Search results for: linear multistep methods

Authors: A. G. Akhundov

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Issues of obtaining unbiased data on the status of pipeline systems of oil- and oil product transportation become especially important when laying and operating pipelines under severe nature and climatic conditions. The essential attention is paid here to researching exogenous processes and their impact on linear facilities of the pipeline system. Reliable operation of pipelines under severe nature and climatic conditions, timely planning and implementation of compensating measures are only possible if operation conditions of pipeline systems are regularly monitored, and changes of permafrost soil and hydrological operation conditions are accounted for. One of the main reasons for emergency situations to appear is the geodynamic factor. Emergency situations are proved by the experience to occur within areas characterized by certain conditions of the environment and to develop according to similar scenarios depending on active processes. The analysis of natural and technical systems of main pipelines at different stages of monitoring gives a possibility of making a forecast of the change dynamics. The integration of GIS technologies, traditional means of geotechnical monitoring (in-line inspection, geodetic methods, field observations), and remote methods (aero-visual inspection, aero photo shooting, air and ground laser scanning) provides the most efficient solution of the problem. The united environment of geo information system (GIS) is a comfortable way to implement the monitoring system on the main pipelines since it provides means to describe a complex natural and technical system and every element thereof with any set of parameters. Such GIS enables a comfortable simulation of main pipelines (both in 2D and 3D), the analysis of situations and selection of recommendations to prevent negative natural or man-made processes and to mitigate their consequences. The specifics of such systems include: a multi-dimensions simulation of facilities in the pipeline system, math modelling of the processes to be observed, and the use of efficient numeric algorithms and software packets for forecasting and analyzing. We see one of the most interesting possibilities of using the monitoring results as generating of up-to-date 3D models of a facility and the surrounding area on the basis of aero laser scanning, data of aerophotoshooting, and data of in-line inspection and instrument measurements. The resulting 3D model shall be the basis of the information system providing means to store and process data of geotechnical observations with references to the facilities of the main pipeline; to plan compensating measures, and to control their implementation. The use of GISs for geotechnical monitoring of pipeline systems is aimed at improving the reliability of their operation, reducing the probability of negative events (accidents and disasters), and at mitigation of consequences thereof if they still are to occur.

Keywords: databases, 3D GIS, geotechnical monitoring, pipelines, laser scaning

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Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Matei Tudor Berceanu, Hema Viswambharan, Kirti Kain, Chew Weng Cheng

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Background - Obesity parameters, particularly visceral obesity as measured by the waist-to-height ratio (WHtR), correlate with insulin resistance. The metabolic microvascular changes associated with insulin resistance causes increased peripheral arteriolar resistance primarily to the lower limb vessels. We hypothesize that ankle systolic blood pressures (SBPs) are more significantly associated with visceral obesity than brachial SBPs. Methods - 1098 adults enriched in south Asians or Europeans with diabetes (T2DM) were recruited from a primary care practice in West Yorkshire. Their medical histories, including T2DM and cardiovascular disease (CVD) status, were gathered from an electronic database. The brachial, dorsalis pedis, and posterior tibial SBPs were measured using a Doppler machine. Their body mass index (BMI) and WHtR were calculated after measuring their weight, height, and waist circumference. Linear regressions were performed between the 6 SBPs and both obesity parameters, after adjusting for covariates. Results - Generally, the left posterior tibial SBP (P=4.559*10⁻¹⁵) and right posterior tibial SBP (P=1.114* 10⁻¹³ ) are the pressures most significantly associated with the BMI, as well as in south Asians (P < 0.001) and Europeans (P < 0.001) specifically. In South Asians, although the left (P=0.032) and right brachial SBP (P=0.045) were associated to the WHtR, the left posterior tibial SBP (P=0.023) showed the strongest association. Conclusion - Regardless of ethnicity, ankle SBPs are more significantly associated with generalized obesity than brachial SBPs, suggesting their screening potential for screening for early detection of T2DM and CVD. A combination of ankle SBPs with WHtR is proposed in south Asians.

Keywords: ankle blood pressures, body mass index, insulin resistance, waist-to-height-ratio

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Authors: Yasin Akgül, Yusuf Polat, Emine Canbay, Ali Kılıç

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Wound dressings have strategically and economic importance considering increase of chronic wounds in the world. In this study, TPU nanofibrous membranes containing propolis as wound dressing are produced by two different methods. Firstly, TPU solution and propolis extract were mixed and this solution was electrospun. The other method is that TPU/propolis blend was centrifugally spun. Properties of nanofibrous membranes obtained by these methods were compared. While realizing the experiments, both systems were optimized to produce nanofibers with nearly same average fiber diameter.

