Search results for: size driven MPB

Authors: Fathiah Mohamed Zuki, Robert George Edyvean

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Electrostatic interaction energy (∆EEDL) is a part of the Extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory, which, together with van der Waals (∆EVDW) and acid base (∆EAB) interaction energies, has been extensively used to investigate the initial adhesion of bacteria to surfaces. Electrostatic or electrical double layer interaction energy is considerably affected by surface potential, however it cannot be determined experimentally and is usually replaced by zeta (ζ) potential via electrophoretic mobility. This paper focuses on the effect of ionic concentration as a function of pH and the effect of mineral grain size on ζ potential. It was found that both ionic strength and mineral grain size play a major role in determining the value of ζ potential for the adhesion of P. putida to hematite and quartz surfaces. Higher ζ potential values lead to higher electrostatic interaction energies and eventually to higher total XDLVO interaction energy resulting in bacterial repulsion.

Keywords: XDLVO, electrostatic interaction energy, zeta potential, P. putida, mineral

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Authors: Smita Singh

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The paper develops a critical framework to the hegemonic discourses resorted to by the dominant powers in the global security architecture. Within this framework, security is viewed as a discourse through which identities and threats are represented and produced to legitimize the security concerns of few at the cost of others. International security have long been driven and dominated by power relations. Since the end of the Cold War, the global transformations have triggered contestations to the idea of security at both theoretical and practical level. These widening and deepening of the concept of security have challenged the existing power hierarchies at the theoretical level but not altered the substance and actors defining it. When discourses are introduced into security studies, several critical questions erupt: how has power shaped security policies of the globe through language? How does one understand the meanings and impact of those discourses? Who decides the agenda, rules, players and outliers of the security? Language as a symbolic system and form of power is fluid and not fixed. Over the years the dominant Western powers, led by the United States of America have employed various discursive practices such as humanitarian intervention, responsibility to protect, non proliferation, human rights, war on terror and so on to reorient the constitution of identities and interests and hence the policies that need to be adopted for its actualization. These power relations are illustrated in this paper through the narratives used in the nonproliferation regime. The hierarchical security dynamics is a manifestation of the global power relations driven by many factors including discourses.

Keywords: hegemonic discourse, global security, non-proliferation regime, power politics

Procedia PDF Downloads 318

Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Esra Alveroglu Durucu, Kenan Koc

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In this study, we synthesized and characterized nano-sized Poly- N-isopropylacrylamide (PNIPAM) hydrogels. N-isopropylacrylamide (NIPAM) micro and macro gels are known as a thermosensitive colloidal structure, and they respond to changes in the environmental conditions such as temperature and pH. Here, nano-sized gels were synthesized via precipitation copolymerization method. N,N-methylenebisacrylamide (BIS) and ammonium persulfate APS were used as crosslinker and initiator, respectively. 8-Hydroxypyrene-1,3,6- trisulfonic Acid (Pyranine, Py) molecules were used for arranging the particle size and thus physical properties of the nano-sized hydrogels. Fluorescence spectroscopy, atomic force microscopy and light scattering methods were used for characterizing the synthesized hydrogels. The results show that the gel size was decreased with increasing amount of ionic molecule from 550 to 140 nm due to the electrostatic behavior of the ionic side groups of pyranine. Light scattering experiments demonstrate that lower critical solution temperature (LCST) of the gels shifts to the lower temperature with decreasing size of gel due to the hydrophobicity–hydrophilicity balance of the polymer chains.

Keywords: hydrogels, lower critical solution temperature, nanogels, poly(n-isopropylacrylamide)

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Authors: Prakriti Diwan, S. Saraf

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The present study involves preparation and evaluation of microparticles of diclofenac sodium. The microparticles were prepared by the emulsion solvent evaporation techniques using ethylcellulose polymer. Four different batches of microspheres were prepared by varying the concentration of polymer from 50% to 80% w/w. The microspheres were characterized for drug content, percentage yield and encapsulation efficiency, particle size analysis and surface morphology. Microsphere prepared with high drug content produces higher percentage yield and encapsulation efficiency values. It was observed the increase in concentration of the polymer, increases the mean particle size of the microspheres. The effect of polymer concentration on the in vitro release of diclofenac from the microspheres was also studied. The production microparticles yield showed 98.74%, mean particle size 956.32µm and loading efficiency 97.15%. The results were found that microparticles prepared had slower release than microparticles (p>0.05). Therefore, it may be concluded that drug loaded microparticles are suitable delivery systems for diclofenac sodium.

