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In this article, we use Simulated Implicit Likelihood Estimation (SimILE) to analyze summary statistics, the sample mean and variance of lognormally distributed replicates, when only these summarie...

In estimation of a mean vector, consider the case that the mean vector is suspected to be in one or two general linear subspaces. Then it is reasonable to shrink a sample mean vector toward the res...

Objective: To determine life satisfaction in old age people attending Fauji Foundation Hospital and to assess relationship of socio-demographic variables on life satisfaction of old aged people. Study Design: Cross sectional study. Place and Duration of Study: Fauji Foundation Hospital Rawalpindi from Feb to Aug 2018. Methodology: A total of 347 individuals were included by using non-probability consecutive sampling. The participants of the 60 years or more attending Fauji foundation hospital, being mentally sound and having comprehensive under-standing without hearing aid were included in the study. Questionnaire was given to respondents including demographic profile and Urdu version of Life Satisfaction Scale for assessing the life satisfaction in old age. Results: The total sample mean life satisfaction score was 14.95 ± 6.54. 5 (1.5%) people were extremely satisfied, 27 (8.4%) were satisfied, 117 (36 %) were dissatisfied and 63 (19.1%) were extremely dissatisfied. Conclusion: Life satisfaction was found statistically significant with female gender, older age 70-80 years, being un married, primary education, monthly income of less than 10,000 and being unemployed.

We consider a non-stationary two-armed bandit framework and propose a change-detection-based Thompson sampling (TS) algorithm, named TS with change-detection (TS-CD), to keep track of the dynamic environment. The non-stationarity is modeled using a Poisson arrival process, which changes the mean of the rewards on each arrival. The proposed strategy compares the empirical mean of the recent rewards of an arm with the estimate of the mean of the rewards from its history. It detects a change when the empirical mean deviates from the mean estimate by a value larger than a threshold. Then, we characterize the lower bound on the duration of the time-window for which the bandit framework must remain stationary for TS-CD to successfully detect a change when it occurs. Consequently, our results highlight an upper bound on the parameter for the Poisson arrival process, for which the TS-CD achieves asymptotic regret optimality with high probability. Finally, we validate the efficacy of TS-CD by testing it for edge-control of radio access technique (RAT)-selection in a wireless network. Our results show that TS-CD not only outperforms the classical max-power RAT selection strategy but also other actively adaptive and passively adaptive bandit algorithms that are designed for non-stationary environments.

This study aims to determine the relationship between self-esteem and subjective well being, the relationship between optimism and subjective well being, the relationship between self-esteem and optimism with subjective well being in the ASN of the Department of Women's Empowerment and Child Protection. This study uses a quantitative approach. The population in this study were 86 State Civil Servants using the total sampling technique. Based on data analysis, it is found that the hypothesis proposed in this study is accepted. This is evidenced by the calculation of multiple regression analysis, it can be seen with the correlation coefficient value rx1y = 0.895 with p = 0.000. This means that there is a significant positive relationship with self-esteem and subjective well being, the coefficient of rx2y = 0.950 with p = 0.000. This means that there is a significant positive relationship between optimism and subjective well being. Furthermore, based on the results of the analysis, the correlation coefficient value of rX1-X2-Y = 0.965 with p = 0.000 is obtained. This means that there is a relationship between self-esteem and optimism with subjective well being. The total contribution of self-esteem to optimism with subjective well being is 93.1%. These results show through the hypothetical mean of self-esteem (82.5 empirical mean 98.92). Optimism classified as high (hypothetical mean 65 empirical mean 80.50). Meanwhile, Subjective well being is classified as high (hypothetical mean 62.5 empirical mean 72.41.

