Search results for: double deck high-speed train

Authors: Edward J. Kansa, Pavel Holoborodko

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Continuously differentiable radial basis functions (RBFs) are meshfree, converge faster as the dimensionality increases, and is theoretically spectrally convergent. When implemented on current single and double precision computers, such RBFs can suffer from ill-conditioning because the systems of equations needed to be solved to find the expansion coefficients are full. However, the Advanpix extended precision software package allows computer mathematics to resemble asymptotically ideal Platonic mathematics. Additionally, full systems with extended precision execute faster graphical processors units and field-programmable gate arrays because no branching is needed. Sparse equation systems are fast for iterative solvers in a very limited number of cases.

Keywords: partial differential equations, Meshfree radial basis functions, , no restrictions on spatial dimensions, Extended arithmetic precision.

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Authors: Raoudha Chaabane, Faouzi Askri, Sassi Ben Nasrallah

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A new numerical algorithm is developed to solve coupled convection-radiation heat transfer in a two dimensional enclosure. Radiative heat transfer in participating medium has been carried out using the control volume finite element method (CVFEM). The radiative transfer equations (RTE) are formulated for absorbing, emitting and scattering medium. The density, velocity and temperature fields are calculated using the two double population lattice Boltzmann equation (LBE). In order to test the efficiency of the developed method the Rayleigh Benard convection with and without radiative heat transfer is analyzed. The obtained results are validated against available works in literature and the proposed method is found to be efficient, accurate and numerically stable.

Keywords: participating media, LBM, CVFEM- radiation coupled with convection

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Authors: S. J. Arif

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In the presented technique, a simple method is given for accurate measurement and control of power frequency deviation. The sinusoidal signal for which the frequency deviation measurement is required is transformed to a low voltage level and passed through a zero crossing detector to convert it into a pulse train. Another stable square wave signal of 10 KHz is obtained using a crystal oscillator and decade dividing assemblies (DDA). These signals are combined digitally and then passed through decade counters to give a unique combination of pulses or levels, which are further encoded to make them equally suitable for both control applications and display units. The developed circuit using discrete components has a resolution of 0.5 Hz and completes measurement within 20 ms. The realized circuit is simulated and synthesized using Verilog HDL and subsequently implemented on FPGA. The results of measurement on FPGA are observed on a very high resolution logic analyzer. These results accurately match the simulation results as well as the results of same circuit implemented with discrete components. The proposed system is suitable for accurate measurement and control of power frequency deviation.

Keywords: digital encoder for frequency measurement, frequency deviation measurement, measurement and control systems, power systems

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Authors: L. Sellami, D. Idoughi, P. F. Tiako

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Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing.

Keywords: cloud computing, intrusion detection system, privacy, trust

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Authors: H. Amellal, Y. Noui, A. Djouab, S. Benamara

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Mech-Degla, Degla-Beida, and Frezza are the date (Phoenix dactylifera L.) common varieties with a more or less good availability and feeble trade value. Some morphologic and physicochemical factors were determined. Results show that the whole date weight is significantly different (P= 95%) concerning Mech-Degla and Degla-Beida which are more commercialised than Frezza whereas the pulp/kernel ratio for this last is highest (above 7) since it represents almost the double of that found for the two other varieties. The water content for all fruits is below 15g/100g (wet basis) what confers a dried consistence for common date. Some other morphologic and chemical proprieties of the whole pulps and their two constitutive parts (brown or pigmented and white) are also investigated. The predominance of phenolics in Mech-Degla (4.01g/100g, w.b) and Frezza (4.96 g/100g, w.b) pulps brown part is the main result revealed in this study.

