Search results for: structural equation modeling

Authors: Shohreh Moshiri, Hossein Alimohammadi

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Building construction has a great impact on climate change. Adaptive design strategies were developed to provide new life and purpose to old buildings and create new environments with economic benefits to meet resident needs. The role of smart material systems is undeniable in providing adaptivity of the architectural environments and their effects on creating better adaptive building environments. In this research, a case study named Neuhoff site located near Cumberland River in the Germantown neighborhood in the city of Nashville, Tennessee, was considered. This building in the early 1920s was constructed as a meat-packing facility and then served as a mixed-use space; however, New City has partnered with world-class architects to reinvent this site to be changed to mixed-use waterfront development. The future office space will be designed with LEED certification as a goal. Environmentally friendly sensitive materials and designs will offer for all adaptive reuse of the building. The smart materials and their applications, especially in the field of building technology and architecture, were emphasized in providing a renovation plan for the site. The advantages and qualities of smart material systems were targeted to explore in this research on the field of architecture. Also, this research helps to understand better the effects of smart material systems on the construction and design processes, exploration of the way to make architecture with better adaptive characteristics, plus provide optimal environmental situations for the users, which reflect on the climatic, structural, and architectural performances.

Keywords: adaptive architecture, building technology, case study, smart material systems

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Authors: Kamran Dastafkan, Chuan Zhao

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Improving surface chemistry is a promising approach in addition to the rational alteration in the catalyst composition to advance water electrolysis. Here, we demonstrate an evident enhancement of oxygen evolution on an iron-nickel vanadate catalyst synthesized by a facile successive ionic adsorption and reaction method. The vanadate-modified catalyst demonstrates a highly efficient oxygen evolution in 1 M KOH by requiring low overpotentials of 274 and 310 mV for delivering large current densities of 100 and 400 mA cm⁻², respectively where vigorous gas bubble evolution occurs. Vanadate modification augments the OER activity from three aspects. (i) Both the electrochemical surface area (47.1 cm²) and intrinsic activity (318 mV to deliver 10 mA cm⁻² per unit ECSA) of the catalytic sites are improved. (ii) The amorphous and roughened nanoparticle-comprised catalyst film exhibits a high surface wettability and a low-gas bubble-adhesion, which is beneficial for the accelerated mass transport and gas bubble dissipation at large current densities. The gas bubble dissipation behavior is studied by operando dynamic specific resistance measurements where a significant change in the variation of the interfacial resistance during the OER is detected for the vanadate-modified catalyst. (iii) The introduced vanadate poly-oxo-anions with high charge density have electronic interplay with Fe and Ni catalytic centers. Raman study reveals the structural evolution of β-NiOOH and γ-FeOOH phases during the OER through the vanadate-active site synergistic interactions. Achievement of a high catalytic turnover of 0.12 s⁻¹ put the developed FeNi vanadate among the best recent catalysts for water oxidation.

Keywords: gas bubble dissipation, iron-nickel vanadate, low-gas bubble-adhesion catalyst, oxygen evolution reaction

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Authors: B. Vinod, L. J. Sudev

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Natural fibers as reinforcement in polymer matrix material are gaining lot of attention in recent years. Natural fibers like jute, sisal, coir, hemp, banana etc. have attracted substantial importance as a potential structural material because of its attractive features along with its good mechanical properties. Cryogenic applications of natural fiber reinforced polymer composites are gaining importance. These materials need to possess good mechanical and physical properties at cryogenic temperatures to meet the high requirements by the cryogenic engineering applications. The objective of this work is to investigate the mechanical behavior of hybrid hemp/jute fibers reinforced epoxy composite material at liquid nitrogen temperature. Hybrid hemp/jute fibers reinforced polymer composite is prepared by hand lay-up method and test specimens are cut according to ASTM standards. These test specimens are dipped in liquid nitrogen for different time durations. The tensile properties, flexural properties and impact strength of the specimen are tested immediately after the specimens are removed from liquid nitrogen container. The experimental results indicate that the cryogenic treatment of the polymer composite has a significant effect on the mechanical properties of this material. The tensile properties and flexural properties of the hybrid hemp/jute fibers epoxy composite at liquid nitrogen temperature is higher than at room temperature. The impact strength of the material decreased after subjecting it to liquid nitrogen temperature.

