Search results for: hybrid models

Authors: Ibrahim A. Elshaer, Alaa M. Shaker

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Several previous empirical studies have operationalized service quality as either a multidimensional or unidimensional construct. While few earlier studies investigated some practices of the assumed dimensional structure of service quality, no study has been found to have tested the construct’s dimensionality using confirmatory factor analysis (CFA). To gain a better insight into the dimensional structure of service quality construct, this paper tests its dimensionality using three CFA models (higher order factor model, oblique factor model, and one factor model) on a set of data collected from 390 British tourists visited Egypt. The results of the three tests models indicate that service quality construct is multidimensional. This result helps resolving the problems that might arise from the lack of clarity concerning the dimensional structure of service quality, as without testing the dimensional structure of a measure, researchers cannot assume that the significant correlation is a result of factors measuring the same construct.

Keywords: service quality, dimensionality, confirmatory factor analysis, Egypt

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Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Huimin Zhao, Xiaoquan Liu, Haochen Liu

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The major challenge facing Alzheimer's Disease (AD) drug development is how to effectively improve cognitive function in clinical practice. Growing evidence indicates that stimulating hippocampal neurogenesis is a strategy for restoring cognition in animal models of AD. The mitogen-activated protein kinase (MAPK) pathway is a crucial factor in neurogenesis, which is negatively regulated by Dual-specificity phosphatase 16 (DUSP16). Transcriptome analysis of post-mortem brain tissue revealed up-regulation of DUSP16 expression in AD patients. Additionally, DUSP16 was involved in regulating the proliferation and neural differentiation of neural progenitor cells (NPCs). Nevertheless, whether the effect of DUSP16 on ameliorating cognitive disorders by influencing NPCs differentiation in AD mice remains unclear. Our study demonstrates an association between DUSP16 SNPs and clinical progression in individuals with mild cognitive impairment (MCI). Besides, we found that increased DUSP16 expression in both 3×Tg and SAMP8 models of AD led to NPC differentiation impairments. By silencing DUSP16, cognitive benefits, the induction of AHN and synaptic plasticity, were observed in AD mice. Furthermore, we found that DUSP16 is involved in the process of NPC differentiation by regulating c-Jun N-terminal kinase (JNK) phosphorylation. Moreover, the increased DUSP16 may be regulated by the ETS transcription factor (ELK1), which binds to the promoter region of DUSP16. Loss of ELK1 resulted in decreased DUSP16 mRNA and protein levels. Our data uncover a potential regulatory role for DUSP16 in adult hippocampal neurogenesis and provide a possibility to find the target of AD intervention.

Keywords: alzheimer's disease, cognitive function, DUSP16, hippocampal neurogenesis

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Authors: J. Nyenhuis, J. Drelich

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This research study was designed to determine if food crops could be bio-fortified with micro-nutrients by growing sprouts on mineral fortified fiber mats. Diets high in processed foods have been found to lack essential micro-nutrients for optimum human development and overall health. Some micro-nutrients such as copper (Cu) have been found to enhance the inflammatory response through its oxidative functions, thereby having a role in cardiovascular disease (CVD), metabolic syndrome (MetS), diabetes and related complications. Recycled cellulose fibers and clay saturated with micro-nutrient ions can be converted to a novel mineral-metal hybrid material in which the fiber mat becomes a carrier of essential micro-nutrients. The reduction of ionic to metallic copper was accomplished using hydrogen at temperatures ranging from 400o to 600oC. Copper particles with diameters ranging from ~1 to 400-500 nm reside on the recycled fibers that make up the mats. Seeds purchased from a commercial, organic supplier were germinated on the specially engineered cellulose fiber mats that incorporated w10 wt% clay fillers saturated with either copper particles or ionic copper. After the appearance of the first leaves, the sprouts were dehydrated and analyzed for Cu content. Nutrient analysis showed 1.5 to 1.6 increase in Cu of the sprouts grown on the fiber mats with copper particles, and 2.3 to 2.5 increase on mats with ionic copper as compared to the control samples. The antibacterial properties of materials saturated with copper ions at room temperature and at temperatures up to 400°C have been verified with halo method tests against Escherichia Coli in previous studies. E. coli is a known pathogenic risk in sprout production. Copper exhibits excellent antibacterial properties when tested on S. aureus, a pathogenic gram-positive bacterium. This has also been confirmed for the fiber-copper hybrid material in this study. This study illustrates the potential for the use of engineered mats as a viable way to increase the micro-nutrient composition of locally-grown food crops and the need for additional research to determine the uptake, nutritional implications and risks of micro-nutrient bio-fortification.

