Search results for: higher order inertia

Authors: Gabrielle Peck, Ryan Hayes

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Polyurethane (PU) foam is typically sold as acoustic foam that is often used as sound insulation in settings such as night clubs and bars. As a construction product, PU is tested by being glued to the walls and ceiling of the ISO 9705 room corner test room. However, when heat is applied to PU foam, it melts and burns as a pool fire due to it being a thermoplastic. The current test layout is unable to accurately measure mass loss and doesn’t allow for the material to burn as a pool fire without seeping out of the test room floor. The lack of mass loss measurement means gas yields pertaining to smoke toxicity analysis can’t be calculated, which makes data comparisons from any other material or test method difficult. Additionally, the heat release measurements are not representative of the actual measurements taken as a lot of the material seeps through the floor (when a tray to catch the melted material is not used). This research aimed to modify the ISO 9705 test to provide the ability to measure mass loss to allow for better calculation of gas yields and understanding of decomposition. It also aimed to accurately measure smoke toxicity in both the doorway and duct and enable dilution factors to be calculated. Finally, the study aimed to examine if doubling the fuel loading would force under-ventilated flaming. The test layout was modified to be a combination of the SBI (single burning item) test set up inside oof the ISO 9705 test room. Polyurethane was tested in two different ways with the aim of altering the ventilation condition of the tests. Test one was conducted using 1 x SBI test rig aiming for well-ventilated flaming. Test two was conducted using 2 x SBI rigs (facing each other inside the test room) (doubling the fuel loading) aiming for under-ventilated flaming. The two different configurations used were successful in achieving both well-ventilated flaming and under-ventilated flaming, shown by the measured equivalence ratios (measured using a phi meter designed and created for these experiments). The findings show that doubling the fuel loading will successfully force under-ventilated flaming conditions to be achieved. This method can therefore be used when trying to replicate post-flashover conditions in future ISO 9705 room corner tests. The radiative heat generated by the two SBI rigs facing each other facilitated a much higher overall heat release resulting in a more severe fire. The method successfully allowed for accurate measurement of smoke toxicity produced from the PU foam in terms of simple gases such as oxygen depletion, CO and CO2. Overall, the proposed test modifications improve the ability to measure the smoke toxicity of materials in different fire conditions on a large-scale.

Keywords: flammability, ISO9705, large-scale testing, polyurethane, smoke toxicity

Procedia PDF Downloads 81

Authors: Awole Seid, Yosef Zenebe, Hadgu Gerensea, Kebede Haile Misgina

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Background: Clinical competence is one of the ultimate goals of nursing education. Clinical skills are more than successfully performing tasks; it incorporates client assessment, identification of deficits and the ability to critically think to provide solutions. Assessment of clinical competence, particularly identifying gaps that need improvement and determining the educational needs of nursing students have great importance in nursing education. Thus this study aims determining clinical self-efficacy of final year school of nursing students in three universities of Tigray Region. Methods: A cross-sectional study was conducted on 224 final year school of nursing students from department of nursing, psychiatric nursing, and midwifery on three universities of Tigray region. Anonymous self-administered questionnaire was administered to generate data collected on June, 2017. The data were analyzed using SPSS version 20. The result is described using tables and charts as required. Logistic regression was employed to test associations. Result: The mean age of students was 22.94 + 1.44. Generally, 21% of students have been graduated in the department in which they are not interested. The study demonstrated 28.6% had poor and 71.4% had good perceived clinical self-efficacy. Beside this, 43.8% of psychiatric nursing and 32.6% of comprehensive nursing students have poor clinical self-efficacy. Among the four domains, 39.3% and 37.9% have poor clinical self- efficacy with regard to ‘Professional development’ and ‘Management of care’. Place of the institution [AOR=3.480 (1.333 - 9.088), p=0.011], interest during department selection [AOR=2.202 (1.045 - 4.642), p=.038], and theory-practice gap [AOR=0.224 (0.110 - 0.457), p=0.000] were significantly associated with perceived clinical self-efficacy. Conclusion: The magnitude of students with poor clinically self efficacy was high. Place of institution, theory-practice gap, students interest to the discipline were the significant predictors of clinical self-efficacy. Students from youngest universities have good clinical self-efficacy. During department selection, student’s interest should be respected. The universities and other stakeholders should improve the capacity of surrounding affiliate teaching hospitals to set and improve care standards in order to narrow the theory-practice gap. School faculties should provide trainings to hospital staffs and monitor standards of clinical procedures.

Keywords: clinical self-efficacy, nursing students, Tigray, northern Ethiopia

Procedia PDF Downloads 176

Authors: Koryukaeva Ksenia, Jinfeng Sun

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Europe has been a traditional importer of Russian natural gas for more than 50 years. In 2021, Russian state-owned company Gazprom supplied about a third of all gas consumed in Europe. The Russia-Europe mutual dependence in terms of natural gas supplies has been causing many concerns about the energy security of the two sides for a long period of time. These days the issue has become more urgent than ever considering recent Russian invasion in Ukraine followed by increased large-scale geopolitical conflicts, making the future of Russian natural gas supplies and global gas markets as well highly uncertain. Hence, the main purpose of this study is to get insight into the possible futures of Russian pipeline natural gas exports by a scenario planning method based on Monte-Carlo simulation within LUSS model framework, and propose Russian pipeline natural gas export strategies based on the obtained scenario planning results. The scenario analysis revealed that recent geopolitical disputes disturbed the traditional, longstanding model of Russian pipeline gas exports, and, as a result, the prospects and the pathways for Russian pipeline gas on the world markets will differ significantly from those before 2022. Specifically, our main findings show, that (i) the events of 2022 generated many uncertainties for the long-term future of Russian pipeline gas export perspectives on both western and eastern supply directions, including geopolitical, regulatory, economic, infrastructure and other uncertainties; (ii) according to scenario modelling results, Russian pipeline exports will face many challenges in the future, both on western and eastern directions. A decrease in pipeline gas exports will inevitably affect country’s natural gas production and significantly reduce fossil fuel export revenues, jeopardizing the energy security of the country; (iii) according to proposed strategies, in order to ensure the long-term stable export supplies in the changing environment, Russia may need to adjust its traditional export strategy by performing export flows and product diversification, entering new markets, adapting its contracting mechanism, increasing competitiveness and gaining a reputation of a reliable gas supplier.

