Search results for: subjective bias detection

Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

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To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved.

Keywords: thermal expansion error of grating scale, error compensation, machine tools, integral method

Procedia PDF Downloads 363

Authors: Leila Sadeghi

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Gender equality is a critical concern in the workplace, particularly in Iran, where legal and social barriers contribute to significant disparities. This abstract presents a case study of Dahi Bondad Co., a company based in Tehran, Iran that recognized the urgency of addressing the gender gap within its organization. Through a comprehensive investigation, the company identified issues related to biased recruitment, pay disparities, promotion biases, internal barriers, and everyday boundaries. This abstract highlights the strategies implemented by Dahi Bondad Co. to combat these challenges and foster gender equality. The company revised its recruitment policies, eliminated gender-specific language in job advertisements, and implemented blind resume screening to ensure equal opportunities for all applicants. Comprehensive pay equity analyses were conducted, leading to salary adjustments based on qualifications and experience to rectify pay disparities. Clear and transparent promotion criteria were established, and training programs were provided to decision-makers to raise awareness about unconscious biases. Additionally, mentorship and coaching programs were introduced to support female employees in overcoming self-limiting beliefs and imposter syndrome. At the same time, practical workshops and gamification techniques were employed to boost confidence and encourage women to step out of their comfort zones. The company also recognized the importance of dress codes and allowed optional hijab-wearing, respecting local traditions while promoting individual freedom. As a result of these strategies, Dahi Bondad Co. successfully fostered a more equitable and empowering work environment, leading to increased job satisfaction for both male and female employees within a short timeframe. This case study serves as an example of practical approaches that human resource managers can adopt to address gender inequality in the workplace, providing valuable insights for organizations seeking to promote gender equality in similar contexts.

Keywords: gender equality, human resource strategies, legal barrier, social barrier, successful result, successful strategies, workplace in Iran

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Authors: Mark Morgan, Christine Li, Shuangyu Xu, Jenny McCarty

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The National Wild and Scenic Rivers System was created by the U.S. Congress in 1968 (Public Law 90-542; 16 U.S.C. 1271 et seq.) to preserve outstanding natural, cultural, and recreational values of some U.S. rivers in a free-flowing condition for the enjoyment of present and future generations. This Act is notable for safeguarding the special character of these rivers while supporting management action that encourages public participation for co-creating river protection goals and strategies. This is not an easy task. To meet the challenges of modern ecosystem management, federal resource agencies must address many legal, environmental, economic, political, and social issues. The U.S. Forest Service manages a 44-mile section of the Eleven Point National Scenic River (EPR) in southern Missouri, mainly for outdoor recreation purposes. About half of the acreage is in private lands, while the remainder flows through the Mark Twain National Forest. Private land along the river is managed by scenic easements to ensure protection of scenic values and natural resources, without public access. A portion of the EPR lies adjacent to a 16,500-acre tract known as the Irish Wilderness. The spring-fed river has steep bluffs, deep pools, clear water, and a slow current, making it an ideal setting for outdoor enthusiasts. A 10-month visitor study was conducted at five access points along the EPR during 2019 so the US Forest Service could update their river management plan. A mail-back survey was administered to 560 on-site visitors, yielding a response rate of 53%. Although different types of visitors use the EPR, boating and fishing were the predominant forms of outdoor recreation. Some river use was from locals, but other visitors came from farther away. Formulating unbiased policies for outdoor recreation is difficult because managers must assign relative values to recreational activities and travel distance. Because policymaking is a subjective process, management decisions can affect user groups in different ways (i.e., boaters vs. fishers; proximate vs. distal visitors), as seen through a GIS analysis.