Keywords: bio-fortification, copper nutrient analysis, micro-nutrient uptake, sprouts and mineral-fortified mats

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Authors: Shidokht Rashiddadash, Mojtaba Sadighi, Soheil Dariushi

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Since sandwich structures are used in many areas ranging from ships, trains, automobiles, aircrafts, bridge and building, connecting sandwich structures is necessary almost in all industries. So application of metallic joints between sandwich panels is increasing. Various joining methods are available such as mechanically fastened joints (riveting or bolting) or adhesively bonded joints and choosing one of them depends on the application. In this research, sandwich specimens were fabricated with two different types of metallic connections with dissimilar geometries. These specimens included beams and plates and were manufactured using glass-epoxy skins and aluminum honeycomb core. After construction of the specimens, bending and low velocity impact tests were executed on them and the behaviors of specimens were discussed. Numerical models were developed using LS-DYNA software and validated with test results. Finally, parametric studies were performed on the thicknesses and lengths of two connections by employing the numerical models.

Keywords: connection, honeycomb, low velocity impact, sandwich panel, static test

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Authors: Renzhi Qi, Zhaoping Zhong

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Under the dual pressure of the global energy crisis and environmental pollution, avoiding the consumption of non-renewable fossil fuels based on carbon as the energy carrier and developing and utilizing non-carbon energy carriers are the basic requirements for the future new energy economy. Electrocatalyst for water splitting plays an important role in building sustainable and environmentally friendly energy conversion. The oxygen evolution reaction (OER) is essentially limited by the slow kinetics of multi-step proton-electron transfer, which limits the efficiency and cost of water splitting. In this work, CeO₂@NiCo-NRGO/NF hybrid materials were prepared using nickel foam (NF) and nitrogen-doped reduced graphene oxide (NRGO) as conductive substrates by multi-step hydrothermal method and were used as highly efficient catalysts for OER. The well-connected nanosheet array forms a three-dimensional (3D) network on the substrate, providing a large electrochemical surface area with abundant catalytic active sites. The doping of CeO₂ in NiCo-NRGO/NF electrocatalysts promotes the dispersion of substances and its synergistic effect in promoting the activation of reactants, which is crucial for improving its catalytic performance against OER. The results indicate that CeO₂@NiCo-NRGO/NF only requires a lower overpotential of 250 mV to drive the current density of 10 mA cm-2 for an OER reaction of 1 M KOH, and exhibits excellent stability at this current density for more than 10 hours. The double layer capacitance (Cdl) values show that CeO₂@NiCo-NRGO/NF significantly affects the interfacial conductivity and electrochemically active surface area. The hybrid structure could promote the catalytic performance of oxygen evolution reaction, such as low initial potential, high electrical activity, and excellent long-term durability. The strategy for improving the catalytic activity of NiCo-LDH can be used to develop a variety of other electrocatalysts for water splitting.

Keywords: CeO₂, reduced graphene oxide, NiCo-layered double hydroxide, oxygen evolution reaction

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Authors: A. Fettahoglu

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Theory of viscoelasticity is used by many researchers to represent the behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell model and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Afterwards, a guide is illustrated to ease using of viscoelasticity tool in ANSYS.

Keywords: ANSYS, generalized Maxwell model, finite element method, Prony series, viscoelasticity, viscoelastic material curve fitting

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Authors: Elizabeth Stojanovski

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Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance, and within study variance and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach.