Background More than one-half of U.S. states have enacted Earned Income Tax Credit (EITC) programs. Yet little is known about the effects of state EITC programs on the health of recipients. This study examines the effects of refundable and nonrefundable state EITC programs on the health of single low-educated women of childbearing age with two or more children, the group receiving the highest credits on average. Methods The data come from the Behavioral Risk Factors Surveillance Survey from 1993 through 2018. Outcomes include self-rated general health, days not in good physical health, and days not in good mental health, both in the past 30 days. The research design accounts for time-invariant differences between states, national trends shared across states, and other state policies. Results Depending on the outcome measure, the analytical sample ranges between 103,362 and 107,782 mothers. Refundable state EITC programs are associated with improvements in all three health outcomes. A 10 percentage-point increase in refundable state EITC is associated with better self-rated health by 0.02 points (95% confidence interval [CI], 0.006–0.04) on a 1- to 5-point scale, or 0.7% improvement above the sample mean; 0.2 fewer days not in good physical health (95% CI, –0.21 to –0.12) in the past 30 days, or 4.4% lower than the sample mean; and 0.2 fewer days not in good mental health (95% CI, –0.29 to –0.1), or 3.4% lower than the sample mean. Estimates for nonrefundable EITC programs are smaller and not statistically significant. As expected, there are small and statistically insignificant refundable EITC effects for single low-educated childless women who receive low state EITC benefits on average. Conclusions These findings suggest that an increase in refundable state EITC improves the health of single women of childbearing age with low incomes and two or more children; this factor may also lead to better preconception health. There is no evidence for effects from nonrefundable state EITC.

It is well known that the independence of the sample mean and the sample variance characterizes the normal distribution. By using Anosov's theorem, we further investigate the analogous characteristic properties in terms of the sample mean and some feasible definite statistics. The latter statistics introduced in this paper for the first time are based on nonnegative, definite and continuous functions of ordered arguments with positive degree of homogeneity. The proposed approach seems to be natural and can be used to derive easily characterization results for many feasible definite statistics, such as known characterizations involving the sample variance, sample range as well as Gini's mean difference., Comment: 18 pages

This paper analyzes the relationship between crop market integration and the use of modern inputs of farmers in developing countries. For this purpose, we used a large-scale household dataset collected in rural Burkina Faso. We found evidence that there is a negative association between the use of yield-increasing inputs by farmers and low crop market integration. An increase of the spatial price dispersion by 10% is significantly associated with a decrease in the probability of using modern inputs by 0.04 points and a decrease in the intensity of adoption by 12.5% approximately relative to the sample mean. Moreover, the results suggest that this association is stronger for farmers who previously adopted these inputs. Accompanying the promotion of modern inputs with market development measures can help increase its chance of success.

Within this pandemic associated with Covid-19, psychological health occupies a prominent place as a result of a situation of forced isolation. Impacts can lead to an increase in mental health disorders as well as a set of adaptive reactions inherent to the recovery. Cooperation is conceived as the ability to jointly operationalize knowledge, attitudes and skills with a view to achieving a common purpose; and assertiveness is conceived as a bilateral behaviour that emphasizes the importance of considering the desires, thoughts and feelings of both the sender and the recipient of the assertive message, predictive of academic success. In this line, the main objective of this study is to present the results of the application of the Global Cooperation Assessment Scale (EAGC) and the findings levels of the Global Assertiveness Assessment Scale (EAGA). The study used a non-probabilistic sample for convenience of 101 Portuguese higher education students. EAGC and EAGA are a self-registration closed-ended Likert type 5 points, closed-response scales that allows assessing the degree of competence in respondents' cooperation and assertiveness. Both scales were administered online in spring semester 2019/2020, with the link to the questionnaire being made available to students the computer platform ensuring the response of a single survey per respondent whose participation in the study was voluntary. The treatment of the information, as well as its statistical analysis, was supported by the R software (R Core Team, 2020), having been assured the confidentiality and anonymity of the respondents. Sociodemographic variables were also used, which seemed promising in contextualizing, interpreting, and discussing the results. The value of the sample mean obtained at EAGC=35 (± 6.5), thus revealing a high capacity for cooperation and in the EAGA=31 (± 5.53), thus revealing a high assertive competence who attend higher education. RESUMEN Dentro de esta pandemia asociada a Covid-19, la salud psicologica ocupa un lugar destacado como consecuencia de una situacion de aislamiento forzoso. Los impactos pueden conducir a un aumento de los trastornos de salud mental, asi como a un conjunto de reacciones adaptativas inherentes a la recuperacion. La cooperacion se concibe como la capacidad de operacionalizar conjuntamente conocimientos, actitudes y habilidades con vistas a lograr un proposito comun; y la asertividad se concibe como un comportamiento bilateral que enfatiza la importancia de considerar los deseos, pensamientos y sentimientos tanto del emisor como del receptor del mensaje asertivo, predictor del exito academico. En esta linea, el objetivo principal de este estudio es presentar los resultados de la aplicacion de la Escala de Evaluacion de la Cooperacion Global (EAGC) y los niveles de hallazgos de la Escala de Evaluacion de la Asertividad Global (EAGA). El estudio utilizo una muestra no probabilistica por conveniencia de 101 estudiantes portugueses de educacion superior. El EAGC y el EAGA son escalas de autorregistro cerrado tipo Likert de 5 puntos, de respuesta cerrada, que permiten evaluar el grado de competencia en cooperacion y asertividad de los encuestados. Ambas escalas se administraron online en el semestre de primavera 2019/2020, poniendo a disposicion de los estudiantes el enlace al cuestionario la plataforma informatica que aseguraba la respuesta de una unica encuesta por encuestado cuya participacion en el estudio era voluntaria. El tratamiento de la informacion, asi como su analisis estadistico, se apoyo en el software R (R Core Team, 2020), habiendose asegurado la confidencialidad y el anonimato de los encuestados. Tambien se utilizaron variables sociodemograficas, que parecian prometedoras para contextualizar, interpretar y discutir los resultados. El valor de la media de la muestra obtenida en el EAGC=35 (± 6,5), revelando asi una alta capacidad de cooperacion y en el EAGA=31 (± 5,53), revelando asi una alta competencia asertiva que cursan estudios superiores.