Keywords: Russian natural gas, Pipeline natural gas, Uncertainty, Scenario simulation, Export strategy

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Authors: B. Casper

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The energy transition towards renewable energies and drastically reduced carbon dioxide emissions in Germany drives multiple sectors into a transformation process. Photovoltaic and on-shore wind power are predominantly feeding in the low and medium-voltage grids. The electricity grid is not laid out to allow an increasing feed-in of power in low and medium voltage grids. Electric mobility is currently in the run-up phase in Germany and still lacks a significant amount of charging stations. The additional power demand by e-mobility cannot be supplied by the existing electric grids in most cases. The future demands in heating and cooling of commercial and residential buildings are increasingly generated by heat-pumps. Yet the most important part in the energy transition is the storage of surplus energy generated by photovoltaic and wind power sources. Water electrolysis is one way to store surplus energy known as power-to-gas. With the vehicle-to-grid technology, the upcoming fleet of electric cars could be used as energy storage to stabilize the grid. All these processes use direct current (DC). The demand of bi-directional flow and higher efficiency in the future grids can be met by using DC. The Flexible Electrical Networks (FEN) research campus at RWTH Aachen investigates interdisciplinary about the advantages, opportunities, and limitations of DC grids. This paper investigates the impact of DC grids as a technological innovation on the urban form and urban life. Applying explorative scenario development, analyzation of mapped open data sources on grid networks and research-by-design as a conceptual design method, possible starting points for a transformation to DC medium voltage grids could be found. Several fields of action have emerged in which DC technology could become a catalyst for future urban development: energy transition in urban areas, e-mobility, and transformation of the network infrastructure. The investigation shows a significant potential to increase renewable energy production within cities with DC grids. The charging infrastructure for electric vehicles will predominantly be using DC in the future because fast and ultra fast charging can only be achieved with DC. Our research shows that e-mobility, combined with autonomous driving has the potential to change the urban space and urban logistics fundamentally. Furthermore, there are possible win-win-win solutions for the municipality, the grid operator and the inhabitants: replacing overhead transmission lines by underground DC cables to open up spaces in contested urban areas can lead to a positive example of how the energy transition can contribute to a more sustainable urban structure. The outlook makes clear that target grid planning and urban planning will increasingly need to be synchronized.

Keywords: direct current, e-mobility, energy transition, grid planning, renewable energy, urban planning

Procedia PDF Downloads 131

Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

Procedia PDF Downloads 191

Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

Procedia PDF Downloads 110

Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

Procedia PDF Downloads 111

Authors: Aldona Kluczek

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Energy efficient process have become a pressing research field in manufacturing. The arguments for having an effective industrial energy efficiency processes are interacted with factors: economic and environmental impact, and energy security. Improvements in energy efficiency are most often achieved by implementation of more efficient technology or manufacturing process. Current processes of electricity production represents the biggest consumption of energy and the greatest amount of emissions to the environment. The goal of this study is to improve the potential energy-savings and reduce greenhouse emissions related to improvement scenarios for the treatment of hardwood lumber produced by an industrial plant operating in the U.S. through the application of green balancing procedure, in order to find the preferable efficient technology. The green procedure for energy is based on analysis of energy efficiency data. Three alternative scenarios of the cogeneration systems plant (CHP) construction are considered: generation of fresh steam, the purchase of a new boiler with the operating pressure 300 pounds per square inch gauge (PSIG), an installation of a new boiler with a 600 PSIG pressure. In this paper, the application of a bottom-down modelling for energy flow to devise a streamlined Energy and Emission Flow Analyze method for the technology of producing electricity is illustrated. It will identify efficiency or technology of a given process to be reached, through the effective use of energy, or energy management. Results have shown that the third scenario seem to be the efficient alternative scenario considered from the environmental and economic concerns for treating hardwood lumber. The energy conservation evaluation options could save an estimated 6,215.78 MMBtu/yr in each year, which represents 9.5% of the total annual energy usage. The total annual potential cost savings from all recommendations is $143,523/yr, which represents 30.1% of the total annual energy costs. Estimation have presented that energy cost savings are possible up to 43% (US$ 143,337.85), representing 18.6% of the total annual energy costs.

Keywords: alternative scenario improvements, cogeneration system, energy and emission flow analyze, energy balancing, green procedure, hardwood lumber manufacturing process

Procedia PDF Downloads 213

Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

Procedia PDF Downloads 335

Authors: Nathaniel Oladimeji Dixon, Adekemi Dorcas Fadun

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Educational managers have observed a downward trend in the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. This is evident in the low-quality service delivery of administrators and unaccomplished institutional goals and missions of higher education. Scholars have thus indicated the need for the deployment and adoption of a practice that encourages information collection and sharing among stakeholders with a view to improving service delivery and outcomes. This study examined the extent to which knowledge management correlated with the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. The study adopted the survey design. Three federal universities (the University of Ibadan, Federal University of Agriculture, Abeokuta, and Obafemi Awolowo University) were purposively selected because administrative ineffectiveness was more pronounced among non-teaching staff in government-owned universities, and these federal universities were long established. The proportional and stratified random sampling was adopted to select 1156 non-teaching staff across the three universities along the three existing layers of the non-teaching staff: secretarial (senior=311; junior=224), non-secretarial (senior=147; junior=241) and technicians (senior=130; junior=103). Knowledge Management Practices Questionnaire with four sub-scales: knowledge creation (α=0.72), knowledge utilization (α=0.76), knowledge sharing (α=0.79) and knowledge transfer (α=0.83); and Administrative Effectiveness Questionnaire with four sub-scales: communication (α=0.84), decision implementation (α=0.75), service delivery (α=0.81) and interpersonal relationship (α=0.78) were used for data collection. Data were analyzed using descriptive statistics, Pearson product-moment correlation and multiple regression at 0.05 level of significance, while qualitative data were content analyzed. About 59.8% of the non-teaching staff exhibited a low level of knowledge management. The indices of administrative effectiveness of non-teaching staff were rated as follows: service delivery (82.0%), communication (78.0%), decision implementation (71.0%) and interpersonal relationship (68.0%). Knowledge management had significant relationships with the indices of administrative effectiveness: service delivery (r=0.82), communication (r=0.81), decision implementation (r=0.80) and interpersonal relationship (r=0.47). Knowledge management had a significant joint prediction on administrative effectiveness (F (4;1151)= 0.79, R=0.86), accounting for 73.0% of its variance. Knowledge sharing (β=0.38), knowledge transfer (β=0.26), knowledge utilization (β=0.22), and knowledge creation (β=0.06) had relatively significant contributions to administrative effectiveness. Lack of team spirit and withdrawal syndrome is the major perceived constraints to knowledge management practices among the non-teaching staff. Knowledge management positively influenced the administrative effectiveness of the non-teaching staff in federal universities in South-west Nigeria. There is a need to ensure that the non-teaching staff imbibe team spirit and embrace teamwork with a view to eliminating their withdrawal syndromes. Besides, knowledge management practices should be deployed into the administrative procedures of the university system.

