Search results for: predictive distribution

Authors: M. Budakoglu, M. Karaman

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Lake Acıgöl is located in area with limited influences from urban and industrial pollution sources, there is nevertheless a need to understand all potential lithological and anthropogenic sources of priority contaminants in this closed basin. This study discusses vertical and horizontal distribution pattern of major, trace elements of recent lake sediments to better understand their current geochemical analog with lithological units in the Lake Acıgöl basin. This study also provides reliable background levels for the region by the detailed surfaced lithological units data. The detail results of surface, subsurface and shallow core sediments from these relatively unperturbed ecosystems, highlight its importance as conservation area, despite the high-scale industrial salt production activity. While P2O5/TiO2 versus MgO/CaO classification diagram indicate magmatic and sedimentary origin of lake sediment, Log(SiO2/Al2O3) versus Log(Na2O/K2O) classification diagrams express lithological assemblages of shale, iron-shale, vacke and arkose. The plot between TiO2 vs. SiO2 and P2O5/TiO2 vs. MgO/CaO also supports the origin of the primary magma source. The average compositions of the 20 different lithological units used as a proxy for geochemical background in the study area. As expected from weathered rock materials, there is a large variation in the major element content for all analyzed lake samples. The A-CN-K and A-CNK-FM ternary diagrams were used to deduce weathering trends. Surface and subsurface sediments display an intense weathering history according to these ternary diagrams. The most of the sediments samples plot around UCC and TTG, suggesting a low to moderate weathering history for the provenance. The sediments plot in a region clearly suggesting relative similar contents in Al2O3, CaO, Na2O, and K2O from those of lithological samples.

Keywords: Lake Acıgöl, recent lake sediment, geochemical speciation of major and trace elements, heavy metals, Denizli, Turkey

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Authors: Qiuling Xie, Shanliang Zhu, Zongdi Sun

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In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given.

Keywords: grey relational degree, multiple linear regression, membership function, nonlinear programming

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Zhichao Song, Swanand Vaidya

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Nowadays, most portable (e.g., smartphones) and wearable (e.g., smartwatches and earphones) consumer hardware are designed to be dustproof following IP5 or IP6 ratings to ensure the product is able to handle potentially dusty outdoor environments. On the other hand, the design guideline is relatively vague for indoor devices (e.g., smart displays and speakers). While it is generally believed that the indoor environment is much less dusty, in certain circumstances, dust ingression is still able to cause functional failures, such as microphone frequency response shift and camera black spot, or cosmetic dissatisfaction, mainly the dust build up in visible pockets and gaps which is hard to clean. In this paper, we developed a simulation methodology to analyze dust settlement and ingression into known ports of a device. A closed system is initialized with dust particles whose sizes follow Weibull distribution based on data collected in a user study, and dust particle movement was approximated as a settlement in stationary fluid, which is governed by Stokes’ law. Following this method, we simulated dust ingression into MEMS microphone through the acoustic port and protective mesh. Various design and environmental parameters are evaluated including mesh pore size, acoustic port depth-to-diameter ratio, mass density of dust material and inclined angle of microphone port. Although the dependencies of dust resistance on these parameters are all monotonic, smaller mesh pore size, larger acoustic depth-to-opening ratio and more inclined microphone placement (towards horizontal direction) are preferred for dust resistance; these preferences may represent certain trade-offs in audio performance and compromise in industrial design. The simulation results suggest the quantitative ranges of these parameters, with more pronounced effects in the improvement of dust resistance. Based on the simulation results, we proposed several design guidelines that intend to achieve an overall balanced design from audio performance, dust resistance, and flexibility in industrial design.

Keywords: dust settlement, numerical simulation, microphone design, Weibull distribution, Stoke's equation

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Authors: Bai-Chen Xie, Xian-Peng Chen

