric outcome and 21.7% of the delivered babies required NICU admission. Obstetric outcomes in our study in terms of midtrimester abortions, placental abruption, and preterm delivery improved for the better after close monitoring of the thyroid hormone [TSH and fT4] levels every 3 to 4 weeks with appropriate dose adjustment throughout pregnancy. Euthyroid women with TPO positive status enrolled in the study incidentally were those with recurrent abortions/infertility and required thyroxin supplements due to elevated Thyroid hormone (TSH, fT4) levels during the course of their pregnancy. Significant associations were found with age>30 years and Hyperhomocysteinemia [p=0.017], recurrent pregnancy loss or previous adverse obstetric outcomes [p=0.067] and APLA [p=0.029]. TPO antibody levels >600 I U/ml were significantly associated with development of gestational hypertension [p=0.041] and fetal growth restriction [p=0.082]. Euthyroid women with TPO positivity were also screened periodically to counter fluctuations of the thyroid hormone levels with appropriate thyroxin supplementation. Thus, early identification along with aggressive management of thyroid dysfunction and stratification of these patients based on their TPO status with appropriate thyroxin supplementation beginning in the first trimester will aid risk modulation and also help avert complications.

Keywords: TPO antibody, subclinical hypothyroidism, anti nuclear antibody, thyroxin

Procedia PDF Downloads 324

Authors: Mostafa Zandi, Ramin Mansouri

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Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. Morning-Glory spillway is one of the common spillways for discharging the overflow water behind dams, these kinds of spillways are constructed in dams with small reservoirs. In this research, the hydraulic flow characteristics of a morning-glory spillways are investigated with CFD model. Two dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k- and k-, were chosen to model Reynolds shear stress term. The power law scheme was used for discretization of momentum, k , and  equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k -ε (Standard) has the most consistent results with experimental results. When the jet is getting closer to end of basin, the computational results increase with the numerical results of their differences. The lower profile of the water jet has less sensitivity to the hydraulic jet profile than the hydraulic jet profile. In the pressure test, it was also found that the results show that the numerical values of the pressure in the lower landing number differ greatly in experimental results. The characteristics of the complex flows over a Morning-Glory spillway were studied numerically using a RANS solver. Grid study showed that numerical results of a 57512-node grid had the best agreement with the experimental values. The desired downstream channel length was preferred to be 1.5 meter, and the standard k-ε turbulence model produced the best results in Morning-Glory spillway. The numerical free-surface profiles followed the theoretical equations very well.

Keywords: morning-glory spillway, CFD model, hydraulic characteristics, wall function

Procedia PDF Downloads 77

Authors: Maged El-Sayed Mohamed

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Eucalyptus camaldulensis is one on the most well-known species of the genus Eucalyptus in the Middle east, its importance relay on the high production of its unique volatile constituents which exhibits many medicinal and pharmacological activities. The gall-forming wasp (Leptocybe invasa) has recently come into sight as the main pest attacking E. camaldulensis and causing severe injury. The wasp lays its eggs in the petiole and midrib of leaves and stems of young shoots of E. camaldulensis, which leads to gall formation. Gall formation by L. invasa damages growing shoot and leaves of Eucalyptus, resulting in abscission of leaves and drying. AIM: This study is an attempt to investigate the effect of the gall wasp (Leptocybe invasa) attack on the volatile constitutes of E. camaldulensis. This could help in the control of this wasp through stimulating plant defenses or production of a new allelochemicals or insecticide. The study of volatile constitutes of Eucalyptus before and after attack by the wasp can help the re-use and recycle of the infected Eucalyptus trees for new pharmacological and medicinal activities. Methodology: The fresh gall wasp-attacked and healthy leaves (100 g each) were cut and immediately subjected to hydrodistillation using Clevenger-type apparatus for 3 hours. The volatile fractions isolated were analyzed using Gas chromatography/mass spectrometry (GC/MS). Kovat’s retention indices (RI) were calculated with respect to a set of co-injected standard hydrocarbons (C10-C28). Compounds were identified by comparing their spectral data and retention indices with Wiley Registry of Mass Spectral Data 10th edition (April 2013), NIST 11 Mass Spectral Library (NIST11/2011/EPA/NIH) and literature data. Results: Fifty-nine components representing 89.13 and 88.60% of the total volatile fraction content respectively were quantitatively analyzed. Twenty-six major compounds at an average concentration greater than 0.1 ± 0.02% have been used for the statistical comparison. From those major components, twenty-one were found in both the attacked and healthy Eucalyptus leaves’ fractions in different concentration and five components, mono terpene p-Mentha-2-4(8) diene and the sesquiterpenes δ-elemene, β-elemene, E-caryophyllene and Bicyclogermacrene, were unique and only produced in the attacked-leaves’ fraction. CONCLUSION: Newly produced components or those commonly found in the volatile fraction and changed in concentration could represent a part of the plant defense mechanisms or might be an element of the plant allelopathic and communication mechanisms. Identification of the components of the gall wasp-damaged leaves can help in their recycling for different physiological, pharmacological and medicinal uses.