Keywords: diclofenac sodium, emulsion solvent evaporation, ethylcellulose, microparticles

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 159

Authors: Mohammad Goli, Akram Sharifi, Mohammad Yousefi Jozdani, Seyed Ali Mortazavi

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An industrial spray dryer was used, and the effects of atomizer speed on the physicochemical properties of milk powder, the textural and sensory characteristics of white cheese made from this milk powder, were evaluated. For this purpose, whole milk was converted into powder by using three different speeds (10,000, 11,000, and 12,000 rpm). Results showed that with increasing atomizer speed in the spray dryer, the average size of casein micelle is significantly decreased (p < 0.05), whereas no significant effect is observed on the chemical properties of milk powder. White cheese characteristics indicated that with increasing atomizer speed, texture parameters, such as hardness, mastication, and gumminess, were significantly reduced (p < 0.05). Sensory evaluation also revealed that cheese samples prepared with dried milk produced at 12,000 rpm were highly accepted by panelists. Overall, the findings suggested that 12,000 rpm is the optimal atomizer speed for milk powder production.

Keywords: spray drying, powder technology, atomizer speed, particle size, white cheese physical properties

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Authors: M. A. Yazdi, J. Yang, L. Yihui, H. Su

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The application of recycle waste tires into civil engineering practices, namely asphalt paving mixtures and cementbased materials has been gaining ground across the world. This review summarizes and compares the recent achievements in the area of plain rubberized concrete (PRC), in details. Different treatment methods have been discussed to improve the performance of rubberized Portland cement concrete. The review also includes the effects of size and amount of tire rubbers on mechanical and durability properties of PRC. The microstructure behaviour of the rubberized concrete was detailed.

Keywords: waste rubber aggregates, microstructure, treatment methods, size and content effects

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Authors: Vakamalla Teja Reddy, Narasimha Mangadoddy

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Hydrocyclones are used to separate particles into different size fractions in the mineral processing, chemical and metallurgical industries. High speed video imaging, Laser Doppler Anemometry (LDA), X-ray and Gamma ray tomography are previously used to measure the two-phase flow characteristics in the cyclone. However, investigation of solids flow characteristics inside the cyclone is often impeded by the nature of the process due to slurry opaqueness and solid metal wall vessels. In this work, a dual-plane high speed Electrical resistance tomography (ERT) is used to measure hydrocyclone internal flow dynamics in situ. Experiments are carried out in 3 inch hydrocyclone for feed solid concentrations varying in the range of 0-50%. ERT data analysis through the optimized FEM mesh size and reconstruction algorithms on air-core and solid concentration tomograms is assessed. Results are presented in terms of the air-core diameter and solids volume fraction contours using Maxwell’s equation for various hydrocyclone operational parameters. It is confirmed by ERT that the air core occupied area and wall solids conductivity levels decreases with increasing the feed solids concentration. Algebraic slip mixture based multi-phase computational fluid dynamics (CFD) model is used to predict the air-core size and the solid concentrations in the hydrocyclone. Validation of air-core size and mean solid volume fractions by ERT measurements with the CFD simulations is attempted.