Keywords: common dates, phenolics, sugars, tissues

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Authors: Mahesh Balan U, Rohith Srinivaas Mohanakrishnan, Venkat Subramanian

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Positive and unlabeled learning (PU) has gained more attention in both academic and industry research literature recently because of its relevance to existing business problems today. Yet, there still seems to be some existing challenges in terms of validating the performance of PU learning, as the actual truth of unlabeled data points is still unknown in contrast to a binary classification where we know the truth. In this study, we propose a novel PU learning technique based on the Pseudo-F measure, where we address this research gap. In this approach, we train the PU model to discriminate the probability distribution of the positive and unlabeled in the validation and spy data. The predicted probabilities of the PU model have a two-fold validation – (a) the predicted probabilities of reliable positives and predicted positives should be from the same distribution; (b) the predicted probabilities of predicted positives and predicted unlabeled should be from a different distribution. We experimented with this approach on a credit marketing case study in one of the world’s biggest fintech platforms and found evidence for benchmarking performance and backtested using historical data. This study contributes to the existing literature on semi-supervised learning.

Keywords: PU learning, semi-supervised learning, pseudo f measure, classification

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Authors: Nkechi V. Osuji

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The use of blockchain to address the issue of climate change is increasingly a discourse among countries, industries, and stakeholders. For a long time, the European Union (EU) has been combating the issue of climate action in industries through sustainability programs. One of such programs is the EU monitoring reporting and verification (MRV) program of the EU ETS. However, the system has some key challenges and areas for improvement, which makes it inefficient. The main objective of the research is to look at how blockchain can be used to improve the inefficiency of the EU ETS program for the Danish energy industry with a focus on its monitoring and reporting framework. Applying empirical data from 13 semi-structured expert interviews, three case studies, and literature reviews, three outcomes are presented in the study. The first is on the current conditions and challenges of monitoring and reporting CO₂ emission trading. The second is putting into consideration if blockchain is the right fit to solve these challenges and how. The third stage looks at the factors that might affect the implementation of such a system and provides recommendations to mitigate these challenges. The first stage of the findings reveals that the monitoring and reporting of CO₂ emissions is a mandatory requirement by law for all energy operators under the EU ETS program. However, most energy operators are non-compliant with the program in reality, which creates a gap and causes challenges in the monitoring and reporting of CO₂ emission trading. Other challenges the study found out are the lack of transparency, lack of standardization in CO₂ accounting, and the issue of double-counting in the current system. The second stage of the research was guided by three case studies and requirement engineering (RE) to explore these identified challenges and if blockchain is the right fit to address them. This stage of the research addressed the main research question: how can blockchain be used for monitoring and reporting CO₂ emission trading in the energy industry. Through analysis of the study data, the researcher developed a conceptual private permissioned Hyperledger blockchain and elucidated on how it can address the identified challenges. Particularly, the smart contract of blockchain was highlighted as a key feature. This is because of its ability to automate, be immutable, and digitally enforce negotiations without a middleman. These characteristics are unique in solving the issue of compliance, transparency, standardization, and double counting identified. The third stage of the research presents technological constraints and a high level of stakeholder collaboration as major factors that might affect the implementation of the proposed system. The proposed conceptual model requires high-level integration with other technologies such as the Internet of Things (IoT) and machine learning. Therefore, the study encourages future research in these areas. This is because blockchain is continually evolving its technology capabilities. As such, it remains a topic of interest in research and development for addressing climate change. Such a study is a good contribution to creating sustainable practices to solve the global climate issue.

Keywords: blockchain, carbon emission trading, European Union emission trading system, monitoring and reporting

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Authors: A. Deswal, N. S. Deora, H. N. Mishra

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The aim of the present study was to develop a rapid method for electronic nose for online quality control of oat milk. Analysis by electronic nose and bacteriological measurements were performed to analyse spoilage kinetics of oat milk samples stored at room temperature and refrigerated conditions for up to 15 days. Principal component analysis (PCA), discriminant factorial analysis (DFA) and soft independent modelling by class analogy (SIMCA) classification techniques were used to differentiate the samples of oat milk at different days. The total plate count (bacteriological method) was selected as the reference method to consistently train the electronic nose system. The e-nose was able to differentiate between the oat milk samples of varying microbial load. The results obtained by the bacteria total viable counts showed that the shelf-life of oat milk stored at room temperature and refrigerated conditions were 20 hours and 13 days, respectively. The models built classified oat milk samples based on the total microbial population into “unspoiled” and “spoiled”.