Keywords: nanofiber, wound dressing, electrospinning, centrifugal spinning

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Authors: Hannah Dean

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The growth ideology, and its association with progress, is an important construct in the narrative of modernity. This ideology is embedded in neoclassical economic growth theory which conceptualises growth as linear and predictable, and the entrepreneur as a rational economic manager. This conceptualisation has been critiqued for reinforcing the managerial discourse in entrepreneurship studies. Despite these critiques, both the neoclassical growth theory and its adjacent managerial discourse dominate entrepreneurship studies notably the literature on female entrepreneurs. The latter is the focus of this paper. Given this emphasis on growth, female entrepreneurs are portrayed as problematic because their growth lags behind their male counterparts. This image which ignores the complexity and diversity of female entrepreneurs’ experience persists in the literature due to the lack of studies that analyse the process and contextual factors surrounding female entrepreneurs’ experience. This study aims to address the subordination of female entrepreneurs by questioning the hegemonic logic of economic growth and the managerial discourse as a true representation for the entrepreneurial experience. This objective is achieved by drawing on Schumpeter’s theorising and narrative inquiry. This exploratory study undertakes in depth interviews to gain insights into female entrepreneurs’ experience and the impact of the economic growth model and the managerial discourse on their performance. The narratives challenge a number of assumptions about female entrepreneurs. The participants occupied senior positions in the corporate world before setting up their businesses. This is at odds with much writing which assumes that women underperform because they leave their career without gaining managerial experience to achieve work-life balance. In line with Schumpeter, who distinguishes the entrepreneur from the manager, the participants’ main function was innovation. They did not believe that the managerial paradigm governing their corporate careers was applicable to their entrepreneurial experience. Formal planning and managerial rationality can hinder their decision making process. The narratives point to the gap between the two worlds which makes stepping into entrepreneurship a scary move. Schumpeter argues that the entrepreneurial process is evolutionary and that failure is an integral part of it. The participants’ entrepreneurial process was in fact irregular. The performance of new combinations was not always predictable. They therefore relied on their initiative. The inhibition to deploy these traits had an adverse effect on business growth. The narratives also indicate that over-reliance on growth threaten the business survival as it faces competing pressures. The study offers theoretical and empirical contributions to (female) entrepreneurship studies by presenting Schumpeter’s theorising as an alternative theoretical framework to the neoclassical economic growth theory. The study also reduces entrepreneurs’ vulnerability by making them aware of the negative influence that the linear growth model and the managerial discourse hold upon their performance. The study has implications for policy makers as it generates new knowledge that incorporates the current social and economic changes in the context of entrepreneurs that can no longer be sustained by the linear growth models especially in the current economic climate.

Keywords: economic growth, female entrepreneurs, managerial discourse, Schumpeter

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Authors: Sung Hee Ahn, Ju Rang Han

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Background: With increasing importance in healthcare organization on patient satisfaction and nurses’ job satisfaction, many studies have been conducted. But no research has been administered how nurses’ satisfaction with healthcare organization influence patient satisfaction and loyalty. Purpose: This study aims to conceptualize nurses‘ satisfaction, patient satisfaction with and patient loyalty to hospitals using a hypothetical linear structural equation model, and to identify the significance of path coefficients and goodness of fit index of the structural equation model as well. Method: A total of 2,079 nurses and 6,776 patients recruited from 5 university hospitals in South Korea participated in this study. The data on nurses, including ward nurses and outpatient nurses, were collected from June 24th to July 12th, at the 204 departments of the 5 hospitals through an on-line survey. The data on the patients, including both inpatients and outpatients, were collected from September 30th to October 24th, 2013 at the 5 hospitals using a structured questionnaire. The variable of nurses’ satisfaction was measured using a scale evaluating internal client satisfaction, which is used in SSM Health Care System in the US. Patient satisfaction with the hospital and nurses and patient loyalty were measured by assessing the patient’s intention to revisit and to recommending the hospital to others using a visual analogue scale. The data were analyzed using SPSS version 21.0 and AMOS version 21.0. Result: The hypothetical model was fairly good in terms of goodness of fit (χ2= 64.897 (df=24, p <. 001), GFI=. 906, AGFI=.823, CFI=.921, NFI=.951, NNFI=.952. RMSEA=.114). The significance of path coefficients includes followings 1)The nurses’ satisfaction has significant influence on the patient satisfaction with nurses. 2)The patient satisfaction with nurses has significant influence on the patient satisfaction with the hospital. 3)The patient satisfaction with the hospital has significant influence on the patients’ revisit intention. 4)The patient satisfaction with the hospital has significant influence on the patients’ intention to the recommendations of the hospital. Conclusion: These results provide several practical implications to hospital administrators, who should incorporate ways of improving nurses' and patients' satisfaction with the hospital into their health care marketing strategies.