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China has become the world's largest energy producer and consumer, and its development of renewable energy is of great significance to global energy governance and the fight against climate change. The rapid growth of solar power in China could help achieve its ambitious carbon peak and carbon neutrality targets early. However, the non-technical costs of solar power in China are much higher than at international levels, meaning that inefficiencies are rooted in poor management and improper policy design and that efficiency distortions have become a serious challenge to the sustainable development of the renewable energy industry. Unlike fossil energy generation technologies, the output of solar power is closely related to the volatile solar resource, and the spatial unevenness of solar resource distribution leads to potential efficiency spatial distribution differences. It is necessary to develop an efficiency evaluation method that considers the volatility of solar resources and explores the mechanism of the influence of natural geography and social environment on the spatially varying characteristics of efficiency distribution to uncover the root causes of managing inefficiencies. The study sets solar resources as stochastic inputs, introduces a chance-constrained data envelopment analysis model combined with the directional distance function, and measures the solar resource utilization efficiency of 222 solar power plants in representative photovoltaic bases in northwestern China. By the meta-frontier analysis, we measured the characteristics of different power plant clusters and compared the differences among groups, discussed the mechanism of environmental factors influencing inefficiencies, and performed statistical tests through the system generalized method of moments. Rational localization of power plants is a systematic project that requires careful consideration of the full utilization of solar resources, low transmission costs, and power consumption guarantee. Suitable temperature, precipitation, and wind speed can improve the working performance of photovoltaic modules, reasonable terrain inclination can reduce land cost, and the proximity to cities strongly guarantees the consumption of electricity. The density of electricity demand and high-tech industries is more important than resource abundance because they trigger the clustering of power plants to result in a good demonstration and competitive effect. To ensure renewable energy consumption, increased support for rural grids and encouraging direct trading between generators and neighboring users will provide solutions. The study will provide proposals for improving the full life-cycle operational activities of solar power plants in China to reduce high non-technical costs and improve competitiveness against fossil energy sources.

Keywords: solar power plants, environmental factors, data envelopment analysis, efficiency evaluation

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Authors: Muhammad Luthfi, Sutikno Sutikno, Purhadi Purhadi

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Weather forecast has necessarily been improved to provide the communities an accurate and objective prediction as well. To overcome such issue, the numerical-based weather forecast was extensively developed to reduce the subjectivity of forecast. Yet the Numerical Weather Predictions (NWPs) outputs are unfortunately issued without taking dynamical weather behavior and local terrain features into account. Thus, NWPs outputs are not able to accurately forecast the weather quantities, particularly for medium and long range forecast. The aim of this research is to aid and extend the development of ensemble forecast for Meteorology, Climatology, and Geophysics Agency of Indonesia. Ensemble method is an approach combining various deterministic forecast to produce more reliable one. However, such forecast is biased and uncalibrated due to its underdispersive or overdispersive nature. As one of the parametric methods, Bayesian Model Averaging (BMA) generates the calibrated ensemble forecast and constructs predictive PDF for specified period. Such method is able to utilize ensemble of any size but does not take spatial correlation into account. Whereas space dependencies involve the site of interest and nearby site, influenced by dynamic weather behavior. Meanwhile, Geostatistical Output Perturbation (GOP) reckons the spatial correlation to generate future weather quantities, though merely built by a single deterministic forecast, and is able to generate an ensemble of any size as well. This research conducts both BMA and GOP to generate the calibrated ensemble forecast for the daily temperature at few meteorological sites nearby Indonesia international airport.

Keywords: Bayesian Model Averaging, ensemble forecast, geostatistical output perturbation, numerical weather prediction, temperature

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Authors: Catherine Felce, Lior Pachter

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Current methods for building phylogenetic trees from gene expression data consider mean expression levels. With single-cell technologies, we can leverage more information about cell dynamics by considering the entire distribution of gene expression across cells. Using biophysical modeling, we propose a method for constructing phylogenetic trees from scRNA-seq data, building on Felsenstein's method of continuous characters. This method can highlight genes whose level of expression may be unchanged between species, but whose rates of transcription/decay may have evolved over time.

Keywords: phylogenetics, single-cell, biophysical modeling, transcription

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Authors: Bae Doobyong, Yoo Jaejun, Park Ilgyu, Choi Seowon, Oh Chang Kook

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Variation of slip coefficient in slip-critical connections of curved plates. This paper presents the results of analytical investigations of slip coefficients in slip-critical bolted connections of curved plates. It may depend on the contact stress distribution at interface and the flexibility of spliced plate. Non-linear FEM analyses have been made to simulate the behavior of bolted connections of curved plates with various radiuses of curvature and thicknesses.