Keywords: electronic-nose, bacteriological, shelf-life, classification

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Authors: Amanda Watson

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The goal of this project is to create the conditions wherein every teacher, especially subjectarea experts, sees themselves as a teacher of language and vocabulary. Assessment and observational data suggest that students are not getting the support they need in vocabulary and reading comprehension, and secondary teachers do not currently have the confidence or expertise to provide this support. This study seeks to examine the impact of 10-20 minutes of daily, targeted instruction around orthography and vocabulary on student competence with the navigation of complex vocabulary and comprehension of subject-specific concepts and texts. The first phase of the pilot included 6 participating classroom teachers of grades 9 and 10 English (95 students in total) who administered an initial reading comprehension assessment. The results of this assessment indicated that the vast majority of students were reading below grade level. Teachers were then provided with a slide deck of complete lessons on orthography, vocabulary (etymology, roots and affixes) and reading comprehension strategies. For five weeks, teachers delivered lessons with their students, implementing the recommended evidence-based teaching strategies. Students and teachers completed surveys to provide feedback on the value and impact of the method. The results confirmed that this was new learning for the students and that the teaching strategies improved engagement. The lessons succeeded in providing equitable access to challenge by simultaneously offering theoretical learning to proficient readers, and exposure and practice to weaker readers. A second reading comprehension was administered after 5 weeks of daily instruction. Average scores increased by 41%, and almost every student experienced progress. The first phase was not long enough to measure the impact of the method on vocabulary acquisition or reading comprehension of subject-specific texts, however. The project will use the results of the first phase to design the second phase, and new teaching and learning strategies will be added. The goals of the second phases are to increase motivation, and to grow the daily practice beyond English class and into science and / or math. This team will continue to document a continuation of the daily lessons, Commented [E1]: Please do not use rhetorical questions in the abstract. measure the impact of the strategies, and address questions about the correlation between daily practice and improvements in the skills students need for vocabulary acquisition and disciplinary reading comprehension.

Keywords: adolescent, comprehension, orthography, reading, vocabulary, etymology, word study, disciplinary, teaching strategies

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Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

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Authors: Jae Hong Kim, Sang Cheol Um, Jong Kook Lee

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Strong and biocompatible wollastonite (CaSiO3) was fabricated by pressureless sintering at temperature range of 1250~ 1300 ℃ and phase transition of to β-wollastonite with an addition of MgSiO3. Starting pure α-wollastonite powder were prepared by solid state reaction, and MgSiO3 powder was added to α-wollastonite powder to induce the phase transition α to β-wollastonite over 1250℃. Sintered wollastonite samples at 1250℃ with 5 and 10 wt% MgSiO3 were α+β phase and β phase respectively, and showed higher densification rate than that of α or β-wollastonite, which are almost the same as the theoretical density. Hardness and Young’s modulus of sintered wollastonite were dependent on the apparent density and the amount of β-wollastonite. Young’s modulus (78GPa) of β-wollastonite added 10 wt% MgSiO3 was almost double time of sintered α-wollastonite. From the in-vitro test, biphasic (α+β) wollastonite with 5wt% MgSiO3 addition had good bioactivity in simulated body fluid solution.

Keywords: β-wollastonite, high density, MgSiO3, phase transition

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Authors: Dmitry V. Fomichev, Vladimir V. Solonin

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This paper presents the findings from a numerical simulation of the flow in 37-rod fuel assembly models spaced by a double-wire trapezoidal wrapping as applied to the BREST-OD-300 experimental nuclear reactor. Data on a high static pressure distribution within the models, and equations for determining the fuel bundle flow friction factors have been obtained. Recommendations are provided on using the closing turbulence models available in the ANSYS Fluent. A comparative analysis has been performed against the existing empirical equations for determining the flow friction factors. The calculated and experimental data fit has been shown. An analysis into the experimental data and results of the numerical simulation of the BREST-OD-300 fuel rod assembly hydrodynamic performance are presented.

