Search results for: gamma distributed degradation model

Authors: Anas H. Aljemely, Jianping Xuan

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Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

Procedia PDF Downloads 200

Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: Sagir Abubakar

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The electronic means of transaction has provided an opportunity especially for commercial banks to entice more customers that will subsequently boost their return on investment. It moves them from traditional marketing into digital marketing and gives them a competitive advantage over others in the same industry. The paper, therefore, examined the competitive advantage of the electronic marketing strategy among commercial banks branches in Bauchi state. The main objective of the study was to determine the impact of e-marketing strategy as a competitive advantage among commercial banks branches in Bauchi state and to evaluate the level of enlightenment campaign offered by the commercial banks branches to their customers on e-marketing. The study obtained data from the staff of the five (s) selected banks branches as the respondents to answer the questionnaire. The research is a quantitative research, where the data where obtained using questionnaire. 100 questionnaires were distributed and analyzed using SPSS’s regression analysis. The research among other findings discovered that the e-marketing has led to a significant improvement in the banking industry and is expected to continue because of the improvement in the ICT sector. It was also found out that most customers are not aware of the electronic products offered by commercial banks branches in Bauchi state. Some of factors affecting the adoption of e-marketing by banks as indicated from the findings include: top management commitment, government policy on ICT and availability of ICT personnel. The study recommended that commercial banks branches should engage in enlightenment campaign about the existing of their e- products/services, management should place an incentive in order to raise the interest of customers to patronize the products/services online.

Keywords: e-marketing strategy, competitive advantage, banks, Bauchi State

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Authors: Yixin Yan, Miao Yan, Irini Angelidaki, Ioannis Fotidis

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Ammonia, which derives from the degradation of urea and protein-substrates, is the major toxicant of the commercial anaerobic digestion reactors causing loses of up to 1/3 of their practical biogas production, which reflects directly on the overall revenue of the plants. The current experimental work is aiming to alleviate the ammonia inhibition in anaerobic digestion (AD) process by developing an innovative bioaugmentation method of ammonia tolerant methanogenic consortia. The ammonia tolerant consortia were cultured in batch reactors and immobilized together with biochar in agar (customized inocula). Three continuous stirred-tank reactors (CSTR), fed with the organic fraction of municipal solid waste at a hydraulic retention time of 15 days and operated at thermophilic (55°C) conditions were assessed. After an ammonia shock of 4 g NH4+-N L-1, the customized inocula were bioaugmented into the CSTR reactors to alleviate ammonia toxicity effect on AD process. Recovery rate of methane production and methanogenic activity will be assessed to evaluate the bioaugmentation performance, while 16s rRNA gene sequence will be used to reveal the difference of microbial community changes through bioaugmentation. At the microbial level, the microbial community structures of the four reactors will be analysed to find the mechanism of bioaugmentation. Changes in hydrogen formation potential will be used to predict direct interspecies electron transfer (DIET) between ammonia tolerant methanogens and syntrophic bacteria. This experimental work is expected to create bioaugmentation inocula that will be easy to obtain, transport, handled and bioaugment in AD reactors to efficiently alleviate the ammonia toxicity, without alternating any of the other operational parameters including the ammonia-rich feedstocks.

Keywords: artisanal fishing waste, acidogenesis, volatile fatty acids, pH, inoculum/substrate ratio

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Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

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This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

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Authors: Constant Gillot, Pauline Michaux, Julien Favresse, Jean-Michel Dogné, Jonathan Douxfils