Keywords: air-core, electrical resistance tomography, hydrocyclone, multi-phase CFD

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Authors: I. S. R. Butswat, D. Zahraddeen

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This study identified and described some skill-based and necessity-driven entrepreneurship in animal agriculture (AA). AA is an integral segment of the world food industry, and provides a good and rapid source of income. The contribution of AA to the Sub-Saharan economy is quite significant, and there are still large opportunities that remain untapped in the sector. However, it is imperative to understand, simplify and package the various components of AA in order to pave way for rapid wealth creation, poverty eradication and women empowerment programmes in sub-Saharan Africa and other developing countries. The entrepreneurial areas of AA highlighted were animal breeding, livestock fattening, dairy production, poultry farming, meat production (beef, mutton, chevon, etc.), rabbit farming, wool/leather production, animal traction, animal feed industry, commercial pasture management, fish farming, sport animals, micro livestock production, private ownership of abattoirs, slaughter slabs, animal parks and zoos, among others. This study concludes that reproductive biotechnology such as oestrous synchronization, super-/multiple ovulation, artificial insemination and embryo transfer can be employed as a tool for improvement of genetic make-up of low-yielding animals in terms of milk, meat, egg, wool, leather production and other economic traits that will necessitate sustainable job and wealth creations.

Keywords: animal, agriculture, entreprenurship, wealth

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Authors: Melvin Chan, Chew Lee Teo

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There has been a growing emphasis in elevating the teachers’ proficiency and competencies through continuing professional development (CPD) opportunities. In this era of a Volatile, Uncertain, Complex, Ambiguous (VUCA) world, teachers are expected to be collaborative designers, critical thinkers and creative builders. However, many of the CPD structures are still revolving in the model of transmission, which stands in contradiction to the cultivation of future-ready teachers for the innovative world of emerging technologies. This article puts forward the framing of CPD through a Principle-Based, Technological-Driven Knowledge Building Approach grounded in the essence of andragogy and progressive learning theories where growth is best exemplified through an authentic immersion in a social/community experience-based setting. Putting this Knowledge Building Professional Development Model (KBPDM) in operation via a Professional Learning Team (PLT) situated in a Secondary School in Singapore, research findings reveal that the intervention has led to a fundamental change in the learning paradigm of the teachers, henceforth equipping and empowering them successfully in their pedagogical design and practices for a 21^st century classroom experience. This article concludes with the possibility in leveraging the Learning Analytics to deepen the CPD experiences for educators.

Keywords: continual professional development, knowledge building, learning paradigm, principle-based

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Authors: Khaled Moh. Alhamad

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This paper describes a tabu search heuristic for a ship routing and scheduling problem (SRSP). The method was developed to address the problem of loading cargos for many customers using heterogeneous vessels. Constraints relate to delivery time windows imposed by customers, the time horizon by which all deliveries must be made and vessel capacities. The results of a computational investigation are presented. Solution quality and execution time are explored with respect to problem size and parameters controlling the tabu search such as tenure and neighbourhood size.

Keywords: heuristic, scheduling, tabu search, transportation

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Authors: Khaleel Sami Hamdan, Dong-Eok Kim, Sang-Ki Moon

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An appropriate model to predict the size of the droplets resulting from the break-up with the structures will help in a better understanding and modeling of the two-phase flow calculations in the simulation of a reactor core loss-of-coolant accident (LOCA). A droplet behavior impacting on a hot surface above the Leidenfrost temperature was investigated. Droplets of known size and velocity were impacted to an inclined plate of hot temperature, and the behavior of the droplets was observed by a high-speed camera. It was found that for droplets of Weber number higher than a certain value, the higher the Weber number of the droplet the smaller the secondary droplets. The COBRA-TF model over-predicted the measured secondary droplet sizes obtained by the present experiment. A simple model for the secondary droplet size was proposed using the mass conservation equation. The maximum spreading diameter of the droplets was also compared to previous correlations and a fairly good agreement was found. A better prediction of the heat transfer in the case of LOCA can be obtained with the presented model.

Keywords: break-up, droplet, impact, inclined hot plate, Leidenfrost temperature, LOCA

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Authors: Zoran Šverko, Saša Vlahinić, Nino Stojković, Ivan Markovinović

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In this article, the classification of target letters is performed using data from the EEG P300 Speller paradigm. Neural networks trained with the results of dynamic connectivity analysis between different brain regions are used for classification. Dynamic connectivity analysis is based on the adaptive window size and the imaginary part of the complex Pearson correlation coefficient. Brain dynamics are analysed using the relative intersection of confidence intervals for the imaginary component of the complex Pearson correlation coefficient method (RICI-imCPCC). The RICI-imCPCC method overcomes the shortcomings of currently used dynamical connectivity analysis methods, such as the low reliability and low temporal precision for short connectivity intervals encountered in constant sliding window analysis with wide window size and the high susceptibility to noise encountered in constant sliding window analysis with narrow window size. This method overcomes these shortcomings by dynamically adjusting the window size using the RICI rule. This method extracts information about brain connections for each time sample. Seventy percent of the extracted brain connectivity information is used for training and thirty percent for validation. Classification of the target word is also done and based on the same analysis method. As far as we know, through this research, we have shown for the first time that dynamic connectivity can be used as a parameter for classifying EEG signals.