Keywords: linear structural equation model, loyalty, nurse, patient satisfaction

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Authors: Jose A. Alvarez Aldegunde, Adrian Fernandez Sanchez, Matthew D. Menden, Bernardo Vila Rodriguez

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Up to five statistical pre-processings have been carried out considering the pollutant records of the stations present in Cartagena de Indias, Colombia, also taking into account the childhood asthma incidence surveys conducted in hospitals in the city by the Health Ministry of Colombia for this study. These pre-processings have consisted of different techniques such as the determination of the quality of data collection, determination of the quality of the registration network, identification and debugging of errors in data collection, completion of missing data and purified data, as well as the improvement of the time scale of records. The characterization of the quality of the data has been conducted by means of density analysis of the pollutant registration stations using ArcGis Software and through mass balance techniques, making it possible to determine inconsistencies in the records relating the registration data between stations following the linear regression. The results obtained in this process have highlighted the positive quality in the pollutant registration process. Consequently, debugging of errors has allowed us to identify certain data as statistically non-significant in the incidence and series of contamination. This data, together with certain missing records in the series recorded by the measuring stations, have been completed by statistical imputation equations. Following the application of these prior processes, the basic series of incidence data for respiratory disease and pollutant records have allowed the characterization of the influence of pollutants on respiratory diseases such as, for example, childhood asthma. This characterization has been carried out using statistical correlation methods, including visual correlation, simple linear regression correlation and spectral analysis with PAST Software which identifies maximum periodicity cycles and minimums under the formula of the Lomb periodgram. In relation to part of the results obtained, up to eleven maximums and minimums considered contemporary between the incidence records and the particles have been identified taking into account the visual comparison. The spectral analyses that have been performed on the incidence and the PM2.5 have returned a series of similar maximum periods in both registers, which are at a maximum during a period of one year and another every 25 days (0.9 and 0.07 years). The bivariate analysis has managed to characterize the variable "Daily Vehicular Flow" in the ninth position of importance of a total of 55 variables. However, the statistical correlation has not obtained a favorable result, having obtained a low value of the R2 coefficient. The series of analyses conducted has demonstrated the importance of the influence of pollutants such as PM2.5 in the development of childhood asthma in Cartagena. The quantification of the influence of the variables has been able to determine that there is a 56% probability of dependence between PM2.5 and childhood respiratory asthma in Cartagena. Considering this justification, the study could be completed through the application of the BenMap Software, throwing a series of spatial results of interpolated values of the pollutant contamination records that exceeded the established legal limits (represented by homogeneous units up to the neighborhood level) and results of the impact on the exacerbation of pediatric asthma. As a final result, an economic estimate (in Colombian Pesos) of the monthly and individual savings derived from the percentage reduction of the influence of pollutants in relation to visits to the Hospital Emergency Room due to asthma exacerbation in pediatric patients has been granted.

Keywords: Asthma Incidence, BenMap, PM2.5, Statistical Analysis

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Authors: Mojtaba Saeedinezhad, Sarah Yousefi

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In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions.

Keywords: system identification, time delay estimation, ARX, OE, merit ratio, multi variable decision making

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Authors: Y. Laib Dit Leksir, S. Bouhouche

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Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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Authors: Flóra Pomázi, Sándor Baranya, Zoltán Szalai

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A harmonized monitoring of the suspended sediment transport along such a large river as the world’s most international river, the Danube River, is a rather challenging task. The traditional monitoring method in Hungary is obsolete but using indirect measurement devices and techniques like optical backscatter sensors (OBS), laser diffraction or acoustic backscatter sensors (ABS) could provide a fast and efficient alternative option of direct methods. However, these methods are strongly sensitive to the particle characteristics (i.e. particle shape, particle size and mineral composition). The current method does not provide sufficient information about particle size distribution, mineral analysis is rarely done, and the shape of the suspended sediment particles have not been examined yet. The aims of the study are (1) to determine the particle characterisation of suspended sediment in the Danube River using advanced particle characterisation methods as laser diffraction and automated imaging, and (2) to perform a sensitivity analysis of the indirect methods in order to determine the impact of suspended particle characteristics. The particle size distribution is determined by laser diffraction. The particle shape and mineral composition analysis is done by the Morphologi G3ID image analyser. The investigated indirect measurement devices are the LISST-Portable|XR, the LISST-ABS (Sequoia Inc.) and the Rio Grande 1200 kHz ADCP (Teledyne Marine). The major findings of this study are (1) the statistical shape of the suspended sediment particle - this is the first research in this context, (2) the actualised particle size distribution – that can be compared to historical information, so that the morphological changes can be tracked, (3) the actual mineral composition of the suspended sediment in the Danube River, and (4) the reliability of the tested indirect methods has been increased – based on the results of the sensitivity analysis and the previous findings.