Keywords: BREST-OD-300, ware-spaces, fuel assembly, computation fluid dynamics

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Authors: Jamshaid ul Rahman, Akhter Ali, Adnan Manzoor

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Learning-based systems have received increasing interest in recent years; recognition structures, including end-to-end speak recognition, are one of the hot topics in this area. A famous work on end-to-end speaker verification by using Angular Softmax Loss gained significant importance and is considered useful to directly trains a discriminative model instead of the traditional adopted i-vector approach. The margin-based strategy in angular softmax is beneficial to learn discriminative speaker embeddings where the random selection of margin values is a big issue in additive angular margin and multiplicative angular margin. As a better solution in this matter, we present an alternative approach by introducing a bit similar form of an additive parameter that was originally introduced for face recognition, and it has a capacity to adjust automatically with the corresponding margin values and is applicable to learn more discriminative features than the Softmax. Experiments are conducted on the part of Fisher dataset, where it observed that the additive parameter with angular softmax to train the front-end and probabilistic linear discriminant analysis (PLDA) in the back-end boosts the performance of the structure.

Keywords: additive parameter, angular softmax, speaker verification, PLDA

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Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi

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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index (PCI), average sample number (ASN), Bayesian approach

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Authors: A. Elrefaei

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The possibility of having sheets with different thicknesses and materials in one assembly facilitates the optimal material distribution within the final product and reduces the weight of the structure. Ability of joining process to assembly these different material combinations is always a challenge to the designer. In this study, 0.6 mm thick 6061-T6 and 2 mm thick 5182-O were robot CMT welded using ER5356 and ER4043 filler metals. The thermal effect of welding resulted in a loss of hardness in the 6061 HAZ. Joints welded by ER5356 filler metal were much higher in fracture load than joints welded by ER4043 and the elongation of joints welded by ER5356 was almost double its corresponding joints welded by ER4043 filler. Owing to the big difference in formability and thickness of base metals, the fracture in forming test occurred in the softened 6061 HAZ out from the weld centerline.

Keywords: aluminum, CMT, mechanical, welding

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Authors: Rakelane A. Mendes, Sandro T. M. Goncalves, Raphaella L. R. Silva

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The concepts of energy harvesting and wireless energy transfer have been widely discussed in recent times. There are some ways to create autonomous systems for collecting ambient energy, such as solar, vibratory, thermal, electromagnetic, radiofrequency (RF), among others. In the case of the RF it is possible to collect up to 100 μW / cm². To collect and/or transfer energy in RF systems, a device called rectenna is used, which is defined by the junction of an antenna and a rectifier circuit. The rectenna presented in this work is resonant at the frequencies of 1.8 GHz and 2.45 GHz. Frequencies at 1.8 GHz band are e part of the GSM / LTE band. The GSM (Global System for Mobile Communication) is a frequency band of mobile telephony, it is also called second generation mobile networks (2G), it came to standardize mobile telephony in the world and was originally developed for voice traffic. LTE (Long Term Evolution) or fourth generation (4G) has emerged to meet the demand for wireless access to services such as Internet access, online games, VoIP and video conferencing. The 2.45 GHz frequency is part of the ISM (Instrumentation, Scientific and Medical) frequency band, this band is internationally reserved for industrial, scientific and medical development with no need for licensing, and its only restrictions are related to maximum power transfer and bandwidth, which must be kept within certain limits (in Brazil the bandwidth is 2.4 - 2.4835 GHz). The rectenna presented in this work was designed to present efficiency above 50% for an input power of -15 dBm. It is known that for wireless energy capture systems the signal power is very low and varies greatly, for this reason this ultra-low input power was chosen. The Rectenna was built using the low cost FR4 (Flame Resistant) substrate, the antenna selected is a microfita antenna, consisting of a Meandered dipole, and this one was optimized using the software CST Studio. This antenna has high efficiency, high gain and high directivity. Gain is the quality of an antenna in capturing more or less efficiently the signals transmitted by another antenna and/or station. Directivity is the quality that an antenna has to better capture energy in a certain direction. The rectifier circuit used has series topology and was optimized using Keysight's ADS software. The rectifier circuit is the most complex part of the rectenna, since it includes the diode, which is a non-linear component. The chosen diode is the Schottky diode SMS 7630, this presents low barrier voltage (between 135-240 mV) and a wider band compared to other types of diodes, and these attributes make it perfect for this type of application. In the rectifier circuit are also used inductor and capacitor, these are part of the input and output filters of the rectifier circuit. The inductor has the function of decreasing the dispersion effect on the efficiency of the rectifier circuit. The capacitor has the function of eliminating the AC component of the rectifier circuit and making the signal undulating.