Keywords: knowledge management, administrative effectiveness of non-teaching staff, federal universities in the south-west of nigeria., knowledge creation, knowledge utilization, effective communication, decision implementation

Procedia PDF Downloads 108

Authors: Zameerpal Kaur

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Ecocriticism comes into existence in 1990s, it tries to explore the relationship of literature with the natural world and further it examines the role that natural surroundings and environment play in the minds of the creative writers during their imagination and creative process. The present study is an attempt to focus on the comparative ecocritical analysis of Shiv Kumar Batalvi and Surjit Patar’s selected poetry in the theoretical framework of ecocriticism in order to shed light on the poet’s vigilant views about the relationship of human life and nature. Shiv Kumar Batalvi is a renowned modern Punjabi poet. He is essentially a poet of nature and love. His opinions towards nature support his position to be considered as a major representative of recent environmental issues and ecocritical concerns in Punjabi literature. He is one of the most outstanding modern Punjabi poets, is endowed with the most artistic temperament in whose poetry nature always has a dominating existence. He seems to consciously portray the scenes of natural surroundings into his poetry; in fact the titles of his poems in themselves signify his love for the nature. Surjit Patar, an imminent modern Punjabi poet tries to present a different picture of nature into his poems; he also uses to write poems about contemporary problems. Surjit Patar’s radical quarrel with the modern cultural context makes him reject all the absolutes and finalities in the form of transcendental reason and religion, history and evolution, he freely writes about the deterioration of nature at selfish materialistic society. He is modern poet who weaves the natural imagery with the syntax of his poems. Patar’s work reflects a universal voice that is dribbled with nuanced humanism and a sense of modernity that seemed neither dated, nor trapped in regional boundaries. Through his poetry he has given a voice to the fragile, disrupting borders, disturbing the status quo. An attempt to analyse the poetic works of above said poets from ecocritical perspective as well as especially focussing on various aspects of ecocriticism like ecocentric ethics, ecoaesthetics, anthropomorphism etc. has been made throughout the comparative study of the selected works.

Keywords: anthropocentrism, degradation, environment and literature, nature

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Authors: Adam Majczak, Michał Bialy, Zbigniew Czyż, Zdzislaw Kaminski

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Increasingly stringent emission standards for passenger cars require us to find alternative drives. The share of electric vehicles in the sale of new cars increases every year. However, their performance and, above all, range cannot be today successfully compared to those of cars with a traditional internal combustion engine. Battery recharging lasts hours, which can be hardly accepted due to the time needed to refill a fuel tank. Therefore, the ways to reduce the adverse features of cars equipped with electric motors only are searched for. One of the methods is a combination of an electric engine as a main source of power and a small internal combustion engine as an electricity generator. This type of drive enables an electric vehicle to achieve a radically increased range and low emissions of toxic substances. For several years, the leading automotive manufacturers like the Mazda and the Audi together with the best companies in the automotive industry, e.g., AVL have developed some electric drive systems capable of recharging themselves while driving, known as a range extender. An electricity generator is powered by a Wankel engine that has seemed to pass into history. This low weight and small engine with a rotating piston and a very low vibration level turned out to be an excellent source in such applications. Its operation as an energy source for a generator almost entirely eliminates its disadvantages like high fuel consumption, high emission of toxic substances, or short lifetime typical of its traditional application. The operation of the engine at a constant rotational speed enables a significant increase in its lifetime, and its small external dimensions enable us to make compact modules to drive even small urban cars like the Audi A1 or the Mazda 2. The algorithm to maintain a constant speed was investigated on the engine dynamometer with an eddy current brake and the necessary measuring apparatus. The research object was the Aixro XR50 rotary engine with the electronic power supply developed at the Lublin University of Technology. The load torque of the engine was altered during the research by means of the eddy current brake capable of giving any number of load cycles. The parameters recorded included speed and torque as well as a position of a throttle in an inlet system. Increasing and decreasing load did not significantly change engine speed, which means that control algorithm parameters are correctly selected. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: electric vehicle, power generator, range extender, Wankel engine

Procedia PDF Downloads 157

Authors: Emmanuel Jaluchimike Iloputaife, Kelechi Nkechinyere Mbah-Omeje

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This study was designed to determine the antimicrobial activities and minimum inhibitory concentration of three different batches (Fresh, Oven dried and Sundried) of Ass Hay extracted with water, ethanol and methanolagainst selected human pathogenic microorganisms (Escherichia coli, Klebsiella Pneumonia, Staphylococcus aureus, Aspergillus niger and Candidaalbicans). All extracts were reconstituted with peptone water and tested for antimicrobial activity. The antimicrobial activity, the Minimum Inhibitory Concentration and Minimum Bactericidal/Fungicidal concentrations were determined by agar well diffusion methodagainst test organismsin which aseptic conditions were observed. The antimicrobial activities of the different batches of Ass Hay on the test organisms varied considerably. The highest inhibition zone diameter at 200 mg/ml for the different batches of Ass Hay was recorded by sundried methanol extract against Escherichia coli at 36.4 ± 0.2 mm while fresh methanol extract inhibited Klebsiela pneumonia with the least inhibition zone diameter at 20.1 ± 0.1mm. At 100 mg/ml the highest inhibition zone diameter was recorded by oven dried water extract against Escherichia coli at 30.3 ± 0.3 mm while sun dried water extract inhibited Staphylococcus aureus with the least inhibition zone diameter at 15.1 ± 0.1 mm. At 50mg/ml, the highest inhibition zone diameter was recorded by fresh water extract against Escherichia coli at 25.9 ± 0.1 mm while oven dried water extract inhibited Klebsiela pneumonia with least inhibition zone diameter at 12.1 ± 0.2 mm. At 25mg/ml, the highest inhibition zone diameter was recorded by fresh water extract against Escherichia coli at 18.3 ± 0.2 mm while sun dried ethanol extract inhibited Escherichia coli with least inhibition zone diameter at 10.1 ± 0.1 mm. The MIC and MBC result of ethanol extract of fresh Ass Hay showed a uniform value of 6.25 mg/ml and 12.5 mg/ml respectively for all test bacterial isolates. The Minimum Inhibitory concentration and Minimum bactericidal concentration results of Oven dried ethanol Ass Hay extract showed a uniform value of 3.125 mg/ml and 6.25 mg/ml respectively for all test bacterial isolates and Minimum fungicidal concentration value of 12.5 mg/ml for Aspergillus niger. Statistical analysis showed there is significant difference in mean zone inhibition diameter of the products at p < 0.05, p = 0.019. This study has shown there is antimicrobial potential in Ass Hay and at such there is need to further exploit Donkey Ass Hay in order to maximize the potential.