Keywords: activity selection, forest recreation, policy, travel distance

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Authors: Huy Q. Tran, Jungwon Huh, Kiseok Kwak, Choonghyun Kang

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Infrared thermography (IRT) technique has been proven to be a good method for nondestructive evaluation of concrete material. In the building, a broad range of applications has been used such as subsurface defect inspection, energy loss, and moisture detection. The purpose of this research is to consider the qualitative and quantitative performance of reinforced concrete deteriorations using active infrared thermography technique. An experiment of three different heating regimes was conducted on a concrete slab in the laboratory. The thermal characteristics of the IRT method, i.e., absolute contrast and observation time, are investigated. A linear relationship between the observation time and the real depth was established with a well linear regression R-squared of 0.931. The results showed that the absolute contrast above defective area increases with the rise of the size of delamination and the heating time. In addition, the depth of delamination can be predicted by using the proposal relationship of this study.

Keywords: concrete building, infrared thermography, nondestructive evaluation, subsurface delamination

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Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing

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Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

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As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

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Authors: Isalira Peroba Ramos, Cherley Borba Vieira de Andrade, Grazielle Suhett, Camila Salata, Paulo Cesar Canary, Guilherme Visconde Brasil, Antonio Carlos Campos de Carvalho, Regina Coeli dos Santos Goldenberg

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Background: The therapeutic options for patients with cancer now include increasingly complex combinations of medications, radiation therapy (RT), and surgical intervention. Many of these treatments have important potential adverse cardiac effects and are likely to have significant effects on patient outcomes. Cell therapy appears to be promising for the treatment of chronic and degenerative diseases, including cardiomyopathy induced by RT, as the current therapeutic options are insufficient. Aims: To evaluate the potential of bone marrow mesenchymal cells (BMMCs) in radioinduced cardiac damage Methods: Female Wistar rats, 3 months old (Ethics Committee 054/14), were divided into 2 groups, non-treated irradiated group (IR n=15) and irradiated and BMMC treated (IRT n=10). Echocardiography was performed to evaluate heart function. After euthanasia, 3 months post treatment; the left ventricle was removed and prepared for RT-qPCR (VEGF and Pro Collagen I) and histological (picrosirius) analysis. Results: In both groups, 45 days after irradiation, ejection fraction (EF) was in the normal range for these animals (> 70%). However, the BMMC treated group had EF (83.1%±2.6) while the non-treated IR group showed a significant reduction (76.1%±2.6) in relation to the treated group. In addition, we observed an increase in VEGF gene expression and a decrease in Pro Collagen I in IRT when compared to IR group. We also observed by histology that the collagen deposition was reduced in IRT (10.26%±0.83) when compared to IR group (25.29%±0.96). Conclusions: Treatment with BMMCs was able to prevent ejection fraction reduction and collagen deposition in irradiated animals. The increase of VEGF and the decrease of pro collagen I gene expression might explain, at least in part, the cell therapy benefits. All authors disclose no financial or personal relationships with individuals or organizations that could be perceived to bias their work. Sources of funding: FAPERJ, CAPES, CNPq, MCT.

Keywords: mesenchymal cells, radioation, cardiotoxicity, bone marrow

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Jijun Shi, Lichen Sun, Jianchao Zhao, Lizhi Sun, Enjun Liu, Chongwu Guo

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Because of the consistency of pressure direction, more short cycle, and high sensitivity, Charging-Vacuum helium mass spectrometer leak testing technology is the most popular leak testing technology for the seal testing of the spacecraft parts, especially the small and medium size ones. Usually, auxiliary pump was used, and the minimum detectable leak rate could reach 5E-9Pa•m3/s, even better on certain occasions. Relative error is more important when evaluating the results. How to choose the reference leak, the background level of helium, and record formats would affect the leak rate tested. In the linearity range of leak testing system, it would reduce 10% relative error if the reference leak with larger leak rate was used, and the relative error would reduce obviously if the background of helium was low efficiently, the record format of decimal was used, and the more stable data were recorded.