Keywords: dynamic connectivity analysis, EEG, neural networks, Pearson correlation coefficients

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Authors: Kai-Fen Tu, Jenn-Wen Huang, Yao-Tung Lin

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Cucumber is a major economic crop in the world. The global production of cucumber in 2017 was more than 71 million tonnes. Nonetheless, downy mildew, caused by Pseudoperonospora cubensis, is a devastating and common disease on cucumber in around 80 countries and causes severe economic losses. The long-term usage of fungicide also leads to the occurrence of fungicide resistance and decreases host resistance. In this study, six types of oil (neem oil, moringa oil, soybean oil, cinnamon oil, clove oil, and camellia oil) were selected to synthesize micro/nano-sized emulsions, and the disease control efficacy of micro/nano-sized emulsions were evaluated. Moreover, oil concentrations (0.125% - 1%) and droplet size of emulsion were studied. Results showed cinnamon-type emulsion had the best efficacy among these oils. The disease control efficacy of these emulsions increased as the oil concentration increased. Both disease incidence and disease severity were measured by detached leaf and pot experiment, respectively. For the droplet size effect, results showed that the 114 nm of droplet size synthesized by 0.25% cinnamon oil emulsion had the lowest disease incidence (6.67%) and lowest disease severity (33.33%). The release of zoospore was inhibited (5.33%), and the sporangia germination was damaged. These results suggest that cinnamon oil emulsion will be a valuable and environmentally friendly alternative to control cucumber downy mildew. The economic loss caused by plant disease could also be reduced.

Keywords: downy mildew, emulsion, oil droplet size, plant protectant

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Authors: Muhammad Gillfran Samual, Rinaldy Dalimi, Fauzan Hanif Jufri, Budi Sudiarto, Ismi Rosyiana Fitri

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Solar energy is increasingly recognized as an important future energy source due to its abundant availability and renewable nature. However, the intermittent nature of solar energy can cause fluctuations in the electricity produced, making it difficult to guarantee a stable and reliable electricity supply. One solution that can be implemented is to use batteries in a photovoltaic solar power plant system with a Moving Average control algorithm, which can help smooth and reduce fluctuations in solar power output power. The parameter that can be adjusted in the Moving Average algorithm is the window size or the arithmetic average width of the photovoltaic output power over time. This research evaluates the effect of a change of window size parameter in the Moving Average algorithm on the resulting smoothed photovoltaic output power and the technical effects on batteries, i.e., power and energy usage. Based on the evaluation, it is found that the increase of window size parameter will slow down the response of photovoltaic output power to changes in irradiation and increase the smoothing quality of the intermittent photovoltaic output power. In addition, increasing the window size will reduce the maximum power received on the load side, and the amount of energy used by the battery during the power smoothing process will increase, which, in turn, increases the required battery capacity.

Keywords: battery, intermittent, moving average, photovoltaic, power smoothing

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Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao

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The main aim of the paper is to implement a technique using distributed generation in distribution systems to reduce the distribution system losses and to improve voltage profiles. The fuzzy logic technique is used to select the proper location of DG and an analytical method is proposed to calculate the size of DG unit at any power factor. The optimal sizes of DG units are compared with optimal sizes obtained using the genetic algorithm. The suggested method is programmed under Matlab software and is tested on IEEE 33 bus system and the results are presented.