Keywords: random-effects, meta-analysis, Bayesian, variation

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: S. O. Oyamakin, A. U. Chukwu

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Richard's growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richard's growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richard's growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richard's nonlinear growth models better than the classical Richard's growth model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, Richard's, stochastic

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Authors: W. H. Wan Zakiyatussariroh, A. A. Nasuhar, W. Y. Wan Fairos, Z. A. Nazatul Shahreen

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Forecasting dengue incidence in a population can provide useful information to facilitate the planning of the public health intervention. Many studies on dengue cases in Malaysia were conducted but are limited in modeling the outbreak and forecasting incidence. This article attempts to propose the most appropriate time series model to explain the behavior of dengue incidence in Malaysia for the purpose of forecasting future dengue outbreaks. Several seasonal auto-regressive integrated moving average (SARIMA) models were developed to model Malaysia’s number of dengue incidence on weekly data collected from January 2001 to December 2011. SARIMA (2,1,1)(1,1,1)52 model was found to be the most suitable model for Malaysia’s dengue incidence with the least value of Akaike information criteria (AIC) and Bayesian information criteria (BIC) for in-sample fitting. The models further evaluate out-sample forecast accuracy using four different accuracy measures. The results indicate that SARIMA (2,1,1)(1,1,1)52 performed well for both in-sample fitting and out-sample evaluation.

Keywords: time series modeling, Box-Jenkins, SARIMA, forecasting

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Authors: Nezha Alaoui

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The early 1950s French colonial context in Morocco provided an opportunity for architects to question the modernist established order by building dwellings for the local population. The dwellings were originally designed to encourage Muslims to adopt an urban lifestyle based on local customs. However, the inhabitants transformed their dwelling into a hybrid habitation. This paper aims to prove the relevance of the design process in accordance with the local colonial context by analyzing the dwellers' appropriation process and the modification of their habitat.

Keywords: colonial heritage, appropriation process, islamic spatial habit, housing experiment, modernist mass housing

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Authors: Roman Knizek, Denisa Knizkova, Ludmila Fridrichova

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The academic environment in Central Europe has recently been transforming itself and is trying to link its research and development with the private sector. However, compared to Western countries, there is a lack of history and continuity because of the centrally controlled economy from the end of the Second World War until the early 1990s. There are two basic models of how to carry out technology transfer between the academic and the business world. The first is to develop something new and then find a suitable private sector partner; the second is to find a partner who has the basic idea and then develop something new in collaboration. This study, unlike some other ones, describes two specific cases that took place in cooperation with the Technical University of Liberec, Faculty of Textiles. As was said before, in one case, a product was first developed, and after that, an investor was sought, and in the other case, there was an investor who wanted a specific product and wanted to help with its development. The study describes the various advantages and disadvantages, including a practical example of the creation of a subsequent start-up.

Keywords: start-up, state university, academic environment, licensing agreement

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Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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Authors: Abdul Haq

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The goal of this research is to better understand how wind loads affect bridges and develop strategies for designing bridges that are more stable and resistant to wind. The effect of wind on bridges is essential to their safety and functionality, especially in areas that are prone to high wind speeds or violent wind conditions. The study looks at the aerodynamic forces and vibrations caused by wind and how they affect bridge construction. Part of the research method involves first understanding the underlying ideas influencing wind flow near bridges. Computational fluid dynamics (CFD) simulations are used to model and forecast the aerodynamic behaviour of bridges under different wind conditions. These models incorporate several factors, such as wind directionality, wind speed, turbulence intensity, and the influence of nearby structures or topography. The results provide significant new insights into the loads and pressures that wind places on different bridge elements, such as decks, pylons, and connections. Following the determination of the wind loads, the structural response of bridges is assessed. By simulating their dynamic behavior under wind-induced forces, Finite Element Analysis (FEA) is used to model the bridge's component parts. This work contributes to the understanding of which areas are at risk of experiencing excessive stresses, vibrations, or oscillations due to wind excitations. Because the bridge has inherent modes and frequencies, the study considers both static and dynamic responses. Various strategies are examined to maximize the design of bridges to withstand wind. It is possible to alter the bridge's geometry, add aerodynamic components, add dampers or tuned mass dampers to lessen vibrations, and boost structural rigidity. Through an analysis of several design modifications and their effectiveness, the study aims to offer guidelines and recommendations for wind-resistant bridge design. In addition to the numerical simulations and analyses, there are experimental studies. In order to assess the computational models and validate the practicality of proposed design strategies, scaled bridge models are tested in a wind tunnel. These investigations help to improve numerical models and prediction precision by providing valuable information on wind-induced forces, pressures, and flow patterns. Using a combination of numerical models, actual testing, and long-term performance evaluation, the project aims to offer practical insights and recommendations for building wind-resistant bridges that are secure, long-lasting, and comfortable for users.