Keywords: leak testing, spacecraft parts, relative error, error control

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

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Authors: Umberto Cerasani, Luca Cerasani

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Methods for earthquakes forecasting have been intensively investigated in the last decades, but there is still no universal solution agreed by seismologists. Rock failure is most often preceded by a tiny elastic movement in the failure area and by the appearance of micro-cracks. These micro-cracks could be detected at the soil surface and represent useful earth-quakes precursors. The aim of this study was to verify whether tiny raw acceleration signals (in the 10⁻¹ to 10⁻⁴ cm/s² range) prior to the arrival of main primary-waves could be exploitable and related to earthquakes magnitude. Mathematical tools such as Fast Fourier Transform (FFT), moving average and wavelets have been applied on raw acceleration data available on the ITACA web site, and the study focused on one of the most unpredictable earth-quakes, i.e., the August 24th, 2016 at 01H36 one that occurred in the central Italy area. It appeared that these tiny acceleration signals preceding main P-waves have different patterns both on frequency and time domains for high magnitude earthquakes compared to lower ones.

Keywords: earthquake, accelerometer, earthquake forecasting, seism

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid

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Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.

Keywords: WSN, routing, cluster based, meme, memetic algorithm

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Authors: Ali N. Siyal, Saima Q. Memon, Latif Elçi, Aydan Elçi

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Polystyrene (PS) was extracted from Styrofoam (expanded polystyrene foam) waste, so called white pollutant. The PS was functionalized with N, N- Bis(2-aminobenzylidene)benzene-1,2-diamine (ABA) ligand through an azo spacer. The resin was characterized by FT-IR spectroscopy and elemental analysis. The PS-N=N-ABA resin was used for the enrichment and speciation of Cr(III)/Cr(VI) ions and total Cr determination in aqueous samples by Flame Atomic Absorption Spectrometry (FAAS). The separation of Cr(III)/Cr(VI) ions was achieved at pH 2. The recovery of Cr(VI) ions was achieved ≥ 95.0% at optimum parameters: pH 2; resin amount 300 mg; flow rates 2.0 mL min-1 of solution and 2.0 mL min-1 of eluent (2.0 mol L-1 HNO3). Total Cr was determined by oxidation of Cr(III) to Cr(VI) ions using H2O2. The limit of detection (LOD) and quantification (LOQ) of Cr(VI) were found to be 0.40 and 1.20 μg L-1, respectively with preconcentration factor of 250. Total saturation and breakthrough capacitates of the resin for Cr(IV) ions were found to be 0.181 and 0.531 mmol g-1, respectively. The proposed method was successfully applied for the preconcentration/speciation of Cr(III)/Cr(VI) ions and determination of total Cr in industrial effluents.

Keywords: styrofoam waste, polymeric resin, preconcentration, speciation, Cr(III)/Cr(VI) ions, FAAS

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Authors: C. Brandt, R. Christopher, N. Damons

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Background: Soccer is one of the most common sports in the world. It is associated with a significant chance of injury either during training or during the course of an actual match. Studies on the epidemiology of soccer injuries have been widely conducted, but methodological appraisal is lacking to make evidence-based decisions. Objectives: The purpose of this study was to conduct a systematic review of common injuries in soccer and their risk factors. Methods: A systematic review was performed based on the Joanna Briggs Institute procedure for conducting systematic reviews. Databases such as SPORT Discus, Cinahl, Medline, Science Direct, PubMed, and grey literature were searched. The quality of selected studies was rated, and data extracted and tabulated. Plot data analysis was done, and incidence rates and odds ratios were calculated, with their respective 95% confidence intervals. I² statistic was used to determine the proportion of variation across studies. Results: The search yielded 62 studies, of which 21 were screened for inclusion. A total of 16 studies were included for the analysis, ten for qualitative and six for quantitative analysis. The included studies had, on average, a low risk of bias and good methodological quality. The heterogeneity amongst the pooled studies was, however, statistically significant (χ²-p value < 0.001). The pooled results indicated a high incidence of soccer injuries at an incidence rate of 6.83 per 1000 hours of play. The pooled results also showed significant evidence of risk factors and the likelihood of injury occurrence in relation to these risk factors (OR=1.12 95% CI 1.07; 1.17). Conclusion: Although multiple studies are available on the epidemiology of soccer injuries and risk factors, only a limited number of studies were of sound methodology to be included in a review. There was also significant heterogeneity amongst the studies. The incidence rate of common soccer injuries was found to be 6.83 per 1000 hours of play. This incidence rate is lower than the values reported by the majority of previous studies on the occurrence of common soccer injuries. The types of common soccer injuries found by this review support the soccer injuries pattern reported in existing literature as muscle strain and ligament sprain of varying severity, especially in the lower limbs. The risk factors that emerged from this systematic review are predominantly intrinsic risk factors. The risk factors increase the risk of traumatic and overuse injuries of the lower extremities such as hamstrings and groin strains, knee and ankle sprains, and contusion.