Keywords: advanced particle characterisation, automated imaging, indirect methods, laser diffraction, mineral composition, suspended sediment

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L. Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts as a motivating starting point. In this work, the authors extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zₚ, zₙ]. The zₚ component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zₙ component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach coined Augmented Posterior CDE (AP-CDE) only requires a simple modification of the common normalizing flow framework while significantly improving the interpretation of the latent component since zₚ represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of 𝑥-related variations due to factors such as lighting condition and subject id from the other random variations. Further, the experiments show that an unconditional NF neural network based on an unsupervised model of z, such as a Gaussian mixture, fails to generate interpretable results.

Keywords: conditional density estimation, image generation, normalizing flow, supervised dimension reduction

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Authors: Yang Xiong, Hua Cheng

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In this paper, for the basic problem of wireless sensor network topology control and deployment, the Roesser model in rectangular grid sensor networks is presented. In addition, a general constructive realization procedure will be proposed. The procedure enables a distributed implementation of linear systems on a sensor network. A non-trivial example is illustrated.

Keywords: grid sensor networks, Roesser model, state-space realization, multidimensional systems

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Authors: Danilo F. Rodrigues, Hérida Regina N. Salgado

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Introduction: The emergence of resistant microorganisms to a large number of clinically approved antimicrobials has been increasing, which restrict the options for the treatment of bacterial infections. As a strategy, drugs with high antimicrobial activities are in evidence. Stands out a class of antimicrobial, the cephalosporins, having as fourth generation cefepime (CEF) a semi-synthetic product which has activity against various Gram-positive bacteria (e.g. oxacillin resistant Staphylococcus aureus) and Gram-negative (e.g. Pseudomonas aeruginosa) aerobic. There are few studies in the literature regarding the development of microbiological methodologies for the analysis of this antimicrobial, so researches in this area are highly relevant to optimize the analysis of this drug in the industry and ensure the quality of the marketed product. The development of microbiological methods for the analysis of antimicrobials has gained strength in recent years and has been highlighted in relation to physicochemical methods, especially because they make possible to determine the bioactivity of the drug against a microorganism. In this context, the aim of this work was the development and validation of a microbiological method for quantitative analysis of CEF in powder lyophilized for injectable solution by turbidimetric assay. Method: For performing the method, Staphylococcus aureus ATCC 6538 IAL 2082 was used as the test microorganism and the culture medium chosen was the Casoy broth. The test was performed using temperature control (35.0 °C ± 2.0 °C) and incubated for 4 hours in shaker. The readings of the results were made at a wavelength of 530 nm through a spectrophotometer. The turbidimetric microbiological method was validated by determining the following parameters: linearity, precision (repeatability and intermediate precision), accuracy and robustness, according to ICH guidelines. Results and discussion: Among the parameters evaluated for method validation, the linearity showed results suitable for both statistical analyses as the correlation coefficients (r) that went 0.9990 for CEF reference standard and 0.9997 for CEF sample. The precision presented the following values 1.86% (intraday), 0.84% (interday) and 0.71% (between analyst). The accuracy of the method has been proven through the recovery test where the mean value obtained was 99.92%. The robustness was verified by the parameters changing volume of culture medium, brand of culture medium, incubation time in shaker and wavelength. The potency of CEF present in the samples of lyophilized powder for injectable solution was 102.46%. Conclusion: The turbidimetric microbiological method proposed for quantification of CEF in lyophilized powder for solution for injectable showed being fast, linear, precise, accurate and robust, being in accordance with all the requirements, which can be used in routine analysis of quality control in the pharmaceutical industry as an option for microbiological analysis.

Keywords: cefepime hydrochloride, quality control, turbidimetric assay, validation

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Authors: Daniel Assefa, Engeda Dessalegn, Chetan Chauhan