Keywords: wind effects, aerodynamic forces, computational fluid dynamics, finite element analysis

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Authors: Shamsulhaq Amin

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Unbound granular materials (UGMs) are pivotal in ensuring long-term quality, especially in the layers under the surface of flexible pavements and other constructions. This study seeks to better understand the behavior of the UGMs by looking at popular models for predicting lasting deformation under various levels of stresses and load cycles. These models focus on variables such as the number of load cycles, stress levels, and features specific to materials and were evaluated on the basis of their ability to accurately predict outcomes. The study showed that these factors play a crucial role in how well the models work. Therefore, the research highlights the need to look at a wide range of stress situations to more accurately predict how much the UGMs bend or shift. The research looked at important factors, like how permanent deformation relates to the number of times a load is applied, how quickly this phenomenon happens, and the shakedown effect, in two different types of UGMs: granite and limestone. A detailed study was done over 100,000 load cycles, which provided deep insights into how these materials behave. In this study, a number of factors, such as the level of stress applied, the number of load cycles, the density of the material, and the moisture present were seen as the main factors affecting permanent deformation. It is vital to fully understand these elements for better designing pavements that last long and handle wear and tear. A series of laboratory tests were performed to evaluate the mechanical properties of materials and acquire model parameters. The testing included gradation tests, CBR tests, and Repeated load triaxial tests. The repeated load triaxial tests were crucial for studying the significant components that affect deformation. This test involved applying various stress levels to estimate model parameters. In addition, certain model parameters were established by regression analysis, and optimization was conducted to improve outcomes. Afterward, the material parameters that were acquired were used to construct graphs for each model. The graphs were subsequently compared to the outcomes obtained from the repeated load triaxial testing. Additionally, the models were evaluated to determine if they demonstrated the two inherent deformation behaviors of materials when subjected to repetitive load: the initial phase, post-compaction, and the second phase volumetric changes. In this study, using log-log graphs was key to making the complex data easier to understand. This method made the analysis clearer and helped make the findings easier to interpret, adding both precision and depth to the research. This research provides important insight into picking the right models for predicting how these materials will act under expected stress and load conditions. Moreover, it offers crucial information regarding the effect of load cycle and permanent deformation as well as the shakedown effect on granite and limestone UGMs.

Keywords: permanent deformation, unbound granular materials, load cycles, stress level

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Authors: Brahim-Fares Zaidi, Malika Boudraa, Sid-Ahmed Selouani

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Our work aims to improve our Automatic Recognition System for Dysarthria Speech (ARSDS) based on the Hidden Models of Markov (HMM) and the Hidden Markov Model Toolkit (HTK) to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients (MFCC's) and Perceptual Linear Prediction (PLP's) and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.

Keywords: hidden Markov model toolkit (HTK), hidden models of Markov (HMM), Mel-frequency cepstral coefficients (MFCC), perceptual linear prediction (PLP’s)

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Diego Liberati

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Standard molecular modeling is traditionally done through Schroedinger equations via the help of powerful tools helping to manage them atom by atom, often needing High Performance Computing. Here, a full portfolio of new tools, conjugating statistical inference in the so called eXplainable Artificial Intelligence framework (in the form of Machine Learning of understandable rules) to the more traditional modeling and simulation control theory of mixed dynamic logic hybrid processes, is offered as quite a general purpose even if making an example to a popular chemical physics set of problems.

Keywords: understandable rules ML, k-means, PCA, PieceWise Affine Auto Regression with eXogenous input

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Authors: Samuel Oluwafemi Oyamakin, Angela Unna Chukwu

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Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model.