Keywords: incidence, prevalence, risk factors, soccer injuries

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Authors: Taru Singh, Shukla Das, V. G. Ramachandran

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Objectives: To develop SYBR green based real-time PCR assay to detect carbapenemases (NDM, IMP) genes in E. coli. Methods: A total of 40 E. coli from stool samples were tested. Six were previously characterized as resistant to carbapenems and documented by PCR. The remaining 34 isolates previously tested susceptible to carbapenems and were negative for these genes. Bacterial RNA was extracted using manual method. The real-time PCR was performed using the Light Cycler III 480 instrument (Roche) and specific primers for each carbapenemase target were used. Results: Each one of the two carbapenemase gene tested presented a different melting curve after PCR amplification. The melting temperature (Tm) analysis of the amplicons identified was as follows: blaIMP type (Tm 82.18°C), blaNDM-1 (Tm 78.8°C). No amplification was detected among the negative samples. The results showed 100% concordance with the genotypes previously identified. Conclusions: The new assay was able to detect the presence of two different carbapenemase gene type by real-time PCR.

Keywords: resistance, b-lactamases, E. coli, real-time PCR

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Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

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Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

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Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

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Authors: Neelamshobha Nirala, R. Periyasamy, Awanish Kumar

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Diabetes is a metabolic disorder and with the increase of global prevalence of diabetes, cardiovascular diseases and mortality related to diabetes has also increased. Diabetes causes the increase of arterial stiffness by elusive hormonal and metabolic abnormalities. We used photoplethysmograph (PPG), a simple non-invasive method to study the change in arterial stiffness due to diabetes. Toe PPG signals were taken from 29 diabetic subjects with mean age of (65±8.4) years and 21 non-diabetic subjects of mean age of (49±14) years. Mean duration of diabetes is 12±8 years for diabetic group. Rise-time (RT) and area under rise time (AUR) were calculated from the PPG signal of each subject and Welch’s t-test is used to find the significant difference between two groups. We obtained a significant difference of (p-value) 0.0005 and 0.03 for RT and AUR respectively between diabetic and non-diabetic subjects. Average value of RT and AUR is 0.298±0.003 msec and 14.4±4.2 arbitrary units respectively for diabetic subject compared to 0.277±0.0005 msec and 13.66±2.3 a.u respectively for non-diabetic subjects. In conclusion, this study support that arterial stiffness is increased in diabetes and can be detected early using PPG.

Keywords: area under rise-time, AUR, arterial stiffness, diabetes, photoplethysmograph, PPG, rise-time (RT)

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Authors: P. S. Surya Meghana, K. Lingeshwaran, C. Kannan, V. Raghavendran, C. Priya

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One of the most basic and powerful tools in all of science and medicine is the light microscope, the fundamental device for laboratory as well as research purposes. With the improving technology, the need for portable, economic and user-friendly instruments is in high demand. The conventional microscope fails to live up to the emerging trend. Also, adequate access to healthcare is not widely available, especially in developing countries. The most basic step towards the curing of a malady is the diagnosis of the disease itself. The main aim of this paper is to diagnose Malaria with the most common device, cell phones, which prove to be the immediate solution for most of the modern day needs with the development of wireless infrastructure allowing to compute and communicate on the move. This opened up the opportunity to develop novel imaging, sensing, and diagnostics platforms using mobile phones as an underlying platform to address the global demand for accurate, sensitive, cost-effective, and field-portable measurement devices for use in remote and resource-limited settings around the world.