Keywords: DG Units, sizing of DG units, analytical methods, optimum size

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Authors: Manon Ghislain, Timothée Bonnet, Olivier Gimenez, Olivier Dehorter, Pierre-Yves Henry

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Climatic fluctuations affect the demography of animal populations, generating changes in population size, phenology, distribution and community assemblages. However, very few studies have identified the underlying demographic processes. For short-lived species, like common passerine birds, are these changes generated by changes in adult survival or in fecundity and recruitment? This study tests for an effect of annual climatic conditions (spring and winter) on annual, local adult survival at very large spatial (a country, 252 sites), temporal (25 years) and biological (25 species) scales. The Constant Effort Site ringing has allowed the collection of capture - mark - recapture data for 100 000 adult individuals since 1989, over metropolitan France, thus documenting annual, local survival rates of the most common passerine birds. We specifically developed a set of multi-year, multi-species, multi-site Bayesian models describing variations in local survival and recapture probabilities. This method allows for a statistically powerful hierarchical assessment (global versus species-specific) of the effects of climate variables on survival. A major part of between-year variations in survival rate was common to all species (74% of between-year variance), whereas only 26% of temporal variation was species-specific. Although changing spring climate is commonly invoked as a cause of population size fluctuations, spring climatic anomalies (mean precipitation or temperature for March-August) do not impact adult survival: only 1% of between-year variation of species survival is explained by spring climatic anomalies. However, for sedentary birds, winter climatic anomalies (North Atlantic Oscillation) had a significant, quadratic effect on adult survival, birds surviving less during intermediate years than during more extreme years. For migratory birds, we do not detect an effect of winter climatic anomalies (Sahel Rainfall). We will analyze the life history traits (migration, habitat, thermal range) that could explain a different sensitivity of species to winter climate anomalies. Overall, we conclude that changes in population sizes for passerine birds are unlikely to be the consequences of climate-driven mortality (or emigration) in spring but could be induced by other demographic parameters, like fecundity.

Keywords: Bayesian approach, capture-recapture, climate anomaly, constant effort sites scheme, passerine, seasons, survival

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Authors: Bok Yae Chung, Eun Hee Oh

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Breast cancer patients require more nutritional interventions than others. However, a few studies have attempted to assess the overall nutritional status, to reduce body weight and BMI by improving diet, and to improve the prognosis of cancer for breast cancer patients. The purpose of this study was to evaluate the effect of diet intervention in the breast cancer patients through meta-analysis. For the study purpose, 16 studies were selected by using PubMed, ScienceDirect, ProQuest and CINAHL. Meta-analysis was performed using a random-effects model, and the effect size on outcome variables in breast cancer was calculated. The effect size for outcome variables of diet intervention was a large effect size. For heterogeneity, moderator analysis was performed using intervention type and intervention duration. All moderators did not significant difference. Diet intervention has significant positive effects on outcome variables in breast cancer. As a result, it is suggested that the timing of the intervention should be no more than six months, but a strategy for sustaining long-term intervention effects should be added if nutritional intervention is to be administered for breast cancer patients in the future.

Keywords: breast cancer, diet, mete-analysis, intervention

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Authors: Isha Saxena, Behzad Kazemtabrizi, Matthias C. M. Troffaes, Christopher Crabtree

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The calculations done at the beginning of the life of a wind farm are rarely reliable, which makes it important to conduct research and study the failure and repair rates of the wind turbines under various conditions. This miscalculation happens because the current models make a simplifying assumption that the failure/repair rate remains constant over time. This means that the reliability function is exponential in nature. This research aims to create a more accurate model using sensory data and a data-driven approach. The data cleaning and data processing is done by comparing the Power Curve data of the wind turbines with SCADA data. This is then converted to times to repair and times to failure timeseries data. Several different mathematical functions are fitted to the times to failure and times to repair data of the wind turbine components using Maximum Likelihood Estimation and the Posterior expectation method for Bayesian Parameter Estimation. Initial results indicate that two parameter Weibull function and exponential function produce almost identical results. Further analysis is being done using the complex system analysis considering the failures of each electrical and mechanical component of the wind turbine. The aim of this project is to perform a more accurate reliability analysis that can be helpful for the engineers to schedule maintenance and repairs to decrease the downtime of the turbine.