Keywords: liquid nitrogen temperature, polymer composite, tensile properties, flexural properties

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Authors: Muhammad Umar Kiani, Muhammad Shahbaz

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Performance of any vehicle can be predicted by its design/modeling and optimization. Design optimization leads to efficient performance. Followed by horizontal launch, the air launch re-entry vehicle undergoes a launch maneuver by introducing a carefully selected angle of attack profile. This angle of attack profile is the basic element to complete a specified mission. Flight program of said vehicle is optimized under the constraints of the maximum allowed angle of attack, lateral and axial loads and with the objective of reaching maximum altitude. The main focus of this study is the endo-atmospheric phase of the ascent trajectory. A three degrees of freedom trajectory model is simulated in MATLAB. The optimization process uses evolutionary algorithm, because of its robustness and efficient capacity to explore the design space in search of the global optimum. Evolutionary Algorithm based trajectory optimization also offers the added benefit of being a generalized method that may work with continuous, discontinuous, linear, and non-linear performance matrix. It also eliminates the requirement of a starting solution. Optimization is particularly beneficial to achieve maximum advantage without increasing the computational cost and affecting the output of the system. For the case of launch vehicles we are immensely anxious to achieve maximum performance and efficiency under different constraints. In a launch vehicle, flight program means the prescribed variation of vehicle pitching angle during the flight which has substantial influence reachable altitude and accuracy of orbit insertion and aerodynamic loading. Results reveal that the angle of attack profile significantly affects the performance of the vehicle.

Keywords: endo-atmospheric, evolutionary algorithm, efficient performance, optimization process

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Authors: Cristina Busuioc, Georgeta Voicu, Sorin-Ion Jinga

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The human bone presents in its dry form piezoelectric properties, which means that a mechanical stress results in electric polarization and an applied electric field causes strain. The immediate consequence was the revealing of piezoelectricity role in bone remodelling, as well as the integration of ceramic materials with piezoelectric behaviour in the composition of unitary or composite biomaterials. Thus, we prepared hydroxyapatite - collagen hybrid materials with barium titanate addition in order to achieve a better osseointegration. Barium titanate powder synthesized by a combined sol-gel-hydrothermal method, commercial hydroxyapatite and laboratory extracted collagen gel were employed as starting materials. Before the composites, fabrication, the powder with piezoelectric features was characterized in detail from the compositional, structural, morphological and electrical point of view. The next step was to elucidate the influence of barium titanate presence especially on the biological properties of the final materials. The biocompatibility of the hybrid supports without or with piezoelectric addition was investigated on mouse osteoblast cells through LDH cytotoxicity assay, LIVE/DEAD cell viability assay, and MTT cell proliferation assay. All results indicated that the analysed materials do not exert cytotoxic effects and present the ability to sustain cell survival and to promote their proliferation. In conclusion, barium titanate nanoparticles exhibit a good biocompatibility and osteoinductive properties, while the derived composite materials based on hydroxyapatite as oxide phase and collagen as polymeric phase can be successfully used for tissue engineering applications.

Keywords: barium titanate, hybrid composites, piezoelectricity, tissue engineering

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Authors: Ellen Lagast, Melissa Ceuterick, Mark Leys

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Although adolescence is a stressful period with an increased risk for mental illnesses such as anxiety and depression, little in-depth knowledge is available on the determinants of the use of psychotropic drugs (BZD/SSRIs) and the effects. A qualitative research with adolescents in Flanders was performed. Based on indepth interviews, the interviewees indicate feelings of ambiguity towards their medication use because on the one hand the medication helps to manage their mental vulnerability and disrupted lives, but on the other hand they experience a loss of control of their self and their environment. Undesired side-effects and stigma led to a negative pharmaceutical self. The interviewed youngsters also express dissatisfaction about the prescription behavior with regard to psychotropic drugs of their general practitioner (GP). They wished to have received more information about alternative non-pharmaceutical treatment options. Notwithstanding these comments, the majority of the interviewees maintained trust in their GP to act in their best interest. This paper will relate the prescription behavior in primary care to the organization of mental health care to better understand the “phamaceuticalization” and medicalization of mental health problems in Belgium. Belgium implemented fundamental mental health care reforms to collaborate, to integrate care and to optimize continuity of care. Children and adolescents still are confronted with long waiting lists to access (non-medicalized) mental health services. This access to mental health care partly explains general practitioners’ prescription behavior of psychotropics. Moreover, multidisciplinary practices have not pervaded primary health care yet. Medicalization and pharmaceuticalization of mental health vulnerabilities of youth are both a structural and cultural problem.

