Different Types Of Settings Research Articles

Picture Perfect: A Task Interdependence and Communication Experiential Activity for Teams

Effective communication in interdependent group tasks plays a pivotal role in organizational effectiveness, especially in today’s dynamic and global workplace. As the modern workplace evolves toward more remote work environments and dynamic work teams, the ability to adapt communication strategies across various job designs and work settings becomes increasingly crucial. In this article, we present an experiential learning activity designed for management education that delves into the impact of task design on communication. Drawing from theories of team interdependence, this immersive experience enables students to identify the essential facets of communication and their relationship with various types of task interdependence. It equips them with valuable skills and communication strategies that are vital for various types of teamwork across different types of settings. Suitable for a wide range of educational settings, this experiential activity serves as a valuable resource for management educators.

Risk evaluation of venue types and human behaviors of COVID-19 outbreaks in public indoor environments: A systematic review and meta-analysis

Despite increasing vaccination rates, the incidence of breakthrough infections with COVID-19 has increased due to the continued emergence of new variants of the SARS-CoV-2 coronavirus. Therefore, Non-pharmaceutical interventions remain the most effective measures for coping with the ever-changing pandemic. The lifting of compulsory interventions has made individuals primary responsibility for their own health, which highlights the importance of increasing awareness of the infection risk from the environment in which they live and their individual behaviors. We systematically searched PubMed, Web of Science, ScienceDirect, and Scopus on April 17, 2023, for all studies reporting COVID-19 outbreaks in public indoor venues. The study outcome was the attack rate. A total of 42 studies, which included cross-sectional studies, cohort studies, and case studies, reporting data on 1951 confirmed cases in 64 COVID-19 outbreaks satisfied the meta-analysis and were included in the review. A random-effect model was used in the meta-analysis, and subgroup analyses were conducted to investigate factors affecting attack rates. We found a strong level of evidence (p < 0.01) supporting a higher pooled attack rate in recreation-related venues (0.44, 95% CI: 0.30 to 0.60) than in work-related venues (0.21, 95% CI: 0.16 to 0.27). Compared to those outbreaks without that, outbreaks with high-intensity exercise, vocalization, contact behavior, or close body proximity had a higher attack rate of 0.51, 0.55, 0.33, and 0.39, respectively. Further studies suggest that different attack rates across different types of settings may be the result of heterogeneity in exposed people's behaviors. There were significant heterogeneities that may limit the interpretation of connections between influencing factors and outbreak outcomes. The identification of key behaviors that may contribute to transmission risk, and their correlation with venue type, has important implications for the development of future public health interventions and individual prevention strategies for respiratory infectious diseases such as COVID-19.

Learning Effects of Augmented Reality and Game-Based Learning for Science Teaching in Higher Education in the Context of Education for Sustainable Development

In the course of digitalization, new technologies and innovations are continuously introduced to the educational sector. For instance, augmented reality (AR) is increasingly applied in science teaching in both school and higher education. Combining real and virtual content potentially enhances interactivity and understanding of the learning process. This teaching and learning approach can positively impact various learning outcomes, such as learning gains and motivation. This paper aims to investigate the positive learning effects of AR using a game-based AR learning environment: “Beat the Beast”. In line with the concept of an education for sustainable development (ESD) topic, microplastics, this learning environment follows an interdisciplinary approach, combining the subjects of biology, chemistry, and engineering. To determine and distinguish the effects of implementing the technology AR in science learning environments as well as the principles of game-based learning, we contrasted the learning environment into two factors: one with AR and one without AR and the other with a game and without a game. A quasi-experimental design with 203 pre-service teachers of the first semester of all subjects was chosen to evaluate the four different types of settings with questionnaires on motivation, technology acceptance, user engagement, cognitive load, computer self-efficacy, knowledge, and ESD outcomes in higher education. Our research demonstrates that although augmented reality (AR) imposes a relatively elevated cognitive load, it does not negatively affect learning effects. In spite of the increased cognitive load, learners in AR settings do not exhibit lesser knowledge acquisition compared to those in alternative environments. Moreover, our investigation highlights AR’s potential to amplify motivation and user engagement. Contrary to expectations, in the context of the selected subject matter and target audience, game-based adaptations of the educational environment fail to enhance learning outcomes. These versions actually underperform compared to other formats in both motivational and engagement metrics.