Keywords: reliability, bayesian parameter inference, maximum likelihood estimation, weibull function, SCADA data

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Authors: Jeong Ju Kim, Hee Yoon Chung, Dong Ho Rhee, Hyung Hee Cho

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There is a gap at combustor-turbine interface where leakage flow comes out to prevent hot gas ingestion into the gas turbine nozzle platform. The leakage flow protects the nozzle endwall surface from the hot gas coming from combustor exit. For controlling flow’s stream, the gap’s geometry is transformed by changing fillet radius size. During the operation, step configuration is occurred that was unintended between combustor-turbine platform interface caused by thermal expansion or mismatched assembly. In this study, CFD simulations were performed to investigate the effect of the fillet and step on heat transfer and film cooling effectiveness on the nozzle platform. The Reynolds-averaged Navier-stokes equation was solved with turbulence model, SST k-omega. With the fillet configuration, predicted film cooling effectiveness results indicated that fillet radius size influences to enhance film cooling effectiveness. Predicted film cooling effectiveness results at forward facing step configuration indicated that step height influences to enhance film cooling effectiveness. We suggested that designer change a combustor-turbine interface configuration which was varied by fillet radius size near endwall gap when there was a step at combustor-turbine interface. Gap shape was modified by increasing fillet radius size near nozzle endwall. Also, fillet radius and step height were interacted with the film cooling effectiveness and heat transfer on endwall surface.

Keywords: gas turbine, film cooling effectiveness, endwall, fillet

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Authors: Ejay Nsugbe, Andrew Starr, Ian Jennions, Cristobal Ruiz-Carcel

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This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250 microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated.

Keywords: acoustic emissions, particle sizing, process monitoring, signal processing

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Authors: Janusz K. Grabara, Bartłomiej Okwiet, Sebastian Kot

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The purpose of the article is presentation and analysis of the aspect of job security in small and medium-size enterprises in Poland with reference to other EU countries. We show the theoretical aspects of the risk with reference to managing small and medium enterprises, next risk management in small and medium enterprises in Poland, which were subjected to a detailed analysis. We show in detail the risk associated with the operation of the mentioned above companies, as well as analyses its levels on various stages and for different kinds of conducted activity.

Keywords: job safety, SME, work risk, risk management

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Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang

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Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

Keywords: hit rate, locality of program, stack cache, stack data

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Authors: Abdelhadi Lotfi, Abdelkader Benyettou

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In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.

Keywords: classification, probabilistic neural networks, network optimization, pattern recognition

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Authors: Hemant Kumar, Nilendu Das

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A study based on ANN structure gives us the information to predict the size of the future in realizing a past event. ANN, IMD (Indian meteorological department) data and remote sensing were used to enable a number of parameters for calculating the size that may occur in the future. A threshold selected specifically above the high-frequency harvest reached the area during the selected seismic activity. In the field of human and local biodiversity it remains to obtain the right parameter compared to the frequency of impact. But during the study the assumption is that predicting seismic activity is a difficult process, not because of the parameters involved here, which can be analyzed and funded in research activity.

Keywords: ANN, Bayesion class, earthquakes, IMD

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Authors: Hsi Wei

Abstract:

Does the language we speak affect the way we think? This question has been discussed for a long time from different aspects. In this article, the issue is examined with an experiment on how speakers of different languages tend to do different sequencing when it comes to the size of general objects. An essential difference between the usage of English and Mandarin is the way we sequence the size of places or objects. In English, when describing the location of something we may say, for example, ‘The pen is inside the trashcan next to the tree at the park.’ In Mandarin, however, we would say, ‘The pen is at the park next to the tree inside the trashcan.’ It’s clear that generally English use the sequence of small to big while Mandarin the opposite. Therefore, the experiment was conducted to test if the difference of the languages affects the speakers’ ability to do the different sequencing. There were two groups of subjects; one consisted of English native speakers, another of Mandarin native speakers. Within the experiment, three nouns were showed as a group to the subjects as their native languages. Before they saw the nouns, they would first get an instruction of ‘big to small’, ‘small to big’, or ‘repeat’. Therefore, the subjects had to sequence the following group of nouns as the instruction they get or simply repeat the nouns. After completing every sequencing and repetition in their minds, they pushed a button as reaction. The repetition design was to gather the mere reading time of the person. As the result of the experiment showed, English native speakers reacted more quickly to the sequencing of ‘small to big’; on the other hand, Mandarin native speakers reacted more quickly to the sequence ‘big to small’. To conclude, this study may be of importance as a support for linguistic relativism that the language we speak do shape the way we think.