Keywords: slip coefficient, curved plates, slip-critical bolted connection, radius of curvature

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Authors: Włodzimierz Lewandowski, Renata Świsłocka, Aleksandra Golonko, Grzegorz Świderski, Monika Kalinowska

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Caffeic acid (3,4-dihydroxycinnamic) is distributed in a free form or as ester conjugates in many fruits, vegetables and seasonings including plants used for medical purpose. Caffeic acid is present in propolis – a substance with exceptional healing properties used in natural medicine since ancient times. The antioxidant, antibacterial, antiinflammatory and anticarcinogenic properties of caffeic acid are widely described in the literature. The biological activity of chemical compounds can be modified by the synthesis of their derivatives or metal complexes. The structure of the compounds determines their biological properties. This work is a continuation of the broader topic concerning the investigation of the correlation between the electronic charge distribution and biological (anticancer and antioxidant) activity of the chosen phenolic acids and their metal complexes. In the framework of this study the synthesis of new metal complexes of sodium, magnesium, aluminium, iron (III) ruthenium (III) and osmium (III) with caffeic acid was performed. The spectroscopic properties of these compounds were studied by means of FT-IR, FT-Raman, UV-Vis, ¹H and ¹³C NMR. The quantum-chemical calculations (at B3LYP/LAN L2DZ level) of caffeic acid and selected complexes were done. Moreover the antioxidant properties of synthesized complexes were studied in relation to selected stable radicals (method of reduction of DPPH and method of reduction of ABTS). On the basis of the differences in the number, intensity and locations of the bands from the IR, Raman, UV/Vis and NMR spectra of caffeic acid and its metal complexes the effect of metal cations on the electronic system of ligand was discussed. The geometry, theoretical spectra and electronic charge distribution were calculated by the use of Gaussian 09 programme. The geometric aromaticity indices (Aj – normalized function of the variance in bond lengths; BAC - bond alternation coefficient; HOMA – harmonic oscillator model of aromaticity and I₆ – Bird’s index) were calculated and the changes in the aromaticity of caffeic acid and its complexes was discussed. This work was financially supported by National Science Centre, Poland, under the research project number 2014/13/B/NZ7/02-352.

Keywords: antioxidant properties, caffeic acid, metal complexes, spectroscopic methods

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Authors: Mohammad Jamal

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Non-alcoholic fatty liver disease (NAFLD) has become one of the most chronic liver diseases, prevalent among people with morbid obesity. NAFLD does not develop clinically significant liver disease, however cirrhosis and liver cancer develop in subset and currently there are no approved therapies for the treatment of NAFLD. The study is aimed to understand the various key genes involved in the mechanism of NAFLD which can be valuable for developing diagnostic and predictive biomarkers based on their histologic stage of liver. The study was conducted on 16 male Sprague Dawley rats. The animals were divided in two groups: control group (n=8) fed on ad libitum normal chow and regular water and the cafeteria group (CAF)) (n=8) fed on high fatty/ carbohydrate diet. The animals received their respective diet from 4 weeks onwards from D.O.B until 25 weeks. Liver was extracted and RT² Profiler PCR Array was used to assess the NAFLD related genes. Histological evaluation was performed using H&E stain in liver tissue sections. Our PCR array results showed that genes involved in anti-inflammatory activity (Ifng, IL10), fatty acid uptake/oxidation (Fabp5), apoptosis (Fas), lipogenesis (Gck and Srebf1), Insulin signalling (Igfbp1) and metabolic pathway (pdk4) were upregulated in the liver of cafeteria fed obese rats. Bloated hepatocytes, displaced nucleus and higher lipid content were seen in the liver of cafeteria fed obese rats. Although Liver biopsies remain the gold standard in evaluating NAFLD, however an approach towards non-invasive markers could be used in understanding the physiology, therapeutic potential, and the targets to combat NAFLD.

Keywords: biomarkers, cafeteria diet, obesity, NAFLD

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Authors: Lahcen Daoudi, Soukaina Elidrissi, Nathalie Fagel

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The calcareous accumulations in the surface formations of the soil, are a very widespread phenomenon in the arid and semi-arid regions. Many aspects of physical and chemical evolution of these soils were debated for more than one century. The last two decades have witnessed a remarkable interest in the study of the calcrete. In Morocco, as in most Mediterranean countries, soils with carbonate accumulation cover large areas of the territory. The isohumic subtropical soils and red Mediterranean soils include always a horizon of calcrete accumulation. In the lowland of Tensift Al Haouz located in the central part of Morocco, the arable lands are underlain by indurate pedogenic calcrete of various thicknesses; this constitutes a serious handicap for agricultural development in the region. Our aims in this study is to analyze the characteristics of the crusts developed in this area in order to identify the various facies, their geographic distribution and the factors that played a significant role in the differentiation of these calcareous accumulations. The characterizations were based on various techniques including field observations, X-ray diffraction analysis (XRD) for both raw materials and clay fractions, SEM analysis, Calcimetry and Loss On Ignition (LOI). The analysis of encrusting calcrete in a rich and varied observation field as the region of Tensift Al Haouz enabled us to specify the important types of accumulations: diffuse, nodular and massive encrusting. The shape of encrusting as well as their consistency and hardness is clearly related to the contents of CaCO3 of the profiles. Among these facies, the hardpan which results from a complex succession of processes is certainly the most morphologically advanced form of encrusting. The vertical and lateral distribution of these forms in the Tensift Al Haouz area indicates that they do not appear randomly but seem related to well defined environmental conditions. The differentiation and evolution of encrusting is under the influence of two major factors: 1) the availability of carbonate rich solution which is controlled by the topography, the nature and texture of underlying host rock and the detrital processes; 2) the climate which is responsible for the evaporation and crystallization of carbonate.