Keywords: cellular, hand-held, health care, image processing, malarial parasites, microscope

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Authors: T. Nishimura, K. Doi, H. Fujimoto, T. Wada

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The Number of people with acquired visual impairments has increased in recent years. In specialized courses at schools for the blind and in Braille lessons offered by social welfare organizations, many people with acquired visual impairments cannot learn to read adequately Braille. One of the reasons is that the common Braille patterns for people visual impairments who already has mature Braille reading skill being difficult to read for Braille reading beginners. In addition, there is the scanty knowledge of Braille book manufacturing companies regarding what Braille patterns would be easy to read for beginners. Therefore, it is required to investigate a suitable Braille patterns would be easy to read for beginners. In order to obtain knowledge regarding suitable Braille patterns for beginners, this study aimed to elucidate the relationship between readability of paper-based Braille and its patterns. This study focused on character spacing, which readily affects Braille reading ability, to determine a suitable character spacing ratio (ratio of character spacing to dot spacing) for beginners. Specifically, considering beginners with acquired visual impairments who are unfamiliar with reading Braille, we quantitatively evaluated the effect of character spacing ratio on Braille readability through an evaluation experiment using sighted subjects with no experience of reading Braille. In this experiment, ten sighted adults took the blindfold were asked to read test piece (three Braille characters). Braille used as test piece was composed of five dots. They were asked to touch the Braille by sliding their forefinger on the test piece immediately after the test examiner gave a signal to start the experiment. Then, they were required to release their forefinger from the test piece when they perceived the Braille characters. Seven conditions depended on character spacing ratio was held (i.e., 1.2, 1.4, 1.5, 1.6, 1.8, 2.0, 2.2 [mm]), and the other four depended on the dot spacing (i.e., 2.0, 2.5, 3.0, 3.5 [mm]). Ten trials were conducted for each conditions. The test pieces are created using by NISE Graphic could print Braille adjusted arbitrary value of character spacing and dot spacing with high accuracy. We adopted the evaluation indices for correct rate, reading time, and subjective readability to investigate how the character spacing ratio affects Braille readability. The results showed that Braille reading beginners could read Braille accurately and quickly, when character spacing ratio is more than 1.8 and dot spacing is more than 3.0 mm. Furthermore, it is difficult to read Braille accurately and quickly for beginners, when both character spacing and dot spacing are small. For this study, suitable character spacing ratio to make reading easy for Braille beginners is revealed.

Keywords: Braille, character spacing, people with visual impairments, readability

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Authors: Irma Wani Othman

Abstract:

The internationalization of higher education in Malaysia mainly focuses to place the implementation of the strategic, comprehensive and integrated range of stakeholders in order to highlight the visibility of Malaysia as a hub of academic excellence. While the concept of 'global citizenship' is used as a two-pronged strategy of aggressive marketing by universities which includes; (i) the involvement of the academic expatriates in stimulating international activities of higher education and (ii) an increase in international student enrollment capacity for the enculturation of science and the development of first class mentality. In this aspect, aspirations for a transnational social movement through global citizenship status to establish the identity of the university community without borders (borderless universities) - regardless of skin colour, thus rationalize and liberalize the universal principles of life and cultural traditions of a nation. The education system earlier referred by the spirit of nationalism is now progressing due to globalization, hence forming a system of higher education that is relevant and generated by the need of all time. However, debates arose when the involvement of global citizenship is said to threaten the ultimate university autonomy in determining the direction of academic affairs and governance of their human resources. Stemming from this debate, this study aims to explore the experience of 'global citizenship' that the academic expatriates and international students in shaping the university's strategic needs and interests which are in line with the transition of contemporary higher education. The objective of this study is to examine the acculturation experience of the global citizen in the form of transnational higher education system and suggest policy and policing IHE which refers directly to the experience of the global citizen. This study offers a detailed understanding of how the university communities assess their expatriation experience, thus becoming useful information for learning and transforming education. The findings also open an advanced perspective on the international mobility of human resources and the implications on the implementation of the policy of internationalization of higher education. The contribution of this study is expected to give new input, thus shift the focus of contextual literature for the internationalization of the education system. Instead of focusing on the purpose of generating income of a university, to a greater understanding of subjective experience in utilizing international human resources hence contributing to the prominent transnational character of higher education.