Keywords: adolescents, antidepressants, benzodiazepines, mental health system, psychotropic drugs

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Authors: Ahmed Mohammed Ghaleb, Ehab Saleh Alnuzaili

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This paper attempts to generally examine Tawfiq Al-Hakim's Song of Death (1950) and John Millington Synge's Riders to the Sea (1904) by comparatively bringing the two plays under focus. Strikingly, the similarities between the two plays appear in the plot, picturization of the characters, tragic intensity, structural perfection, and the economy of language. Plot structure, albeit a simple one in both plays, is enriched by the playwrights' effective use of language, symbols, imagery, and tragic irony. Neither of the two plays has the traditional five-act structure; they are one-act plays. From a feminist point of view, the domination of female characters is observed in both plays. The female protagonists are the main focus of the two plays. Their brave characters and struggle are highly depicted. While Al-Hakim's protagonist is presented as a victim of tribal customs, Synge's protagonist is shown as a victim of nature. Both plays can be described as 'feminine tragedies' using the words of Oona Frwaley. Although the two plays appeared in totally different historical periods of time, both share considerable similarities, thematic as well as linguistic, which result in a concern to investigate them. The paper, basically, aims at asserting the commonalities between human beings and creating awareness of intercultural negotiations and connections. It attempts to bridge the cultural, intellectual, and social gap between Arab and Irish drama by exploring the common elements of the two plays. Thus, the paper presents a critical and comparative study of both plays highlighting the portrayal of the female protagonists.

Keywords: economy of language, imagery, protagonist, symbols, tragic intensity, tragic irony

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Authors: Vineeta Kaushik, Manisha Goel

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Chaperones are proteins that help other proteins fold correctly, and are found in all domains of life i.e., prokaryotes, eukaryotes and archaea. Various comparative genomic studies have suggested that the archaeal protein folding machinery appears to be highly similar to that found in eukaryotes. In case of protein folding; slow rotation of peptide prolyl-imide bond is often the rate limiting step. Formation of the prolyl-imide bond during the folding of a protein requires the assistance of other proteins, termed as peptide prolyl cis-trans isomerases (PPIases). Cyclophilins constitute the class of peptide prolyl isomerases with a wide range of biological function like protein folding, signaling and chaperoning. Most of the cyclophilins exhibit PPIase enzymatic activity and play active role in substrate protein folding which classifies them as a category of molecular chaperones. Till date, there is not very much data available in the literature on archaeal cyclophilins. We aim to compare the structural and biochemical features of the cyclophilin protein from within the three domains to elucidate the features affecting their stability and enzyme activity. In the present study, we carry out in-silico analysis of the cyclophilin proteins to predict their conserved residues, sites under positive selection and compare these proteins to their bacterial and eukaryotic counterparts to predict functional divergence. We also aim to clone and express these proteins in heterologous system and study their biophysical characteristics in detail using techniques like CD and fluorescence spectroscopy. Overall we aim to understand the features contributing to the folding, stability and dynamics of the archaeal cyclophilin proteins.

Keywords: biophysical characterization, x-ray crystallography, chaperone-like activity, cyclophilin, PPIase activity

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Authors: Tamrat Tesfaye, Bruce Sithole, Deresh Ramjugernath

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Worldwide, the poultry–processing industry generates large quantities of feather by-products that amount to 40 billion kilograms annually. The feathers are considered wastes although small amounts are often processed into valuable products such as feather meal and fertilizers. The remaining waste is disposed of by incineration or by burial in controlled landfills. Improper disposal of these biological wastes contributes to environmental damage and transmission of diseases. Economic pressures, environmental pressures, increasing interest in using renewable and sustainable raw materials, and the need to decrease reliance on non-renewable petroleum resources behove the industry to find better ways of dealing with waste feathers. A closer look at the structure and composition of feathers shows that the whole part of a chicken feather (rachis and barb) can be used as a source of a pure structural protein called keratin which can be exploited for conversion into a number of high-value bio products. Additionally, a number of technologies can be used to convert other biological components of feathers into high value added products. Thus, conversion of the waste into valuable products can make feathers an attractive raw material for the production of bio products. In this review, possible applications of chicken feathers in a variety of technologies and products are discussed. Thus, using waste feathers as a valuable resource can help the poultry industry to dispose of the waste feathers in an environmentally sustainable manner that also generates extra income for the industry. Their valorisation can result in their sustainable conversion into high-value materials and products on the proviso of existence or development of cost-effective technologies for converting this waste into the useful products.

