Analysis Of Variance Method Research Articles

Costumer Experience Analyzing the Comparison of Brand and Company Characteristics of Airlines Services

Analyzing the comparison of brand and company characteristics of airlines services is important in the aviation industry. The purpose of this analysis is to determine if there is a significant difference in the quality of service among different airlines. The ANOVA (Analysis of Variance) method can be used to compare more than two groups of data and determine if the differences between the groups are significant or not. In this analysis, the measured variables can be the quality of service provided by airlines such as comfort, safety, speed, accuracy, and others. Data can be obtained from various sources such as surveys, personal experiences, and reviews from various media. Analyzing the comparison of brand and company characteristics of airlines services using the ANOVA method can provide valuable insights for airlines in improving the quality of service provided to customers. The analysis results can be used to identify the strengths and weaknesses of each airline, which can be used to improve the quality of service and create a better experience for customers. The ANOVA method can provide useful information in comparing the quality of service among airlines. However, it is important to note that the analysis results are not always 100% accurate and need to be interpreted carefully. Analyzing the comparison of brand and company characteristics of airlines services using the ANOVA method can provide significant benefits for airlines in improving the quality of service and maintaining customer satisfaction. The conclusion of this analysis is that brand and company characteristics have a significant influence in providing services in airlines. Therefore, companies must pay attention to both brand and company characteristics in providing services to customers to improve the customer experience and increase customer satisfaction.

Proportion optimization and strength prediction of CGS backfill materials based on GA-ELM mode

ABSTRACT The strength of the backfill body is an important aspect of safe production in backfill mining technology. In order to quickly and accurately obtain the strength of coal gasification slag -based cemented backfill materials with different ratios, the orthogonal design of 4 factors and 5 levels and variance analysis method were used to study the mass concentration (A), coal gasification slag (CGS)/cement (B), bone glue ratio (C), activator content (D) on the compressive strength of backfill body and a genetic algorithm with 28-day compressive strength of CGS-based backfill material as the response value was constructed, and verify the applicability of the model. The results show that: the primary and secondary factors affecting the 28-day compressive strength are C > A > B > D, the optimal ratio is 80% mass concentration, CGS/cement ratio 4:1, bone glue ratio 3:7, and activator 3%, according to orthogonal variance analysis; the activity of CGS is gradually stimulated as the curing age grows, the hydration products Ettringite and C-S-H are continually generated, and the compressive strength of the backfill material increases in tandem; In the GA-ELM model test set, the intensity correlation coefficient between the prediction and the measured value reached an average of 0.99, and the prediction accuracy was 71.8% and 43.5% higher than that of ELM and PSO-ELM respectively; Laboratory studies have shown that the GA-ELM prediction model has a prediction accuracy of 98.2% and that it can accurately estimate the strength of CGS cemented backfill.

Early Strength of Cold Recycled Emulsified Asphalt Mixtures

In order to study the influence of different factors on the early strength of the cold recycled emulsified asphalt mixtures, 16 different types of cold recycled mixtures were designed and produced, which were combined with different cement content, water content, and cement-water ratio. The indirect tensile strength (IDT), compressive strength (UCS), tensile strength at 15°C (TS), and indirect tensile strength ratio (ITSR) tests were used to test the early strength of the cold recycled mixture. The variance analysis method was utilized to analyze the influence of the single factor on the early strength of the cold recycled mixture. The results show that appropriate cement-water ratio content can effectively improve the early strength of cold recycled mixtures. According to the Spearman correlation coefficient and comparison of each evaluation indicator, IDT and ITSR are significantly affected by various factors, and the results are relatively stable and well-differentiated, which is recommended as indicators of early strength evaluation. Cement-water ratio is recommended as the main control factor to control the early strength of the cold recycled emulsified asphalt mixtures. The optimal cement-water ratio ranges from 0.6 to 1.0, while the cement content is controlled from 1.2% to 1.5% and the water content from 3.8% to 4.3%. This study is of great significance for promoting the design of emulsified asphalt cold regenerative mixture with cement-water ratio and improving and accelerating its early strength development.