Keywords: microorganisms, Ass Hay, antimicrobial activity, extracts

Procedia PDF Downloads 142

Authors: Y. Landkocz, C. Lepers, P.J. Martin, B. Fougère, F. Roy Saint-Georges. A. Verdin, F. Cazier, F. Ledoux, D. Courcot, F. Sichel, P. Gosset, P. Shirali, S. Billet

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In 2013, the International Agency for Research on Cancer (IARC) classified air pollution and fine particles as carcinogenic to humans. Causal relationships exist between elevated ambient levels of airborne particles and increase of mortality and morbidity including pulmonary diseases, like lung cancer. However, due to a double complexity of both physicochemical Particulate Matter (PM) properties and tumor mechanistic processes, mechanisms of action remain not fully elucidated. Furthermore, because of several common properties between air pollution PM and tobacco smoke, like the same route of exposure and chemical composition, potential mechanisms of synergy could exist. Therefore, smoking could be an aggravating factor of the particles toxicity. In order to identify some mechanisms of action of particles according to their size, two samples of PM were collected: PM0.03 2.5 and PM0.33 2.5 in the urban-industrial area of Dunkerque. The overall cytotoxicity of the fine particles was determined on human bronchial cells (BEAS-2B). Toxicological study focused then on the metabolic activation of the organic compounds coated onto PM and some genetic and epigenetic changes induced on a co-culture model of BEAS-2B and alveolar macrophages isolated from bronchoalveolar lavages performed in smokers and non-smokers. The results showed (i) the contribution of the ultrafine fraction of atmospheric particles to genotoxic (eg. DNA double-strand breaks) and epigenetic mechanisms (eg. promoter methylation) involved in tumor processes, and (ii) the influence of smoking on the cellular response. Three main conclusions can be discussed. First, our results showed the ability of the particles to induce deleterious effects potentially involved in the stages of initiation and promotion of carcinogenesis. The second conclusion is that smoking affects the nature of the induced genotoxic effects. Finally, the in vitro developed cell model, using bronchial epithelial cells and alveolar macrophages can take into account quite realistically, some of the existing cell interactions existing in the lung.

Keywords: air pollution, fine and ultrafine particles, genotoxic and epigenetic alterations, smoking

Procedia PDF Downloads 349

Authors: Tomasz Dubiel, Tadeusz Balawender, Miroslaw Osetek

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The paper presents the influence of non-metallic inclusions on the multi-stage forging process and the mechanical properties of the dodecagon socket bolt used in the automotive industry. The detected metallurgical defect was so large that it directly influenced the mechanical properties of the bolt and resulted in failure to meet the requirements of the mechanical property class. In order to assess the defect, an X-ray examination and metallographic examination of the defective bolt were performed, showing exogenous non-metallic inclusion. The size of the defect on the cross-section was 0.531 [mm] in width and 1.523 [mm] in length; the defect was continuous along the entire axis of the bolt. In analysis, a FEM simulation of the multi-stage forging process was designed, taking into account a non-metallic inclusion parallel to the sample axis, reflecting the studied case. The process of defect propagation due to material upset in the head area was analyzed. The final forging stage in shaping the dodecagonal socket and filling the flange area was particularly studied. The effect of the defect was observed to significantly reduce the effective cross-section as a result of the expansion of the defect perpendicular to the axis of the bolt. The mechanical properties of products with and without the defect were analyzed. In the first step, the hardness test confirmed that the required value for the mechanical class 8.8 of both bolt types was obtained. In the second step, the bolts were subjected to a static tensile test. The bolts without the defect gave a positive result, while all 10 bolts with the defect gave a negative result, achieving a tensile strength below the requirements. Tensile strength tests were confirmed by metallographic tests and FEM simulation with perpendicular inclusion spread in the area of the head. The bolts were damaged directly under the bolt head, which is inconsistent with the requirements of ISO 898-1. It has been shown that non-metallic inclusions with orientation in accordance with the axis of the bolt can directly cause loss of functionality and these defects should be detected even before assembling in the machine element.

Keywords: continuous casting, multi-stage forging, non-metallic inclusion, upset bolt head

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Authors: Ruth Diego, Luis M. Romeo, Antonio Morán

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In the present work, a study of the coupling of a Bioelectrochemical System together with an oxy-combustion boiler is carried out; specifically, it proposes to connect the combustion gas outlet of a boiler with a microbial electrolysis cell (MEC) where the CO2 from the gases are transformed into methane in the cathode chamber, and the oxygen produced in the anode chamber is recirculated to the oxy-combustion boiler. The MEC mainly consists of two electrodes (anode and cathode) immersed in an aqueous electrolyte; these electrodes are separated by a proton exchange membrane (PEM). In this case, the anode is abiotic (where oxygen is produced), and it is at the cathode that an electroactive biofilm is formed with microorganisms that catalyze the CO2 reduction reactions. Real data from an oxy-combustion process in a boiler of around 20 thermal MW have been used for this study and are combined with data obtained on a smaller scale (laboratory-pilot scale) to determine the yields that could be obtained considering the system as environmentally sustainable energy storage. In this way, an attempt is made to integrate a relatively conventional energy production system (oxy-combustion) with a biological system (microbial electrolysis cell), which is a challenge to be addressed in this type of new hybrid scheme. In this way, a novel concept is presented with the basic dimensioning of the necessary equipment and the efficiency of the global process. In this work, it has been calculated that the efficiency of this power-to-gas system based on MEC cells when coupled to industrial processes is of the same order of magnitude as the most promising equivalent routes. The proposed process has two main limitations, the overpotentials in the electrodes that penalize the overall efficiency and the need for storage tanks for the process gases. The results of the calculations carried out in this work show that certain real potentials achieve an acceptable performance. Regarding the tanks, with adequate dimensioning, it is possible to achieve complete autonomy. The proposed system called OxyMES provides energy storage without energetically penalizing the process when compared to an oxy-combustion plant with conventional CO2 capture. According to the results obtained, this system can be applied as a measure to decarbonize an industry, changing the original fuel of the oxy-combustion boiler to the biogas generated in the MEC cell. It could also be used to neutralize CO2 emissions from industry by converting it to methane and then injecting it into the natural gas grid.