Offensive pass tactics analysis of volleyball setters in olympic finals of 2000 and 2021

The aim of the current study was to analyse offensive pass tactics in Olympic Games finals in 2000 and 2021. The authors of the study were interested how the game of volleyball has developed in 20 years, whether it has become faster or even slower. We were also interested whether setters’ game tactics had changed in 20 years. Therefore, we undertook three tasks: to compare offensive pass tactics according to types of sets; to compare the distribution of offensive passes between zones and to compare the ball flight phase times of offensive passes. Based on videos of two Olympic finals (eight sets), a total of 327 offensive passes were analysed, which were divided into different types of sets, and the ball flight phase time of each offensive pass was fixed. It was also taken into account whether the setter had had an excellent, good or bad reception or first touch before performing the set. The videos were analysed using the Kinovea program; the quality of the first video was 360p and of the second 1080p. The first final studied was played in Sydney, Australia, on 1 October 2000 between the men’s volleyball teams of Yugoslavia and Russia, and the second on 7 August in Tokyo, Japan, between the men’s teams of France and Russia.&#x0D; To find statistically significant differences in data, Student’s t-test, p &lt; 0.05, was used. The results revealed that in 20 years setters’ offensive pass tactics had changed; new offensive pass types had been introduced in both back and front zones. As a result of comparison of mean times of ball flight phases, the authors state that in one case the flight phase speed increased, namely in the case of offensive pass into zone 4; in another case, it became slower – in the case of offensive pass tempo forward. In addition to offensive passes played in 2000, new types of offensive pass were played in 2021, such as back line set between zones 6 and 1, back line set between zones 5 and 6, and the shoot set. The tandem combination played in 2000 was not performed once in 2021. The five most popular offensive passes turned out to be sharp sets into zone 4, sharp sets into zone 2, tempo sets forward, sharp back line sets into zone 2, high sets into zone 4. The difference of 2021 compared to 2000 was that the shoot combination was played on the frontline (6% of all the sets), and the back line attack was used 5% more often. The comparison of ball flight phase times revealed that the mean time of the flight phase decreased only in the case of the sharp set into zone 4. Namely, the mean time of the ball flight phase in 2000 was 1.12 seconds, in 2021, however, 0.97 seconds. This can be explained by sharper and faster sets into zone 4. But in the case of the tempo set forward, the mean time of the ball flight phase increased from 0.40 to 0.49 seconds by 2021. The authors’ explanation is that tempo sets were not hit from so near to the setter but, to make blocking more difficult, tempo sets were set longer, or somewhat higher tempo set was used. A statistically significant difference between the two finals was found in the case of sharp set into zone 4 and tempo set forward.

Characterization of Positive Invariance of Quadratic Convex Sets for Discrete-Time Systems Using Optimization Approaches

A positively invariant set is an important concept in dynamical systems. The study of positively invariant set conditions for discrete-time systems is one interesting topic in both theoretical studies and practical applications research. Different methods for characterizing the invariance of different types of sets have been established. For example, the ellipsoidal and the Lorenz cone, which are quadratic convex sets, have different properties from a polyhedral set. This paper presents an optimization method and a dual optimization method to characterize the positive invariance of the ellipsoidal and the Lorenz cone. The proposed methods are applicable to both linear and nonlinear discrete-time systems. Using nonlinear programming and an induced norm, the positive invariance condition problems are transformed into optimization problems, and the dual optimization method is also used to give equivalent dual forms. Fewer results on the positive invariance condition of Lorenz cones can be found than for the other type of set; this paper fulfills the results of this problem. In addition, the proposed methods in this paper provide more options for checking the positive invariance of quadratic convex sets from the perspective of optimization and dual optimization. The effectiveness of this method is demonstrated by numerical examples.