Keywords: Eucalyptus camaldulensis, eucalyptus recycling, gall wasp, Leptocybe invasa, plant defense mechanisms, Terpene fraction

Procedia PDF Downloads 358

Authors: Evgeny V. Blagin, Aleksandr I. Dovgjallo, Dmitry A. Uglanov

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This article deals with research of the working process in the thermocompressor which operates on cryogenic working fluid. Thermocompressor is device suited for the conversation of heat energy directly to the potential energy of pressure. Suggested thermocompressor is suited for operation during liquid natural gas (LNG) re-gasification and is placed after evaporator. Such application of thermocompressor allows using of the LNG cold energy for rising of working fluid pressure, which then can be used for electricity generation or another purpose. Thermocompressor consists of two chambers divided by the regenerative heat exchanger. Calculation algorithm for unsteady calculation of thermocompressor working process was suggested. The results of this investigation are to change of thermocompressor’s chambers temperature and pressure during the working cycle. These distributions help to find out the parameters, which significantly influence thermocompressor efficiency. These parameters include regenerative heat exchanger coefficient of the performance (COP) dead volume of the chambers, working frequency of the thermocompressor etc. Exergy analysis was performed to estimate thermocompressor efficiency. Cryogenic thermocompressor operated on nitrogen working fluid was chosen as a prototype. Calculation of the temperature and pressure change was performed with taking into account heat fluxes through regenerator and thermocompressor walls. Temperature of the cold chamber significantly differs from the results of steady calculation, which is caused by friction of the working fluid in regenerator and heat fluxes from the hot chamber. The rise of the cold chamber temperature leads to decreasing of thermocompressor delivery volume. Temperature of hot chamber differs negligibly because losses due to heat fluxes to a cold chamber are compensated by the friction of the working fluid in the regenerator. Optimal working frequency was selected. Main results of the investigation: -theoretical confirmation of thermocompressor operation capability on the cryogenic working fluid; -optimal working frequency was found; -value of the cold chamber temperature differs from the starting value much more than the temperature of the hot chamber; -main parameters which influence thermocompressor performance are regenerative heat exchanger COP and heat fluxes through regenerator and thermocompressor walls.

Keywords: cold energy, liquid natural gas, thermocompressor, regenerative heat exchanger

Procedia PDF Downloads 582

Authors: Evren Isen

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In grid-connected renewable energy systems, input power is controlled by AC/DC converter or/and DC/DC converter depending on output voltage of input source. The power is injected to DC-link, and DC-link voltage is regulated by inverter controlling the grid current. Inverter performance is considerable in grid-connected renewable energy systems to meet the utility standards. In this paper, modelling and simulation of hysteresis current controlled single-phase grid-connected inverter that is utilized in renewable energy systems, such as wind and solar systems, are presented. 2 kW single-phase grid-connected inverter is simulated in Simulink and modeled in Matlab-m-file. The grid current synchronization is obtained by phase locked loop (PLL) technique in dq synchronous rotating frame. Although dq-PLL can be easily implemented in three-phase systems, there is difficulty to generate β component of grid voltage in single-phase system because single-phase grid voltage exists. Inverse-Park PLL with low-pass filter is used to generate β component for grid angle determination. As grid current is controlled by constant bandwidth hysteresis current control (HCC) technique, average switching frequency and variation of switching frequency in a fundamental period are considered. 3.56% total harmonic distortion value of grid current is achieved with 0.5 A bandwidth. Average value of switching frequency and total harmonic distortion curves for different hysteresis bandwidth are obtained from model in m-file. Average switching frequency is 25.6 kHz while switching frequency varies between 14 kHz-38 kHz in a fundamental period. The average and maximum frequency difference should be considered for selection of solid state switching device, and designing driver circuit. Steady-state and dynamic response performances of the inverter depending on the input power are presented with waveforms. The control algorithm regulates the DC-link voltage by adjusting the output power.