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Introduction: NETosis has emerged as a crucial yet paradoxical factor in severe COVID-19 cases. While neutrophil extracellular traps (NETs) help contain and eliminate viral particles, excessive NET formation can lead to hyperinflammation, exacerbating tissue damage and acute respiratory distress syndrome (ARDS). Aims: This study evaluates the relationship between COVID-19-infected sera and NETosis using an ex-vivo model. Methods: Sera from 8 post-admission COVID-19 patients, after receiving corticoid therapy, were used to induce NETosis in neutrophils from a healthy donor. NET formation was tracked using fluorescent markers for DNA and neutrophil elastase (NE) every 2 minutes for 8 hours. The results were expressed as a percentage of DNA/NE released over time. Key metrics, including T50 (time to 50% release) and AUC (area under the curve), representing total NETosis potential), were calculated. A 27-cytokine screening kit was used to assess the cytokine composition of the sera. Results: COVID-19 sera induced NETosis based on their cytokine profile. The AUC of NE and DNA release decreased with time following corticoid therapy, showing a significant reduction in 6 of the 8 patients (p<0.05). T50 also decreased in parallel with AUC for both markers. Cytokines concentration decrease with time after therapy administration. There is correlation between 14 cytokines concentration and NE release. Conclusion: This ex-vivo model successfully demonstrated the induction of NETosis by COVID-19 sera using two markers. A clear decrease in NETosis potential was observed over time with glucocorticoid therapy. This model can be a valuable tool for monitoring NETosis and investigating potential NETosis inducers and inhibitors.

Keywords: NETosis, COVID-19, cytokine storm, biomarkers

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Authors: Riya Roy, Anjana Bhasi

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Column-supported embankments provide a practical and efficient solution for construction on soft soil due to the low cost and short construction times. In the recent years, geosynthetic have been used in combination with column systems to support embankments. The load transfer mechanism in these systems is a combination of soil arching effect, which occurs between columns and membrane effect of the geosynthetic. This paper aims at the study of soil arching effect on columnar embankments using finite element software, ABAQUS. An axisymmetric finite element model is generated and using this model, parametric studies are carried out. Thus the effects of various factors such as height of embankment fill, elastic modulus of pile and tensile stiffness of geosynthetic, on soil arching have been studied. The development of negative skin friction along the pile-soil interface have also been studied and the results obtained from this study are compared with the current design methods.

Keywords: ABAQUS, geosynthetic, negative skin friction, soil arching

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Authors: Rida Batool, Faizah Altaf, Saba Nadeem, Afifa Aslam, Faisal Alamgir, Ghazanfar Abbas

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Today, the need of the hour is to find out alternative renewable energy resources in order to reduce the burden on fossil fuels and prevent alarming environmental degradation. Solid oxide fuel cell (SOFC) is considered a good alternative energy conversion device because it is environmentally benign and supplies energy on demand. The only drawback associated with SOFC is its high operating temperature. In order to reduce operating temperature, different types of composite material are prepared. In this work, titanium doped lanthanum gallium cerate (LGCT) composite is prepared through the co-precipitation method as electrolyte and examined for low temperature SOFCs (LTSOFCs). The structural properties are analyzed by X-Ray Diffractometry (XRD) and Fourier Transform Infrared (FTIR) Spectrometry. The surface properties are investigated by Scanning Electron Microscopy (SEM). The electrolyte LGCT has the formula LGCTO₃ because it showed two phases La.GaO and Ti.CeO₂. The average particle size is found to be (32 ± 0.9311) nm. The ionic conductivity is achieved to be 0.073S/cm at 650°C. Arrhenius plots are drawn to calculate activation energy and found 2.96 eV. The maximum power density and current density are achieved at 68.25mW/cm² and 357mA/cm², respectively, at 650°C with hydrogen. The prepared material shows excellent ionic conductivity at comparatively low temperature, that makes it a potentially good candidate for LTSOFCs.

Keywords: solid oxide fuel cell, LGCTO₃, cerium composite oxide, ionic conductivity, low temperature electrolyte

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Authors: Kim Byeong-Gon, Lee Pureun-Haneul, Hong Jisu, Jang An-Soo