Keywords: soil calcrete, characterization, morphology, Tensift Al Haouz, Morocco

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Authors: Ahmad Fakhriy Hassan, Rohani Ahmad, Zurainee Mohamed Nor, Wan Najdah Wan Mohamad Ali

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In Malaysia, it was realized that while the incidence of human malaria is decreasing, the incidence of Plasmodium knowlesi malaria appears to be on the rise, especially in rural areas of Sabah, East Malaysia. The primary vector for P. knowlesi malaria in Sabah is An. balabacensis a species found abundant in rural areas, shown to rest and feed outdoor throughout the night, which makes its control very challenging. This study aims to examine the distribution of malaria-infected Anopheles mosquitoes in three areas in Sabah, namely Kudat, Ranau, and Tenom, known as areas in Sabah that presented high number of malaria cases. Briefly, mosquitoes were caught every 6 weeks for the period of 18 months using Human Landing Catching (HLC) technique from May 2016 to November 2017. Identification of species was done using microscopy and molecular methods. Molecular method is also used to detect malaria parasite in all mosquito collected. An. balabacensis was present in all the study areas. In Kudat, six other Anopheles species were also detected, namely, An. barumbrosus, An. latens, An. letifer, An. maculatus, An. sundaicus and An. tesselatus. In Ranau five other Anopheles species were detected, namely, An. barumbrosus, An. donaldi., An. hodgkini, An. maculatus, and An. tesselatus while in Tenom seven more species An. donaldi, An. umbrosus, An. barumbrosus, An.latens, An. hodgkini, An. maculatus, and An. tesselatus were detected. This study showed 24% out of 259, 39% out of 127, and 26% out of 265 Anopheles mosquito collected in Kudat, Ranau, and Tenom were detected positive for malaria parasite respectively. In Kudat An. balabacensis, An. barumbrosus, An. latens, An. maculatus, An. sundaicus and An. tesselatus were the six out of eight Anopheles species that were found infected with malaria parasite. All Anopheles species collected in Ranau were positive for malaria while In Tenom, only five out of eight species; An. balabacensus, An. donaldi, An. hodgkini, An. maculatus, and An. latens were detected positive for malaria parasite. Interestingly, for all study areas An. balabacensis was shown to be the only species infected with four malaria species; P. falciparum, P. knowlesi, P. vivax, and Plasmodium sp. This finding clearly indicates that An. balabacensis is the dominant malaria vector in Kudat, Ranau, and Tenom.

Keywords: Anopheles balabacensis, human landing catching technique, nested PCR, Plasmodium knowlesi, Simian malaria

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Authors: Edward P. Guillen, A. Karina Martinez Barliza

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Powerline Communications (PLC) as last mile solution to provide communication services, has the advantage of transmitting over channels already used for electrical distribution. However these channels have been not designed with this purpose, for that reason telecommunication companies in Colombia want to know how good would be using PLC in costs and network performance in comparison to cable modem or DSL. This paper analyzes PLC throughput for residential complex scenarios using a PLC network scenarios and some statistical results are shown.