AN INNOVATIVE MULTIDISCIPLINARY PAID APPRENTICESHIP PROGRAM TO DEVELOP A NEW WORKFORCE IN GERONTOLOGY

Abstract There is an acute need to develop new workforce talent in the Gerontology industry due to (a) a rapidly increasing older population; (b) new and evolving needs of older adults due to increased life spans and the long-term impact of COVID-19, and (c) high attrition rates of the current workforce due to death and retirement. One practical strategy to increase new talent is to develop paid apprenticeship opportunities for undergraduate students from different disciplines. The author developed multiple hybrid apprenticeship opportunities to create an "earn and learn" program through funds received from the Louisiana Board of Regents. The program was open to students from all majors because Gerontology is a multi-disciplinary field and there is a need to provide gerontological training to professionals from different disciplines to prepare them to serve older adults in different types of settings. As a pilot project, ten students were selected after an application process. Students in this project were required to complete two three-credit hour fully online courses in Gerontology with a grade of “B” or better. They were also required to complete an eight-hour orientation to help them develop soft skills to work with older adults during their apprenticeship period. They were then required to complete a 150-hour paid summer-apprenticeship in an organization that serves older adults and/or people with disabilities. The program was successful with a 100% completion rate. The students enrolled in this program completed the final step by presenting their apprenticeship experiences at a conference organized by the author.

Children’s agentic capacity, schoolification and risk: competing discourses and young children’s experiences in pre-school settings

ABSTRACT In the Republic of Ireland there has been substantial investment in Early Years provision. The number of different types of settings for pre-school children and the associated research has grown significantly. This paper contributes to existing knowledge by reporting the findings of a qualitative participatory study carried out in the Republic of Ireland and involving a comparative analysis of the views of 90 pre-school children from three different types of setting. Within a conceptual framework that acknowledges the impact of neo-liberalism, the paper argues that despite the growing diversity of settings, provision is underpinned by three main dominant discourses, namely schoolification, risk avoidance and quality assurance. The influence of these on the lived experiences of young children is then explored focusing in particular on how, and in what ways, children exercise their agentic capacity. It is argued that young children’s opportunities to exercise their social agency is at times constrained because of the influence of the combined discourses, which creates a sense of fear in staff (fear of parental complaint, fear of losing job, status and setting registration). Implications for provision and practice are explored.

Practices of Care in a Multipavilion Prison: An Exploratory Study on the Role of the Built Environment

People’s health and well-being is known to be affected by the built environment. Since prisons are confronted with an overrepresentation of people with mental and physical health issues, we examine how the built prison environment affects the provision of care for prisoners with specific needs. Based on observations and (focus group) interviews with prisoners, prison officers, and care-staff, we report on the experiences of specific groups in highly particular prison environments: various pavilions of a former penal colony. By analyzing spatialities in relation to practices and temporalities of care, we provide a nuanced understanding of what caring entails in a prison environment. We show that in this context caring for safety, normality, and physical health ideally go hand in hand. To conclude, we illustrate that the need for control within a prison environment can be reduced by spatial variety, offering different types of settings matching different care and living needs, and allowing movement between settings depending on these needs.

“Black CNN”: Cultural Transmission of Moral Norms through Narrative Art

Abstract In recent debates in moral psychology and literary Darwinism, several authors suggested that narrative art plays a significant role in the process of the social learning of moral norms, functioning as storage of locally salient moral information. However, an integrative view, which would help explain the inner workings of this morally educative function of narrative art, is still lacking. This paper provides such a unifying theoretical account by bringing together insights from moral psychology (concerning the non-reflective nature of moral cognition), educational sciences (concerning different types of settings and methods of moral learning), cognitive/evolutionary narratology (concerning how easy narrative art lends itself to the transmission of moral information), and cultural evolution (concerning different types of learning strategies/biases in relation to narrative art). A study of contemporary American rap music is included to showcase the benefits of this integrative approach in the context of one particular type of narrative art.

Decompositions and eigenvectors of Riordan matrices

Riordan matrices are infinite lower triangular matrices determined by a pair of formal power series over the real or complex field. These matrices have been mainly studied as combinatorial objects with an emphasis placed on the algebraic or combinatorial structure. The present paper contributes to the linear algebraic discussion with an analysis of Riordan matrices by means of the interaction of the properties of formal power series with the linear algebra. Specifically, it is shown that if a Riordan matrix A is an n×n pseudo-involution then the singular values of A must come in reciprocal pairs. Moreover, we give a complete analysis of existence and nonexistence of the eigenvectors of Riordan matrices. This leads to a surprising partition of the group of Riordan matrices into matrices with three different types of sets of eigenvectors. Finally, given a nonzero vector v, we investigate the Riordan matrices A that stabilize the vector v, i.e.Av=v.

The Resident VIEW in Community-Based Care Residential Settings.