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Background: Diesel exhaust particles (DEPs) lead to trigger airway hyperresponsiveness (AHR) and airway dysfunction or inflammation in respiratory systems. Whether tight junction protein changes can contribute to development or exacerbations of airway diseases remain to be clarified. Objective: The aim of this study was to observe the effect of DEP on tight junction proteins in one airway both nose and lung in a mouse model. Methods: Mice were treated with saline (Sham) and exposed to 100 μg/m³ DEPs 1 hour a day for 5 days a week for 4 weeks and 8 weeks in a closed-system chamber attached to a ultrasonic nebulizer. Airway hyperresponsiveness (AHR) was measured and bronchoalveolar lavage (BAL) fluid, nasal lavage (NAL) fluid, lung and nasal tissue was collected. The effects of DEP on tight junction proteins were estimated using western blot, immunohistochemical in lung and nasal tissue. Results: Airway hyperresponsiveness and number of inflammatory cells were higher in DEP exposure group than in control group, and were higher in 4 and 8 weeks model than in control group. The expression of tight junction proteins CLND4, -5, and -17 in both lung and nasal tissue were significantly increased in DEP exposure group than in the control group. Conclusion: These results suggesting that CLDN4, -5 and -17 may be involved in the airway both nose and lung, suggesting that air pollutants cause to disruption of epithelial and endothelial cell barriers. Acknowledgment: This research was supported by Korea Ministry of Environment (MOE) as 'The Environmental Health Action Program' (2016001360009) and Soonchunhyang University Research Fund.

Keywords: diesel exhaust particles, air pollutant, tight junction, Claudin, Airway inflammation

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Authors: Mona Awad Wanis Gad

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The method of factory making plans has changed loads, in particular, whilst it's miles approximately making plans the factory building itself. Factory making plans have the venture of designing merchandise, plants, tactics, organization, regions, and the construction of a factory. Ordinary restructuring is turning into greater essential for you to preserve the competitiveness of a manufacturing unit. Regulations in new regions, shorter lifestyle cycles of product and manufacturing era, in addition to a VUCA global (Volatility, Uncertainty, Complexity and Ambiguity) cause extra common restructuring measures inside a factory. A digital factory model is the planning foundation for rebuilding measures and turns into a critical device. Furthermore, digital building fashions are increasingly being utilized in factories to help facility management and manufacturing processes. First, exclusive styles of digital manufacturing unit fashions are investigated, and their residences and usabilities to be used instances are analyzed. Within the scope of research are point cloud fashions, building statistics fashions, photogrammetry fashions, and those enriched with sensor information are tested. It investigated which digital fashions permit a simple integration of sensor facts and in which the variations are. In the end, viable application areas of virtual manufacturing unit models are determined by a survey, and the respective digital manufacturing facility fashions are assigned to the application areas. Ultimately, an application case from upkeep is selected and implemented with the assistance of the best virtual factory version. It is shown how a completely digitalized preservation process can be supported by a digital manufacturing facility version by offering facts. Among different functions, the virtual manufacturing facility version is used for indoor navigation, facts provision, and display of sensor statistics. In summary, the paper suggests a structuring of virtual factory fashions that concentrates on the geometric representation of a manufacturing facility building and its technical facilities. A practical application case is proven and implemented. For that reason, the systematic selection of virtual manufacturing facility models with the corresponding utility cases is evaluated.

Keywords: augmented reality, digital factory model, factory planning, restructuring digital factory model, photogrammetry, factory planning, restructuring building information modeling, digital factory model, factory planning, maintenance

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Esraa Mohamed El-Fawal

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A facile solvothermal procedure was applied to fabricate zinc ferrite nanoparticles (ZnFe₂O₄ NPs). Activated carbon (AC) derived from peanut shells is synthesized using a microwave through the chemical activation method. The ZnFe₂O₄-AC composite is then mixed with a cerium-based metal-organic framework (CeMOF) by solid-state adding to formulate ZnFe₂O₄-AC/CeMOF composite. The synthesized photo materials were tested by scanning/transmission electron microscope (SEM/TEM), Photoluminescence (PL), (XRD) X-Ray diffraction, (FTIR) Fourier transform infrared, (UV-Vis/DRS) ultraviolet-visible/diffuse reflectance spectroscopy. The prepared ZnFe₂O₄-AC/CeMOFphotomaterial shows significantly boosted efficiency for photodegradation of methyl orange /methylene blue (MO/MB) compared with the pristine ZnFe₂O₄ and ZnFe₂O₄-AC composite under the irradiation of visible-light. The favorable ZnFe₂O₄-AC/CeMOFphotocatalyst displays the highest photocatalytic degradation efficiency of MB/MO (R: 91.5-88.6%, consecutively) compared with the other as-prepared materials after 30 min of visible-light irradiation. The apparent reaction rate K: 1.94-1.31 min-1 is also calculated. The boosted photocatalytic proficiency is ascribed to the heterojunction at the interface of prepared photo material that assists the separation of the charge carriers. To reach optimization, statistical analysis using response surface methodology was applied. The effect of independent parameters (such as A (pH), B (irradiation time), and (c) initial pollutants concentration on the response function (%)photodegradation of MB/MO dyes (as examples of azodyes) was investigated via using central composite design. At the optimum condition, the photodegradation efficiency (%) of the MB/MO is 99.8-97.8%, respectively. ZnFe2O₄-AC/CeMOF hybrid reveals good stability over four consecutive cycles.

