• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.91-100
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• 2021

Educational institutions play a critical role in national development through the advancement of skilled human resources and intellectual society. The number of higher educational institutions (HEIs) is increasing significantly in Bangladesh. Students have a number of options from which to select their preferred educational institutions. Hence, HEIs should think about the quality of services they provide to students. The objective of this study is to measure students' satisfaction and university reputation through service quality (SQ) in a private higher educational institution (PriHEI) in Bangladesh. Primary data was collected from 270 students of International Islamic University Chittagong (IIUC), Bangladesh, through a simple random sampling technique. In this study, data was analyzed through descriptive statistics, correlation, measurement model using confirmatory factor analyses, and structural equation modeling (SEM). The results showed that transport services have indirect but medical and physical facilities have both direct and indirect significant effects on overall students' satisfaction. Further, the administrative services and research facilities have significant indirect effects on overall students' satisfaction. Finally, the results of structural equation modeling (SEM) confirm that the reputation of the university is directly associated with overall students' satisfaction.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.895-904
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• 2021

This study aims to investigate the impact of innovation on firm efficiency. Panel data of fourteen finance companies and nine technology companies from 2011 to 2019 on the Vietnam Stock Exchange Market is derived from audited financial statements, annual reports, and other crucial reports that are provided by Vietstock; macroeconomic variables are collected from the World Bank Database. A two-stage approach is used. First, use of the Data Envelopment Analysis methodology to measure firm efficiency. Second, use of the Pooled ordinary least squares, the Fixed effects model, and the Random effects model to investigate the impact of innovation on firm efficiency. Furthermore, the Generalized Method of Moments and the Tobit model are used to validate the impact of innovation on firm efficiency, and the t-test is used to confirm the difference in efficiency with and without the impact of innovation between two industries. The results show that there is a significant impact of innovation on efficiency, and innovation plays a more important in increasing the efficiency of the finance industry than the technology industry. Moreover, the relation between age and efficiency is like the U-shaped, and between size and efficiency is like the inverted U-shaped, whereas efficiency is not associated with inflation.

• Journal of the Korean Applied Science and Technology
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• v.37 no.6
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• pp.1475-1488
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• 2020

This is a quasi-experimental study with one-group pretest-posttest design to investigate the effect of dementia club activities on college life satisfaction, dementia knowledge, and dementia attitude in nursing students. The subjects were 26 nursing students who participated in club activities for more than three hours per a week. The college life satisfaction was measured using School Life Satisfaction Scale and dementia knowledge was measuring using Questionnaire for Awareness of Dementia used in dementia prevalence survey. Dementia Attitude Scale (DAS) was used to measure dementia attitude. The tests were performed before and after club activity, and collected data were analyzed using descriptive statistics and paired sample t-test. The results showed that the scores of college life satisfaction (t=-2.38, p= .025), dementia knowledge (t=-5.56, p< .001), dementia attitude social comfort that evaluate emotion, behavior, and awareness about dementia (t=-4.50, p< .001), dementia attitude dementia knowledge (t=-2.59, p= .016), and dementia attitude total score (t=-4.20, p< .001) increased statistically significantly after club activity. It is concluded, based on the results, that the club activities in college improve college life satisfaction, dementia knowledge, and dementia attitude thus provide contribute to caring for patients with dementia. The replication studies with larger random samples, however, are necessary to confirm the findings obtained from this study.

• Geomechanics and Engineering
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• v.30 no.3
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• pp.247-258
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• 2022

A field velocity resistivity probe (FVRP) can measure compressional waves, shear waves and electrical resistivity in boreholes. The objective of this study is to perform the soil classification through a machine learning technique through elastic wave velocity and electrical resistivity measured by FVRP. Field and laboratory tests are performed, and the measured values are used as input variables to classify silt sand, sand, silty clay, and clay-sand mixture layers. The accuracy of k-nearest neighbors (KNN), naive Bayes (NB), random forest (RF), and support vector machine (SVM), selected to perform classification and optimize the hyperparameters, is evaluated. The accuracies are calculated as 0.76, 0.91, 0.94, and 0.88 for KNN, NB, RF, and SVM algorithms, respectively. To increase the amount of data at each soil layer, the synthetic minority oversampling technique (SMOTE) and conditional tabular generative adversarial network (CTGAN) are applied to overcome imbalance in the dataset. The CTGAN provides improved accuracy in the KNN, NB, RF and SVM algorithms. The results demonstrate that the measured values by FVRP can classify soil layers through three kinds of data with machine learning algorithms.

• Clinical and Experimental Reproductive Medicine
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• v.49 no.3
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• pp.196-201
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• 2022

Objective: This prospective consecutive study investigated the variation in sperm DNA fragmentation (SDF) in multiple semen samples from patients with cancer. Methods: Eighty-one patients with various cancers underwent multiple semen collections on 3 consecutive days for sperm cryopreservation prior to cancer treatment. A commercial Halosperm kit was used to measure SDF. Within- and between-subject coefficients of variation were estimated via random-effects analysis of variance to assess the consistency of semen parameters and SDF. Intraclass correlation coefficients (ICCs) were calculated to assess the magnitude of the between-subject component of variance relative to the total variance. Results: The volume of semen in the day-2 and day-3 samples was significantly lower compared with the day-1 sample. Most parameters showed high ICC values, suggesting that within-subject fluctuations were small relative to the between-subject variability. The highest ICC values were identified for the SDF (ICC, 0.68; 95% confidence interval [CI], 0.45-0.84) and semen volume (ICC, 0.67; 95% CI, 0.45-0.84). Conclusion: Our findings showed that repeated ejaculates from patients with cancer had stable SDF levels.