This study aims to empirically determine the description of organizational commitment to MTs Al-Islamiyah Karang Anyar teachers. The sampling technique was carried out by total sampling technique and got 43 samples. The research instrument used was the organizational commitment scale. This type of research is quantitative research with descriptive and comparative models. The data analysis technique used is the one sample t-test. Researchers hypothesized that married teachers would tend to have higher organizational commitment than unmarried teachers. The results showed that the organizational commitment of the teachers was generally high. In accordance with the proposed hypothesis, it is said that there is a difference in organizational commitment between teachers who are married and teachers who are not married. The t-test results obtained were p = 0.000 (p

Adults can do sexual bullying that leads to aspects of sexuality physically or non-physically and occurs repeatedly. This study aims to determine the level of sexual bullying behavior in early adult in Kupang, totaling 373 participants aged 18-25. The hypothesis is that early adult individuals tend to have high sexual bullying behavior. Collecting data using the Likert scale Sexual Bullying - ASBAE and distributed online, then analyzed using descriptive statistical techniques using SPSS 16.0 software and Microfost Excel 2010. The test results show sexual bullying has a Cronbach alpha value in the range of 0.960-0.966. The results showed that early adult individuals in the city of Kupang had sexual bullying behavior and dimensions of sexual bullying tended to be low because the empirical mean was smaller than the theoretical means. Finally, gender also influenced the level of sexual bullying behavior and the dimensions of sexual bullying for early adults.

In the formulation of dried sweet sausage, pork meat and fat are traditionally used, which can be replaced by healthy products such as pecans (Carya illinoinensis) and kañiwa (Chenopodium pallidicaule); as well as llama meat (Lama glama) that is low in fat and cholesterol. For this reason, the present investigation aimed to optimize a formulation of dried sweet sausage considering three main components: llama meat, kañiwa flour and pecans. The D-Optimal mixture design method of the Design-Expert®7 program was applied, obtaining fourteen formulations. For each formulation, color, water activity and texture profile were evaluated. Only the cohesiveness fit a meaningful mathematical model. Subsequently, the optimization of the variable response was carried out, using the desirability function of the "objective value" type, so that the product could resemble the target (sausage made with pork meat and fat). In the sensory analysis of the optimal formulation, four sensory attributes were evaluated: color, odor, taste and texture, in a Z test to demonstrate whether the sample mean of the degree of satisfaction for each attribute of the product was acceptable or not. All these attributes are believed to be above the population mean taken as a target. In conclusion, the optimal formula was composed of 80% llama meat and 20% pecans, observing that kañiwa flour did not improve the texture and color of the sausage.