Keywords: azo-dyes, photo-catalysis, zinc ferrite, response surface methodology

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Authors: Giriprasath Ramanathan, Sivakumar Singaravelu, M. D. Raja, Uma Tirichurapalli Sivagnanam

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Collagen is the abundant protein found in the skin of the animal body that has been designed to provide adequate structural support for the adhesion of cells. The dressing material widely used for tissue engineering and biomedical application has to posses good swelling and biological property for the absorption of exudates and cell proliferation. Acid solubilised collagen from the fish skin of the Arothron stellatus was extracted. The collagen with hydroxypropyl and carboxy methyl cellulose has the better biological property to enhance the healing efficiency. The inter property of collagen with interesting perspectives in the tissue engineering process leads to the development of biomaterial with natural polymer with biologically derived collagen. Keeping this as an objective, the composite biomaterial was fabricated to improve the wound healing and biological properties. In this study the collagen from Arothron stellatus fish skin (ACO) was uniformly blended separately with hydroxypropyl methyl cellulose (HPMC) and carboxyl methyl cellulose (CMC) as biosheets. The casted biosheets were impregnated with mupirocin to get rid of infection from the microbes. Further, the results obtained from differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), tensile studies and biocompatibility of the biosheets were assessed. The swelling, porosity and degradation of the casted biosheets were studied to make the biosheets as a suitable wound dressing material. ACO-HPMC and ACO-CMC biosheets both showed good results, but ACO-HPMC biosheet showed better results than ACO-CMC and hence it can be used as a potential dermal substitute in skin tissue engineering.

Keywords: arothron stellatus, biocompatibility, collagen, tensile strenght

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Authors: Alfred Kamate Siviri, Angelus Mafikiri Tsongo, Jean Robert Kala Kamdjoug

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Digitalization and information systems well organized have been selected as relevant measures to mitigate operational risks within organizations. Unfortunately, information system comes with new threats that can cause severe damage and quick organization lockout. This study aims to measure perceived information system risks and their effects on operational risks within the microfinance institution in D.R. Congo. Also, the factors influencing the operational risk are identified, and the link between operational risk with other risks and performance is to be assessed. The study proposes a research model drawn on the combination of Resources-Based-View, dynamic capabilities, the agency theory, the Information System Security Model, and social theories of risk. Therefore, we suggest adopting a mixed methods research with the sole aim of increasing the literature that already exists on perceived operational risk assessment and its link with other risk and performance, a focus on IT risk.

Keywords: Democratic Republic Congo, information system risk, microfinance performance, operational risk

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Authors: Ali A. Hashim Habib, Ahmed A. Abdel-Rehim

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Assuredly, massive amounts of wastes that are not utilized and dumped in uncontrolled dumpsites will be one of the major sources of diseases, fires, and emissions. With easy steps and minimum effort, energy can be produced from these gases. The present work introduces an experimental and theoretical analysis to estimate the amount of landfill gas and the corresponding energy which can be produced based on actual Egyptian municipal wastes composition. Two models were utilized and compared, EPA (Environmental Protection Agency) model and CDM (Clean Development Mechanisms) model to estimate methane generation rates and total CH4 emissions based on a particular landfill. The results showed that for every ton of municipal waste, 140 m3 of landfill gas can be produced. About 800 kW of electricity for a minimum of 24 years can be generated form one million ton of municipal waste. A total amount of 549,025 ton of carbon emission can be avoided during these 24 years.