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Moringa stenopetala is a socioeconomic valued tree that is widely available and cultivated in the Southern part of Ethiopia. The leaves have been traditionally used as a food source with high nutritional and medicinal values. The present work was carried out to evaluate the effect of thermal treatment on the total phenolic content, antioxidant and alpha-amylase inhibition activities of aqueous leaf extracts during maceration and different decoction time interval (5, 10 and 15 min). The total phenolic content was determined by the Folin-ciocalteu methods whereas antioxidant activities were determined by 2,2-diphenyl-1-picryl-hydrazyl(DPPH) radical scavenging, reducing power and ferrous ion chelating assays and alpha-amylase inhibition activity was determined using 3,5-dinitrosalicylic acid method. Total phenolic content ranged from 34.35 to 39.47 mgGAE/g. Decoction for 10 min extract showed ferrous ion chelating (92.52), DPPH radical scavenging (91.52%), alpha-amylase inhibition (69.06%) and ferric reducing power (0.765), respectively. DPPH, reducing power and alpha-amylase inhibition activities showed positive linear correlation (R2=0.853, R2= 0.857 and R2=0.930), respectively with total phenolic content but ferrous ion chelating activity was found to be weakly correlated (R2=0.481). Based on the present investigation, it could be concluded that major loss of total phenolic content, antioxidant and alpha-amylase inhibition activities of the crude leaf extracts of Moringa stenopetala leaves were observed at decoction time for 15 min. Therefore, to maintain the total phenolic content, antioxidant, and alpha-amylase inhibition activities of leaves, cooking practice should be at the optimum decoction time (5-10 min).

Keywords: alpha-amylase inhibition, antioxidant, Moringa stenopetala, total phenolic content

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Ravi Patel, Krishna K. Krishnan

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In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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Authors: Intanri Kurniati, Raja Iqbal Mulya Harahap, Agustyas Tjiptaningrum, Reni Zuraida

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Background: Diabetes mellitus is still increasing and has become a health and social burden in the world. It is known that glycation among various proteins is increased in diabetic patients compared with non-diabetic subjects. Some of these glycated proteins are suggested to be involved in the development and progression of chronic diabetic complications. Among these glycated proteins, glycated hemoglobin (HbA1C) is commonly used as the gold standard index of glycemic control in the clinical setting. HbA1C testing has some methods, and the most commonly used is immunoturbidimetry. This research aimed to compare the HbA1c level between immunoturbidimetry and HbA1C level in T2DM patients. Methods: This research involves 77 patients from Abd Muluk Hospital Bandar Lampung; the patient was asked for consent in this research, then underwent phlebotomy to be tested for HbA1C; the sample was then examined for HbA1C with Turbidimetric Inhibition Immunoassay (TINIA) and High-Performance Liquid Chromatography (HPLC) method. Result: Mean± SD of the samples with the TINIA method was 9.2±1,2; meanwhile, the level HbA1C with the HPLC method is 9.6±1,2. The t-test showed no significant difference between the group subjects. (p<0.05). It was proposed that the two methods have high suitability in testing, and both are eligibly used for the patient. Discussion: There was no significant difference among research subjects, indicating that the high conformity of the two methods is suitable to be used for monitoring patients clinically. Conclusion: There is increasing in HbA1C level in a patient with T2DM measured with HPLC and or Turbidimetric Inhibition Immunoassay (TINIA) method, and there were no significant differences among those methods.

Keywords: diabetes mellitus, glycated albumin, HbA1C, HPLC, immunoturbidimetry

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Authors: Lakmali Anthony, Madeline Gillies

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Background: Incisional and ventral hernias are highly prevalent, with primary ventral hernias occurring in approximately 20% of adults and incisional hernias developing in up to 30% of midline abdominal incisions. Recent data from the United States have shown an increasing incidence of elective incisional and ventral hernia repair (IVHR) and emergency repair of complicated hernias. This study examines Australian population trends in IVHR over a two-decade study period. Methods: This retrospective study was performed using procedure data from the Australian Institute of Health and Welfare, and population data from the Australian Bureau of Statistics captured between 2000 and 2021 to calculate incidence rates per 100,000 population by age and sex for selected subcategories of IVHR operations. Trends over time were evaluated using simple linear regression. Results: There were 809,308 IVHR operations performed in Australia during the study period. The cumulative incidence adjusted for the population was 182 per 100,000; this increased by 9.578 per year during the study period (95% CI = 8.431- 10.726, p<.001). IVHR for primary umbilical hernias experienced the most significant increase in population-adjusted incidence, 1.177 per year. (95% CI = 0.654- 1.701, p<.001). Emergency IVHR for incarcerated, obstructed, and strangulated hernias increased by 0.576 per year (95% CI = 0.510 -0.642, p<.001). Only 20.2% of IVHR procedures were performed as day surgery. Conclusions: Australia has seen a significant increase in IVHR operations performed in the last 20 years, particularly those for primary ventral hernias. IVHR for hernias complicated by incarceration, obstruction, and strangulation also increased significantly. The proportion of IVHR operations performed as day surgery is well below the target set by the Royal Australasian College of Surgeons. With the increasing incidence of IVHR operations and an increasing proportion of these being emergent, elective IVHR should be performed as day surgery when it is safe.