Keywords: home network, power line communication, throughput analysis, power factor, cost, last mile solution

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Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Magnolia G. Martinez-Rivera, Pablo de J. Angeles-Salto, Carlos Herrera-Ventosa

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In order to diminish health risks, it is of major importance to monitor air quality. However, this process is accompanied by the high costs of physical and human resources. In this context, this research is carried out with the main objective of developing a predictive model for concentrations of inhalable particles (PM10-2.5) using remote sensing. To develop the model, satellite images, mainly from Landsat 8, of the Mexico City’s Metropolitan Area were used. Using historical PM10 and PM2.5 measurements of the RAMA (Automatic Environmental Monitoring Network of Mexico City) and through the processing of the available satellite images, a preliminary model was generated in which it was possible to observe critical opportunity areas that will allow the generation of a robust model. Through the preliminary model applied to the scenes of Mexico City, three areas were identified that cause great interest due to the presumed high concentration of PM; the zones are those that present high plant density, bodies of water and soil without constructions or vegetation. To date, work continues on this line to improve the preliminary model that has been proposed. In addition, a brief analysis was made of six models, presented in articles developed in different parts of the world, this in order to visualize the optimal bands for the generation of a suitable model for Mexico City. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air quality, modeling pollution, particulate matter, remote sensing

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Authors: Nasir Mehmood, Muhammad Yar Khan, Anam Javeed

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This study aims to scrutinize the dynamics which tend to impact customer’s purchasing intention of Islamic credit card and nexus of product’s knowledge and religiosity with the attitude of potential Islamic credit card’s customer. The theory of reasoned action strengthened the idea that intentions due to its proven predictive power are most likely to instigate intended consumer behavior. Particularly, the study examines the relationships of perceived financial cost (PFC), subjective norms (SN), and attitude (ATT) with the intention to purchase Islamic credit cards. Using a convenience sampling approach, data have been collected from 450 customers of banks located in Rawalpindi and Islamabad. A five-point Likert scale self-administered questionnaire was used to collect the data. The data were analyzed using the Statistical Package of Social Sciences (SPSS) through the procedures of principal component and multiple regression analysis. The results suggested that customer’s religiosity and product knowledge are strong indicators of attitude towards buying Islamic credit cards. Likewise, subjective norms, attitude, and perceived financial cost have a significant positive impact on customers’ purchase intent of Islamic bank’s credit cards. This study models a useful path for future researchers to further investigate the underlined phenomenon along with a variety of psychodynamic factors which are still in its infancy, at least in the Pakistani banking sector. The study also provides an insight to the practitioners and Islamic bank managers for directing their efforts toward educating customers regarding the use of Islamic credit cards and other financial products.

Keywords: attitude, Islamic credit card, religiosity, subjective norms

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Authors: Abdul Waris Jalili, Yanqing Wang, Som Suor

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This research paper explores the relationship between entrepreneurship education and students' entrepreneurial intentions. It aims to determine if entrepreneurship education reliably predicts students' intention to become entrepreneurs and how and when this relationship occurs. This study aims to investigate the predictive relationship between entrepreneurship education and student entrepreneurial intentions. The goal is to understand the factors that influence this relationship and to identify any mediating or moderating factors. A thorough and systematic search and review of empirical articles published between 2013 and 2023 were conducted. Three databases, Google Scholar, Science Direct, and PubMed, were explored to gather relevant studies. Criteria such as reporting empirical results, publication in English, and addressing the research questions were used to select 35 papers for analysis. The collective findings of the reviewed studies suggest a generally positive relationship between entrepreneurship education and student entrepreneurial intentions. However, recent findings indicate that this relationship may be more complex than previously thought. Mediators and moderators have been identified, highlighting instances where entrepreneurship education indirectly influences student entrepreneurial intentions. The review also emphasizes the need for more robust research designs to establish causality in this field. This research adds to the existing literature by providing a comprehensive review of the relationship between entrepreneurship education and student entrepreneurial intentions. It highlights the complexity of this relationship and the importance of considering mediators and moderators. The study also calls for future research to explore different facets of entrepreneurship education independently and examine complex relationships more comprehensively.

Keywords: entrepreneurship, entrepreneurship education, entrepreneurial intention, entrepreneurial self-efficacy

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Authors: Jiazhen Chen, Yue Sun, Joanne Yip, Kit-Lun Yick