Keywords: energy from landfill gases, landfill biogas, methane emission, municipal solid waste, renewable energy sources

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Authors: Amber Dummett, Efstathia Tzemou

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Narcissism is a personality trait characterized by selfishness, entitlement, and superiority. Narcissism is split into two subtypes, grandiose narcissism (GN) and vulnerable narcissism (VN). Grandiose narcissists are extraverted and arrogant, while vulnerable narcissists are introverted and insecure. This study investigates the psychological mechanisms that lead to differences in academic achievement (AA) between grandiose and vulnerable narcissists, specifically the mediating effects of self-esteem and self-efficacy. While narcissism is considered to be a negative trait, one of the Dark Triads, GN, has been found to have some benefits; therefore, this study considers if better AA is one of them. Moreover, further research into VN is essential to fully compare and contrast it with GN. We hypothesize that grandiose narcissists achieve higher marks due to having high self-esteem and self-efficacy. In comparison, we hypothesize that vulnerable narcissists underperform and achieve lower marks due to having low self-esteem and self-efficacy. Two online surveys were distributed to undergraduate university students. The first was a collection of scales measuring the mentioned dimensions and semester one AA, and the second investigated end of year AA. Sequential mediation analyses were conducted using the gathered data. Our analysis shows that neither self-esteem nor self-efficacy mediates the relationship between GN and AA. GN positively predicts self-esteem but has no relationship with self-efficacy. Self-esteem does not mediate the relationship between VN and AA. VN has a negative indirect effect on AA via self-efficacy, and VN negatively predicts self-esteem. Self-efficacy positively predicts AA. GN does not affect AA through the mediation of self-esteem and then self-efficacy, and neither does VN in this way. Overall, having grandiose or vulnerable narcissistic traits does not affect students’ AA. However, being highly efficacious does lead to academic success; therefore, universities should employ methods to improve the self-efficacy of their students.

Keywords: academic achievement, grandiose narcissism, self-efficacy, self-esteem, vulnerable narcissism

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Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

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A method of effective planning and control of industrial facility energy consumption is offered. The method allows to optimally arrange the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics

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Authors: Shaya Alshahrani

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Perceived risks play a major role in consumer intentions, behaviors, attitudes, and decisions about online shopping in the KSA. This paper investigates the influence of six perceived risk dimensions on Saudi consumers: product risk, information risk, financial risk, privacy and security risk, delivery risk, and terms and conditions risk empirically. To ensure the success of this study, a random survey was distributed to reflect the consumers’ perceived risk and to enable the generalization of the results. Data were collected from 323 respondents in the Kingdom of Saudi Arabia (KSA): 50 who had never shopped online and 273 who had done so. The results indicated that all six risks influenced the respondents’ perceptions of online shopping. The non-online shoppers perceived financial and delivery risks as the most significant barriers to online shopping. This was followed closely by performance, information, and privacy and security risks. Terms and conditions were perceived as less significant. The online consumers considered delivery and performance risks to be the most significant influences on internet shopping. This was followed closely by information and terms and conditions. Financial and privacy and security risks were perceived as less significant. This paper argues that introducing adequate legal solutions to addressing related problems arising from this study is an urgent need. This may enhance consumer trust in the KSA online market, increase consumers’ intentions regarding online shopping, and improve consumer protection.

Keywords: perceived risk, online contracts, Saudi Arabia, consumer protection

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Authors: Yongzhe Zhao, Ying Liu, Zhiyong Liu, Hui You

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The soil behind retaining wall is normally subjected to cyclic loading, for example traffic loading. Geotextile has been widely used to reinforce the soil for the purpose of reducing the settlement of the soil. A series of physical model tests were performed to investigate the settlement of footing under cyclic loading. The settlement of the footing, ground deformation and the vertical earth pressure in subsoil were presented and discussed under different types of geotextiles. The results indicate that including geotextiles significantly decreases the footing settlement and the stiffer the geotextile, the less the settlement. Under cyclic loading, the soil below the footing shows dilation within certain depths and beyond that it experiences contraction. The location of footing relative to the retaining wall has important effects on the deformation behavior of the soil in the ground, and the closer the footing to the retaining wall, the greater the contraction soil shows. This is because the retaining wall experienced greater lateral displacement.