Keywords: internationalization, global citizens, Malaysia higher education, academic expatriate, international students

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Authors: Morello Sara, Pederiva Sabina, Bianchi Manila, Martucci Francesca, Marchis Daniela, Decastelli Lucia

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Vegetables represent an integral part of a healthy diet due to their valuable nutritional properties and the growth in consumer demand in recent years is particularly remarkable for a diet rich in vitamins and micronutrients. However, plant-based products are involved in several food outbreaks connected to various sources of contamination and quite often, bacteria responsible for side effects showed high resistance to antibiotics. The abuse of antibiotics can be one of the main mechanisms responsible for increasing antibiotic resistance (AR). Plants grown for food use can be contaminated directly by spraying antibiotics on crops or indirectly by treatments with antibiotics due to the use of manure, which may contain both antibiotics and genes of antibiotic resistance (ARG). Antibiotic residues could represent a potential way of human health risk due to exposure through the consumption of plant-based foods. The presence of antibiotic-resistant bacteria might pose a particular risk to consumers. The present work aims to investigate through a multidisciplinary approach the occurrence of ARG by means of a biomolecular approach (PCR) and the prevalence of antibiotic residues using a multi residues LC-MS/MS method, both in different plant-based products. During the period from July 2020 to October 2021, a total of 74 plant samples (33 lettuces and 41 tomatoes) were collected from 57 farms located throughout the Piedmont area, and18 out of 74 samples (11 lettuces and 7 tomatoes) were selected to LC-MS/MS analyses. DNA extracted (ExtractME, Blirt, Poland) from plants used on crops and isolated bacteria were analyzed with 6 sets of end-point multiplex PCR (Qiagen, Germany) to detect the presence of resistance genes of the main antibiotic families, such as tet genes (tetracyclines), bla (β-lactams) and mcr (colistin). Simultaneous detection of 43 molecules of antibiotics belonging to 10 different classes (tetracyclines, sulphonamides, quinolones, penicillins, amphenicols, macrolides, pleuromotilines, lincosamides, diaminopyrimidines) was performed using Exion LC system AB SCIEX coupled to a triple quadrupole mass spectrometer QTRAP 5500 from AB SCIEX. The PCR assays showed the presence of ARG in 57% (n=42): tetB (4.8%; n=2), tetA (9.5%; n=4), tetE (2.4%; n=1), tetL (12%; n=5), tetM (26%; n=11), blaSHV (21.5%; n=9), blaTEM (4.8%; n =2) and blaCTX-M (19%; n=8). In none of the analyzed samples was the mcr gene responsible for colistin resistance detected. Results obtained from LC-MS/MS analyses showed that none of the tested antibiotics appear to exceed the LOQ (100 ppb). Data obtained confirmed the presence of bacterial populations containing antibiotic resistance determinants such as tet gene (tetracycline) and bla genes (beta-lactams), widely used in human medicine, which can join the food chain and represent a risk for consumers, especially with raw products. The presence of traces of antibiotic residues in vegetables, in concentration below the LOQ of the LC-MS/MS method applied, cannot be excluded. In conclusion, traces of antibiotic residues could be a health risk to the consumer due to potential involvement in the spread of AR. PCR represents a useful and effective approach to characterize and monitor AR carried by bacteria from the entire food chain.

Keywords: plant-based products, ARG, PCR, antibiotic residues

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Authors: Raghuveer Kaur, Kartikay Sharma, Ashu Khanna

Abstract:

Earnings management has been present from times immemorial. The recent downfall of giant enterprises like Enron, Satyam and WorldCom has brought a lot of focus on the study and detection of earnings management. The present study is an attempt to study earnings management in one of the fastest emerging economy - India. The study makes an attempt to understand earnings management in different sectors of the economy. The paper first tests a hypothesis to check whether different sectors of India are engaged in earnings management or not. In the later section the paper aims to study the level of earnings management in 6 popular sectors of India: IT&BPO, Retail, Telecom, Biotech, Hotels and coffee. To measure earnings management two popular techniques of detecting earnings management has been employed: Modified Jones Model and Beniesh M Score. A total of 332 companies were studied. Publicly available data from Capitaline database has been used. The paper also classifies the top and bottom five performers on the basis of sales turnover in each sector and identifies whether they manage their earnings or not.