Keywords: height, diameter at breast height, DBH, hyperbolic sine function, Pinus caribaea, Richards' growth model

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Authors: Tae-min Byun, Chang-soo Chon, Dong-hyun Seo, Han-sung Kim, Bum-mo Ahn, Hui-suk Yun, Cheolwoong Ko

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In this study, a 3-point bending computational analysis of normal and osteoporosis mouse models was performed based on the Micro-CT image information of the femurs. The finite element analysis (FEA) found 1.68 N (normal group) and 1.39 N (osteoporosis group) in the average maximum force, and 4.32 N/mm (normal group) and 3.56 N/mm (osteoporosis group) in the average stiffness. In the comparison of the 3-point bending test results, the maximum force and the stiffness were different about 9.4 times in the normal group and about 11.2 times in the osteoporosis group. The difference between the analysis and the test was greatly significant and this result demonstrated improvement points of the material properties applied to the computational analysis of this study. For the next study, the material properties of the mouse femur will be supplemented through additional computational analysis and test.

Keywords: 3-point bending test, mouse, osteoporosis, FEA

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Authors: Marko Kolakovic

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Creative industries are an important sector of growth and development of knowledge economies. They have a positive impact on employment, economic growth, export and the quality of life in the areas where they are developed. Creative sectors include architecture, design, advertising, publishing, music, film, television and radio, video games, visual and performing arts and heritage. Following the positive trends of development of creative industries on the global and European level, this paper analyzes creative industries in general and specific characteristics of creative entrepreneurship. Special focus in this paper is put on the influence of the information communication technology on the development of new creative business models and protection of the intellectual property rights. One part of the paper is oriented on the analysis of the status of creative industries and creative entrepreneurship in Croatia. The main objective of the paper is by using the statistical analysis of creative industries in Croatia and information gained during the interviews with entrepreneurs, to make conclusions about potentials and development of creative industries in Croatia. Creative industries in Croatia are at the beginning of their development and growth strategy still does not exist at the national level. Statistical analysis pointed out that in 2015 creative enterprises made 9% of all enterprises in Croatia, employed 5,5% of employed people and their share in GDP was 4,01%. Croatian creative entrepreneurs are building competitive advantage using their creative resources and creating specific business models. The main obstacles they meet are lack of business experience and impossibility of focusing on the creative activities only. In their business, they use digital technologies and are focused on export. The conclusion is that creative industries in Croatia have development potential, but it is necessary to take adequate measures to use this potential in a right way.

Keywords: creative entrepreneurship, knowledge economy, business models, intellectual property

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Authors: Nicolas Bae, Theodore L. Karavasilis

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Increasingly, a large number of new and existing tall buildings are required to improve their resilient performance against strong winds and earthquakes to minimize direct, as well as indirect damages to society. Those advent stationary functions of tall building structures in metropolitan regions can be severely hazardous, in socio-economic terms, which also increase the requirement of advanced seismic performance. To achieve these progressive requirements, the seismic reinforcement for some old, conventional buildings have become enormously costly. The methods of increasing the buildings’ resilience against wind or earthquake loads have also become more advanced. Up to now, vibration control devices, such as the passive damper system, is still regarded as an effective and an easy-to-install option, in improving the seismic resilience of buildings at affordable prices. The main purpose of this paper is to examine 1) the optimization of the shape of visco plastic brace damper (VPBD) system which is one of hybrid damper system so that it can maximize its energy dissipation capacity in tall buildings against wind and earthquake. 2) the verification of the seismic performance of the visco plastic brace damper system in tall buildings; up to forty-storey high steel frame buildings, by comparing the results of Non-Linear Response History Analysis (NLRHA), with and without a damper system. The most significant contribution of this research is to introduce the optimized hybrid damper system that is adequate for high rise buildings. The efficiency of this visco plastic brace damper system and the advantages of its use in tall buildings can be verified since tall buildings tend to be affected by wind load at its normal state and also by earthquake load after yielding of steel plates. The modeling of the prototype tall building will be conducted using the Opensees software. Three types of modeling were used to verify the performance of the damper (MRF, MRF with visco-elastic, MRF with visco-plastic model) 22-set seismic records used and the scaling procedure was followed according to the FEMA code. It is shown that MRF with viscous, visco-elastic damper, it is superior effective to reduce inelastic deformation such as roof displacement, maximum story drift, roof velocity compared to the MRF only.