Keywords: microbial electrolysis cells, oxy-combustion, co2, power-to-gas

Procedia PDF Downloads 113

Authors: Chih-Chung Huang, Po-Hsun Peng

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Ultrasound transient elastography has become a valuable tool for many clinical diagnoses, such as liver diseases and breast cancer. The pathological tissue can be distinguished by elastography due to its stiffness is different from surrounding normal tissues. An ultrafast frame rate of ultrasound imaging is needed for transient elastography modality. The elastography obtained in the ultrafast system suffers from a low quality for resolution, and affects the robustness of the transient elastography. In order to overcome these problems, a coherent plane wave compounding technique has been proposed for conventional ultrasound system which the operating frequency is around 3-15 MHz. The purpose of this study is to develop a novel beamforming technique for high frequency ultrasound coherent plane-wave compounding imaging and the simulated results will provide the standards for hardware developments. Plane-wave compounding imaging produces a series of low-resolution images, which fires whole elements of an array transducer in one shot with different inclination angles and receives the echoes by conventional beamforming, and compounds them coherently. Simulations of plane-wave compounding image and focused transmit image were performed using Field II. All images were produced by point spread functions (PSFs) and cyst phantoms with a 64-element linear array working at 35MHz center frequency, 55% bandwidth, and pitch of 0.05 mm. The F number is 1.55 in all the simulations. The simulated results of PSFs and cyst phantom which were obtained using single, 17, 43 angles plane wave transmission (angle of each plane wave is separated by 0.75 degree), and focused transmission. The resolution and contrast of image were improved with the number of angles of firing plane wave. The lateral resolutions for different methods were measured by -10 dB lateral beam width. Comparison of the plane-wave compounding image and focused transmit image, both images exhibited the same lateral resolution of 70 um as 37 angles were performed. The lateral resolution can reach 55 um as the plane-wave was compounded 47 angles. All the results show the potential of using high-frequency plane-wave compound imaging for realizing the elastic properties of the microstructure tissue, such as eye, skin and vessel walls in the future.

Keywords: plane wave imaging, high frequency ultrasound, elastography, beamforming

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Fathimath Warda, Mariyam Nihaadh

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Students with Special Education Needs (SEN) are increasing in the Maldives, like anywhere else in the world, due to the changes in lifestyle of the people and ease of being diagnosed with advancements in medical health. With the growth in the population of these students, the demand for professionals in various fields is unmet. Thus, with the introduction of the Inclusive Education Policy in 2013, all students are educated in the same classroom by the regular teacher. This poses problems as the teachers are not well trained and qualified to meet the varying needs of the students, given the limited time and the large number of students in the classroom. This is a major concern for all stakeholders in the education sector and research has been conducted by various local scholars in this area. However, studies on the role of parents of such students is an area that remains yet to be explored in the Maldives, which makes a study of this nature crucial. The main aim of this study is to determine the ways in which the education provided to Special Needs Students can be maximized for a better outcome. Therefore, the study intends to understand the involvement of parents in providing education to special needs students from the teachers' perspectives. The basis for this study is the Parent Development Theory developed by Mowder, which was initially known as Parent Role Development Theory. A qualitative research has thus been utilised for the purpose of the study as it requires to find the beliefs and attitudes of teachers, along with relevant justifications regarding the role of parents in educating students with special needs. Data was gathered using one-to-one interviews, as it is one of the most reliable ways of getting meaningful and in-depth data. The study employs a total of 8 participants who are teachers teaching in inclusive classes where students with special needs are included. Emphasis was paid to select teachers who have the experience of teaching students with different disorders commonly found in the Maldives, namely in the four areas, Autism Spectrum Disorder, Down Syndrome, Attention Deficit Hyperactive Disorder and speech impairment. Hence, purposive sampling will be used to select the participants. Data analysis has been done using thematic coding. The findings revealed that teachers highlighted that parents' involvement was a key factor in ensuring success of education in children with special needs. Thus, the study concludes that the role of parents as a necessary input for the proper development of children and in educating children with special needs, suggesting that extra measures have to be taken develop a positive relationship between teachers and parents in order to strengthen this aspect.

Keywords: involvement, parents' role, special education needs, teachers' voice

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Hategekimana Jean Paul, Irakoze Josiane, Ishimweyizerwe Valentin, Iradukunda Dieudonne, Uwanyirigira Jeannette

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Orange fleshed sweet potatoes (OFSP) are highly grown and are available plenty in rural and urban local markets and its contribution in reduction of food insecurity in Rwanda is considerable. But the postharvest loss of this commodity is a critical challenge due to its high perishability. Several research activities have been conducted on how fresh food commodities can be transformed into extended shelf life food products for prevention of post-harvest losses. However, such activity was not yet well studied in Rwanda. The aim of the present study was the processing of backed products from (OFSP)combined with wheat composite flour and assess the nutritional content and consumer acceptability of new developed products. The perishability of OFSP and their related lack during off season can be eradicated by producing cake, doughnut and bread with OFSP puree or flour. The processing for doughnut and bread were made by making OFSP puree and other ingredients then a dough was made followed by frying and baking while for cake OFSP was dried through solar dryer to have a flour together with wheat flour and other ingredients to make dough cake and baking. For each product, one control and three experimental samples, (three products in three different ratios (30,40 and50%) of OFSP and the remaining percentage of wheat flour) were prepared. All samples including the control were analyzed for the consumer acceptability (sensory attributes). Most preferred samples (One sample for each product with its control sample and for each OFSP variety) were analyzed for nutritional composition along with control sample. The Cake from Terimbere variety and Bread from Gihingumukungu supplemented with 50% OFSP flour or Puree respectively were most acceptable except Doughnut from Vita variety which was highly accepted at 50% of OFSP supplementation. The moisture, ash, protein, fat, fiber, Total carbohydrate, Vitamin C, reducing sugar and minerals (Sodium, Potassium and Phosphorus.) content was different among products. Cake was rich in fibers (14.71%), protein (6.590%), and vitamin c(19.988mg/100g) compared to other samples while bread found to be rich in reducing sugar with 12.71mg/100g compared to cake and doughnut. Also doughnut was found to be rich in fat content with 6.89% compared to other samples. For sensory analysis, doughnut was highly accepted in ratio of 60:40 compared to other products while cake was least accepted at ratio of 50:50. The Proximate composition and minerals content of all the OFSP products were significantly higher as compared to the control samples.