Keywords: biodegradable product, keratin, poultry waste, feathers, valorisation

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Authors: Alli Smith Yemisi Rufina, Adanlawo Isaac Gbadura

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Liver disorders are one of the major problems of the world. Despite its frequent occurrence, high morbidity, and high mortality, its medical management is currently inadequate. This study was designed to evaluate the Hepatoprotective effect of saponin extract of the root of Garcinia kola on the integrity of the liver of paracetamol induced Wistar albino rats. Twenty-five male adult Wistar albino rats were divided into five (5) groups. Group I, was the Control group that received distilled water only, group II was the negative control that received 2 g/kg of paracetamol on the 13th day, and group III, IV, and V were pre-treated with 100, 200 and 400 mg/kg of the saponin extract before inducing the liver damage on the 13th day with 2 g/kg of paracetamol. Twenty-four hours after administration, the rats were sacrificed, and blood samples were collected. The serum Alanine Transaminase (ALT), Aspartate Transaminase (AST), Alkaline Phosphatase (ALP) activities, Bilirubin and Conjugated Bilirubin, Glucose and Protein concentrations were evaluated. The liver was fixed immediately in Formalin and was processed and stained with Haematoxylin and Eosin (H&E). Administration of saponin extract from the root of Garcinia kola significantly decreased paracetamol induced elevated enzymes in the test group. Also, histological observations showed that saponin extract of the root of Garcinia kola exhibited a significant liver protection against the toxicant as evident by the cells trying to return to normal. Saponin extract from the root of Garcinia kola indicated a protection of the structural integrity of the hepatocytic cell membrane and regeneration of the damaged liver.

Keywords: hepatoprotective, liver damage, Garcinia kola, saponin, paracetamol

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Authors: Abubakar Mukhtar Yakasai, Muhammad Tahir Jan

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Purpose: This paper is aimed at exploring factors influencing online shopping intention among the young consumers in Nigeria. Design/Methodology/approach: The paper adopted and extended Technology Acceptance Model (TAM) as the basis for literature review. Additionally, the paper proposed a framework with the inclusion of culture as a moderating factor of consumer online shopping intention among consumers in Nigeria. Findings: Despite high rate of internet penetration in Nigerian, as well as the rapid advancement of online shopping in the world, little attention was paid to this important revolution specifically among Nigeria’s consumers. Based on the review of extant literature, the TAM extended to include perceived risk and enjoyment (PR and PE) was discovered to be a better alternative framework for predicting Nigeria’s young consumers’ online shopping intention. The moderating effect of culture in the proposed model is shown to help immensely in ascertaining differences, if any, between various cultural groups among online shoppers in Nigeria. Originality/ value: The critical analysis of different factors will assist practitioners (like online retailers, e-marketing managers, website developers, etc.) by signifying which combinations of factors can best predict consumer online shopping behaviour in particular instances, thereby resulting in effective value delivery. Online shopping is a newly adopted technology in Nigeria, hence the paper will give a clear focus for effective e-marketing strategy. In addition, the proposed framework in this paper will guide future researchers by providing a tool for systematic evaluation and testing of real empirical situation of online shopping in Nigeria.

Keywords: online shopping, perceived ease of use, perceived usefulness, perceived enjoyment, technology acceptance model, Nigeria

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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Authors: Keivan Jamshidi

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Distal swelling and eventual degeneration of axon in the CNS and PNS have been considered to be the characteristic neuropathological effects of acrylamide (ACR) neuropathy. This study was conducted to determine the neurotoxic effects of different doses of ACR (0.5, 5, 50, 100, and 500 mg/kg per day × 11days i. p.) on hypothalamus of rat using the de Olmos amino cupric-silver stain and electron microscopy. For this purpose 60 adult male rats (Wistar, approximately 250 g) were randomly assigned in 5 treatment groups as A, B, C, D, E) exposed to 0.5, 5, 50, 100, and 500 mg/kg per dayx11days i. p. and one control group as F received daily i. p. injections of 0.9% saline (3ml/kg). As indices of developing neurotoxicity, weight gain, gait scores and landing hindlimb foot splay were determined. After 11 days, two rats for silver stain, and two rats for EM were randomly selected; dissected and proper samples were collected from hypothalamus. Results did show no neurological behavior in groups A, B and F were observed in group C. Rats in groups D and E died within 1-2 hours due to sever toxemia. In histopathological studies based on de Olmos technique no argyrophilic neurons or processes were observed in stained sections obtained from hypothalamus of rats belong to groups A, B, and F while moderate to severe argyrophilic changes were observed in different nuclei and regions of stained sections obtained from hypothalamus of rats belong to group C. In ultra-structural studies some variations in the myelin sheet of injured axons including decompactation, interlaminar space formation, disruption of the laminar sheet, accumulation of neurofilaments, vacculation, and clumping inside the axolem, and finally complete disappearance of laminar sheet were observed.