Keywords: ventral, incisional, hernia, trends

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Climatic factors are the subject of considerable research, both methodologically and instrumentally. Under the effect of climate change, the approach to climate parameters with precision remains one of the main objectives of the scientific community. This is from the perspective of assessing climate change and its repercussions on humans and the environment. However, many regions of the world suffer from a severe lack of reliable instruments that can make up for this deficit. Alternatively, the use of empirical methods becomes the only way to assess certain parameters that can act as climate indicators. Several scientific methods are used for the evaluation of evapotranspiration which leads to its evaluation either directly at the level of the climatic stations or by empirical methods. All these methods make a point approach and, in no case, allow the spatial variation of this parameter. We, therefore, propose in this paper the use of three sources of information (network of weather stations of Meteo France, World Databases, and Moodis satellite images) to evaluate spatial evapotranspiration (ETP) using the Turc method. This first step will reflect the degree of relevance of the indirect (satellite) methods and their generalization to sites without stations. The spatial variation representation of this parameter using the geographical information system (GIS) accounts for the heterogeneity of the behaviour of this parameter. This heterogeneity is due to the influence of site morphological factors and will make it possible to appreciate the role of certain topographic and hydrological parameters. A phase of predicting the evolution over the medium and long term of evapotranspiration under the effect of climate change by the application of the Intergovernmental Panel on Climate Change (IPCC) scenarios gives a realistic overview as to the contribution of aquatic systems to the scale of the region.

Keywords: climate change, ETP, MODIS, GIEC scenarios

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Authors: Luís Marques, João Rocha, Andreia Fernandes, Maria Moura, Cláudia Caseiro, Filipa Figueiredo, João Nunes

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The implementation of circularity strategies other than recycling, such as reducing the amount of raw material, as well as reusing or sharing existing products, remains marginal. The European Commission announced that the transition towards a more circular economy could lead to the net creation of about 700,000 jobs in Europe by 2030, through additional labour demand from recycling plants, repair services and other circular activities. Efforts to create new circular business models in accordance with completely circular processes, as opposed to linear ones, have increased considerably in recent years. In order to create a societal Circular Economy transition model, it is necessary to include innovative solutions, where startups play a key role. Early-stage startups based on new business models according to circular processes often face difficulties in creating enough impact. The StartUp Zero Program designs a model and approach to increase the flow of startups in the Circular Economy field, focusing on a systemic decision analysis and multi-generational approach, considering Multi-Criteria Decision Analysis to support a decision-making tool, which is also supported by the use of a combination of an Analytical Hierarchy Process and Multi-Attribute Value Theory methods. We define principles, criteria and indicators for evaluating startup prerogatives, quantifying the evaluation process in a unique result. Additionally, this entrepreneurship program spanning 16 months involved more than 2400 young people, from ages 14 to 23, in more than 200 interaction activities.

Keywords: circular economy, entrepreneurship, startups;, multi-criteria decision analysis

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Authors: Arash Jafari, Mehdi Taghaddosi, Azin Parvin

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In the paper, our purpose is to enhance the ability to solve a nonlinear differential equation which is about the motion of an incompressible fluid flow going down of an inclined plane without thermal effect with a simple and innovative approach which we have named it new method. Comparisons are made amongst the Numerical, new method, and HPM methods, and the results reveal that this method is very effective and simple and can be applied to other nonlinear problems. It is noteworthy that there are some valuable advantages in this way of solving differential equations, and also most of the sets of differential equations can be answered in this manner which in the other methods they do not have acceptable solutions up to now. A summary of the excellence of this method in comparison to the other manners is as follows: 1) Differential equations are directly solvable by this method. 2) Without any dimensionless procedure, we can solve equation(s). 3) It is not necessary to convert variables into new ones. According to the afore-mentioned assertions which will be proved in this case study, the process of solving nonlinear equation(s) will be very easy and convenient in comparison to the other methods.

Keywords: viscos fluid, incompressible fluid flow, inclined plane, nonlinear phenomena

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Authors: Balazs Somodi, Balazs Kovesdi

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In the research praxis of civil engineering the statistical evaluation of experimental and numerical investigations is an essential task in order to compare the experimental and numerical resistances of a specific structural problem with the proposed resistances of the standards. However, in the standards and in the international literature there are several different safety factor evaluation methods that can be used to check the necessary safety level (e.g.: 5% quantile level, 2.3% quantile level, 1‰ quantile level, γM partial safety factor, γM* partial safety factor, β reliability index). Moreover, in the international literature different calculation methods could be found even for the same safety factor as well. In the present study the flexural buckling resistance of high strength steel (HSS) welded closed sections are analyzed. The authors investigated the flexural buckling resistances of the analyzed columns by laboratory experiments. In the present study the safety levels of the obtained experimental resistances are calculated based on several safety approaches and compared with the EN 1990. The results of the different safety approaches are compared and evaluated. Based on the evaluation tendencies are identified and the differences between the statistical evaluation methods are explained.