Application of grey relational analysis and Taguchi method in cutter working parameters for tea-leaf mechanical harvester

The tea tree is a type of horticultural crop and agricultural crop, its leaves are used to be an important ingredient in many beverages. However, the tea-leaf harvest is mainly accomplished by hands, which has an enormous impact on the yield of tea leaves. The wide application of tea-leaf mechanical harvester could improve the harvest efficiency of the tea-leaf, and then increase the harvest yield of the tea-leaf. To improve the harvest yield of the tea-leaf, the working parameters (structural and kinematic parameter) of the cutter on tea-leaf mechanical harvester need to be considered. And the cutting diagram of the cutter was used to optimize the working parameters. In this paper, the tooth top width, tooth root width, tooth depth, teeth space and cutting speed ratio were selected as working parameters of cutter that were considered to enhance the harvest efficiency. Taguchi method coupled with grey relational analysis (GRA) was used to determine the optimal combination of working parameters. Besides, the variance analysis method was performed to statistical analyse the influence of multiple parameters. The results showed that the key parameters of the variation of cutting, re-cutting and blank ratio was the teeth space. The optimal parameter combination was 4.5 mm tooth top width, 12.5 mm tooth root width, 26.0 mm tooth depth, 45.0 mm teeth space and 0.8 cutting speed ratio. Grey relational grade of the optimal parameter combination increased 0.367 compared to the grade with initial parameter combination. Based on the optimal parameter combination, the tea-leaf harvest flatness, efficiency and quality were completely in conformity with the requirements of the tea-leaf mechanical harvester. So that, the Taguchi method coupled with GRA is a practical one to optimize the working parameters of the cutter on the tea-leaf mechanical harvester.

Application Analysis of Portfolio Theory in Financial Markets

Based on portfolio theory, this paper reviews and summarizes the role of investors and examines two aspects of portfolio theory: the mean variance analysis method and the efficient limit model of the portfolio. And its limitations are analyzed. So that investors can invest better. Indifference curves vary from person to person, and deviations will likely affect the resulting final maximum utility point. Although the research on financial market risk has been relatively mature, there are still some puzzles to be solved in the effective measurement of risk. Markowitz takes the ROI as a representation of ROI and the variance as a representation of ROI, which solves the problem of measurement of asset risk. He thinks that most investors are risk-averse; they will try to avoid risk at the same time as they seek high returns. Therefore, Markowitz has proposed a portfolio investment theory based on the analysis of the mean variance.

Deep learning based spatio‐temporal hand gesture recognition system in complex environment

AbstractGesture recognition nowadays has grabbed the attention of researchers as they represent human behaviour in multiple practical ways. Amongst a variety of gestures available, hand gestures play an essential role in the field of human‐computer interaction when recognised efficiently in complex and dynamic environments. In this paper, we propose a dynamic hand gesture recognition system to recognise hand gestures appearing in different indoor and outdoor environments. Hand detection and tracking uses a two‐level system resulting in the formation of gesture trajectory in challenging conditions in which existing detection and tracking algorithms could not do so. A set of 45 features is provided as input to the various classification techniques. The redundancy problem has been reduced by selecting a set of optimum features using the analysis of variance method, which ranks the list of features. An incremental feature selection technique calculates recognition accuracy by selecting features according to rankings. This system provides an accuracy of 96.32% when used with machine learning and 97.5% when used with deep learning techniques. Recognition accuracy is calculated for various environments, including an extra hand, multiple persons in the video frame, and outdoor environment. All machine‐learning classifiers are combined using classifier combination to calculate the accuracy according to the majority‐voting rule. Based on the experimental results, it has been observed that deep learning provides better results compared to machine learning.

Efficiency of application of different apple trees protection systems against harmful organisms in the Precarpathian province of the Carpathian mountain area of Ukraine