Keywords: acrylamide, hypothalamus, rat, de Olmos amino cupric, silver stain, electron microscopy

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Authors: Thohaku Abdul Hadi, Hadyan Perdana Putra, Nugroho Wicaksono, Adhika Prajna Nandiwardhana, Onang Surya Nugroho, Heri Suryoatmojo, Soedibjo

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Access to electricity is now a basic requirement of mankind. Unfortunately, there are still many places around the world which have no access to electricity, such as small islands, where there could potentially be a factory, a plantation, a residential area, or resorts. Many of these places might have substantial potential for energy generation such us Photovoltaic (PV) and Wind turbine (WT), which can be used to generate electricity independently for themselves. Solar energy and wind power are renewable energy sources which are mostly found in nature and also kinds of alternative energy that are still developing in a rapid speed to help and meet the demand of electricity. PV and Wind has a characteristic of power depend on solar irradiation and wind speed based on geographical these areas. This paper presented a control methodology of hybrid small scale PV/Wind energy system that use a fuzzy logic controller (FLC) to extract the maximum power point tracking (MPPT) in different solar irradiation and wind speed. This paper discusses simulation and analysis of the generation process of hybrid resources in MPP and power conditioning unit (PCU) of Photovoltaic (PV) and Wind Turbine (WT) that is connected to the three-phase low voltage electricity grid system (380V) without battery storage. The capacity of the sources used is 2.2 kWp PV and 2.5 kW PMSG (Permanent Magnet Synchronous Generator) -WT power rating. The Modeling of hybrid PV/Wind, as well as integrated power electronics components in grid connected system, are simulated using MATLAB/Simulink.

Keywords: fuzzy MPPT, grid connected inverter, photovoltaic (PV), PMSG wind turbine

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Tarnveer Kaur

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Amino acids, as fundamental structural units of peptides and proteins, have an important role in biological systems by affecting solubility, denaturation, and activity of biomolecules. A study of these effects on thermophysical properties of model compounds in the presence of electrolytes solutions provides information about solute-solvent and solute-solute interactions on biomolecules. Ionic liquids (ILs) as organic electrolytes and green solvents are composed of an organic cation and an inorganic anion, which are liquid at ambient conditions. In the past decade, extensive investigations showed that the use of ILs as reaction media for processes involving biologically relevant compounds is promising in view of their successful application in kinetic resolution, biocatalysis, biosynthesis, separation, and purification processes. The scope of this information is valuable to explore the interactions of amino acids in ILs. To reach this purpose, apparent molar volumes of glycine/L-alanine in aqueous solutions of 1-butyl-3-methylimidazolium bromide/chloride were determined from precise density measurements at temperatures T = (288.15-318.15) K and at atmospheric pressure. Positive values for all the studied amino acids indicate the dominance of hydrophilic-ionic interactions between amino acids and Ionic liquids. The effect of temperature on volumetric properties of glycine/L-alanine in solutions has been determined from the partial molar expansibility and second-order partial molar expansibility. Further, volumetric interaction parameters and hydration number have been calculated, which have been interpreted in terms of possible solute-solvent interactions.

Keywords: ILs, amino acids, volumetric properties, hydration numbers

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Daofan Guo, Dong Yang

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For decades, well logging with coiled tubing has relied solely on surface data such as pump pressure, wellhead pressure, depth counter, and weight indicator readings. While this data serves the oil industry well, modern smart logging utilizes real-time downhole information, which automatically increases operational efficiency and optimizes intervention qualities. For example, downhole pressure, temperature, and depth measurement data can be transmitted through the electro-optical hybrid cable in the coiled tubing to surface operators on a real-time base. This paper mainly introduces the unique structural features and various applications of the electro-optical hybrid cables which were deployed into downhole with the help of coiled tubing technology. Fiber optic elements in the cable enable optical communications and distributed measurements, such as distributed temperature and acoustic sensing. The electrical elements provide continuous surface power for downhole tools, eliminating the limitations of traditional batteries, such as temperature, operating time, and safety concerns. The electrical elements also enable cable telemetry operation of cable tools. Both power supply and signal transmission were integrated into an electro-optical hybrid cable, and the downhole information can be captured by downhole electrical sensors and distributed optical sensing technologies, then travels up through an optical fiber to the surface, which greatly improves the accuracy of measurement data transmission.

