Independent Test Results Research Articles

The COMPARISON OF SHARIA BANKING PERFORMANCE BASED ON RISK PROFILE AND EARNING AND CAPITAL (REC)

This study aims to describe the performance of Islamic banking REC method better or equal to the performance of Islamic banks.
 Descriptive method isused to find how ratio of Non Performing Loans and Loan to Deposit Ratio representing Risk Profile, Earning representing Return on Assets and Capital ratio representing Capital Adequacy Ratio in Islamic banking for the period 2014-2017.
 The Independent sample t-test hypothesis test results show that, at th eaverage value of theNPL, FDR and CAR is in significant differences between 11 Islamic banks in Indonesia.Where as ROA has a very significant difference between one bank and an other from 11 Islamic banking in Indonesia

An Investigation into the Use of Socio-cultural Writing Strategies Among English Majors

Recently, research on writing strategies has been prolific. However, little attention has been paid to the studies on the socio-cultural writing strategy. Accordingly, this study investigates the use of the socio-cultural writing strategies of 306 English majors by means of questionnaire survey and interview. The paper analyzes the data in a descriptive and inferential way and the results show that: 1) The use of Role-mediated writing strategies is at a high level and the use of Tool-mediated strategies, Sign-mediated strategies, Rule-mediated strategies, and Community-mediated strategies are at a medium level. 2) The Independent test results demonstrate that students of different year show statistically significant differences in some types of socio-cultural writing strategies. The conclusion of this study is conducive to improving English writing class efficiency among English majors and offer suggestions for English teaching reform of English majors.

A methodology to assess the evolution of viscoelastic properties of hardened cement pastes through dynamic mechanical analysis

This paper presents a new methodology to determine dynamic mechanical characterization of cements pastes in the frequency domain, and also non-aging time dependent creep compliances from interconversion of short duration torsional frequency sweep tests on hardened cement pastes. The experimental results show the behavior of the phase angle, storage and loss moduli in frequency domain at three loading ages for two pastes with different water cement ratios. Validation is performed through comparison between creep compliance predictions and laboratory results of independent test of the elastic Young modulus. The results show good agreement between the independent standard test and predicted values demonstrating the predictive and repeatability capabilities of the proposed methodology. Hypothesis tests further analyzed that the differences in the results from the simulation of the interconverted creep compliance and the independent standard test is only due to inherent statistical scatter for at least 4% of significance level for both pastes and all loading ages. The proposed methodology demonstrated to deliver not only dynamic characterization of cement pastes, but also the creep compliance in the time domain and the static secant modulus of cement pastes.

Fertility-GRU: Identifying Fertility-Related Proteins by Incorporating Deep-Gated Recurrent Units and Original Position-Specific Scoring Matrix Profiles.

Protein function prediction is one of the well-known problems in proteome research, attracting the attention of numerous researchers. However, the implementation of deep neural networks, which helps to increase the protein function prediction, still poses a big challenge. This study proposes a deep learning approach namely Fertility-GRU that incorporates gated recurrent units and position-specific scoring matrix profiles to predict the function of fertility-related protein, which is a highly crucial biological function. Fertility-related proteins also have been proven to be important in many biological entities (i.e., bone marrow and peripheral blood, postnatal mammalian ovary) and parameters (i.e., daily sperm production). As a result, our model can achieve a cross-validation accuracy of 85.8% and an independent accuracy of 91.1%. We also solve the problem of overfitting in the data set by adding dropout layers in the deep learning model. The independent testing results showed sensitivity, specificity, and Matthews correlation coefficient (MCC) values of 90.5%, 91.7%, and 0.82, respectively. Fertility-GRU demonstrates superiority in performance against the state-of-the-art predictor on the same data set. In our proposed study, we provided a method that enables more proteins to be discovered, especially proteins associated with fertility. Moreover, our achievement could promote the use of recurrent networks and gated recurrent units in proteome research. The source code and data set are freely accessible via https://github.com/khanhlee/fertility-gru .