Keywords: post-harvest loss, OFSP products, wheat flour, sensory evaluation, proximate composition

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Authors: A. van Staden, M. M. Coetzee

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Despite numerous efforts to increase the literacy level of South African learners, for example, through the implementation of educational policies such as the Revised National Curriculum statement, advocating mother-tongue instruction (during a child's formative years), in reality, the majority of South African children are still being educated in a second language (in most cases English). Moreover, despite the fact that a significant percentage of our country's budget is spent on the education sector and that both policy makers and educationalists have emphasized the importance of learning English in this globalized world, the poor overall academic performance and English literacy level of a large number of school leavers are still a major concern. As we move forward in an attempt to comprehend the nuances of English language and literacy development in our country, it is imperative to explore both extrinsic and intrinsic factors that contribute or impede the effective development of English as a second language. In the present study, the researchers set out to investigate how intrinsic factors such as motivation and self-concept contribute to or affect English language learning amongst high school learners in South Africa. Emanating from the above the main research question that guided this research is the following: Is there a significant relationship between high school learners' self-concept, motivation, and English second language performances? In order to investigate this hypothesis, this study utilized quantitative research methodology to investigate the interplay of self-concept and motivation in English language learning. For this purpose, we sampled 201 high school learners from various schools in South Africa. Methods of data gathering inter alia included the following: A biographical questionnaire; the Academic Motivational Scale and the Piers-Harris Self-Concept Scale. Pearson Product Moment Correlation Analyses yielded significant correlations between L2 learners' motivation and their English language proficiency, including demonstrating positive correlations between L2 learners' self-concept and their achievements in English. Accordingly, researchers have argued that the learning context, in which students learn English as a second language, has a crucial influence on students' motivational levels. This emphasizes the important role the teacher has to play in creating learning environments that will enhance L2 learners' motivation and improve their self-concepts.

Keywords: motivation, self-concept, language learning, English second language learners (L2)

Procedia PDF Downloads 274

Authors: Kathleen L. Seifert

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Students with special needs are expected to achieve the same academic standards as their general education peers, yet many students with special needs are pulled-out of general content instruction. Because of this, many students with special needs are denied content knowledge from a content expert and instead receive content instruction in a more restrictive setting. Collaborative teaching, where a general education and special education teacher work alongside each other in the same classroom, has become increasingly popular as a means to meet the diverse needs of students in America’s public schools. The idea behind co-teaching is noble; to ensure students with special needs receive content area instruction from a content expert while also receiving the necessary supports to be successful. However, in spite of this noble effort, the effects of co-teaching are not always positive. The reasons why have produced several hypotheses, one of which has to do with lack of proper training and implementation of effective evidence-based co-teaching practices. In order to examine the effects of co-teacher training, eleven teaching pairs from a small mid-western school district in the United States participated in a study. The purpose of the study was to examine the effects of co-teacher training on middle and high school student achievement in Math and Language Arts. A local university instructor provided teachers with training in co-teaching via a three-day workshop. In addition, co-teaching pairs were given the opportunity for direct observation and feedback using the Co-teaching Core Competencies Observation Checklist throughout the academic year. Data are in the process of being collected on both the students enrolled in the co-taught classes as well as on the teachers themselves. Student data compared achievement on standardized assessments and classroom performance across three domains: 1. General education students compared to students with special needs in co-taught classrooms, 2. Students with special needs in classrooms with and without co-teaching, 3. Students in classrooms where teachers were given observation and feedback compared to teachers who refused the observation and feedback. Teacher data compared the perceptions of the co-teaching initiative between teacher pairs who received direct observation and feedback from those who did not. The findings from the study will be shared with the school district and used for program improvement.

Keywords: collabortive teaching, collaboration, co-teaching, professional development

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Authors: Mastoor Qubra

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Cyber-attacks have frequently disrupted the critical infrastructures of the major global states and now, cyber threat has become one of the dire security risks for the states across the globe. Recently, ransomware cyber-attacks, wannacry and petya, have affected hundreds of thousands of computer servers and individuals’ private machines in more than hundred countries across Europe, Middle East, Asia, United States and Australia. Although, states are rapidly becoming aware of the destructive nature of this new security threat and counter measures are being taken but states’ isolated efforts would be inadequate to deal with this heinous security challenge, rather a global coordination and cooperation is inevitable in order to develop a credible cyber deterrence policy. Hence, the paper focuses that coordinated global approach is required to deter posed cyber threat. This paper intends to analyze the cyber security counter measures in four dimensions i.e. evaluation of prevalent strategies at bilateral level, initiatives and limitations for cooperation at global level, obstacles to combat cyber terrorism and finally, recommendations to deter the threat by applying tools of deterrence theory. Firstly, it focuses on states’ efforts to combat the cyber threat and in this regard, US-Australia Cyber Security Dialogue is comprehensively illustrated and investigated. Secondly, global partnerships and strategic and analytic role of multinational organizations, particularly United Nations (UN), to deal with the heinous threat, is critically analyzed and flaws are highlighted, for instance; less significance of cyber laws within international law as compared to other conflict prone issues. In addition to this, there are certain obstacles and limitations at national, regional and global level to implement the cyber terrorism counter strategies which are presented in the third section. Lastly, by underlining the gaps and grey areas in the current cyber security counter measures, it aims to apply tools of deterrence theory, i.e. defense, attribution and retaliation, in the cyber realm to contribute towards formulating a credible cyber deterrence strategy at global level. Thus, this study is significant in understanding and determining the inevitable necessity of counter cyber terrorism strategies.