Keywords: dipole antenna, double-band, high efficiency, rectenna

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Authors: Benny Alexander, Ikhlashia N. Fadhilah, Muhammad R. Pasha, Michelle Julia, Anne Z. Syahrial

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Brake shoe is a component that serves to reduce speed or stop the train's speed by utilizing the friction force. Generally, the material used as a brake shoe is cast iron, where cast iron itself is a heavy, expensive, and easily worn material. Aluminum matrix composites are one of candidates for the cast iron replacement material as the basic material for brake shoe. The matrix in the composite used is Aluminum AC4B. Reinforcement used in aluminum matrix composites is nano-alumina, where the use of nano-alumina of 0.25%, 0.3%, 0.35%, 0.4%, and 0.5% volume fraction will be tested. The sample is made using the stir casting method; then, it will be tested mechanically. The use of nano-alumina as a reinforcement will increase the strength of the matrix. SEM (scanning electron microscopy) testing is used to test the distribution of reinforcing particles due to stirring. Therefore, the addition of nano-alumina will improve AC4B aluminum matrix composites.

Keywords: aluminium matrix composites, brake shoe application, stir casting, nano-alumina

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Authors: Syed Javed Arif, Mohd Ayyub Khan, Saleem Anwar Khan

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In this paper, a simple method is presented for measurement of power frequency deviations. A phase locked loop (PLL) is used to multiply the signal under test by a factor of 100. The number of pulses in this pulse train signal is counted over a stable known period, using decade driving assemblies (DDAs) and flip-flops. These signals are combined using logic gates and then passed through decade counters to give a unique combination of pulses or levels, which are further encoded. These pulses are equally suitable for both control applications and display units. The experimental circuit developed gives a resolution of 1 Hz within the measurement period of 20 ms. The proposed circuit is also simulated in Verilog Hardware Description Language (VHDL) and implemented using Field Programing Gate Arrays (FPGAs). A Mixed signal Oscilloscope (MSO) is used to observe the results of FPGA implementation. These results are compared with the results of the proposed circuit of discrete components. The proposed system is useful for frequency deviation measurement and control in power systems.

Keywords: frequency measurement, digital control, phase locked loop, encoder, Verilog HDL

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Authors: Tarek S. Jamil, Ahmed M. Shaban, Eman S. Mansor, Ahmed A. Karim, Azza M. Abdel Aty

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In this manuscript, 35 m³/d NF unit was designed and applied for surface water treatment of river Nile water. Intake of Embaba drinking water treatment plant was selected to install that unit at since; it has the lowest water quality index value through the examined 6 sites in greater Cairo area. The optimized operating conditions were feed and permeate flow, 40 and 7 m³/d, feed pressure 2.68 bar and flux rate 37.7 l/m2.h. The permeate water was drinkable according to Egyptian Ministerial decree 458/2007 for the tested parameters (physic-chemical, heavy metals, organic, algal, bacteriological and parasitological). Single and double sand filters were used as pretreatment for NF membranes, but continuous clogging for sand filters moved us to use UF membrane as pretreatment for NF membrane.

Keywords: River Nile, NF membrane, pretreatment, UF membrane, water quality

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Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

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Authors: Mohammad A. Alolayan, John S. Evans, James K. Hammitt

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The value of statistical life has been estimated for a middle eastern country with high economical subsidization system. In this study, in-person interviews were conducted on a stratified random sample to estimate the value of mortality risk. Double-bounded dichotomous choice questions followed by open-ended question were used in the interview to investigate the willingness to pay of the respondent for mortality risk reduction. High willingness to pay was found to be associated with high income and education. Also, females were found to have lower willingness to pay than males. The estimated value of statistical life is larger than the ones estimated for western countries where taxation system exists. This estimate provides a baseline for monetizing the health benefits for proposed policy or program to the decision makers in an eastern country. Also, the value of statistical life for a country in the region can be extrapolated from this this estimate by using the benefit transfer method.