EVALUATION OF RELATIONSHIP BETWEEN ONLINE SHOPPING AND CONSUMER CONFIDENCE SENSE

The main purpose of this study is to examine the relationship between online shopping and consumer trust. Survey technique was used in the research. The research population consists of individuals over the age of 18 living in the province of Düzce. Easy sampling method is used for study. The size of this sample is 400. Factor analysis, correlation analysis, ANOVA and Independent Sample T-test were performed using SPSS 21 package program. As a result of the factor analysis, three dimensions related to online shopping have emerged. These dimensions are "Online Addiction", "Payment Simplicity" and "Complexity". According to consumer trust factor analysis result, four dimensions have emerged. These dimensions are "Control", "Self-confidence", "Comfort" and "Fear". According to the results of correlation analysis; meaningful relationships were observed between online shopping and consumer trust. According to the Independent Sample T-test and ANOVA test results, meaningful differences have emerged.

2D-ROC: a receiver operating surface and its illustrative application in clinical diagnostics

Objective: When there are multiple tests, the receiver operating characteristic (ROC) curve analysis does not answer the question of how the individual tests can be combined in medicine. Approach: In this study, 2D-ROC analysis is considered to calculate the correct classification rate (CCR) by using two independent test results. To obtain the best combination of paired tests, results were combined as ‘BOTH’, ‘ANY’ or ‘AVERAGE’ for the final 2D-ROC decision. Main results: When the combined model was ‘AVERAGE’, the CCR was better than individual test results. At every correlation level, the 2D-ROC was shown to have a better CCR compared to individual tests, and when the correlations were lower, the CCR of 2D-ROC was even better. For uncorrelated test pairs (r = 0, p < 0.0001), in healthy and diseased populations with normal distributions, the improvement in CCR compared to individual tests were from 2.6% to 6.5%, and leptokurtic distribution of diseased population (k = 2, p < 0.0001) was better by 1.3% to 5.3%. As a clinical application, multifrequency bioelectric impedance (BI) spectroscopy characteristic frequency (f c) and body mass index (BMI) measurements from 53 post-menopausal women were used in finding the 2D-ROC decision matrix to determine the hip area bone mineral deficiency. Using the ‘AVERAGE’ combination model, the CCR of 2D-ROC was 1.6% better than BMI and 14.8% better than fc alone. In the second clinical application of prediction of metabolic syndrome (MeS), parameters such as BMI, waist circumference, abnormal fasting blood sugar, triglyceride and high-density lipoprotein cholesterol were measured from 5533 subjects and combined to assess individual and paired success rates. Using the ‘AVERAGE’ combination model, the CCR of pairs were up to 6.1% better compared to using each parameter alone. Significance: Although the use of a simple ‘AVERAGE’ function was promising, the formulation for combining paired test results could be extended to include the deviations from ideal by weighted averaging of individual tests or by adding other parameters like their kurtosis or disease prevalence into the formulation.

Characterization and identification of antimicrobial peptides with different functional activities.

In recent years, antimicrobial peptides (AMPs) have become an emerging area of focus when developing therapeutics hot spot residues of proteins are dominant against infections. Importantly, AMPs are produced by virtually all known living organisms and are able to target a wide range of pathogenic microorganisms, including viruses, parasites, bacteria and fungi. Although several studies have proposed different machine learning methods to predict peptides as being AMPs, most do not consider the diversity of AMP activities. On this basis, we specifically investigated the sequence features of AMPs with a range of functional activities, including anti-parasitic, anti-viral, anti-cancer and anti-fungal activities and those that target mammals, Gram-positive and Gram-negative bacteria. A new scheme is proposed to systematically characterize and identify AMPs and their functional activities. The 1st stage of the proposed approach is to identify the AMPs, while the 2nd involves further characterization of their functional activities. Sequential forward selection was employed to extract potentially informative features that are possibly associated with the functional activities of the AMPs. These features include hydrophobicity, the normalized van der Waals volume, polarity, charge and solvent accessibility-all of which are essential attributes in classifying between AMPs and non-AMPs. The results revealed the 1st stage AMP classifier was able to achieve an area under the receiver operating characteristic curve (AUC) value of 0.9894. During the 2nd stage, we found pseudo amino acid composition to be an informative attribute when differentiating between AMPs in terms of their functional activities. The independent testing results demonstrated that the AUCs of the multi-class models were 0.7773, 0.9404, 0.8231, 0.8578, 0.8648, 0.8745 and 0.8672 for anti-parasitic, anti-viral, anti-cancer, anti-fungal AMPs and those that target mammals, Gram-positive and Gram-negative bacteria, respectively. The proposed scheme helps facilitate biological experiments related to the functional analysis of AMPs. Additionally, it was implemented as a user-friendly web server (AMPfun, http://fdblab.csie.ncu.edu.tw/AMPfun/index.html) that allows individuals to explore the antimicrobial functions of peptides of interest.