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The design of sports bras poses a considerable challenge due to the difficulty in accurately predicting the wearing result after computer-aided design (CAD). It needs repeated physical try-on or virtual try-on to obtain a comfortable pressure range during motion. Specifically, in the context of running, the exact support area and force exerted on the breasts remain unclear. Consequently, obtaining an effective method to design the sports bra pads shape becomes particularly challenging. This predicament hinders the successful creation and production of sports bras that cater to women's health needs. The purpose of this study is to propose an effective method to obtain the 3D shape of sports bra pads and to understand the relationship between the supporting force and the 3D shape parameters of the pads. Firstly, the static 3D shape of the sports bra pad and human motion data (Running) are obtained by using the 3D scanner and advanced 4D scanning technology. The 3D shape of the sports bra pad is parameterised and simplified by Free-form Deformation (FFD). Then the sub-models of sports bra and human body are constructed by segmenting and meshing them with MSC Apex software. The material coefficient of sports bras is obtained by material testing. The Marc software is then utilised to establish a dynamic contact model between the human breast and the sports bra pad. To realise the reverse design of the sports bra pad, this contact model serves as a forward model for calculating the inverse problem. Based on the forward contact model, the inverse problem of the 3D shape parameters of the sports bra pad with the target bra-wearing pressure range as the boundary condition is solved. Finally, the credibility and accuracy of the simulation are validated by comparing the experimental results with the simulations by the FE model on the pressure distribution. On the one hand, this research allows for a more accurate understanding of the support area and force distribution on the breasts during running. On the other hand, this study can contribute to the customization of sports bra pads for different individuals. It can help to obtain sports bra pads with comfortable dynamic pressure.

Keywords: sports bra design, breast motion, running, inverse problem, finite element dynamic model

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Authors: Kara J. Coffman-Rea, Karen E. Samonds

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Microplastic pollution is an urgent global threat to our planet and human health. Microplastic particles have been detected within our food, water, and atmosphere, and found within the human stool, placenta, and lung tissue. However, most spectrometric microplastic detection methods require chemical digestion which can alter or destroy microplastic particles and makes it impossible to acquire information about their in-situ distribution. MALDI TOF MS (Matrix-assisted laser desorption ionization-time of flight mass spectrometry) is an analytical method using a soft ionization technique that can be used for polymer analysis. This method provides a valuable opportunity to both acquire information regarding the in-situ distribution of microplastics and also minimizes the destructive element of chemical digestion. In addition, MALDI TOF MS allows for expanded analysis of the microplastics including detection of specific additives that may be present within them. MALDI TOF MS is particularly sensitive to sample preparation and has not yet been used to analyze environmental microplastics within their specific location (e.g., biological tissues, sediment, water). In this study, microplastics were created using polyethylene gloves, polystyrene micro-foam, and polyethylene terephthalate cable sleeving. Plastics were frozen using liquid nitrogen and ground to obtain small fragments. An artificial tissue was created using a cellulose sponge as scaffolding coated with a MaxGel Extracellular Matrix to simulate human lung tissue. Optimal preparation techniques (e.g., matrix, cationization reagent, solvent, mixing ratio, laser intensity) were first established for each specific polymer type. The artificial tissue sample was subsequently spiked with microplastics, and specific polymers were detected using MALDI-TOF-MS. This study presents a novel method for the detection of environmental polyethylene, polyethylene terephthalate, and polystyrene microplastics within a complex sample. Results of this study provide an effective method that can be used in future microplastics research and can aid in determining the potential threats to environmental and human health that they pose.

Keywords: environmental plastic pollution, MALDI-TOF MS, microplastics, polymer identification

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Ran Etgar

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The process of rounding off measurements in continuous variables is commonly encountered. Although it usually has minor effects, sometimes it can lead to poor outcomes in statistical process control using X ̅-chart. The traditional control limits can cause incorrect conclusions if applied carelessly. This study looks into the limitations of classical control limits, particularly the impact of asymmetry. An approach to determining the distribution function of the measured parameter (Y ̅) is presented, resulting in a more precise method to establish the upper and lower control limits. The proposed method, while slightly more complex than Shewhart's original idea, is still user-friendly and accurate and only requires the use of two straightforward tables.

Keywords: quality control, process control, round-off, measurement, rounding error

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Authors: Mesbah Tarek, Kelaiaia Samia, Chiheb Sofien, Kelaiaia Mounia Samira, Labar Hocine

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As every power systems short circuit failure can occur for HVDC at the DC link. So, the power devices should be protected against over heath produced by this over-current. This can be achieved through the power switchers or fast breaker. After short circuit the system is unable to restart, only after a time delay, because of the potential distribution along the DC link line. An appropriate fast and safety control is proposed and tested successfully. The detailed development and discussion of these faults is presented in this paper.