Keywords: mortality, risk, VSL, willingness-to-pay

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Authors: Steve Haberlin

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United States college students are experiencing record-high stress and anxiety rates, and due to technological advances, there are more distractions in the classroom. With these challenges comes the need to explore additional, non-traditional pedagogical strategies that can help students de-stress, become centered, and feel more deeply connected to content. In addition, embedding contemplative practices, such as mindfulness meditation, in the higher education classroom could assist faculty in presenting a more holistic education that encourages students to develop self-awareness, emotional intelligence, compassion, interconnectedness, and other “non-academic” qualities. Brief meditation may help students de-stress, focus, and connect. A facilitation guide could also help faculty implement classroom meditation practices; however, additional research is needed to determine how to best train faculty, what meditation techniques work best with students, and how to handle resistance. In this paper, a two-phase study is presented that involves a mindfulness meditation intervention with 180 undergraduate students at a private college in the southeastern United States. Data were collected through qualitative surveys and journaling and analyzed for themes. Findings included a majority of students reporting improved calm, reduced stress, and increased focus and ability to transition to classroom instruction.

Keywords: college students, higher education, mindfulness meditation, stress

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Authors: Supriyono, Sumardiyono

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Biodiesel is one of the alternative fuels that promising for substituting petrodiesel as energy source which is have advantage on sustainability and eco-friendly. Due to the raw material that tend to decompose during storage, biodiesel also have the same characteristic that tend to decompose and formed higher acid value which is the result of oxidation to double bond on a chain of ester. Decomposition of biodiesel due to oxidation reaction could prevent by introduce a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. The quality degradation on biodiesel could evaluated by measuring iodine value and acid number of biodiesel. Biodiesel made from High Fatty Acid Jatropha curcas oil equality by using esterification and esterification process will stand on the quality by introduce 90 ppm pyrogallol powder on the biodiesel, which could extend the quality from 2 hours to more than 6 hours in rancimat test evaluation.

Keywords: biodiesel, antioxidant, iodine number, acid value

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Authors: JongWon Han, NoHoon Kim, HyoIk Ahn, HaeWoo Lee

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In this study, shielded metal arc welding was performed as a function of Nb content at 2.24 wt%, 3.25 wt%, and 4.26 wt%. The microstructure was observed using scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS) and showed the development of a columnar dendrite structure in the specimen having the least Nb content. From the hardness test, the hardness value was confirmed to reduce with decreasing Nb content. From electron backscatter diffraction (EBSD) analysis, the largest grain size was found in the specimen with Nb content of 2.24 wt%. The potentiodynamic polarization test was carried out to determine the pitting corrosion resistance; there was no significant difference in the pitting corrosion resistance with increasing Nb content. To evaluate the degree of sensitization to intergranular corrosion, the Double Loop Electrochemical Potentiodynamic Reactivation(DL-EPR test) was conducted. A similar degree of sensitization was found in two specimens except with a Nb content of 2.24 wt%, while a relatively high degree of sensitization was found in the specimen with a Nb content of 2.24 wt%.

Keywords: inconel 625, Nb content, potentiodynamic test, DL-EPR test

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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

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Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

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This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

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Authors: Simran Baweja, Bhavika Kalal, Surajit Maity

Abstract:

Photoinduced tautomerization reactions have been the centre of attention among the scientific community over the past several decades because of their significance in various biological systems. 7-azaindole (7AI) is considered a model system for DNA base pairing and to understand the role of such tautomerization reactions in mutations. To the best of our knowledge, extensive studies have been carried out on 7-azaindole and its solvent clusters exhibiting proton/ hydrogen transfer in both solution as well as gas phases. Derivatives of the above molecule, like 2,7- and 2,6-diazaindoles are proposed to have even better photophysical properties due to the presence of -aza group on the 2nd position. However, there are studies in the solution phase that suggest the relevance of these molecules, but there are no experimental studies reported in the gas phase yet. In our current investigation, we present the first gas phase spectroscopic data of 2,7-diazaindole (2,7-DAI) and its solvent cluster (2,7-DAI-H2O). In this, we have employed state-of-the-art laser spectroscopic methods such as fluorescence excitation (LIF), dispersed fluorescence (DF), resonant two-photon ionization-time of flight mass spectrometry (2C-R2PI), photoionization efficiency spectroscopy (PIE), IR-UV double resonance spectroscopy, i.e., fluorescence-dip infrared spectroscopy (FDIR) and resonant ion-dip infrared spectroscopy (IDIR) to understand the electronic structure of the molecule. The origin band corresponding to the S1 ← S0 transition of the bare 2,7-DAI is found to be positioned at 33910 cm-1, whereas the origin band corresponding to S1 ← S0 transition of the 2,7-DAI-H2O is positioned at 33074 cm-1. The red-shifted transition in the case of solvent cluster suggests the enhanced feasibility of excited state hydrogen/ proton transfer. The ionization potential for the 2,7-DAI molecule is found to be 8.92 eV which is significantly higher than the previously reported 7AI (8.11 eV) molecule, making it a comparatively complex molecule to study. The ionization potential is reduced by 0.14 eV in the case of 2,7-DAI-H2O (8.78 eV) cluster compared to that of 2,7-DAI. Moreover, on comparison with the available literature values of 7AI, we found the origin band of 2,7-DAI and 2,7-DAI-H2O to be red-shifted by -729 and -280 cm-1 respectively. The ground and excited state N-H stretching frequencies of the 27DAI molecule were determined using fluorescence-dip infrared spectra (FDIR) and resonant ion dip infrared spectroscopy (IDIR), obtained at 3523 and 3467 cm-1, respectively. The lower value of vNH in the electronically excited state of 27DAI implies the higher acidity of the group compared to the ground state. Moreover, we have done extensive computational analysis, which suggests that the energy barrier in the excited state reduces significantly as we increase the number of catalytic solvent molecules (S= H2O, NH3) as well as the polarity of solvent molecules. We found that the ammonia molecule is a better candidate for hydrogen transfer compared to water because of its higher gas-phase basicity. Further studies are underway to understand the excited state dynamics and photochemistry of such N-rich chromophores.

Keywords: excited state hydrogen transfer, supersonic expansion, gas phase spectroscopy, IR-UV double resonance spectroscopy, laser induced fluorescence, photoionization efficiency spectroscopy

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

Abstract:

This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: Usman Ghani

Abstract:

Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.

Keywords: simulation, feedback, training, hands-on, labs

Procedia PDF Downloads 371

Authors: Vijay Kumar Kutala, Addepalli Pavani, M. Amresh Rao, Naushad Sm

Abstract:

In this study, we evaluated the impact of CYP2C9*2 and CYP2C9*3 variants on binding and hydroxylation of warfarin. In silico data revealed that warfarin forms two hydrogen bonds with protein backbone i.e. I205 and S209, one hydrogen bond with protein side chain i.e. T301 and stacking interaction with F100 in CYP2C9*1. In CYP2C9*2 and CYP2C9*3 variants, two hydrogen bonds with protein backbone are disrupted. In double variant, all the hydrogen bonds are disrupted. The distances between C7 of S-warfarin and Fe-O in CYP2C9*1, CYP2C9*2, CYP2C9*3 and CYP2C9*2/*3 were 5.81A°, 7.02A°, 7.43° and 10.07°, respectively. The glide scores (Kcal/mol) were -7.698, -7.380, -6.821 and -6.986, respectively. Increase in warfarin/7-hydroxy warfarin ratio was observed with increase in variant alleles. To conclude, CYP2C9*2 and CYP2C9*3 variants result in disruption of hydrogen bonding interactions with warfarin and longer distance between C7 and Fe-O thus impairing warfarin 7-hydroxylation due to lower binding affinity of warfarin.

Keywords: warfarin, CYP2C9 polymorphism, personalized medicine, in Silico

Procedia PDF Downloads 315