Prediction of dissolution profiles by non-destructive NIR spectroscopy in bilayer tablets.

This study describes how near infrared (NIR) spectroscopy can be used to predict the dissolution of bilayer tablets as a non-destructive approach. Tablets in this study consist of two active pharmaceutical ingredients (APIs) physically separated in layers and manufactured under three levels of hardness. NIR spectra were individually acquired for both layers in diffuse reflectance mode. Reference dissolution profile values were obtained using dissolution apparatus & HPLC. A multivariate partial least squares (PLS) calibration model was developed for each API relating its dissolution profile to spectral data. This calibration model was used to predict dissolution profiles of an independent test set and results of the prediction were compared using model free approaches i.e. dissimilarity (f1) & similarity (f2) factors to assure similarity in dissolution performance.

THE EFFECTIVENESS OF ARIAS LEARNING MODEL ASSISTED AUDIOVISUAL MEDIA IMPROVING LEARNING OUTCOMES

ARIAS learning model instills confidence, relevance, interest, attention, and evaluation to find out success and pride in the results of achievement. With the help of audiovisual media, it will further enhance students' interest, attention, and activeness. Research Objectives 1) finding out differences in learning outcomes of significant ARIAS learning model with audiovisual media and conventional learning models. 2) Determining effectiveness of using ARIAS Learning Model assisted by audiovisual assisted audiovisual media in improving learning outcomes with conventional learning models. Quantitative research is a true design experiment. Design used was a pretest-posttest control group design. The population is all the third-semester students majoring in economics. Sample by means of non probability sampling with a purposive sampling technique, Data analysis techniques use independent test t-test and paired test. Results of independent test t test obtained t count = 3.375 with sig (2tailed) = 0.001 &lt;0.05 which means a significant difference in learning outcomes between ARIAS learning model with conventional learning models. Paired test results obtained a value of t count of -20,378 with the sig. (2-tailed) = 0.00 &lt;0.05 which means an increase in learning outcomes between ARIAS learning models with conventional models. The results obtain of average pre-test is 56.07 and post-test is 79.97. Furthermore, the conclusion is Arias assisted audiovisual learning model effectively improved learning outcomes of English subjects.

Developing Inquiry-Based Learning Materials to Promote Students’ Academic Achievement

The purpose of this study was to develop English learning materials based on Inquiry approach to promote students’ academic achievement. The study was a Research and Development. The learning materials were developed by using ADDIE (Analyze, Design, Develop, Implement, and Evaluate) model. It was validated by some experts, such as experts of media, materials, language, and learning design. The result of those validation showed that the English learning materials were very appropriate to be implemented. Data collected through questionnaire. The data of students’ academic achievement were taken through written test that was given to 67 students at Midwifery Academy of Harapan Mulya Ponorogo, East Java, Indonesia. They were divided into 35 students in experiment class and 32 students in control class. Data analyzed by using paired t test, and independent sample test. Result of statistical test between pretest and posttest in experimental class showed the significance level was 0.000< 0.05. The result of paired T test in control class was 0.007<0.05. The result of independent sample test between experiment and control class showed that the significance level was 0.004 < 0.05. It can be concluded that inquiry-based learning materials can be a tool to promote students’ academic achievement. https://doi.org/10.26803/ijlter.18.1.4

Validation of a Modified ANSR® for E. coli O157:H7 Method for Detection of E. coli O157:H7 in Select Foods.