Goal. Study of the efficiency of application of chemical, biological and biological-chemical protection systems of apple trees against harmful organisms in the conditions of the Precarpathian province of the Carpathian mountain zone of Ukraine.
 Methods. Phytosanitary monitoring was carried out visually and with the help of pheromone traps. Phytophagous colonization and disease development were recorded according to generally accepted methods in the phases of apple development: «swelling of buds», «green cone», «bud extension», «bud separation», «pink bud», «blooming», «end of flowering», «fruit formation», «fruit growth» and «fruit ripening». The technical effectiveness of insecticides was determined after 5 and 7 days, and the effectiveness of fungicides — after 7 days. Statistical processing of research results was carried out by the method of variance analysis.
 Results. The results of monitoring the phytosanitary state of apple plantations established that the most common pests in 2018—2020 in the conditions of the Precarpathian Province of the Carpathian Mountain Zone of Ukraine were: apple fruit borer (37.2%), aphids (19.5%), leafhoppers (12.2%), mites (8.0%), apple moth (8.3%), flower eater (7.9%), hairy deer (6.9%); the most common diseases: scab (38.2%), powdery mildew (32.8%), moniliosis (14.2%), fruit rot (14.8%). All studied apple tree protection systems against harmful organisms in the conditions of the Precarpathian province of the Carpathian mountain zone of Ukraine obtained high yield rates, and all protection systems allowed to reliably protect apple orchards from pests and diseases. The technical efficiency of the chemical protection system, which included 12 treatments with chemical pesticides, averaged 82.5—96.5%. Productivity using this system was 26.5—26.7 t/ha. The biological protection system, which was based on 7 treatments with biological preparations, made it possible to obtain an apple yield 22.4—22.9 t/ha. The technical efficiency of the preparations of the biological defense system was at the level 66.1% — 72.3%. The system of biological and chemical protection of apple trees against harmful organisms included 7 treatments, reducing the use of chemical protection agents to one treatment, which made it possible to significantly reduce the amount of chemical agents used, minimize the negative impact of pesticides on the ecosystem of the apple orchard, and obtain productivity 23.5—25.1 t/ ha, for the effectiveness of drugs 66.3 94.3%.
 Conclusions. When apple orchards are heavily colonized by pests and diseases, it is recommended to use a chemical protection system that includes 12 treatments with chemical pesticides (9 treatments with a mixture of insecticides and fungicides, 2 treatments with fungicides and one treatment with insecticides) in accordance with the 12 main phases of apple tree development in which the most harmful organisms inhabit and damage the ecosystem of the apple orchard during the period from the «green cone» phenophase to the «fruit ripening» phenophase. To reduce the use of chemical protection agents in apple orchards, a biological and chemical system should be used: in the «green cone» phenophase, one treatment with chemical pesticides, and in the «end of flowering» phenophase — «fruit ripening» — with biological preparations. Under the condition of complete withdrawal from the use of chemical pesticides, the system of biological protection of the apple tree should be used, which is based on seven treatments with biological preparations in the phenophase «separation of buds» — «ripening of fruits».

Longitudinal SARS-CoV-2 Seroprevalence among Employees in Outpatient Care Services in Hamburg.

The risk of SARS-CoV-2 infection is particularly high for healthcare workers during the pandemic. Home care workers visit many different households per shift. Encounters with mostly elderly patients and their relatives increase the potential for the undetected spread of SARS-CoV-2. In order to gain insight into the seroprevalence of SARS-CoV-2 antibodies and possible transmission risks in outpatient care, this follow-up study was conducted with nursing services in Hamburg. The aim was to estimate the dynamics of seroprevalence in this occupational group over a 12-month period, to identify occupation-specific risk factors, and to collect information on the vaccination status of the surveyed nursing staff. Antibody testing for SARS-CoV-2 IgG against the S1 domain (EUROIMUN Analyser I® Lübeck, Germany) was performed on participating healthcare workers with patient contact at a total of four time points within one year from July 2020 to October 2021 (baseline, follow-up after three, six and twelve months). The data were mostly analysed descriptively. Differences in IgG titres were analysed using variance analysis methods, particularly Tukey's range test. The seroprevalence was 1.2% (8/678) at baseline and 1.5% (9/581) at the three-month follow-up (T1). At the second follow-up (T2) after six months, vaccination against SARS-CoV-2 was available from January 2021 onwards. The prevalence rate of positive IgG antibodies relative to the S1 domain of the spike protein test among unvaccinated individuals was 6.5%. At (T3) after twelve months (July to October 2021), 482 participants were enrolled, and 85.7% of the workers were considered fully vaccinated at this time point, while 51 individuals were unvaccinated. The prevalence was 13.7% (7/51). In our study, a low seroprevalence was found among home care workers, which was lower than in our studies conducted in the clinical setting. Therefore, it can be assumed that the occupational risk of infection is rather low for both the nursing staff and the patients/clients cared for in the outpatient setting. The good provision of protective equipment and the high vaccination rate of the staff probably had a positive influence.