Keywords: earnings management, India, modified Jones model, Beneish M score

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Authors: Alina Beraudi, Simona Catalani, Dalila De Pasquale, Eva Bianconi, Umberto Santoro, Susanna Stea, Pietro Apostoli

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Recently the European Community, in line with the international scientific community such as with the Consensus Statement, has determined to stop the use of metal-on-metal big head stemmed hip prosthesis. Among the factors accounted as responsible for the high failure rates of these hip implants are the release and accumulation of metal ions. Many studies have correlated the presence of these ions, besides other factors, with the induction of oxidative stress response. In our study on 12 subjects, we observed the patient specific capability to eliminate metal ions after revision surgery. While for cobalt all the patients were able to completely excrete cobalt ions within 5-7 months after metal-on-metal bearing removal, for chromium ions it didn’t happen. If on the one hand the toxicokinetic differences between the two types of ions are confirmed by toxicological and occupational studies, on the other hand, this peculiar way of exposition represents a novel and important point of view. Thus, two different approaches were performed to better understand the subject specific capability to transport metal ions (albumin study) and to manage the response to them (heme-oxygenase-1 study): - a mutational screening of ALBUMIN gene was conducted in 30 MoM prosthetic patients resulting in the absence of nucleotidic changes compared with the ALB reference sequence. To this study was also added the analysis of expression of modified albumin protein; - a gene and protein expression study on 44 patients of heme-oxygenase-1, that is one of the most important antioxidant enzyme induced by metallic ions, was performed. This study resulted in no statistically significant differences in the expression of the gene and protein heme-oxygenase-1 between prosthetic and non-prosthetic patients, as well as between patients with high and low ions levels. Our results show that the protein studied (albumin and heme-oxygenase-1) seem to be not involved in determining chromium and cobalt ions level. On the other hand, achromium and cobalt elimination rates are different, but similar in all patients analyzed, suggesting that this process could be not patient-related. We support the importance of researching more about ions transport within the organism once released by hip prosthesis, about the chemical species involved, the districts where they are contained and the mechanisms of elimination, not excluding the existence of a subjective susceptibility to these metals ions.

Keywords: chromium, cobalt, hip prosthesis, individual susceptibility

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

Abstract:

Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: Jyun-Guo You, Wei-Lung Tseng

Abstract:

Herein, this study represents a synthetic route for producing highly luminescent AuNCs based on the integration of two concepts, including thiol-induced luminescence enhancement of ligand-insufficient GSH-AuNCs and Ce3+-induced aggregation of GSH-AuNCs. The synthesis of GSH-AuNCs was conducted by modifying the previously reported procedure. To produce more Au(I)-GSH complexes on the surface of ligand-insufficient GSH-AuNCs, the extra GSH is added to attach onto the AuNC surface. The formed ligand-sufficient GSH-AuNCs (LS-GSH-AuNCs) emit relatively strong luminescence. The luminescence of LS-GSH-AuNCs is further enhanced by the coordination of two carboxylic groups (pKa1 = 2 and pKa2 = 3.5) of GSH and lanthanide ions, which induce the self-assembly of LS-GSH-AuNCs. As a result, the quantum yield of the self-assembled LS-GSH-AuNCs (SA-AuNCs) was improved to be 13%. Interestingly, the SA-AuNCs were dissembled into LS-GSH-AuNCs in the presence of adenosine triphosphate (ATP) because of the formation of the ATP- lanthanide ion complexes. Our assay was employed to detect alkaline phosphatase (ALP) activity over the range of 0.1−10 U/mL with a limit of detection (LOD) of 0.03 U/mL.

Keywords: self-assembly, lanthanide ion, adenosine triphosphate, alkaline phosphatase

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