The Resident VIEW is a measure of person-centered care (PCC) from residents' perspectives and was previously studied in nursing homes. The current study presents descriptive data for the Resident VIEW in community-based care settings including assisted living, residential care (AL/RC), and adult foster homes (AFH). Using a two-stage sampling design, we recruited 31 AL/RC and 119 AFH in Oregon and completed face-to-face structured interviews with 227 and 195 residents, respectively. Residents provided ratings for both the importance of and their experience with 66 items that tapped into PCC practices in eight domains. Results are provided for each item, many of which are significantly associated with greater quality of life, better resident satisfaction, and fewer depressive symptoms, especially in the domains of personalized care and being treated like a person. Incongruence between importance and experience ratings indicate many residents experience unmet needs across multiple domains. The Resident VIEW performed well in different types of settings, providing an important tool for researchers and providers who wish to learn about the PCC experience from residents' points of view.

Prevalence of collusion in cancer communications: A meta-analysis.

Collusion is the non-disclosure of information about diagnosis or prognosis, frequently encountered in cancer care and palliative services. Unraveling collusion is a skill and differences among communication techniques by Health Care Workers have maintained the process of non-disclosure to patients and caregivers. Identifying the prevalence of collusion in cancer care is required to improve the existing strategies across the world. A systematic review of the literature from 1991 to 2020 in the English language was conducted with the protocol registration on PROSPERO ID (CRD 42021249216.) to identify the pooled prevalence of collusion. By using random effect model, the pooled prevalence estimate among patients for the diagnostic and prognostic collusion was 24.15, (95% CI [17.09; 32.96], Tou2=1.0801, I2 =97.9%, Cochran's Q=1058.22, df=21, p-value<0.001) and 37.92, (95% CI [22.46; 56.30], Tou2=1.9641, I2 =98.6%, Cochran's Q=944.26, df=13, p-value<0.001) respectively. There was no difference across subgroups with different types of setting for the interview, WHO regions and trend over the years. Substantial prevalence of collusion goes unnoticed in cancer care. A meaningful understanding of such a large prevalence requires inquiry into the existing communication paradigm in cancer care across the world. The findings also question the need of formulating uniform interview techniques and structured assessment tools or questionnaires in cancer care to improve the disclosure rates.

Conditional density estimation tools in python and R with applications to photometric redshifts and likelihood-free cosmological inference

It is well known in astronomy that propagating non-Gaussian prediction uncertainty in photometric redshift estimates is key to reducing bias in downstream cosmological analyses. Similarly, likelihood-free inference approaches, which are beginning to emerge as a tool for cosmological analysis, require a characterization of the full uncertainty landscape of the parameters of interest given observed data. However, most machine learning (ML) or training-based methods with open-source software target point prediction or classification, and hence fall short in quantifying uncertainty in complex regression and parameter inference settings. As an alternative to methods that focus on predicting the response (or parameters) $\mathbf{y}$ from features $\mathbf{x}$, we provide nonparametric conditional density estimation (CDE) tools for approximating and validating the entire probability density function (PDF) $\mathrm{p}(\mathbf{y}|\mathbf{x})$ of $\mathbf{y}$ given (i.e., conditional on) $\mathbf{x}$. As there is no one-size-fits-all CDE method, the goal of this work is to provide a comprehensive range of statistical tools and open-source software for nonparametric CDE and method assessment which can accommodate different types of settings and be easily fit to the problem at hand. Specifically, we introduce four CDE software packages in $\texttt{Python}$ and $\texttt{R}$ based on ML prediction methods adapted and optimized for CDE: $\texttt{NNKCDE}$, $\texttt{RFCDE}$, $\texttt{FlexCode}$, and $\texttt{DeepCDE}$. Furthermore, we present the $\texttt{cdetools}$ package, which includes functions for computing a CDE loss function for tuning and assessing the quality of individual PDFs, along with diagnostic functions. We provide sample code in $\texttt{Python}$ and $\texttt{R}$ as well as examples of applications to photometric redshift estimation and likelihood-free cosmological inference via CDE.