Demystifying longitudinal data analyses using structural equation models in school psychology

Structural equation models (SEM) are a method of latent variable analysis that offer a high degree of flexibility in terms of modeling methods for applied research questions. Recent advancements associated with longitudinal SEM have unlocked innovative ways to decompose variance and to estimate mean trends over time (e.g., Allison et al., 2017; Berry & Willoughby, 2017; Hamaker et al., 2015; McArdle & Nesselroade, 2014). However, these longitudinal methods are not necessarily readily accessible to scholars seeking to advance theory and practice in school psychology. Importantly, not all longitudinal data are the same and not all longitudinal SEMs are the same; thus, analytic approaches must be appropriately matched to specific research aims to meaningfully inform school psychology theory and practice. The present article highlights recent advances in longitudinal SEMs, clarifies their similarities to other—perhaps more familiar—methods, and matches their applications to specific types of research questions. The intent of this work is to promote careful thinking about the correspondence between estimands, developmental theory, and practical applications to foster specificity in testing quantitative questions in school psychology research and advance a more rigorous evaluation of longitudinal trends relevant to research and practice in the field.

Experimental Study on Shear Rheological Polishing of Si Surface of 4H-SiC Wafer

In this study, shear rheological polishing was used to polish the Si surface of six-inch 4H-SiC wafers to improve polishing efficiency. The surface roughness of the Si surface was the main evaluation index, and the material removal rate was the secondary evaluation index. An experiment was designed using the Taguchi method to analyze the effects of four critical parameters (abrasive particle size, abrasive particle concentration, polishing speed, and polishing pressure) on the Si surface polishing of SiC wafers. By evaluating the experimental results for the signal-to-noise ratio, the weight of each factor was calculated using the analysis of variance method. The optimal combination of the process parameters was obtained. Below are the weightings for the influence of each process on the polishing result. A higher value for the percentage means that the process has a greater influence on the polishing result. The wear particle size (85.98%) had the most significant influence on the surface roughness, followed by the polishing pressure (9.45%) and abrasive concentration (3.25%). The polishing speed had the least significant effect on the surface roughness (1.32%). Polishing was conducted under optimized process conditions of a 1.5 μm abrasive particle size, 3% abrasive particle concentration, 80 r/min polishing speed, and 20 kg polishing pressure. After polishing for 60 min, the surface roughness, Ra, decreased from 114.8 to 0.9 nm, with a change rate of 99.2%. After further polishing for 60 min, an ultrasmooth surface with an Ra of 0.5 nm and MRR of 20.83 nm/min was obtained. Machining the Si surface of 4H-SiC wafers under optimal polishing conditions can effectively remove scratches on the Si surface of 4H-SiC wafers and improve the surface quality.

"Ideal employees" and "good wives and mothers": Influence mechanism of bi-directional work-family conflict on job satisfaction of female university teachers in China.

Work and family are two important areas in people's life, and the relationship between them will have an important impact on the attitudes and behaviors of employees in an organization. In the context of Chinese culture, the organization hopes to have an ideal employee, and the family hopes to have a good wife and mother. Based on the resource conservation theory, this paper examines the relationship between bi-directional work-family conflict and job burnout, perceived organizational support and job satisfaction by using latent variable path analysis method with 527 Chinese female university teachers as subjects. The results showed that: (1) Work-family conflict, family-work conflict and job burnout could negatively predict job satisfaction, while perceived organizational support could positively predict job satisfaction, (2) Job burnout played a partial mediating role in the process of work-family conflict and family-work conflict affecting job satisfaction, and the effect values were - 0.220 and - 0.168, and (3) Perceived organizational support played a moderating role in the first half of the mediating effect of "work-family conflict → job burnout → job satisfaction" and "family-work conflict → job burnout → job satisfaction," and the moderating mediating index was 0.015 and 0.010. The study contributes to a better understanding of the relationships among bi-directional work-family conflict, job burnout, perceived organizational support, and job satisfaction among female university teachers. Our findings highlight potential avenues for interventions by university administrators in the context of Chinese culture aimed at balancing work and family and improving job satisfaction among female university teachers.