Keywords: tall steel building, seismic retrofit, viscous, viscoelastic damper, performance based design, resilience based design

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Authors: Hadayat Ullah, Pervez Khalid, Saad Ahmed Mashwani, Zaheer Abbasi, Mubashir Mehmood, Muhammad Jahangir, Ehsan ul Haq

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The aim of the study is to explore subsurface structures through data that is acquired from the seismic survey to delineate the characteristics of the reservoir through petrophysical analysis. Ghazij Shale of Eocene age is regional seal rock in this field. In this research work, 3D property models of subsurface were prepared by applying Petrel software to identify various lithologies and reservoir fluids distribution throughout the field. The 3D static modeling shows a better distribution of the discrete and continuous properties in the field. This model helped to understand the reservoir properties and enhance production by selecting the best location for future drilling. A complete workflow is proposed for formation evaluation, electrofacies modeling, and structural interpretation of the subsurface geology. Based on the wireline logs, it is interpreted that the thickness of the Pab Sandstone varies from 250 m to 350 m in the entire study area. The sandstone is massive with high porosity and intercalated layers of shales. Faulted anticlinal structures are present in the study area, which are favorable for the accumulation of hydrocarbon. 3D structural models and various seismic attribute models were prepared to analyze the reservoir character of this clastic reservoir. Based on wireline logs and seismic data, clean sand, shaly sand, and shale are marked as dominant facies in the study area. However, clean sand facies are more favorable to act as a potential net pay zone.

Keywords: cretaceous, pab sandstone, petrophysics, electrofacies, hydrocarbon

Procedia PDF Downloads 143

Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

Procedia PDF Downloads 203

Authors: Safa Ladhari, Alireza Saidi, Phuong Nguyen-Tri

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During health crises, such as COVID-19, using disposable protective equipment (PEs) (masks, gowns, etc.) causes long-term problems, increasing the volume of hazardous waste that must be handled safely and expensively. Therefore, producing textiles for antimicrobial and reusable materials is highly desirable to decrease the use of disposable PEs that should be treated as hazardous waste. In addition, if these items are used regularly in the workplace or for daily activities by the public, they will most likely end up in household waste. Furthermore, they may pose a high risk of contagion to waste collection workers if contaminated. Therefore, to protect the whole population in times of sanitary crisis, it is necessary to equip these materials with tools that make them resilient to the challenges of carrying out daily activities without compromising public health and the environment and without depending on them external technologies and producers. In addition, the materials frequently used for EPs are plastics of petrochemical origin. The subject of the present work is replacing petroplastics with bioplastic since it offers better biodegradability. The chosen polymer is polyhydroxybutyrate (PHB), a family of polyhydroxyalkanoates synthesized by different bacteria. It has similar properties to conventional plastics. However, it is renewable, biocompatible, and has attractive barrier properties compared to other polyesters. These characteristics make it ideal for EP protection applications. The current research topic focuses on the preparation and rapid evaluation of the biological activity of nanotechnology-based antimicrobial agents to treat textile surfaces used for PE. This work will be carried out to provide antibacterial solutions that can be transferred to a workplace application in the fight against short-term biological risks. Three main objectives are proposed during this research topic: 1) the development of suitable methods for the deposition of antibacterial agents on the surface of textiles; 2) the development of a method for measuring the antibacterial activity of the prepared textiles and 3) the study of the biodegradability of the prepared textiles. The studied textile is a non-woven fabric based on a biodegradable polymer manufactured by the electrospinning method. Indeed, nanofibers are increasingly studied due to their unique characteristics, such as high surface-to-volume ratio, improved thermal, mechanical, and electrical properties, and confinement effects. The electrospun film will be surface modified by plasma treatment and then loaded with hybrid antibacterial silver and titanium dioxide nanoparticles by the dip-coating method. This work uses simple methods with emerging technologies to fabricate nanofibers with suitable size and morphology to be used as components for protective equipment. The antibacterial agents generally used are based on silver, zinc, copper, etc. However, to our knowledge, few researchers have used hybrid nanoparticles to ensure antibacterial activity with biodegradable polymers. Also, we will exploit visible light to improve the antibacterial effectiveness of the fabric, which differs from the traditional contact mode of killing bacteria and presents an innovation of active protective equipment. Finally, this work will allow for the innovation of new antibacterial textile materials through a simple and ecological method.