Keywords: grid-connected inverter, hysteresis current control, inverter modelling, single-phase inverter

Procedia PDF Downloads 478

Authors: Rezvan Ravanfar Haghighi, V. C. Vani, Suresh Perumal, Sabyasachi Chatterjee, Pratik Kumar

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X-ray attenuation coefficient [µ(E)] of any substance, for energy (E), is a sum of the contributions from the Compton scattering [ μCom(E)] and photoelectric effect [µPh(E)]. In terms of the, electron density (ρe) and the effective atomic number (Zeff) we have µCom(E) is proportional to [(ρe)fKN(E)] while µPh(E) is proportional to [(ρeZeffx)/Ey] with fKN(E) being the Klein-Nishina formula, with x and y being the exponents for photoelectric effect. By taking the sample's HU at two different excitation voltages (V=V1, V2) of the CT machine, we can solve for X=ρe, Y=ρeZeffx from these two independent equations, as is attempted in DECT inversion. Since µCom(E) and µPh(E) are both energy dependent, the coefficients of inversion are also dependent on (a) the source spectrum S(E,V) and (b) the detector efficiency D(E) of the CT machine. In the present paper we tabulate these coefficients of inversion for different practical manifestations of S(E,V) and D(E). The HU(V) values from the CT follow: <µ(V)>=<µw(V)>[1+HU(V)/1000] where the subscript 'w' refers to water and the averaging process <….> accounts for the source spectrum S(E,V) and the detector efficiency D(E). Linearity of μ(E) with respect to X and Y implies that (a) <µ(V)> is a linear combination of X and Y and (b) for inversion, X and Y can be written as linear combinations of two independent observations <µ(V1)>, <µ(V2)> with V1≠V2. These coefficients of inversion would naturally depend upon S(E, V) and D(E). We numerically investigate this dependence for some practical cases, by taking V = 100 , 140 kVp, as are used for cardiological investigations. The S(E,V) are generated by using the Boone-Seibert source spectrum, being superposed on aluminium filters of different thickness lAl with 7mm≤lAl≤12mm and the D(E) is considered to be that of a typical Si[Li] solid state and GdOS scintilator detector. In the values of X and Y, found by using the calculated inversion coefficients, errors are below 2% for data with solutions of glycerol, sucrose and glucose. For low Zeff materials like propionic acid, Zeffx is overestimated by 20% with X being within1%. For high Zeffx materials like KOH the value of Zeffx is underestimated by 22% while the error in X is + 15%. These imply that the source may have additional filtering than the aluminium filter specified by the manufacturer. Also it is found that the difference in the values of the inversion coefficients for the two types of detectors is negligible. The type of the detector does not affect on the DECT inversion algorithm to find the unknown chemical characteristic of the scanned materials. The effect of the source should be considered as an important factor to calculate the coefficients of inversion.

Keywords: attenuation coefficient, computed tomography, photoelectric effect, source spectrum

Procedia PDF Downloads 400

Authors: Piotr Wisniewski, Sławomir Dykas

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Condensation has a negative impact on turbomachinery efficiency in many energy processes.In technical applications, it is often impossible to dry the working fluid at the nozzle inlet. One of the most popular working fluid is atmospheric air that always contains water in form of steam, liquid, or ice crystals. Moreover, it always contains some amount of suspended particles which influence the phase change process. It is known that the phenomena of evaporation or condensation are connected with release or absorption of latent heat, what influence the fluid physical properties and might affect the machinery efficiency therefore, the phase transition has to be taken under account. This researchpresents an attempt to evaluate the impact of solid and liquid particles suspended in the air on the expansion of moist air in a low expansion rate, i.e., with expansion rate, P≈1000s⁻¹. The numerical study supported by analytical and experimental research is presented in this work. The experimental study was carried out using an in-house experimental test rig, where nozzle was examined for different inlet air relative humidity values included in the range of 25 to 51%. The nozzle was tested for a supersonic flow as well as for flow with shock waves induced by elevated back pressure. The Schlieren photography technique and measurement of static pressure on the nozzle wall were used for qualitative identification of both condensation and shock waves. A numerical model validated against experimental data available in the literature was used for analysis of occurring flow phenomena. The analysis of the suspended particles number, diameter, and character (solid or liquid) revealed their connection with heterogeneous condensation importance. If the expansion of fluid without suspended particlesis considered, the condensation triggers so called condensation wave that appears downstream the nozzle throat. If the solid particles are considered, with increasing number of them, the condensation triggers upwind the nozzle throat, decreasing the condensation wave strength. Due to the release of latent heat during condensation, the fluid temperature and pressure increase, leading to the shift of normal shock upstream the flow. Owing relatively large diameters of the droplets created during heterogeneous condensation, they evaporate partially on the shock and continues to evaporate downstream the nozzle. If the liquid water particles are considered, due to their larger radius, their do not affect the expanding flow significantly, however might be in major importance while considering the compression phenomena as they will tend to evaporate on the shock wave. This research proves the need of further study of phase change phenomena in supersonic flow especially considering the interaction of droplets with the aerodynamic waves in the flow.