Keywords: HVDC, DC link, switchers, short circuit, faults

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Authors: Suwapitch Chalongkulasak, Teerasak E-Kobon, Pramote Chumnanpuen

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Acne vulgaris is a common skin disease mainly caused by the Gram–positive pathogenic bacterium, Propionibacterium acnes. This bacterium stimulates inflammation process in human sebaceous glands. Giant African snail (Achatina fulica) is alien species that rapidly reproduces and seriously damages agricultural products in Thailand. There were several research reports on the medical and pharmaceutical benefits of this snail mucus peptides and proteins. This study aimed to in silico predict multifunctional bioactive peptides from A. fulica mucus peptidome using several bioinformatic tools for determination of antimicrobial (iAMPpred), anti–biofilm (dPABBs), cytotoxic (Toxinpred), cell membrane penetrating (CPPpred) and anti–quorum sensing (QSPpred) peptides. Three candidate peptides with the highest predictive score were selected and re-designed/modified to improve the required activities. Structural and physicochemical properties of six anti–P. acnes (APA) peptide candidates were performed by PEP–FOLD3 program and the five aforementioned tools. All candidates had random coiled structure and were named as APA1–ori, APA2–ori, APA3–ori, APA1–mod, APA2–mod and APA3–mod. To validate the APA activity, these peptide candidates were synthesized and tested against six isolates of P. acnes. The modified APA peptides showed high APA activity on some isolates. Therefore, our biomimetic mucus peptides could be useful for preventing acne vulgaris and further examined on other activities important to medical and pharmaceutical applications.

Keywords: Propionibacterium acnes, Achatina fulica, peptidomes, antibacterial peptides, snail mucus

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Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

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This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

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Authors: O. D. Ohijeagbon, Oluseyi O. Ajayi, M. Ogbonnaya, Ahmeh Attabo

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This study analyzed the electricity generation potential from wind at seven sites spread across seven states of the North-Central region of Nigeria. Twenty-one years (1987 to 2007) wind speed data at a height of 10m were assessed from the Nigeria Meteorological Department, Oshodi. The data were subjected to different statistical tests and also compared with the two-parameter Weibull probability density function. The outcome shows that the monthly average wind speeds ranged between 2.2 m/s in November for Bida and 10.1 m/s in December for Jos. The yearly average ranged between 2.1m/s in 1987 for Bida and 11.8 m/s in 2002 for Jos. Also, the power density for each site was determined to range between 29.66 W/m2 for Bida and 864.96 W/m2 for Jos, Two parameters (k and c) of the Weibull distribution were found to range between 2.3 in Lokoja and 6.5 in Jos for k, while c ranged between 2.9 in Bida and 9.9m/s in Jos. These outcomes points to the fact that wind speeds at Jos, Minna, Ilorin, Makurdi and Abuja are compatible with the cut-in speeds of modern wind turbines and hence, may be economically feasible for wind-to-electricity at and above the height of 10 m. The study further assessed the potential and economic viability of standalone wind generation systems for off-grid rural communities located in each of the studied sites. A specific electric load profile was developed to suite hypothetic communities, each consisting of 200 homes, a school and a community health center. Assessment of the design that will optimally meet the daily load demand with a loss of load probability (LOLP) of 0.01 was performed, considering 2 stand-alone applications of wind and diesel. The diesel standalone system (DSS) was taken as the basis of comparison since the experimental locations have no connection to a distribution network. The HOMER® software optimizing tool was utilized to determine the optimal combination of system components that will yield the lowest life cycle cost. Sequel to the analysis for rural community utilization, a Distributed Generation (DG) analysis that considered the possibility of generating wind power in the MW range in order to take advantage of Nigeria’s tariff regime for embedded generation was carried out for each site. The DG design incorporated each community of 200 homes, freely catered for and offset from the excess electrical energy generated above the minimum requirement for sales to a nearby distribution grid. Wind DG systems were found suitable and viable in producing environmentally friendly energy in terms of life cycle cost and levelised value of producing energy at Jos ($0.14/kWh), Minna ($0.12/kWh), Ilorin ($0.09/kWh), Makurdi ($0.09/kWh), and Abuja ($0.04/kWh) at a particluar turbine hub height. These outputs reveal the value retrievable from the project after breakeven point as a function of energy consumed Based on the results, the study demonstrated that including renewable energy in the rural development plan will enhance fast upgrade of the rural communities.

Keywords: wind speed, wind power, distributed generation, cost per kilowatt-hour, clean energy, North-Central Nigeria

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Authors: Beciri Mohamed Walid

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Some architectural conditions required some shapes often lead to an irregular distribution of masses, rigidities and resistances. The main object of the present study consists in estimating the influence of the irregularity both in plan and in elevation which presenting some structures on the dynamic characteristics and his influence on the behavior of this structures. To do this, it is necessary to make apply both dynamic methods proposed by the RPA99 (spectral modal method and method of analysis by accelerogram) on certain similar prototypes and to analyze the parameters measuring the answer of these structures and to proceed to a comparison of the results.