Keywords: language, linguistic relativism, size, sequencing

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Authors: Sultan Ghaleb Aldaihani

Abstract:

- The environment in which educational leadership takes place is becoming increasingly complex due to factors like globalization and rapid technological change. - This is creating a "leadership gap" where the complexity of the environment outpaces the ability of leaders to effectively respond. - Educational leadership involves guiding teachers and the broader school system towards improved student learning and achievement. 2. Implications of Artificial Intelligence (AI) in Educational Leadership: - AI has great potential to enhance education, such as through intelligent tutoring systems and automating routine tasks to free up teachers. - AI can also have significant implications for educational leadership by providing better information and data-driven decision-making capabilities. - Computer-adaptive testing can provide detailed, individualized data on student learning that leaders can use for instructional decisions and accountability. 3. Enhancing Decision-Making Processes: - Statistical models and data mining techniques can help identify at-risk students earlier, allowing for targeted interventions. - Probability-based models can diagnose students likely to drop out, enabling proactive support. - These data-driven approaches can make resource allocation and decision-making more effective. 4. Improving Efficiency and Productivity: - AI systems can automate tasks and change processes to improve the efficiency of educational leadership and administration. - Integrating AI can free up leaders to focus more on their role's human, interactive elements.

Keywords: Education, Leadership, Technology, Artificial Intelligence

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Authors: Ummeh Saika, Toshio Kikuchi

Abstract:

Population growth and urbanization is a global phenomenon. As the rapid progress of technology, many cities in the international community are facing serious problems of urbanization. There is no doubt that the urbanization will proceed to have significant impact on the ecology, economy and society at local, regional, and global levels. The inhabitants of Dhaka city suffer from lack of proper urban facilities. The green spaces are needed for different functional and leisure activities of the urban dwellers. Again growing densification, a number of green space are transferred into open space in the Dhaka city. As a result greenery of the city's decreases gradually. Moreover, the existing green space is frequently threatened by encroachment. The role of green space, both at community and city level, is important to improve the natural environment and social ties for future generations. Therefore, it seems that the green space needs to be more effective for public interaction. The main objective of this study is to address the effectiveness of urban green space (Urban Park) of Dhaka City. Two approaches are selected to fulfill the study. Firstly, analyze the long-term spatial changes of urban green space using GIS and secondly, investigate the relationship of urban park network with physical and social environment. The case study site covers eight urban parks of Dhaka metropolitan area of Bangladesh. Two aspects (Physical and Social) are applied for this study. For physical aspect, satellite images and aerial photos of different years are used to find out the changes of urban parks. And for social aspect, methods are used as questionnaire survey, interview, observation, photographs, sketch and previous information of parks to analyze about the social environment of parks. After calculation of all data by descriptive statistics, result is shown by maps using GIS. According to physical size, parks of Dhaka city are classified into four types: Small, Medium, Large and Extra Large parks. The observed result showed that the physical and social environment of urban parks varies with their size. In small size parks physical environment is moderate by newly tree plantation and area expansion. However, in medium size parks physical environment are poor, example- tree decrease, exposed soil increase. On the other hand, physical environment of large size and extra large size parks are in good condition, because of plenty of vegetation and well management. Again based on social environment, in small size parks people mainly come from surroundings area and mainly used as waiting place. In medium-size parks, people come to attend various occasion from different places. In large size and extra large size parks, people come from every part of the city area for tourism purpose. Urban parks are important source of green space. Its influence both physical and social environment of urban area. Nowadays green space area gradually decreases and transfer into open space. The consequence of this research reveals that changes of urban parks influence both physical and social environment and also impact on urban life.

Keywords: physical environment, social environment, urban life, urban parks

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