Keywords: physical model tests, reinforced retaining wall, cyclic loading, footing

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Yassir AbdelRazig, Amine Ghanem

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Construction projects are information intensive in nature and involve many activities that are related to each other. Wireless technologies can be used to improve the accuracy and timeliness of data collected from construction sites and shares it with appropriate parties. Nonetheless, the construction industry tends to be conservative and shows hesitation to adopt new technologies. A main concern for owners, contractors or any person in charge on a job site is the cost of the technology in question. Wireless technologies are not cheap. There are a lot of expenses to be taken into consideration, and a study should be completed to make sure that the importance and savings resulting from the usage of this technology is worth the expenses. This research attempts to assess the effectiveness of using the appropriate wireless technologies based on criteria such as performance, reliability, and risk. The assessment is based on a utility function model that breaks down the selection issue into alternatives attribute. Then the attributes are assigned weights and single attributes are measured. Finally, single attribute are combined to develop one single aggregate utility index for each alternative.

Keywords: analytic hierarchy process, decision theory, utility function, wireless technologies

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Authors: C. R. Stein; K. Skeff Neto, K. L. C. Miranda, P. P. C. Sartoratto, M. E. Xavier, Z. G. M. Lacava, S. M. De Freita, P. C. Morais

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In this study, static magnetic birefringence (SMB) and transmission electron microscopy (TEM) were used to investigate the self-assembling of maghemite nanoparticles suspended as biocompatible magnetic fluid (BMF) while incubated or not with the Black Eyed–Pea Trypsin Chymotripsin Inhibitor–BTCI protein. The stock samples herein studied are dextran coated maghemite nanoparticles (average core diameter of 7.1 nm, diameter dispersion of 0.26, and containing 4.6×1016 particle/mL) and the dextran coated maghemite nanoparticles associated with the BTCI protein. Several samples were prepared by diluting the stock samples with deionized water while following their colloidal stability. The diluted samples were investigated using SMB measurements to assess the average sizes of the self-assembled and suspended mesoscopic structures whereas the TEM micrographs provide the morphology of the as-suspended units. The SMB data were analyzed using a model that includes the particle-particle interaction within the mean field model picture.

Keywords: biocompatible magnetic fluid, maghemite nanoparticles, self-assembling

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Authors: Nonso Ochinanwata, Patrick Oseloka Ezepue

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This paper explores challenges and prospects in Nigerian higher education. The paper develops an integrated business model that aimed to innovate Nigeria higher education system. A survey and semi-structured interview among Nigerian higher education academics, students and graduates are used to explore the challenges and prospects. The study provides a comparison between lecturers, students and graduates opinions to evaluate challenges and prospects in Nigerian higher institutions. The study found to achieve efficient and effectiveness innovation in Nigerian higher education, there is a need for higher institutions to collaborate with industry professionals and other stakeholders such as company management, and government policy makers in designing higher education institutions curricula. The study found that the curriculum design and delivery need to blend theoretical understanding and real-life experience from industry, and with social cultural influences related to Nigerian environment. This will enable lecturers to organise their teaching and assessments such that students can learn around theoretical and practical study themes. The curriculum design and delivery need to link the core ideas to challenging problems in society, nationally and globally. Hence, this approach will support business start-ups and social entrepreneurship which resolve key societal problems. The study suggests that higher education executives, directors, deans, head of departments, and even individual academics need to emulate innovative business managers to create value-adding products and services from innovative research and academic work.