Keywords: flexural buckling, high strength steel, partial safety factor, statistical evaluation

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Authors: Deborah Amas

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Global accreditation standards require Higher Education Institutions to ensure social work students develop self-awareness by reflecting on their personal values and critically evaluating how these influence their thinking for professional practice. The knowledge base indicates there are benefits and vulnerabilities for students when they self-reflect and more needs to be understood about the learning environments that nurture self-awareness. The connection between teaching methods and self-awareness is of interest in this paper which reports findings from an on-line survey with students on BA and MA qualifying social work programs in an English university (n=120). Students were asked about the importance of self-awareness and their experiences of teaching methods for self-reflection. Generally, students thought that self-awareness is of high importance in their education. Students also shared stories that illuminated deeper feelings about the potential risks associated with self-disclosure. The findings indicate that students appreciate safe opportunities for self-reflection, but can be wary of associated assessments or feeling judged. The research supports arguments to qualitatively improve facilitation of self-awareness through the curriculum.

Keywords: reflection, self-awareness, self-reflection, social work education

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Authors: N. Chetty, K. Singh

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In this work, the relationship between the melanin content in a tissue and subsequent absorption of light through that tissue was determined using a digital camera. This technique proved to be simple, cost effective, efficient and reliable. Tissue phantom samples were created using milk and soy sauce to simulate the optical properties of melanin content in human tissue. Increasing the concentration of soy sauce in the milk correlated to an increase in melanin content of an individual. Two methods were employed to measure the light transmitted through the sample. The first was direct measurement of the transmitted intensity using a conventional lux meter. The second method involved correctly calibrating an ordinary digital camera and using image analysis software to calculate the transmitted intensity through the phantom. The results from these methods were then graphically compared to the theoretical relationship between the intensity of transmitted light and the concentration of absorbers in the sample. Conclusions were then drawn about the effectiveness and efficiency of these low cost methods.

Keywords: tissue phantoms, scattering coefficient, albedo, low-cost method

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Authors: Suzanne Zazycki, Bamidele Osamika, Heather Craska, Kaelyn Conaway, Reena Murphy, Stephanie Spence

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Invasive Plant Species (IPS) are an important component of effective preservation and conservation of natural lands management. IPS are non-native plants which can aggressively encroach upon native species and pose a significant threat to the ecology, public health, and social welfare of a community. The presence of IPS in U.S. nature preserves has caused economic costs, which has estimated to exceed $26 billion a year. While different methods have been identified to control IPS, few methods have been recognized for early detection of IPS. This study examined identified methods for early detection of IPS in Hueston Woods State Nature Preserve. Mixed methods research design was adopted in this four-phased study. The first phase entailed data gathering, the phase described the characteristics and qualities of IPS and the importance of early detection (ED). The second phase explored ED methods, Geographic Information Systems (GIS) and Citizen Science were discovered as ED methods for IPS. The third phase of the study involved the creation of hotspot maps to identify likely areas for IPS growth. While the fourth phase involved testing and evaluating mobile applications that can support the efforts of citizen scientists in IPS detection. Literature reviews were conducted on IPS and ED methods, and four regional experts from ODNR and Miami University were interviewed. A questionnaire was used to gather information about ED methods used across the state. The findings revealed that geospatial methods, including Unmanned Aerial Vehicles (UAVs), Multispectral Satellites (MSS), and Normalized Difference Vegetation Index (NDVI), are not feasible for early detection of IPS, as they require GIS expertise, are still an emerging technology, and are not suitable for every habitat for the ED of IPS. Therefore, Other ED methods options were explored, which include predicting areas where IPS will grow, which can be done through monitoring areas that are like the species’ native habitat. Through literature review and interviews, IPS are known to grow in frequently disturbed areas such as along trails, shorelines, and streambanks. The research team called these areas “hotspots” and created maps of these hotspots specifically for HW NP to support and narrow the efforts of citizen scientists and staff in the ED of IPS. The results further showed that utilizing citizen scientists in the ED of IPS is feasible, especially through single day events or passive monitoring challenges. The study concluded that the creation of hotspot maps to direct the efforts of citizen scientists are effective for the early detection of IPS. Several recommendations were made, among which is the creation of hotspot maps to narrow the ED efforts as citizen scientists continues to work in the preserves and utilize citizen science volunteers to identify and record emerging IPS.