Keywords: electro-optical hybrid cable, underground photoelectric composite cable, seismic cable, coiled tubing, real-time monitoring

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Authors: Hamid Kazemi, Abbasali Sadeghi

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Assessment of seismic behavior of frame structures is just done for evaluating life and financial damages or lost. The new structural seismic behavior assessment methods have been proposed, so it is necessary to define a formulation as a damage index, which the damage amount has been quantified and qualified. In this paper, four new steel moment-resisting frames with intermediate ductility and different height (2, 5, 8, and 12-story) with regular geometry and simple rectangular plan were supposed and designed. The three existing groups’ damage indices were studied, each group consisting of local index (Drift, Maximum Roof Displacement, Banon Failure, Kinematic, Banon Normalized Cumulative Rotation, Cumulative Plastic Rotation and Ductility), global index (Roufaiel and Meyer, Papadopoulos, Sozen, Rosenblueth, Ductility and Base Shear), and story (Banon Failure and Inter-story Rotation). The necessary parameters for these damage indices have been calculated under the effect of far-fault ground motion records by Non-linear Dynamic Time History Analysis. Finally, prioritization of damage indices is defined based on more conservative values in terms of more damageability rate. The results show that the selected damage index has an important effect on estimation of the damage state. Also, failure, drift, and Rosenblueth damage indices are more conservative indices respectively for local, story and global damage indices.

Keywords: damage index, far-fault ground motion records, non-linear time history analysis, SeismoStruct software, steel moment-resisting frame

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Authors: Muhammet Baldan, Emel Timuçin

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Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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Authors: Emmanuel O Ajani, Sabiu S, Mariam Zakari, Fisayo A Bamisaye

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Hydrocotyl bonariensis is a plant which anticataractogenic potentials have been reported. In the present study an attempt was made to evaluate the in vitro antioxidant activity of the fractionates of the leaves extract and also characterize some of its chemical constituents. DPPH, H₂O₂, OH and NO free radical scavenging, metal chelating and reducing power activity was used to evaluate the antioxidant activity of the crude extract fractionates. Fresh leaves of Hydrocotyl bonariensis leaves were extracted in 70% methanol. The extract was partitioned with different solvent system of increasing polarity (n-hexane, chloroform, ethyl acetate methanol and water). Compounds were isolated from the aqueous practitionate using accelerated gradient chromatography, vacuum liquid chromatography, preparative TLC and conventional column chromatography. The presence of the chemical groups was established with HPLC and Fourier Transform Infra Red. The structures of isolated compounds were elucidated by spectroscopic study and chemical shifts. Data from the study indicates that all the fractionates contain compounds with free radical scavenging activity. This activity was more pronounced in the aqueous fractionate (DPPH IC₅₀, 0025 ± 0.011 mg/ml, metal chelating capacity 27.5%, OH- scavenging IC₅₀, 0.846 ± 0.037 mg/ml, H₂O₂ scavenging IC₅₀ 0.521 ± 0.015 mg/ml, reducing power IC₅₀ 0.248 ± 0.025 mg/ml and NO scavenging IC₅₀ 0.537 ± 0.038 mg/ml). Two compounds were isolated and when compared with data from the literature; the structures were suggestive of polyphenolic flavonoid, quercetin and 3-O-β-D-glucopyranosyl-sitosterol. The result indicates that H. bonariensis leaves contain bioactive compounds with antioxidant activity.

Keywords: antioxidant, cataract, free radical, flavonoids, hydrocotyl bonariensis