Keywords: attribution, critical infrastructure, cyber terrorism, global cooperation

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Authors: Chuang-Hung Lin, Cheng-Yuan Hsu, Jia-Yan Lin

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It is an indispensible strategy to adopt greenery approach on architectural bases so as to improve ecological habitats, decrease heat-island effect, purify air quality, and relieve surface runoff as well as noise pollution, all of which are done in an attempt to achieve sustainable environment. How we can do with plant design to attain the best visual quality and ideal carbon dioxide fixation depends on whether or not we can appropriately make use of greenery according to the nature of architectural bases. To achieve the goal, it is a need that architects and landscape architects should be provided with sufficient local references. Current greenery studies focus mainly on the heat-island effect of urban with large scale. Most of the architects still rely on people with years of expertise regarding the adoption and disposition of plantation in connection with microclimate scale. Therefore, environmental design, which integrates science and aesthetics, requires fundamental research on landscape environment technology divided from building environment technology. By doing so, we can create mutual benefits between green building and the environment. This issue is extremely important for the greening design of the bases of green buildings in cities and various open spaces. The purpose of this study is to establish plant selection and allocation strategies under different building sunshade levels. Initially, with the shading of sunshine on the greening bases as the starting point, the effects of the shades produced by different building types on the greening strategies were analyzed. Then, by measuring the PAR( photosynthetic active radiation), the relative DLI( daily light integral) was calculated, while the DLI Map was established in order to evaluate the effects of the building shading on the established environmental greening, thereby serving as a reference for plant selection and allocation. The discussion results were to be applied in the evaluation of environment greening of greening buildings and establish the “right plant, right place” design strategy of multi-level ecological greening for application in urban design and landscape design development, as well as the greening criteria to feedback to the eco-city greening buildings.

Keywords: daily light integral, plant design, urban open space

Procedia PDF Downloads 515

Authors: Diriba Gemechu, Lamessa Abebe

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The aim of this study was to examine the effect of cooperative learning method on student’s academic achievement and on the achievement level over a usual method in teaching different topics of mathematics. The study also examines the perceptions of students towards cooperative learning. Cooperative learning is the instructional strategy in which pairs or small groups of students with different levels of ability work together to accomplish a shared goal. The aim of this cooperation is for students to maximize their own and each other learning, with members striving for joint benefit. The teacher’s role changes from wise on the wise to guide on the side. Cooperative learning due to its influential aspects is the most prevalent teaching-learning technique in the modern world. Therefore the study was conducted in order to examine the effect of cooperative learning on the academic achievement of grade 9 students in Mathematics in case of Mettu secondary school. Two sample sections are randomly selected by which one section served randomly as an experimental and the other as a comparison group. Data gathering instruments are achievement tests and questionnaires. A treatment of STAD method of cooperative learning was provided to the experimental group while the usual method is used in the comparison group. The experiment lasted for one semester. To determine the effect of cooperative learning on the student’s academic achievement, the significance of difference between the scores of groups at 0.05 levels was tested by applying t test. The effect size was calculated to see the strength of the treatment. The student’s perceptions about the method were tested by percentiles of the questionnaires. During data analysis, each group was divided into high and low achievers on basis of their previous Mathematics result. Data analysis revealed that both the experimental and comparison groups were almost equal in Mathematics at the beginning of the experiment. The experimental group out scored significantly than comparison group on posttest. Additionally, the comparison of mean posttest scores of high achievers indicates significant difference between the two groups. The same is true for low achiever students of both groups on posttest. Hence, the result of the study indicates the effectiveness of the method for Mathematics topics as compared to usual method of teaching.

Keywords: academic achievement, comparison group, cooperative learning, experimental group

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Authors: Chao Yang, Jinchuan Zhang, Yongqiang Xiong

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The Lower Cambrian Niutitang Formation shale (NFS) deposited in the marine deep-shelf environment in Southeast Upper Yangtze (SUY), possess excellent source rock basis for shale gas generation, however, it is currently challenged by being over-mature with strong tectonic deformations, leading to much uncertainty of gas-bearing potential. With emphasis on the shale gas enrichment of the NFS, analyses were made based on the regional gas-bearing differences obtained from field gas-desorption testing of 18 geological survey wells across the study area. Results show that the NFS bears low gas content of 0.2-2.5 m³/t, and the eastern region of SUY is higher than the western region in gas content. Moreover, the methane fraction also presents the similar regional differentiation with the western region less than 10 vol.% while the eastern region generally more than 70 vol.%. Through the analysis of geological theory, the following conclusions are drawn: Depositional environment determines the gas-enriching zones. In the western region, the Dengying Formation underlying the NFS in unconformity contact was mainly plateau facies dolomite with caves and thereby bears poor gas-sealing ability. Whereas the Laobao Formation underling the NFS in eastern region was a set of siliceous rocks of shelf-slope facies, which can effectively prevent the shale gas from escaping away from the NFS. The tectonic conditions control the gas-enriching bands in the SUY, which is located in the fold zones formed by the thrust of the Southern China plate towards to the Sichuan Basin. Compared with the western region located in the trough-like folds, the eastern region at the fold-thrust belts was uplifted early and deformed weakly, resulting in the relatively less mature level and relatively slight tectonic deformation of the NFS. Faults determine whether shale gas can be accumulated in large scale. Four deep and large normal faults in the study area cut through the Niutitang Formation to the Sinian strata, directly causing a large spillover of natural gas in the adjacent areas. For the secondary faults developed within the shale formation, the reverse faults generally have a positive influence on the shale accumulation while the normal faults perform the opposite influence. Overall, shale gas enrichment targets of the NFS, are the areas with certain thickness of siliceous rocks at the basement of the Niutitang Formation, and near the margin of the paleouplift with less developed faults. These findings provide direction for shale gas exploration in South China, and also provide references for the areas with similar geological conditions all over the world.