Keywords: higher education, curriculum innovation, business model innovation, teaching and research excellence, economic development

Procedia PDF Downloads 265

Authors: Arshad Ali

Abstract:

The Taliban insurgency in Swat which started apparently as a social movement in 2004 transformed into an anti-Pakistan Islamist insurgency by joining hands with the Tehrik-e-Taliban Pakistan (TTP) upon its formation in 2007. It quickly spread beyond Swat by 2009 making Swat the second stronghold of TTP after FATA. It prompted the Pakistan military to launch a full-scale counterinsurgency military operation code named Rah-i-Rast to regain the control of Swat. Operation Rah-i-Rast was successful not only in restoring the writ of the State but more importantly in creating a consensus against the spread of Taliban insurgency in Pakistan at political, social and military levels. This operation became a test case for civilian government and military to seek for a sustainable solution combating the TTP insurgency in the north-west of Pakistan. This study analyzes why the counterinsurgency operation Rah-i-Rast was successful and why the previous ones came into failure. The study also explores factors which created consensus against the Taliban insurgency at political and social level as well as reasons which hindered such a consensual approach in the past. The study argues that the previous initiatives failed due to various factors including Pakistan army’s lack of comprehensive counterinsurgency model, weak political will and public support, and states negligence. Also, the initial counterinsurgency policies were ad-hoc in nature fluctuating between military operations and peace deals. After continuous failure, the military revisited its approach to counterinsurgency in the operation Rah-i-Rast. The security forces learnt from their past experiences and developed a pragmatic counterinsurgency model: ‘clear, hold, build, and transfer.’ The military also adopted the population-centric approach to provide security to the local people. This case Study of Swat evaluates the strengths and weaknesses of the Pakistan's counterinsurgency operations as well as peace agreements. It will analyze operation Rah-i-Rast in the light of David Galula’s model of counterinsurgency. Unlike existing literature, the study underscores the bottom up approach adopted by the Pakistan’s military and government by engaging the local population to sustain the post-operation stability in Swat. More specifically, the study emphasizes on the hybrid counterinsurgency model “clear, hold, and build and Transfer” in Swat.

Keywords: Insurgency, Counterinsurgency, clear, hold, build, transfer

Procedia PDF Downloads 353

Authors: He Chao, Zhang Lei, Liu Ran, Li Ang

Abstract:

Temperature regulating system by gaseous nitrogen is of importance to the space environment simulator, which keep the shrouds in the temperature range from -150℃ to +150℃. Liquid nitrogen spray equipment is one of the most critical parts in the temperature regulating system by gaseous nitrogen. Y type jet atomizer and internal mixing atomizer of the liquid nitrogen spray equipment are studied in this paper, 2D/3D atomizer model was established and grid division was conducted respectively by the software of Catia and ICEM. Based on the above preparation, numerical simulation on the spraying process of the atomizer by FLUENT is performed. Using air and water as the medium, comparison between the tests and numerical simulation was conducted and the results of two ways match well. Hence, it can be conclude that this atomizer model can be applied in the numerical simulation of liquid nitrogen spray equipment.

Keywords: space environmental simulator, liquid nitrogen spray, Y type jet atomizer, internal mixing atomizer, numerical simulation, fluent

Procedia PDF Downloads 401

Authors: Sang Kompiang Wirawan, Chandra Purnomo

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Carbon dioxide (CO2) adsorption on the activated Klaten-Indonesian natural zeolite (AKINZ) in a packed bed adsorber has been studied. Experiment works consisted of acid activation and adsorption experiments. The natural zeolite sample was activated using 0.3 M HCl at the temperature of 353 K. In the adsorption experiments the feed gas concentrations were 40 and 80 % CO2 in helium within various temperatures of 303; 323 and 373 K. The experiments were conducted by using transient step change adsorption and 20 % Ar/He tracer experiment was conducted to measure dispersion and time lag effect of the packed bed system. A mathematical model of CO2 adsorption had been set up by assuming plug flow;isothermal;isobaric and no gas film mass transport resistance. Single site Langmuir physisorption and Maxwell Stefan mass transport in micropore were applied. All the data were then optimized to get the best value of modified fitted parameter. The model was in a good agreement with the experiment data. Diffusivity tended to increase by increasing temperatures.