Keywords: aerodynamics, computational fluid dynamics, condensation, moist air, multi-phase flows

Procedia PDF Downloads 118

Authors: Berfin Yildiz

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These days, increasing global warming effects, limited amount of energy resources, etc., necessitates the awareness that must be present in every profession group. The architecture and construction sectors are responsible for both the embodied and operational energy of the materials. This responsibility has led designers to seek alternative solutions for energy-efficient material selection. The choice of energy-efficient material requires consideration of the entire life cycle, including the building's production, use, and disposal energy. The aim of this study is to investigate the method of material selection of external thermal insulation composite systems (ETICS). Embodied and in-use energy values of material alternatives were used for the evaluation in this study. The operational energy is calculated according to the u-value calculation method defined in the TS 825 (Thermal Insulation Requirements) standard for Turkey, and the embodied energy is calculated based on the manufacturer's Energy Performance Declaration (EPD). ETICS consists of a wall, adhesive, insulation, lining, mechanical, mesh, and exterior finishing materials. In this study, lining, mechanical, and mesh materials were ignored because EPD documents could not be obtained. The material selection problem is designed as a hypothetical volume area (5x5x3m) and defined as a multi-objective discrete optimization problem for external thermal insulation composite systems. Defining the problem as a discrete optimization problem is important in order to choose between materials of various thicknesses and sizes. Since production and use energy values, which are determined as optimization objectives in the study, are often conflicting values, material selection is defined as a multi-objective optimization problem, and it is aimed to obtain many solution alternatives by using Hypervolume (HypE) algorithm. The enrollment process started with 100 individuals and continued for 50 generations. According to the obtained results, it was observed that autoclaved aerated concrete and Ponce block as wall material, glass wool, as insulation material gave better results.

Keywords: embodied energy, multi-objective discrete optimization, performative design, thermal insulation

Procedia PDF Downloads 141

Authors: Susan C. Graham

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Islands have a long established allure for travellers the world over. From earliest accounts of human history, travellers were drawn by the sense of islandness embodied by these destinations. The concept of islandness describes the essence of what makes islands unique relative to non-islands and extends beyond geographic interpretations by attempting to capture the specific sense of self-exhibited by islanders in relation to their connection to place. The themes most strongly associated with islandness include a) a strong connection to water as both the life blood and a physical barrier, b) a unique culture and robust arts community that is deeply linked to both the island and islanders, c) an appreciation of and for nature, d) a rich sense of history and tradition connected to the place, e) a sense of community and belonging that arose through shared triumphs and struggles, and f) a profound awareness of independence, separateness, and uniqueness derived from both physical and social experience. The island brand, like all brands, is a marketing tactic designed to succinctly express a specific value proposition in simplistic ways which might include a brand symbol, logo, slogan, or representation meant to distinguish one brand from another. If a value proposition is the identification of attributes that separate one brand from another by highlighting the brand’s uniqueness, then presumably island brands may, at least in part, emphasize islandness as part of the destination brand. Yet it may in naïve to expect all islands to brand themselves using similar themes when islands can differ so substantially in terms of population, geography, political climate, economy, culture, and history. Of particular interest is the increased focus on tourism among 'cold-water' islands. This paper will examine the incorporation of themes related to islandness in tourism branding among cold-water, warm-water, and temperate-water islands. The tourism logos of 83 islands were collected and assessed for the use of themes related to islandness, namely water, arts and culture, nature, history and tradition, community and belongingness, and independence, separateness, and uniqueness. The ratings for each theme related to islandness for each of the 83 island destinations were then analyzed to identify if differences exist between cold-water, warm-water, and temperate-water islands. A general consensus of what constitutes 'cold-water' destinations is lacking, therefore a water temperature of 15C was adopted using the guidelines from the National Center for Cold Water Safety. Among these 83 islands, the average high and average low water temperatures of 196 specific locations, including the capital, northern, and southern most points of each island, was recorded to determine if the location was a cold-water (average high and low below 15C), warm-water (average high and low above 15C), or temperate-water (average high above 15C and low below 15C) location.