Procedia PDF Downloads 249

Authors: Iacopo Carnacina, Mohammad Keshtpoor, Richard Yablonsky

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Non-structural protection measures against flooding are becoming increasingly popular flood risk mitigation strategies. In particular, coastal flood insurance impacts not only private citizens but also insurance and reinsurance companies, who may require it to retain solvency and better understand the risks they face from a catastrophic coastal flood event. In this context, a framework is presented here to assess the risk for coastal flooding across the UK. The area has a long history of catastrophic flood events, including the Great Flood of 1953 and the 2013 Cyclone Xaver storm, both of which led to significant loss of life and property. The current framework will leverage a technology based on a hydrodynamic model (Delft3D Flexible Mesh). This flexible mesh technology, coupled with a calibration technique, allows for better utilisation of computational resources, leading to higher resolution and more detailed results. The generation of a stochastic set of extra tropical cyclone (ETC) events supports the evaluation of the financial losses for the whole area, also accounting for correlations between different locations in different scenarios. Finally, the solution shows a detailed analysis for the Thames River, leveraging the information available on flood barriers and levees. Two realistic disaster scenarios for the Greater London area are simulated: In the first scenario, the storm surge intensity is not high enough to fail London’s flood defences, but in the second scenario, London’s flood defences fail, highlighting the potential losses from a catastrophic coastal flood event.

Keywords: storm surge, stochastic model, levee failure, Thames River

Procedia PDF Downloads 217

Authors: Silvano Salvador, Maryam Zarrinderakht, Alan Martin

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Open pits, which are the result of mining, are filled by water over time until the water reaches the elevation of the local water table and generates mine pit lakes. There are several specific regulations about the water quality of pit lakes, and mining operations should keep the quality of groundwater above pre-defined standards. Therefore, an accurate, acceptable numerical model predicting pit lakes’ water balance and water quality is needed in advance of mine excavation. We carry on analyzing and developing the model introduced by Crusius, Dunbar, et al. (2002) for pit lakes. This model, called “PitMod”, simulates the physical and geochemical evolution of pit lakes over time scales ranging from a few months up to a century or more. Here, a lake is approximated as one-dimensional, horizontally averaged vertical layers. PitMod calculates the time-dependent vertical distribution of physical and geochemical pit lake properties, like temperature, salinity, conductivity, pH, trace metals, and dissolved oxygen, within each model layer. This model considers the effect of pit morphology, climate data, multiple surface and subsurface (groundwater) inflows/outflows, precipitation/evaporation, surface ice formation/melting, vertical mixing due to surface wind stress, convection, background turbulence and equilibrium geochemistry using PHREEQC and linking that to the geochemical reactions. PitMod, which is used and validated in over 50 mines projects since 2002, incorporates physical processes like those found in other lake models such as DYRESM (Imerito 2007). However, unlike DYRESM PitMod also includes geochemical processes, pit wall runoff, and other effects. In addition, PitMod is actively under development and can be customized as required for a particular site.

Keywords: pit lakes, mining, modeling, hydrology

Procedia PDF Downloads 119

Authors: Sophia Anastasiou, Cosmas Nathanailides, Fotini Kakali, Kostas Karipoglou

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Wild fish are considered as testier and in fish restaurants are offered at twice the price of farmed fish. Several chemical and structural differences can affect the consumer's attitudes for farmed fish. The structure and chemical composition of fish muscle is also important for the performance of farmed fish during handling, storage and processing. In the present work we present the chemical and sensory parameters which are used as indicators of fish flesh quality and we investigated the perceptions of consumers for farmed sea bass and the organoleptic differences between samples of wild and farmed sea bass. A questionnaire was distributed to a group of various ages that were regular consumers of sea bass. The questionnaire included a survey on the perceptions on taste and appearance differences between wild and farmed sea bass. A significant percentage (>40%) of the participants stated their perception of superior taste of wild sea bass versus the farmed fish. The participants took part in an organoleptic assessment of wild and farmed sea bass prepared and cooked by a local fish restaurant. Portions were evaluated for intensity of sensorial attributes from 1 (low intensity) to 5 (high intensity). The results indicate that contrary to the assessor's perception, farmed sea bass scored better in al organoleptic parameters assessed with marked superiority in texture and taste over the wild sea bass. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III. Investing in knowledge society through the European Social Fund.

Keywords: fish marketing, farmed fish, seafood quality, wild fish

Procedia PDF Downloads 380

Authors: Goksel Ezgi Guzey, Bihrat Onoz

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The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region.