Keywords: adsorption, Langmuir, Maxwell-Stefan, natural zeolite, surface diffusion

Procedia PDF Downloads 350

Authors: Hecson Christian, Joel Macwan

Abstract:

Landfill site selection in an urban area is a critical issue in the planning process. With the growth of the urbanization, it has a mammoth impact on the economy, ecology, and environmental health of the region. Outsized amount of wastes are produced and the problem gets soared every day. Hence, selection of ideal site for sanitary landfill is a challenge for urban planners and solid waste managers. Disposal site is a function of many parameters. Among all, Geotechnical parameters are very vital as the same is related to surrounding open land. Moreover, the accessible safe and acceptable land is also scarce. Therefore, in this paper geotechnical parameters are used to develop a GIS model to identify an ideal location for landfill purpose. Metropolitan city of Surat is highly populated and fastest growing urban area in India. The research objectives are to conduct field experiments to collect data and to transfer the facts in GIS platform to evolve a model, to find ideal location. Planners’ preferences were obtained to use analytical hierarchical process (AHP) to find weights of each parameter. Integration of GIS and Multi-Criteria Decision Analysis (MCDA) techniques are applied to improve decision-making. It augments an environment for transformation and combination of geographical data and planners’ preferences. GIS performs deterministic overlay and buffer operations. MCDA methods evaluate alternatives based on the decision makers’ subjective values and priorities. Research results have shown many alternative locations. Economic analysis of selected site from actual operations point of view is not included in this research.

Keywords: GIS, AHP, MCDA, Geo-technical

Procedia PDF Downloads 144

Authors: Ahmidah Elgali

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SCADA is the abbreviation for "Administrative Control And Data Acquisition." SCADA frameworks are generally utilized in industry for administrative control and information securing of modern cycles. Regular SCADA frameworks use PC, journal, slim client, and PDA as a client. In this paper, a Java-empowered cell phone has been utilized as a client in an example SCADA application to show and regulate the place of an example model crane. The paper presents a genuine execution of the online controlling of the model crane through a cell phone. The remote correspondence between the cell phone and the SCADA server is performed through a base station by means of general parcel radio assistance GPRS and remote application convention WAP. This application can be used in industrial sites in areas that are likely to be exposed to a security emergency (like terrorist attacks) which causes the sudden exit of the operators; however, no time to perform the shutdown procedures for the plant. Hence this application allows shutting down units and equipment remotely by mobile and so avoids damage and losses.

Keywords: control, industrial, mobile, network, remote, SCADA

Procedia PDF Downloads 70

Authors: Binod Shrestha, Sandrine Hoppe, Thierry Ghislain, Phillipe Marchal, Nicolas Brosse, Anthony Dufour

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The thermochemical conversion of lignin has received an increasing interest in the frame of different biorefinery concepts for the production of chemicals or energy. It is needed to better understand the physical and chemical conversion of lignin for feeder and reactor designs. In-situ rheology reveals the viscoelastic behaviour of lignin upon thermal conversion. The softening, re-solidification (char formation), swelling and shrinking behaviours are quantified during pyrolysis in real-time [1]. The in-situ rheology of an alkali lignin (Protobind 1000) was conducted in high torque controlled strain rheometer from 35°C to 400°C with a heating rate of 5°C.min-1. The swelling, through glass phase transition overlapped with depolymerization, and solidification (crosslinking and “char” formation) are two main phenomena observed during lignin pyrolysis. The onset of temperatures for softening and solidification for this lignin has been found to be 141°C and 248°C respectively. An ex-situ characterization of lignin/char residues obtained at different temperatures after quenching in the rheometer gives a clear understanding of the pathway of lignin degradation. The lignin residues were sampled from the mid-point temperatures of the softening range and solidification range to study the chemical transformations undergoing. Elemental analysis, FTIR and solid state NMR were conducted after quenching the solid residues (lignin/char). The quenched solid was also extracted by suitable solvent and followed by acetylation and GPC-UV analysis. The combination of 13C NMR and GPC-UV reveals the depolymerization followed by crosslinking of lignin/char. NMR and FTIR provide the evolution of functional moieties upon temperature. Physical and chemical mechanisms occurring during lignin pyrolysis are accounted in this study. Thanks to all these complementary methods.

Keywords: pyrolysis, bio-chemicals, valorization, mechanism, softening, solidification, cross linking, rheology, spectroscopic methods

Procedia PDF Downloads 422

Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

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Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

Procedia PDF Downloads 182