Keywords: structure, irregular, code, seismic, method, force, period

Procedia PDF Downloads 302

Authors: Md. Najiur Rahman

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This hypothesis reveals a profound and symmetrical connection that goes beyond the boundaries of quantum physics and cosmology, revolutionizing our understanding of the fundamental building blocks of the cosmos, given its name ‘The Theory of the Mystery’. This theory has an elegantly simple equation, “R = ∆r / √∆m” which establishes a beautiful and well-crafted relationship between the radius (R) of an elementary particle or galaxy, the relative change in radius (∆r), and the mass difference (∆m) between related entities. It is fascinating to note that this formula presents a super synchronization, one which involves the convergence of every basic particle and any single celestial entity into perfect alignment with its respective mass and radius. In addition, we have a Supporting equation that defines the mass-radius connection of an entity by the equation: R=√m/N, where N is an empirically established constant, determined to be approximately 42.86 kg/m, representing the proportionality between mass and radius. It provides precise predictions, collects empirical evidence, and explores the far-reaching consequences of theories such as General Relativity. This elegant symmetry reveals a fundamental principle that underpins the cosmos: each component, whether small or large, follows a precise mass-radius relationship to exert gravity by a universal law. This hypothesis represents a transformative process towards a unified theory of physics, and the pursuit of experimental verification will show that each particle and galaxy is bound by gravity and plays a unique but harmonious role in shaping the universe. It promises to reveal the great symphony of the mighty cosmos. The predictive power of our hypothesis invites the exploration of entities at the farthest reaches of the cosmos, providing a bridge between the known and the unknown.

Keywords: unified theory, quantum gravity, mass-radius relationship, dark matter, uniform gravity

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Authors: Ran Etgar

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The process of rounding off measurements in continuous variables is commonly encountered. Although it usually has minor effects, sometimes it can lead to poor outcomes in statistical process control using X̄ chart. The traditional control limits can cause incorrect conclusions if applied carelessly. This study looks into the limitations of classical control limits, particularly the impact of asymmetry. An approach to determining the distribution function of the measured parameter ȳ is presented, resulting in a more precise method to establish the upper and lower control limits. The proposed method, while slightly more complex than Shewhart's original idea, is still user-friendly and accurate and only requires the use of two straightforward tables.

Keywords: SPC, round-off data, control limit, rounding error

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

Procedia PDF Downloads 125

Authors: Yuanxiaoyue Yang

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Emissions trading, or ‘cap-and-trade', has been long promoted by economists as a more cost-effective pollution control approach than traditional performance standard approaches. While there is a large body of empirical evidence for the overall effectiveness of emissions trading, relatively little attention has been paid to other unintended consequences brought by emissions trading. One important consequence is that cap-and-trade could introduce the risk of creating high-level emission concentrations in areas where emitting facilities purchase a large number of emission allowances, which may cause an unequal distribution of environmental benefits. This study will contribute to the current environmental policy literature by linking trading activity with environmental injustice concerns and empirically analyzing the causal relationship between trading activity and emissions reduction under a cap-and-trade program for the first time. To investigate the potential environmental injustice concern in cap-and-trade, this paper uses a differences-in-differences (DID) with instrumental variable method to identify the causal effect of allowance trading behaviors on emission reduction levels under the clean air interstate rule (CAIR), a cap-and-trade program targeting on the power sector in the eastern US. The major data source is the facility-year level emissions and allowance transaction data collected from US EPA air market databases. While polluting facilities from CAIR are the treatment group under our DID identification, we use non-CAIR facilities from the Acid Rain Program - another NOx control program without a trading scheme – as the control group. To isolate the causal effects of trading behaviors on emissions reduction, we also use eligibility for CAIR participation as the instrumental variable. The DID results indicate that the CAIR program was able to reduce NOx emissions from affected facilities by about 10% more than facilities who did not participate in the CAIR program. Therefore, CAIR achieves excellent overall performance in emissions reduction. The IV regression results also indicate that compared with non-CAIR facilities, purchasing emission permits still decreases a CAIR participating facility’s emissions level significantly. This result implies that even buyers under the cap-and-trade program have achieved a great amount of emissions reduction. Therefore, we conclude little evidence of environmental injustice from the CAIR program.

Keywords: air pollution, cap-and-trade, emissions trading, environmental justice

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Authors: Juan M. Rodriguez-Diaz

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The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

Procedia PDF Downloads 428