Keywords: branding, cold-water, islands, tourism

Procedia PDF Downloads 224

Authors: Anna Fowler

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When considering assets that may need protection, the mind begins to contemplate homes, cars, and investment funds. In most cases, the protection of those assets can be covered through security systems and insurance. Data is not the first thought that comes to mind that would need protection, even though data is at the core of most supply chain operations. It includes trade secrets, management of personal identifiable information (PII), and consumer data that can be used to enhance the overall experience. Data is considered a critical element of success for supply chains and should be one of the most critical areas to protect. In the supply chain industry, there are two major misconceptions about protecting data: (i) We do not manage or store confidential/personally identifiable information (PII). (ii) Reliance on Third-Party vendor security. These misconceptions can significantly derail organizational efforts to adequately protect data across environments. These statistics can be exciting yet overwhelming at the same time. The first misconception, “We do not manage or store confidential/personally identifiable information (PII)” is dangerous as it implies the organization does not have proper data literacy. Enterprise employees will zero in on the aspect of PII while neglecting trade secret theft and the complete breakdown of information sharing. To circumvent the first bullet point, the second bullet point forges an ideology that “Reliance on Third-Party vendor security” will absolve the company from security risk. Instead, third-party risk has grown over the last two years and is one of the major causes of data security breaches. It is important to understand that a holistic approach should be considered when protecting data which should not involve purchasing a Data Loss Prevention (DLP) tool. A tool is not a solution. To protect supply chain data, start by providing data literacy training to all employees and negotiating the security component of contracts with vendors to highlight data literacy training for individuals/teams that may access company data. It is also important to understand the origin of the data and its movement to include risk identification. Ensure processes effectively incorporate data security principles. Evaluate and select DLP solutions to address specific concerns/use cases in conjunction with data visibility. These approaches are part of a broader solutions framework called Data Security Assurance (DSA). The DSA Framework looks at all of the processes across the supply chain, including their corresponding architecture and workflows, employee data literacy, governance and controls, integration between third and fourth-party vendors, DLP as a solution concept, and policies related to data residency. Within cloud environments, this framework is crucial for the supply chain industry to avoid regulatory implications and third/fourth party risk.

Keywords: security by design, data security architecture, cybersecurity framework, data security assurance

Procedia PDF Downloads 88

Authors: Naser Kazemi Eilaki, Carolyn Ahmer, Ilona Heldal, Bjarne Christian Hagen

Abstract:

Older people and people with disabilities are recognized as at-risk groups when it comes to egress and travel from hazard zone to safe places. One's disability can negatively influence her or his escape time, and this becomes even more important when people from this target group live alone. This research deals with the fire safety of mentioned people's buildings by means of probabilistic methods. For this purpose, fire safety is addressed by modeling the egress of our target group from a hazardous zone to a safe zone. A common type of detached house with a prevalent plan has been chosen for safety analysis, and a limit state function has been developed according to the time-line evacuation model, which is based on a two-zone and smoke development model. An analytical computer model (B-Risk) is used to consider smoke development. Since most of the involved parameters in the fire development model pose uncertainty, an appropriate probability distribution function has been considered for each one of the variables with indeterministic nature. To achieve safety and reliability for the at-risk groups, the fire safety index method has been chosen to define the probability of failure (causalities) and safety index (beta index). An improved harmony search meta-heuristic optimization algorithm has been used to define the beta index. Sensitivity analysis has been done to define the most important and effective parameters for the fire safety of the at-risk group. Results showed an area of openings and intervals to egress exits are more important in buildings, and the safety of people would improve with increasing dimensions of occupant space (building). Fire growth is more critical compared to other parameters in the home without a detector and fire distinguishing system, but in a home equipped with these facilities, it is less important. Type of disabilities has a great effect on the safety level of people who live in the same home layout, and people with visual impairment encounter more risk of capturing compared to visual and movement disabilities.

Keywords: fire safety, at-risk groups, zone model, egress time, uncertainty

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