Keywords: hydrology, streamflow estimation, climate change, hydrologic modeling, HBV, hydropower

Procedia PDF Downloads 100

Authors: Edward Nartey

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Although the boundaries of sustainable performance and growth in the field of service supply chains (SCs) have been broadened by scholars in recent years, research on the impact and promises of Industry 4.0 Destructive Technologies (IDTs) on sustainability performance under disruptive events is still scarce. To mitigate disruptions in the SC and improve efficiency by identifying areas for cost savings, organizations have resorted to investments in digitalization, automation, and control mechanisms in recent years. However, little is known about the sustainability implications for IDT adoption and controls in service SCs, especially during disruptive events. To investigate this paradox, survey data were sought from 223 public health managers across Ghana and analyzed via covariance-based structural equations modelling. The results showed that both formal and informal control have a positive and significant relationship with IDT adoption. In addition, formal control has a significant and positive relationship with environmental and economic sustainability but an insignificant relationship with social sustainability. Furthermore, informal control positively impacts economic performance but has an insignificant relationship with social and environmental sustainability. While the findings highlight the prevalence of the IDTs being initiated by Ghanaian public health institutions (PHIs), this study concludes that the installed control systems in these organizations are inadequate for promoting sustainable SC behaviors under destructive events. Thus, in crisis situations, PHIs need to redesign their control systems to facilitate IDT integration towards sustainability issues in SCs.

Keywords: industry 4.0 destructive technologies, formal control, informal control, sustainable supply chain performance, public health organizations

Procedia PDF Downloads 35

Authors: Hamidreza Hoshyarmanesh, Benjamin Durante, Alex Irwin, Sanju Lama, Kourosh Zareinia, Garnette R. Sutherland

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This study reports on a proposed method to evaluate the accuracy and precision of Excalibur I, a neurosurgery-specific haptic hand controller, designed and developed at Project neuroArm. Having an efficient and successful robot-assisted telesurgery is considerably contingent on how accurate and precise a haptic hand controller (master/local robot) would be able to interpret the kinematic indices of motion, i.e., position and orientation, from the surgeon’s upper limp to the slave/remote robot. A proposed test rig is designed and manufactured according to standard ASTM F2554-10 to determine the accuracy and precision range of Excalibur I at four different locations within its workspace: central workspace, extreme forward, far left and far right. The test rig is metrologically characterized by a coordinate measuring machine (accuracy and repeatability < ± 5 µm). Only the serial linkage of the haptic device is examined due to the use of the Structural Length Index (SLI). The results indicate that accuracy decreases by moving from the workspace central area towards the borders of the workspace. In a comparative study, Excalibur I performs on par with the PHANToM PremiumTM 3.0 and more accurate/precise than the PHANToM PremiumTM 1.5. The error in Cartesian coordinate system shows a dominant component in one direction (δx, δy or δz) for the movements on horizontal, vertical and inclined surfaces. The average error magnitude of three attempts is recorded, considering all three error components. This research is the first promising step to quantify the kinematic performance of Excalibur I.

Keywords: accuracy, advanced metrology, hand controller, precision, robot-assisted surgery, tele-operation, workspace

Procedia PDF Downloads 321

Authors: Ramiro Quintanilla-Licea, Isvar K. Angeles-Hernandez, Javier Vargas-Villarreal

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Amebiasis caused by Entamoeba histolytica, associated with high morbidity and mortality, is currently a significant public health problem worldwide, especially in developing countries. In the world, around 50 million people develop this illness, and up to 100,000 deaths occur annually. Due to the side-effects and the resistance that pathogenic protozoa show against common antiparasitic drugs (e.g., metronidazole), growing attention has been paid to plants used in traditional medicine around the world to find new antiprotozoal agents. In this study is reported about the isolation and structure elucidation of antiamoebic compounds occurring in Lippia graveolens Kunth (Mexican oregano). The work-up of the methanol extract of L. graveolens afforded the known flavonoids pinocembrin (1), sakuranetin (2), cirsimaritin (3) and naringenin (4) by bioguided isolation using several chromatographic techniques. Structural elucidation of the isolated compounds was based on spectroscopic/spectrometric analyses (IR; 1H- and 13C-NMR; MS) and comparison with literature data. These compounds showed significant antiprotozoal activity against Entamoeba histolytica trophozoites using in vitro tests (positive control metronidazole IC50 0.205 µg/mL). The antiprotozoal activity of pinocembrin and naringenin (IC50 of 29.51 µg/mL and 28.85 µg/mL, respectively) was higher compared with sakuranetin (44.47 µg/mL) and with cirsimaritin (150.00 µg/mL), revealing that a 5,7-dihydroxylated A ring is essential for antiprotozoal activity. These research funds may validate the use of this plant in the traditional Mexican medicine for the treatment of some digestive disorders and can help to integrate the use of extracts of L. graveolens in the conventional and complementary medicine for the treatment of parasitic diseases.

Keywords: amoebiasis, antiprotozoal agents, bioguided isolation, infectious diseases

Procedia PDF Downloads 169