Multiple Response Prediction and Optimization in Thin-Walled Milling of 6061 Aluminum Alloy

In this study, the multi-objective optimization method for thin-wall milling of 6061 aluminum alloy is addressed. The technological parameters including the cutting speed Vc, the feed of tooth fz, and the width of cut ar are considered input variables, while the manufacturing responses are surface roughness Ra, production rate MRR, and flatness deviation FL. The goal is to find the optimum cutting parameters to minimize Ra and FL and maximize MRR, at the same time. To solve this problem, the desirability function approach was used based on Taguchi orthogonal array. Twenty-seven experiments were conducted and the measured data were collected. The mathematical regression models for responses Ra, MRR, and FL were then generated and evaluated by using the analysis of variance method. Then, the multiple objective optimization problems were solved by using the desirability function approach. The optimum cutting parameters set are Vc=120m/min, fz=0.06mm, and ar=0.13131mm, corresponding to Ra=0.1613µm, MRR=17197.45cm3/min, and FL=0.0995mm.

Dynamic material parameter inversion of high arch dam under discharge excitation based on the modal parameters and Bayesian optimised deep learning

Vibration-based dam safety monitoring methods have increasingly become a research hotspot for assessing dam safety. The accurate material parameters of a high arch dam and its foundation are critical for monitoring vibration safety. Accordingly, a dynamic material parameter inversion framework for an arch dam is developed based on modal parameters and deep learning. Firstly, an determined-order stochastic subspace identification method with adaptive variational modal decomposition is proposed based on the prototype vibration signal obtained under the discharge excitation, which can effectively identify the modal parameters. Secondly, the sensitivity of the dynamic elastic modulus (DEM) in different regions to the modal parameters of the arch dam was analysed using the orthogonal test method and variance analysis method, and it was utilised to ascertain the DEM to be inverted. Finally, a Bayesian optimised multi-output long short-term memory neural network is used to establish a nonlinear mapping relationship between the DEM and the modal parameters as an alternative to finite element calculations, and the identified modal parameters are employed as network inputs to inverse the actual DEM of each zoning. An engineering example shows that the proposed DEM inversion method for high arch dams is effective and accurate, providing a good basis for the vibration safety analysis of arch dams. This study overcomes the limitations of difficult to effectively extract modal parameters of arch dams under discharge excitation, and advances the application of deep learning technology in hydraulic engineering by combining modal parameters.

Exergoeconomic analysis and multi-objective optimization of ORC configurations via Taguchi-Grey Relational Methods

Recovery of low-grade waste heat in industrial processes is an essential energy management topic. Yet, most low-temperature heat sources discharge their heat directly into the environment. The Organic Rankine Cycle (ORC), which has the benefits of being energy-efficient, enabling investment savings, and being ecologically friendly, is crucial in recycling energy from low-temperature waste heat. Both the application of the optimum cycle design and the provision of optimum working conditions are the issues that need to be focused on efficiently using energy. This study performs the energy, exergy, and exergoeconomic analysis of four different organic Rankine cycle configurations operating with renewable or low grade waste heat. The effect degrees and ratios of selected control factors are calculated using Taguchi and variance analysis methods to compare thermal and exergy efficiencies, total system cost, and unit cost of electricity produced by the system. The objective function of the multi-objective optimization problem is defined, and its solution is realized with the Taguchi-Grey Relational Analysis method. The best thermodynamic and exergoeconomic performance result is calculated for the configuration of ORC with Feed Fluid Heater-Internal Heat Exchanger (IHE–FFH–ORC). As a result of Taguchi and ANOVA analysis, the factors that most affect the thermal efficiency of the system, the exergy efficiency, the total system investment cost, and the unit cost of the electricity produced are, respectively, the evaporation temperature (∼50%), turbine efficiency (∼25%), working fluid (∼20%), subcooling (∼4%), pump efficiency (∼0.05%), and superheating (∼0.05%). As a result of the optimization process, the thermal and exergy efficiencies, the total system cost and the unit cost of produced electricity for the IHE–FFH–ORC power system are calculated as 22.6% and 73.5%, 1.06 $/h, 0.039 $/kWh and 2.9 years, respectively.