Background: The ANSR method is based on isothermal nucleic acid amplification technology. The modifications to assay components improve sensitivity of the assay and robustness of the internal positive control. Objective: A Performance Tested MethodSM validation study was conducted to assess performance of a modified version of the ANSR® for Escherichia coli O157:H7 method. Methods: The validation study included inclusivity/exclusivity, matrix, robustness, accelerated stability, and independent laboratory testing. Results: In inclusivity testing of 55 strains of E. coli O157:H7 and E. coli O157:NM variants, all strains produced positive results. In exclusivity testing of 41 strains including E. coli of other serotypes and bacteria of closely related genera, all strains produced negative results. In matrix testing of beef trim, raw ground beef, spinach, and sprout-irrigation water, ANSR method performance was compared with that of the U.S. Department of Agriculture Food Safety and Inspection Service Microbiology Laboratory Guidebook or the U.S. Food and Drug Administration Bacteriological Analytical Manual reference culture procedures. Conclusions: all trials, ANSR method performance was not statistically different from that of the reference methods. Results of independent laboratory testing of ground beef corroborated those of internal testing. Introducing modest changes to three assay operating parameters did not materially affect ANSR method performance. Finally, accelerated stability testing results of three independently manufactured lots of ANSR reagents support a shelf-life of 1 year when stored at 2-8°C.

Comparison of multiple detection methods of Mycoplasma pneumoniae antibody for the early diagnosis of pediatric mycoplasma pneumonia

Mycoplasma pneumoniae pneumonia (MPP) is a common disease in infants and young children. MPP can also be a potential cause of healthcare-associated pneumonia. However, it is challenging to make an accurate diagnosis in a timely fashion. Our goal is to determine the assay consistencies of acridinium ester chemiluminescence immunoassay (AECLIA) and gelatin particle agglutination (GPA) test for the detection of Mycoplasma pneumoniae (MP) antibody. In this study, a total of 1404 children with suspected MPP were enrolled. Among them, 130 were diagnosed as MPP positive by mycoplasma culture, and 186 were negative. MP antibodies were detected by AECLIA, enzyme-linked immunosorbent assay (ELISA) and GPA. Consistency rates, differences among assays, and diagnosis performance were compared for the three methods. The independent χ2 test results of AECLIA and ELISA for the detection of MP-IgG and MP-IgM antibodies were χ2 = 29.210, P &lt; 0.001; χ2 = 9.081, P = 0.017, respectively, suggesting that the two detection methods are well correlated. Similar analyses were done for the comparison of AECLIA and GPA as well as the comparison of ELISA and GPA. The positive rates of these methods agree with epidemiology data and have good consistency. Thus, AECLIA with a much shorter assay time could be a better option for the screening of MPP.

Effects of Neuromuscular Electrical Stimulation [NMES] On Quadriceps Muscle to Improve the Functional Exercise Capacity and Quality Of Life in Mild to Moderate COPD Patients

Background: Prevalence of COPD is common in INDIA, though there are various means used for the treatment of this condition; NMES is still not included in usual rehabilitation of these patients. Since the beneficial effects of NMES on functional capacity are evident through various studies, we would like to evaluate the effect of the same in short treatment duration. Specific Objective: To find out the effectiveness of Neuromuscular electrical stimulation with usual pulmonary rehabilitation on functional exercise capacity and quality of life in mild to moderate COPD patients. Study Design: Quasi experimental study (pre-test and post-test with control group) Study Setting: Institute of Pulmonology -Pulmonology Rehabilitation, PSG Hospitals, Coimbatore. Participants: 30 mild to moderate COPD patients. Sampling: Convenience Sampling Study Duration: 6 months Treatment Duration: Group A – 45 minutes of usual pulmonary rehabilitation (short term package of PSG Institute of pulmonology) daily for 6 days. Group B – 30 minutes of NMES and 45 minutes of usual pulmonary rehabilitation (short term package of PSG Institute of pulmonology) for 6 days Measurement Tools: Six minute walk test (6MWT), Peak expiratory flow rate (PEFR),Modified BORG dyspnea scale, Physical activity index Results: The pre and post-test values for SMWT, PEFR, modified BORG dyspnea scale and PAI of Group A and Group B were documented and analyzed using paired ‘t’ test to compare the outcomes within the group and between the groups it was analyzed and compared using independent ‘t’ test. The calculated values of paired ‘t’ test for SMWT. PWFR, modified BORG dyspnea scale and PAI for group A is 8.910, 4.465, 3.205, 3.22 and that of group B is 7.898, 7.534, 10.738, 4.039 which are more than the table value at p<0.05 and this shows there is a significant difference within the groups. Based on SWMT, PEFR, and Modified BORG dyspnea scale, calculated ‘t’ values for independent ‘t’ test 3.901, 2.44, and 3.638 are greater than the ‘p’ value, and the value of PAI is 0.735 which is lesser than the ‘p’ value indicating there is significant improvement in functional exercise capacity and quality of life in mild to moderate COPD patients. Conclusion: Based on the paired and independent test results of the study, it is concluded that combination of NMES with usual pulmonary rehabilitation shows significant improvement in functional exercise capacity and quality of life in mild to moderate COPD patients.