Keywords: early detection, hueston woods state nature preserve, invasive plant species, hotspots

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Authors: Emily Hickmann, Peggy Richter, Maren Kaehlig, Hannes Schlieter

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Patient engagement is a cornerstone of high-quality care and essential for patients with chronic diseases to achieve improved health outcomes. Through digital transformation, possibilities to engage patients in their personal healthcare have multiplied. However, the exploitation of this potential is still lagging. To support the transmission of patient engagement theory into practice, this paper’s objective is to give a state-of-the-art overview of patient engagement tools and methods. A systematic literature review was conducted. Overall, 56 tools and methods were extracted and synthesized according to the four attributes of patient engagement, i.e., personalization, access, commitment, and therapeutic alliance. The results are discussed in terms of their potential to be implemented in digital health solutions under consideration of the “computers are social actors” (CASA) paradigm. It is concluded that digital health can catalyze patient engagement in practice, and a broad future research agenda is formulated.

Keywords: chronic diseases, digitalization, patient-centeredness, patient empowerment, patient engagement

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Authors: S. Cencek, A. Markun

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Noise assessment methods are regularly used in scope of Environmental Impact Assessments for planned projects to assess (predict) the expected noise emissions of these projects. Different noise assessment methods could be used. In recent years, we had an opportunity to collaborate in some noise assessment procedures where noise assessments of different laboratories have been performed simultaneously. We identified some significant differences in noise assessment results between laboratories in Slovenia. We estimate that despite good input Georeferenced Data to set up acoustic model exists in Slovenia; there is no clear consensus on methods for predictive noise methods for planned projects. We analyzed input data, methods and results of predictive noise methods for two planned industrial projects, both were done independently by two laboratories. We also analyzed the data, methods and results of two interlaboratory collaborative noise models for two existing noise sources (railway and motorway). In cases of predictive noise modelling, the validations of acoustic models were performed by noise measurements of surrounding existing noise sources, but in varying durations. The acoustic characteristics of existing buildings were also not described identically. The planned noise sources were described and digitized differently. Differences in noise assessment results between different laboratories have ranged up to 10 dBA, which considerably exceeds the acceptable uncertainty ranged between 3 to 6 dBA. Contrary to predictive noise modelling, in cases of collaborative noise modelling for two existing noise sources the possibility to perform the validation noise measurements of existing noise sources greatly increased the comparability of noise modelling results. In both cases of collaborative noise modelling for existing motorway and railway, the modelling results of different laboratories were comparable. Differences in noise modeling results between different laboratories were below 5 dBA, which was acceptable uncertainty set up by interlaboratory noise modelling organizer. The lessons learned from the study were: 1) Predictive noise calculation using formulae from International standard SIST ISO 9613-2: 1997 is not an appropriate method to predict noise emissions of planned projects since due to complexity of procedure they are not used strictly, 2) The noise measurements are important tools to minimize noise assessment errors of planned projects and should be in cases of predictive noise modelling performed at least for validation of acoustic model, 3) National guidelines should be made on the appropriate data, methods, noise source digitalization, validation of acoustic model etc. in order to unify the predictive noise models and their results in scope of Environmental Impact Assessments for planned projects.

Keywords: environmental noise assessment, predictive noise modelling, spatial planning, noise measurements, national guidelines

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Authors: Chidiebere Samuel Ijeoma

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The impact and importance of technology in all domains of existence cannot be overemphasized. It is like a double-edged sword which can be both constructive and destructive. The paper, therefore, tends to evaluate the impact of technology so far in the teaching and learning of French language in Nigeria. According to the study, the traditional methods of teaching French as a Foreign Language and recognized as our cultural methods of knowledge transfer are being fast replaced by digitalization in teaching. This, the research tends to portray and suggest the best way forward. In the Nigerian Primary Education System, the use of some local and cultural Instructional materials (teaching aids) is now almost history which the paper frowns at. Consequently, the study has these questions to ask?; Where are the chalks and blackboards? Where are the ‘Handworks’ (local brooms) submitted by school children as part of their Continuous Assessment? Finally, the research is in no way against the application of technology in the Nigerian French Language Teaching System but tries to draw a curtain between Technological methods of teaching French as a Foreign Language and the Original Nigerian System of teaching the language before the arrival of technology.

Keywords: French language teaching, future, impact, importance of technology

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Authors: Mozhdeh Khalili Kordabadi

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. By adopting these strategies, the textile industry can contribute to a more sustainable and environmentally friendly future. Introduction: Textiles, particularly clothing, are essential to human existence. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion: The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension.

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