Effect of corruption on green growth

Corruption as a social and cultural epidemic is likely to influence the environmental sustainability and quality of the world we live in, where climate change threatens our survival, both now and in the future. Therefore, in this paper, we use large panel data of 123 countries between 2000 and 2017 to examine the environmental effect of corruption on green growth. Consistent with prior studies and due to the slow-changing nature of corruption, we used the pooled ordinary least square as the primary estimator. We also employ the System-Generalised Method of Moments and Two-Stage Least Square Instrumental Variable analysis to control country-specific effects and simultaneity bias caused by potential endogeneity. The results show a negative and significant relationship between corruption and green growth, suggesting that highly corrupt countries are less likely to improve the environmental consequences of rapid economic growth. Quantitatively, ceteris paribus, a 1% increase in corruption (control of corruption), given its standard deviation, leads to a 15.47% decrease in green growth. This is equivalent to about 0.912 US dollars per kilogram decrease in green growth. In further analyses, we find that the relationship between corruption and green growth is similar in both developed and developing countries implying that no country is immune from the environmental effect of corruption. The findings highlight the need to control corruption to achieve sustainable economic and environmentally friendly development, especially as Agenda 2030 fast approaches.

Effect of fly ash and red mud on strength and electrochemical properties of seawater mixed concrete

The utilisation of seawater (SW) for making concrete appears to be a reasonable alternative to conserve freshwater. This paper investigates the possibility of making seawater mixed concrete (SMC) using cementitious replacement of fly ash (FA) and red mud (RM) to offset the adverse effects of SW in concrete. FA was added by replacing from 10% to 40% by weight of cement and RM from 5% to 20% and compressive strength, split tensile strength and electrochemical properties of concrete were evaluated for different mixes for 7, 28 and 90 days of testing. Analysis of variance method was used to identify the influences of FA, RM and concrete testing age on the SMC properties. The best mix was then finalised using the response surface method (RSM). It was observed that RM and especially FA were very effective in improving SW concrete properties, that is, increasing mechanical strength and controlling corrosion of steel in concrete. The results showed that to successfully utilise SW for making concrete, the best results at the testing age of 90 days were obtained on replacing cement with approximately 40% FA. The novel mix showed approximately 23% increase in compressive strength and 12% increase in tensile strength compared to SWM concrete. In addition, the novel mix electrical resistivity is around 60 kΩcm showing it to be in low corrosion zone.

Investigating the Effectiveness of Educational Program Based on Academic Engagement Derived from the Model on Students' Academic Satisfaction

Background: Academic engagement is one of the important educational issues that can affect the academic satisfaction of students to maintain their motivation and will to continue their studies. Objectives: The objective of this research was to determine the effectiveness of the educational program developed based on the model derived from the research on students' academic satisfaction. Methods: This applied research was a pre-test, post-test and follow-up with a control group. The statistical population consisted of all female students of the second year of high school in Sanandaj, who were studying in the academic year of 2022-2023. Using the random sampling method, 40 students whose academic satisfaction scores were low were selected and replaced randomly in two groups of 20 people, experimental and control. The experimental group was taught ten 90-minute sessions of the program based on academic engagement. The members of both groups completed the academic satisfaction questionnaire of Lent et al. The data were also analyzed by mixed variance analysis method in SPSS-25. Results: The results indicated that the average academic satisfaction scores in the experimental group compared to the control group increased significantly in the post-test and follow-up phase. Conclusions: The educational program based on academic engagement has been effective on students' academic satisfaction.

Variability of the Linguistic Consciousness development of an Individual in the Artificial Bilingualism Conditions