Keywords: over-mature marine shale, shale gas accumulation, structure-complicated area, Southeast Upper Yangtze

Procedia PDF Downloads 153

Authors: Piyawan Srisuruk, Janya Boonmeeprasert, Romwarin Gamlunglert, Benjamaporn Choikhruea, Ornjira Jaraepram, Jarin Boonsuchat, Sakdadech Singkibud, Kusalaporn Chaiudomsom, Chanatiporn Chonprai, Pornchanaka Tana, Suchat Paholpak

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Objective: To develop an Intensive and comprehensive program (ICP) for the Inclusive Class Teacher (ICPICT) to teach elementary students (ES) with ASD in order to enhance the students’ academic and social skills (ASS) and to study the effect of the teaching program. Methods: The purposive sample included 15 Khon Kaen inclusive class teachers and their 15 elementary students. All the students were diagnosed by a child and adolescent psychiatrist to have DSM-5 level 1 ASD. The study tools included 1) an ICP to teach teachers about ASD, a teaching method to enhance academic and social skills for ES with ASD, and an assessment tool to assess the teacher’s knowledge before and after the ICP. 2) an ICPICT to teach ES with ASD to enhance their ASS. The project taught 10 sessions, 3 hours each. The ICPICT had its teaching structure. Teaching media included: pictures, storytelling, songs, and plays. The authors taught and demonstrated to the participant teachers how to teach with the ICPICT until the participants could display the correct teaching method. Then the teachers taught ICPICT at school by themselves 3) an assessment tool to assess the students’ ASS before and after the completion of the study. The ICP to teach the teachers, the ICPICT, and the relevant assessment tools were developed by the authors and were adjusted until consensus agreed as appropriate for researching by 3 curriculum of teaching children with ASD experts. The data were analyzed by descriptive and analytic statistics via SPSS version 26. Results: After the briefing, the teachers increased the mean score, though not with statistical significance, of knowledge of ASD and how to teach ES with ASD on ASS (p = 0.13). Teaching ES with ASD with the ICPICT could increase the mean scores of the students’ skills in learning and expressing social emotions, relationships with a friend, transitioning, and skills in academic function 3.33, 2.27, 2.94, and 3.00 scores (full scores were 18, 12, 15 and 12, Paired T-Test p = 0.007, 0.013, 0.028 and 0.003 respectively). Conclusion: The program to teach academic and social skills simultaneously in an intensive and comprehensive structure could enhance both the academic and social skills of elementary students with ASD. Keywords: Elementary students, autism spectrum, academic skill, social skills, intensive program, comprehensive program, integration.

Keywords: academica and social skills, students with autism, intensive and comprehensive, teaching program

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Authors: Hande Barkan-Ozturk, Angelika Menner, Alexander Bismarck

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Microfluidic mixing technology grew rapidly in the past few years due to its many advantages over the macro-scale mixing, especially the ability to use small amounts of internal volume and also very high surface-to-volume ratio. The Reynold number identify whether the mixing is operated by the laminar or turbulence flow. Therefore, mixing with very fast kinetic can be achieved by diminishing the channel dimensions to decrease Reynold number and the laminar flow can be accomplished. Moreover, by using obstacles in the micromixer, the mixing length and the contact area between the species have been increased. Therefore, the channel geometry and its surface property have great importance to reach satisfactory mixing results. Since poly(-merised) High Internal Phase Emulsions (polyHIPEs) have more than 74% porosity and their pores are connected each other with pore throats, which cause high permeability, they are ideal candidate to build a micromixer. The HIPE precursor is commonly produced by using an overhead stirrer to obtain relatively large amount of emulsion in batch process. However, we will demonstrate that a desired amount of emulsion can be prepared continuously with micromixer build from polyHIPE, and such HIPE can subsequently be employed as ink in 3D printing process. In order to produce the micromixer a poly-Pickering(St-co-DVB)HIPE with 80% porosity was prepared with modified silica particles as stabilizer and surfactant Hypermer 2296 to obtain open porous structure and after coating of the surface, the three 1/16' ' PTFE tubes to transfer continuous (CP) and internal phases (IP) and the other is to collect the emulsion were placed. Afterwards, the two phases were injected in the ratio 1:3 CP:IP with syringe dispensers, respectively, and highly viscoelastic H(M)IPE, which can be used as an ink in 3D printing process, was gathered continuously. After the polymerisation of the resultant emulsion, polyH(M)IPE has interconnected porous structure identical to the monolithic polyH(M)IPE indicating that the emulsion can be prepared constantly with poly-Pickering-HIPE as micromixer and it can be used to prepare desired pattern with a 3D printer. Moreover, the morphological properties of the emulsion can be adjustable by changing flow ratio, flow speed and structure of the micromixer.

Keywords: 3D-Printing, emulsification, macroporous polymer, micromixer, polyHIPE

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

Abstract:

The U.S. Federal Emergency Management Agency (FEMA) developed flood maps based on experts’ experience and estimates of the probability of flooding. Current flood-risk models evaluate flood risk with regional and subjective measures without impact from torrential rain and nuisance flooding at the neighborhood level. Nuisance flooding occurs in small areas in the community, where a few streets or blocks are routinely impacted. This type of flooding event occurs when torrential rainstorm combined with high tide and sea level rise temporarily exceeds a given threshold. In South Florida, this threshold is 1.7 ft above Mean Higher High Water (MHHW). The National Weather Service defines torrential rain as rain deposition at a rate greater than 0.3-inches per hour or three inches in a single day. Data from the Florida Climate Center, 1970 to 2020, shows 371 events with more than 3-inches of rain in a day in 612 months. The purpose of this research is to develop a data-driven method to determine comprehensive analytical damage-avoidance criteria that account for nuisance flood events at the single-family home level. The method developed uses the Failure Mode and Effect Analysis (FMEA) method from the American Society of Quality (ASQ) to estimate the Damage Avoidance (DA) preparation for a 1-day 100-year storm. The Consequence of Nuisance Flooding (CoNF) is estimated from community mitigation efforts to prevent nuisance flooding damage. The Probability of Nuisance Flooding (PoNF) is derived from the frequency and duration of torrential rainfall causing delays and community disruptions to daily transportation, human illnesses, and property damage. Urbanization and population changes are related to the U.S. Census Bureau's annual population estimates. Data collected by the United States Department of Agriculture (USDA) Natural Resources Conservation Service’s National Resources Inventory (NRI) and locally by the South Florida Water Management District (SFWMD) track the development and land use/land cover changes with time. The intent is to include temporal trends in population density growth and the impact on land development. Results from this investigation provide the risk of nuisance flooding as a function of CoNF and PoNF for coastal areas of South Florida. The data-based criterion provides awareness to local municipalities on their flood-risk assessment and gives insight into flood management actions and watershed development.

Keywords: flood risk, nuisance flooding, urban flooding, FMEA

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