• Journal of Distribution Science
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• v.20 no.10
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• pp.93-103
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• 2022

Purpose: This study aims to determine the relationship between disruptive factors and customer satisfaction at chain stores. Survey-based questionnaires were designed in the distribution technique to measure the findings in this study. Research design, data, and methodology: In terms of the sampling technique, the researchers adopted the simple random sampling technique with a total of 200 sample sizes. For the statistical method, the researchers applied multiple linear regression analysis to determine the potential factors that affect customer satisfaction at chain stores. The analysis of this study measured how product quality, pricing policies of chain stores, design and layout, responsiveness, and location of chain stores impart their roles in customer satisfaction. Results: This study found a significant relationship between the product quality and location of chain stores on customer satisfaction. In addition, the responsiveness, pricing policy, and physical design of chain stores impart an insignificant role in customer satisfaction. However, it is proven that the location of chain stores and product quality positively impact customer satisfaction. Conclusions: The study is geographically limited to the region of Karachi, Pakistan. Therefore, the findings may differ in the context of study implications in the other areas.

• Physical Therapy Rehabilitation Science
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• v.12 no.2
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• pp.177-184
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• 2023

Objective: Manual therapy is a commonly utilized approach in managing chronic pain, but its specific impact on pain catastrophizing remains uncertain. The objective of this systematic review and meta-analysis was to examine the effects of manual therapy on pain catastrophizing in individuals with chronic pain. Design: A systematic review and meta-analysis Methods: A comprehensive search was conducted in electronic databases to identify relevant studies published from 2014 onwards. Studies that evaluated the impact of manual therapy on pain catastrophizing in individuals with chronic pain were incorporated. The risk of bias in the selected studies was evaluated using the Cochrane tool for risk of bias in qualitative analysis. For the quantitative analysis, RevMan 5.4 software was utilized, employing a random-effects model as the analysis model. The effect measure used in the analysis was the standardized mean difference (SMD). Results: In total, 26 studies were collected, and following the screening process, three of them were incorporated into the final analysis. The included studies involved a total of 153 patients with chronic pain. The interventions comprised various manual therapy techniques targeting different areas of the body. Pain catastrophizing and pain intensity were the primary outcomes of interest. The meta-analysis revealed a significant reduction in pain catastrophizing scores following manual therapy intervention compared to control conditions (SMD = -0.91, 95% CI: -1.25 to -0.58). However, heterogeneity between the studies was observed. Conclusions: Despite the limited quantity and heterogeneity of studies, it has been demonstrated that manual therapy intervention is effective in reducing pain catastrophizing in individuals with chronic pain.

• Computers and Concrete
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• v.33 no.2
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• pp.137-145
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• 2024

The technique of experimentally determining concrete's compressive strength for a given mix design is time-consuming and difficult. The goal of the current work is to propose a best working predictive model based on different machine learning algorithms such as Gradient Boosting Machine (GBM), Stacked Ensemble (SE), Distributed Random Forest (DRF), Extremely Randomized Trees (XRT), Generalized Linear Model (GLM), and Deep Learning (DL) that can forecast the compressive strength of ternary geopolymer concrete mix without carrying out any experimental procedure. A geopolymer mix uses supplementary cementitious materials obtained as industrial by-products instead of cement. The input variables used for assessing the best machine learning algorithm not only include individual ingredient quantities, but molarity of the alkali activator and age of testing as well. Myriad statistical parameters used to measure the effectiveness of the models in forecasting the compressive strength of ternary geopolymer concrete mix, it has been found that GBM performs better than all other algorithms. A sensitivity analysis carried out towards the end of the study suggests that GBM model predicts results close to the experimental conditions with an accuracy between 95.6 % to 98.2 % for testing and training datasets.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.141-150
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• 2024

Ground subsidence in urban areas is mainly caused by anthropogenic factors such as excessive groundwater extraction and underground infrastructure development in the subsurface composed of soft materials. Global Navigation Satellite System data with high temporal resolution have been widely used to measure surface displacements accurately. However, these point-based terrestrial measurements with the low spatial resolution are somewhat limited in observing two-dimensional continuous surface displacements over large areas. The synthetic aperture radar interferometry (InSAR) technique can construct relatively high spatial resolution surface displacement information with accuracy ranging from millimeters to centimeters. Although constellation operations of SAR satellites have improved the revisit cycle, the temporal resolution of space-based observations is still low compared to in-situ observations. In this study, we evaluate the extraction of a time-series of surface displacement in Incheon Metropolitan City, South Korea, using the small baseline subset technique implemented using the commercial software, Gamma. For this purpose, 24 COSMO-SkyMed X-band SAR observations were collected from July 12, 2011, to August 27, 2012. The time-series surface displacement results were improved by reducing random phase noise, correcting residual phase due to satellite orbit errors, and mitigating nonlinear atmospheric phase artifacts. The perpendicular baseline of the collected COSMO-SkyMed SAR images was set to approximately 2-300 m. The surface displacement related to the ground subsidence was detected approximately 1 cm annually around a few Incheon Subway Line 2 route stations. The sufficient coherence indicates that the satellite orbit has been precisely managed for the interferometric processing.