Purpose. The purpose of this study was to outline the variable markers of the individual linguistic awareness/consciousness development in the conditions of artificial bilingualism.
 Methods. The main method of the study was the method of selective observation with the fixation of markers of the linguistic awareness development and qualitative indicators of respondents' mastery of English as a foreign language in the artificial bilingualism conditions. Potential standards of passive-mechanical (imitation) and active (cognitive-communicative) models of artificial bilingualism were used for comparison. Markers of the respondents’ linguistic awareness were subject to monitoring: language knowledge, culture and speaking skills (at a level sufficient for formulating and expressing thoughts in the process of interpersonal communication in a foreign language), manifestations of language socialization (mastering the norms of listening, perceiving and speaking in a foreign language at a level sufficient for communication and coordination of semantic codes of communication subjects).The obtained data were subjected to content analysis, which made it possible to evaluate the markers of the development of the respondents’ linguistic awareness in the artificial bilingualism conditions and to reveal the level of using a foreign language in communication. In order to statistically confirm the significance of the obtained data, the method of one-factor variance analysis (Fisher’s φ-criterion) was used. A multidimensional procedure of cluster analysis (K-means clustering) was also used, which made it possible to distinguish subsets of the levels of the linguistic awareness development among the respondents of the research project.
 Results. The results of the data analysis of the research project proved that the differences between the experimental and control groups of junior high school students in identifying markers of linguistic awareness are reliably significant relative to individual predictors of the logical ordering of speech-thinking dimensions of language awareness (at p ≤ 0.05).Respondents of the experimental group demonstrate better results in listening, understanding the content of oral expression in a familiar everyday context and in communicative competences. The dominance of markers of an average level of linguistic awareness development among younger schoolchildren was also recorded.
 Conclusions. In the realities of permanent transformations of the modern information society, bilingualism appears as a predictor of foreign language mastery at a level sufficient for communication and exchange of ideas with other subjects of linguistic activity. Language (and foreign language in particular) is not only a communication tool, but also a way of perceiving, organizing and encoding (or decoding) the surrounding reality. In this context, linguistic awareness is interpreted as an invariant of possible schemes of mastering reality, which is most suitable for the purposes of communication between people. The analysis of markers of the junior high school students’ linguistic awareness development proved that when an active (cognitive-communicative) model of artificial bilingualism is implemented, the respondents demonstrate statistically better results in listening, understanding the content of oral expression in a familiar everyday context and in identifying communicative competences.

The Effect of Ethics in Business on Happiness, Aggressiveness and Inconsistency of Efforts and Rewards

The present study investigates the effect of business ethics on happiness, aggression and inconsistency of effort and reward of auditors in Iran and Iraq. The statistical population of the present study includes all partners, managers and auditors working in audit institutions in Iran and partners of the audit institutions, assistant auditors, auditors, individual second rank and individual first rank, with a total of 365 questionnaires completed by Iranian respondents out of 450 questionnaires and 250 questionnaires completed by Iraqi respondents out of 350 questionnaires, a total of 615 questionnaires from the two countries in 2022. Also, the methods of variance analysis and ordinary least squares regression and Smart PLS 3 and Stata 15 software were used to analyze the data and test the hypotheses. The results from testing this research’s hypotheses indicate a negative and significant relationship between business ethics and aggression, effort-reward mismatch and a positive and significant relationship between business ethics and happiness. Since the current research was conducted in the emerging financial markets of Iran and Iraq, which are highly competitive, along with having special economic conditions, and since the occupation of the ISIS terrorist group, the civil wars in Iraq, severe world economic sanctions against Iran and the global crisis of Covid-19 in Iran and Iraq have led to special conditions, the current research can bring helpful information to readers and help the development of science and knowledge in this field.

Optimisation on machining parametres by EDM of TiN coated Ti6Al4V alloys

ABSTRACT This study investigated the effects of electro-erosion (EDM) processing parameters on TiN-coated Ti6Al4V alloy by the physical vapour deposition (PVD) technique. Electrode wear rate (TWR), workpiece machining rate (MRR), and surface roughness (Ra) values were determined by including discharge current, pulse time (ton), and two different tool electrodes (E-Cu and CuBe) into the EDM process parameters. Variables affecting the experimental study (ANOVA) were performed depending on the analysis of variance method. For the analysed (ANOVA) TiN-coated Ti6Al4V samples, the most optimal parameters of MRR value were determined using current 12 A, ton 100, and Cu electrodes. For the TWR value, the optimum parameters were examined by using current 6 A, ton 100, and CuBe electrodes. Finally, 12 A current, ton 100, and electrode E-Cu were analysed for the lowest Ra value. The results showed a better result in MRR and Ra with increasing discharge current, while a better result was obtained in TWR with increasing pulse duration and decreasing discharge current. In addition, it was observed that the E-Cu electrode performed better than the CuBe electrode in processing TiN-coated Ti6Al4V.