MPS-APO: a rapid and automatic parameter optimizer for multiple-point geostatistics

Multiple-point statistics (MPS) have been widely used in Earth and environmental sciences because of their ability to generate realistic stochastic realizations of complex natural processes. The spatial patterns and statistical information required for MPS modeling are represented by a training image. However, each MPS algorithm has a specific set of parameters that have a direct impact on the quality of pattern reproduction and should be chosen prior to the modeling. While there are some general guidelines for some MPS algorithms, a general parameter interference methodology is currently lacking. To date, the common practice for finding optimal parameters is to carry out a sensitivity analysis, which can be cumbersome especially in complex applications. In this study, we propose the MPS Automatic Parameter Optimizer (MPS-APO), a generic method based on stochastic optimization to rapidly approximate optimal parameters for any MPS method and different types of settings. The MPS-APO formulates an objective function that quantifies spatial pattern reproduction for each set of parameters. The Simultaneous Perturbation Stochastic Approximation (SPSA) optimization method is used because of its computational efficiency, and also its ability to cope with the stochastic nature of the objective function. The optimization proceeds in two steps. The first step aims to optimize the parameters for the best quality regardless of computational cost. When no more improvement can be achieved, the second step minimizes the CPU cost without degrading the spatial structures reproduction attained in the first step. In this study, MPS-APO is performed on different pixel-based and patch-based MPS methods: SNESIM, FILTERSIM, Direct Sampling and Image Quilting. Test cases show that MPS-APO is a useful heuristic to automatically approximate optimal parameters for good patterns reproduction with minimal computational cost. Therefore, it can help non-expert users and increase the usability of MPS methods for practical applications.

Pains of Imprisonment Beyond Prison Walls: Qualitative Research With Females Labelled as Not Criminally Responsible.

Research on the importation and deprivation models has focused almost exclusively on male inmates, and these models have not yet been studied in any setting other than prison. This research explores the importation and deprivation experiences of females labelled as not criminally responsible (FNCR). During the first part of the study, all the participants interviewed were in prison (n = 51). Follow-up interviews were carried out 18 months later, and while some participants were still in prison, others had been moved to (forensic or general) care. At that point, the study transcended the prison walls and extended its theoretical framework to forensic and general care facilities. In conclusion, the importation and deprivation framework, and the pains defined by Crewe, can be applied to FNCR in different types of setting. Most women were strongly affected by deprivations in prisons and in forensic care. Participants in forensic care sometimes felt more deprived than those in prison facilities.

Children and youth in out-of-home care: What can predict an initial change in placement?

A significant proportion of children placed in out of-home care experience placement disruptions in the United States. Placement instability has deleterious effects on children's well-being. (a) To measure the time-to-initial placement change in different types of settings, including non-relative foster homes, kinship care, residential treatment centers (RTC), group homes and other types of settings; and (b) To identify predictors of the initial placement change. Data were obtained from the State Automated Child Welfare Information System operated by the child welfare agency in a Mid-Atlantic state. The sample included 4177 children who entered into the foster care and were followed over three years. Descriptive, bivariate, and survival Cox regression models were conducted. More than half (53%) of the children had experienced placement change within 3 years. The mean length for an initial change in placement was longer for children in RTC and kinship care compared to children in foster and group homes, and other placements (χ2 = 322.31, p < 0.001). Several factors significantly increased the likelihood of an initial change, including: older children (p < 0.001, HR = 1.01), children with behavioral problems (p < 0.001, HR = 1.26), parental substance abuse (p < 0.05, HR = 1.12), and cases in which the parents voluntarily gave up their parental rights (p < 0.05, HR = 1.12). The type of placement also increased the risk for placement change. Providing early interventions and services to these children and their families is essential to increase placement stability.

How regulations of multidisciplinary diagnostic settings for children with a neurobiological developmental delay or disorder impact on integration of care: the case of Flanders, Belgium