Keywords: protective equipment, antibacterial textile materials, biodegradable polymer, electrospinning, hybrid antibacterial nanoparticles

Procedia PDF Downloads 80

Authors: Asmamaw Yehun, Tsegaye Kassa, Addisu Hunegnaw, Martin Vermeer

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There are various models to estimate the neutral atmospheric parameter values, such as in-suite and reanalysis datasets from numerical models. Accurate estimated values of the atmospheric parameters are useful for weather forecasting and, climate modeling and monitoring of climate change. Recently, Global Navigation Satellite System (GNSS) measurements have been applied for atmospheric sounding due to its robust data quality and wide horizontal and vertical coverage. The Global Positioning System (GPS) solutions that includes tropospheric parameters constitute a reliable set of data to be assimilated into climate models. The objective of this paper is, to estimate the neutral atmospheric parameters such as Wet Zenith Delay (WZD), Precipitable Water Vapour (PWV) and Total Zenith Delay (TZD) using six selected GPS stations in the equatorial regions, more precisely, the Ethiopian GPS stations from 2012 to 2015 observational data. Based on historic estimated GPS-derived values of PWV, we forecasted the PWV from 2015 to 2030. During data processing and analysis, we applied GAMIT-GLOBK software packages to estimate the atmospheric parameters. In the result, we found that the annual averaged minimum values of PWV are 9.72 mm for IISC and maximum 50.37 mm for BJCO stations. The annual averaged minimum values of WZD are 6 cm for IISC and maximum 31 cm for BDMT stations. In the long series of observations (from 2012 to 2015), we also found that there is a trend and cyclic patterns of WZD, PWV and TZD for all stations.

Keywords: atmosphere, GNSS, neutral atmosphere, precipitable water vapour

Procedia PDF Downloads 61

Authors: Faiz Khan Mohammad, Saumya Ray Chaudhari, Raghunathan Rengaswamy, Swagatika Sahoo

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Cholera caused by pathogenic gut bacteria Vibrio Cholerae (VC), is a major health problem in developing countries. Different strains of VC exhibit variable responses subject to different extracellular medium (Nag et al, Infect Immun, 2018). In this study, we present a new approach to model the variable VC responses in mono- and co-cultures, subject to continuously changing growth medium, which is otherwise difficult via simple FBA model. Nine VC strain and seven E. coli (EC) models were assembled and considered. A continuously changing medium is modelled using a new iterative-based controlled medium technique (ITC). The medium is appropriately prefixed with the VC model secretome. As the flux through the bacteria biomass increases secretes certain by-products. These products shall add-on to the medium, either deviating the nutrient potential or block certain metabolic components of the model, effectively forming a controlled feed-back loop. Different VC models were setup as monoculture of VC in glucose enriched medium, and in co-culture with VC strains and EC. Constrained to glucose enriched medium, (i) VC_Classical model resulted in higher flux through acidic secretome suggesting a pH change of the medium, leading to lowering of its biomass. This is in consonance with the literature reports. (ii) When compared for neutral secretome, flux through acetoin exchange was higher in VC_El tor than the classical models, suggesting El tor requires an acidic partner to lower its biomass. (iii) Seven of nine VC models predicted 3-methyl-2-Oxovaleric acid, mysirtic acid, folic acid, and acetate significantly affect corresponding biomass reactions. (iv) V. parhemolyticus and vulnificus were found to be phenotypically similar to VC Classical strain, across the nine VC strains. The work addresses the advantage of the ITC over regular flux balance analysis for modelling varying growth medium. Future expansion to co-cultures, potentiates the identification of novel interacting partners as effective cholera therapeutics.

Keywords: cholera, vibrio cholera El. tor, vibrio cholera classical, acetate

Procedia PDF Downloads 162