Forecasting wildfire disease on tobacco: toward developing a high-accuracy prediction model for disease index using local climate factors and support vector regression

Tobacco wildfire disease is common globally, and climate change may increase the risk of outbreaks. Therefore, there is an urgent need to establish an effective climate model to forecast the occurrence of wildfire disease. To design such a model, we collected data for 40 wildfire disease indices via tobacco field surveys and data for 15 climate factors of Guiyang County in China from 2012 to 2016. First, we built multiple linear regression (MLR), stepwise linear regression (SLR) and support vector regression (SVR) models using three climate features (precipitation, mean daily temperature and sunshine duration), and we could not find an effective model. Second, we built three corresponding models using expanded 15 climate features and an in-house WDEM method (the worst descriptor elimination multi-roundly), and the independent test results showed that the best SVR model had not only a higher predictive accuracy ( $$ {Q}_{ext}^2 $$ = 0.94) but also a better stability. Finally, we further evaluated the biological significance of their retained climate features and the single-factor effects of the best model according to the interpretability analysis, and our results indicated that (1) the three climate factors (minimum value of wind velocity, daily range of temperature and daily pressure) strongly affected the occurrence of wildfire disease; (2) the ranges of relative humidity and sunshine hours were negatively correlated with the occurrence of wildfire disease, while daily mean vapour pressure was positively correlated with the occurrence of the disease. Our work enables a useful theoretical prediction for wildfire disease, especially in terms of climate-related predictions.

HAZIR GİYİM ÜRÜNLERİNDE TÜKETİCİLERİN DEMOGRAFİK ÖZELLİKLERİ İLE RENK ALGILARININ DEĞERLENDİRİLMESİ

The ready wear sector is heavily influenced by consumers' purchasing behavior with the continuous changing consumer profile. Because of this, businesses should closely monitor consumer preferences. In fact, the perceptual differences in the consumers' minds; sometimes it can be a shape or even a color. The purpose of this study is to examine the effect of colors on consumer purchases of ready wear products. Survey technique was used in the study. The research population consists of consumers living in Düzce province. The sample size is 400 in this study where the easily sampling method is used. In the study using SPSS package program; frequency, ANOVA, Independent Sample T-test and factor analysis were conducted. Five dimensions emerged as a result of the factor analysis. These dimensions; Personality Structure, Casuality, Culture, Social Environment and Psychological Situation. Significant differences were also found according to the Independent Sample T-test and ANOVA test results. In addition, according to the results of factor analysis, the average personality and culture dimensions are higher. In the light of these results, it is understood that consumers pay more attention to these factors. In similar studies to be done later, the effects of colors on consumer purchases of ready wear with different dimensions can be investigated.

4mCPred: machine learning methods for DNA N4-methylcytosine sites prediction.

N4-methylcytosine (4mC), an important epigenetic modification formed by the action of specific methyltransferases, plays an essential role in DNA repair, expression and replication. The accurate identification of 4mC sites aids in-depth research to biological functions and mechanisms. Because, experimental identification of 4mC sites is time-consuming and costly, especially given the rapid accumulation of gene sequences. Supplementation with efficient computational methods is urgently needed. In this study, we developed a new tool, 4mCPred, for predicting 4mC sites in Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, Escherichia coli, Geoalkalibacter subterraneus and Geobacter pickeringii. 4mCPred consists of two independent models, 4mCPred_I and 4mCPred_II, for each species. The predictive results of independent and cross-species tests demonstrated that the performance of 4mCPred_I is a useful tool. To identify position-specific trinucleotide propensity (PSTNP) and electron-ion interaction potential features, we used the F-score method to construct predictive models and to compare their PSTNP features. Compared with other existing predictors, 4mCPred achieved much higher accuracies in rigorous jackknife and independent tests. We also analyzed the importance of different features in detail. The web-server 4mCPred is accessible at http://server.malab.cn/4mCPred/index.jsp. Supplementary data are available at Bioinformatics online.