Introduction: An early and fluent diagnostic trajectory, accessible for every child, is currently not guaranteed in Flanders despite the availability of different types of settings offering multidisciplinary diagnostics for neurobiological developmental delays or disorders NDDD. Regulative, organizational and work practice differences potentially impact on the development of collaborative networks guaranteeing accessible and integrated diagnostics, along the trajectories of children. Methods: Mapping the regulative frameworks at the federal and community levels for specialized multidisciplinary diagnostic teams for children with suspected NDDD in Flanders. Analysis of policy documents and legal frameworks of the centers for ambulatory rehabilitation CAR, centers for developmental disorders CDD, student guidance centers SGC, ambulatory mental health care centers MHC, autism reference centers ARC, ambulatory hospital services for pediatric neuropsychiatry APP. Results: Organizations are currently regulated by Federal or Community regulations. The different organizations providing multidisciplinary diagnostics for NDDD fall under different policy domains mental health, rehabilitation, hospitals, education. Federal regulations are more detailed and regulate more aspect than community regulations. For diagnostics at a CAR or MHC, children have to be referred. The regulations on target group facility for the CAR, ARC and MHC, is pathology-based; on CDD, SGC and APP more generally described. In a CAR, MHC and APP diagnostics aim at support and rehabilitation. Diagnostics at SGC aims at support, referral and coordination. ARC and CDD do clinical classifying diagnostics, referral and further coordination. The ARC uses a standardized protocol for diagnostics. The regulations on team composition numbers and disciplines are set for the CDD and MHC; more detailed rules are set for ARC, CAR, SGC and APP. Discussion: Literature on policy or mandated networks suggests that network approaches help to tackle complex problems, if settings offer complementary services and are mutually dependent to reach societal goals. The current confusion and ineffectiveness in the field is partly affected by regulations that do not promote collaboration and complementarity. Services were historically regulated specifically in different fields sectors. Those regulations do not refer to collaboration or cooperation. For the population, it is not clear what types of service are offered, how they differ from or overlap with each other, or for what purpose different organizations can be consulted. Conclusion: Regulations in public services impact on the organization of services and clinical practice. Current regulations in Flanders are not adapted to support network practice and an integrated way of providing accessible diagnostics along NDDD trajectories. Lessons learned: Current regulative frameworks for multidisciplinary diagnostics of NDDD are not adequately adapted to implement accessible and integrated care. The literature on mandated or policy networks urges to develop supportive regulative frameworks identifying complementarities of the different types of facilities. Limitations: Private, non-subsidized multidisciplinary settings are not included. Suggestions for future research: Additional health service research is needed on differences in organizational practice in the field of multidisciplinary diagnostics of NDDD, affecting network development, and on governance mechanisms supporting the development of integrated care. This should include research on factors affecting the accessibility of services.

Professional love is taking over our childcare settings

A recent conference talk, given by Dr Jools Page, gave my colleague and myself cause for reflection regarding the type of relationship we have with children and parents in different types of settings.

SOME NEW TYPES OF APPROXIMATIONS VIA MINIMAL STRUCTURE

In this paper, we use the notions of a minimal structure approximation space (short MSAS)and the notion of near open sets to introduce a new approximation of uncertain sets as a mathematicaltool to modify the approximations. Relationships between these types are established via proof andcounter examples. Also, some basic concepts of near approximations set are investigated and studied therelations between these different types of sets in MSAS. This set is a specific importance to help withthe modifications of an approximation space via adding new concepts and facts. Finally, we use thisconcept to introduce the definitions of near lower approximation, near upper approximation, nearboundary region, near rough and near exact sets and study some of the properties of this notion.

Parametric Point Estimation of the Geeta Distribution

Geeta distribution is a new discrete random variable distribution defined over all the positive integers with two parameters. This distribution belongs to the family of Location-parameter (LDPD) system and is of the form L – shaped model. Pareto and Yule distributions belong to the same family but these distributions have a disadvantage of having a single parameter which makes them not versatile to meet the needs of modern complex data sets. Geeta distribution is found to be very versatile and flexible to fit observed count data sets and can be used efficiently to model different types of sets. This paper investigates the characteristics of Geeta distribution, such as the existence of the mean, variance, moment generating function, probability generating function and that the sum of probabilities for all values of X for Geeta Distribution model is unity. It is well known that the sample mean is the estimator of a population mean from a given population of interest as a point estimator which assume a single number that is obtained by taking a random sample of a specified size from the entire population, depending on whether the population mean and variance is known or unknown These point estimators were obtained by employing the method of Moments, Maximum Likelihood (MLE) and Bayesian estimator. Further the estimators were subjected to the conditions like unbiasedness, efficiency, sufficiency and completeness which are properties of a good estimator. For the first aspect, the results of the mean, variance, moments and generating functions were achieved that proves the distribution is a probability density function (pdf). The methods of moments and the maximum likelihood and their properties were applied and yielded the desired and expected results for any given probability distribution. The best estimator obtained is best linear unbiased estimator (BLUE).