A unified interaction equation for strength and global stability of solid and hollow concrete-filled steel tube columns under room and elevated temperatures

On the basis of plastic limit analysis, this paper proposes a novel, simple and unified interaction equation (N-M) for Concrete-filled Steel Tube (CFST) columns subjected to combined compression and bending. A unique feature of the new N-M equation is that the single equation is valid for a range of columns that can be solid, hollow, circular, polygonal, short or long. The single equation can also apply to columns under both room and elevated temperatures. Validations against independent laboratory test, analytical and numerical results are carried out to assess the accuracy and applicability of the equation. The new equation agrees well with most of the results used in the comparisons. It can be concluded that the simple and unified equation can be used in practical design with sufficient accuracy.

The Effect of Listening Strategy Instruction on Iranian Pre-intermediate EFL Learners’ Listening ability

Listening comprehension plays an important role in the process of language learning as it is one of the four major skills in language acquisition. This study was conducted to investigate the effectiveness of listening strategy instruction on improving listening comprehension of Iranian EFL learners. To achieve this goal, forty students studying at Birjand University were participated in the current study. All of thestudents were within the age range of 18 to 22. Then, they were non-randomly divided into two groups, as a control and an experimental group. Theexperimental was taught based on a guide lesson plan regarding listening strategies while the control group did not receive any treatment. The listening section of TOEFL was utilized to measure the listening performance of the participants before and after the treatment. The results of Independent Samples Test indicated thatinstructing listening strategies had no significant impact onlistening comprehension of Iranian pre-intermediate EFL learners.

Inquiry Based Learning Module to Empower Cooperation Skills

The education in the 21st century focuses on knowledge and encourages students to generate information and encourage developing new skills. The framework of 21st century learning skill is communication, collaboration, critical thinking, creativity and innovation. Cooperation skills in the world of education is an important thing to be done in learning. Therefore, a solution is needed to optimize student empower cooperation skills process by using the teaching material in the form of module. The objective of this research is to know the effectiveness of inquiry based learning module to empower cooperation skills. This research was conducted in one of high school in Surakarta, Indonesia. The research method is quasi experiment, used pretest and posttest design by using two randomly selected classes those were experimental class used an inquiry based learning module and control one used a modules made by biology teachers in Surakarta. The results showed that there were significant differences of learning outcomes between the control and the experimental classes based on the independent samples t-test test results, also seen with the n-gain scores that obtained at 0.78 (middle) in the control class and 0.87 (high) in the experimental class. As the study concluded, using inquiry based learning module in the learning process in effective to empower cooperation skills.

Sleep Apnea Detection from Single-Lead ECG Using Features Based on ECG-Derived Respiration (EDR) Signals

Background and objectiveOne of the important applications of non-invasive respiration monitoring using ECG signal is the detection of obstructive sleep apnea (OSA). ECG-derived respiratory (EDR) signals, contribute to useful information about apnea occurrence. In this paper, two EDR extraction methods are proposed, and their application in automatic OSA detection using single-lead ECG is investigated. MethodsEDR signals are extracted based on new respiration-related features in ECG beats morphology, such as ECG variance (EDRVar) and phase space reconstruction area (EDRPSR). After evaluating the EDRs by comparing them to a reference respiratory signal, they are used in an automatic OSA detection application. Fantasia and Apnea-ECG database from PhysioNet are used for EDRs assessments and OSA detection, respectively. The final performance of our OSA detection is tested on an independent test data which is also compared with results of other techniques in the literature. ResultsThe extracted EDRs, EDRVar and EDRPSR show correlations of 72% and 70% with reference respiration, which outperform the other state-of-the-art EDR methods. After feature extraction from EDRs and RR intervals series, the combination of RR and EDRPSR feature sets achieved 100% accuracy in subject-based apnea detection on independent test data, and also minute-based apnea detection is done with accuracy, sensitivity and specificity of 90.9%, 89.6% and 91.8%, which is better than other automatic algorithms in the literature. ConclusionsOur OSA detection system using EDRs features yields better independent test results compared with other state-of-the-art automatic apnea detection methods. The results indicate that ECG-based OSA detection system can classify OSA events with high accuracy and suggest a promising, non-invasive and efficient method for apnea detection.