We consider the problem of estimation of the hazard rate from a selected gamma population. Let $$\Pi _{1}$$ , $$\Pi _{2}$$ be two populations, where $$\Pi _{i}$$ follows an one parameter gamma distribution with hazard rate $$\lambda _{i}$$ , $$i=1,2$$ . Let $$ X_{i1},X_{i2},\ldots ,X_{in}$$ be an independent random sample drawn from the population $$\Pi _{i}$$ , $$i=1,2$$ . Consider $$ X_{i}={\sum _{j=1}}^{n}X_{ij} $$ to be the sample mean of the ith population The natural selection rule is to select the population with largest(smallest) mean. That is $$\Pi _{i}$$ if $$X_{i}=max(min)(X_{1},X_{2})$$ . Some natural estimator are proposed and it was shown that they are admissible within a class of estimators with respect to the entropy loss. Further some improved estimators are obtained which improves upon the natural estimators.

Control charts based on the sample mean X¯ are used for monitoring shifts in the process mean under the assumption that the process standard deviation is stable or well estimated. However, in many ...

Traditional static threshold–based state analysis methods can be applied to specific signal-to-noise ratio situations but may present poor performance in the presence of large sizes and complexity of power system. In this article, an improved maximum eigenvalue sample covariance matrix algorithm is proposed, where a Marchenko–Pastur law–based dynamic threshold is introduced by taking all the eigenvalues exceeding the supremum into account for different signal-to-noise ratio situations, to improve the calculation efficiency and widen the application fields of existing methods. The comparison analysis based on IEEE 39-Bus system shows that the proposed algorithm outperforms the existing solutions in terms of calculation speed, anti-interference ability, and universality to different signal-to-noise ratio situations.

Background Growing evidence suggests that emotion dysregulation may be predictive of posttraumatic stress disorder (PTSD) severity, with emotional non-acceptance, lack of counter strategies, impulse control deficits, and lack of emotional awareness all being positive predictors. However, findings have been mixed. This may be due to no previous study examining the association between emotion dysregulation and PTSD severity with shame, a maintaining factor of PTSD, as a potential moderator. Methods The present study examined the relationship between emotion dysregulation, shame, and PTSD severity among 78 male combat veterans (mean age = 42.19) upon their admission to a residential combat PTSD program. Results Results demonstrated that shame and all facets of emotion dysregulation (except lack of emotional awareness & clarity) were positively associated with PTSD severity. Shame moderated the relationship between lack of emotional awareness and strategies. Among those at or below the sample mean on shame, lack of access to strategies was a positive predictor of PTSD severity. Comparatively, among those with high levels of shame, emotional awareness predicted greater PTSD severity, while among those with low levels of shame, emotional awareness predicted lower PTSD severity. Limitations Limitations included reliance on self-report questionnaires and an all-male sample. Conclusions Thus, emotion dysregulation may only predict PTSD severity among those reporting lower levels of shame, suggesting the importance of addressing shame as well as emotion dysregulation deficits among those with PTSD. Moreover, emotional awareness may be either a risk or protective factor depending on levels of shame.

The Shewhart median (denoted as X˜) chart can be used in place of the Shewhart X¯ chart for detecting mean shifts when outliers are present because the sample mean is easily affected by outliers. H...

Motivated by the practical needs of simulation-based optimization, this paper considers a problem for selecting the best feasible design from a finite set of alternatives, subject to stochastic constraints given in several secondary objectives. We propose an efficient ranking and selection procedure that maximizes the accuracy of the selection under a limited simulation budget. The proposed procedure sequentially updates the simulation data of designs with a heuristic policy that allocates further simulation replications according to the evaluation results of data based on a statistical hypothesis test. Compared to recent studies, such as OCBA-CO and SCORE, this procedure can be more efficient when the simulation model involves large stochastic noise because its heuristic policy considers the precision of the sample mean ignored by the previous studies. Several experimental results of benchmarks demonstrate its improved efficiency, and a case study on the design of military network system shows its effectiveness for practical problems.

We use large-scale federal survey data linked to administrative death records to investigate the relationship between Medicaid enrollment and mortality. Our analysis compares changes in mortality for near-elderly adults in states with and without Affordable Care Act Medicaid expansions. We identify adults most likely to benefit using survey information on socioeconomic status, citizenship status, and public program participation. We find that prior to the ACA expansions, mortality rates across expansion and nonexpansion states trended similarly, but beginning in the first year of the policy, there were significant reductions in mortality in states that opted to expand relative to nonexpanders. Individuals in expansion states experienced a 0.132 percentage point decline in annual mortality, a 9.4% reduction over the sample mean, as a result of the Medicaid expansions. The effect is driven by a reduction in disease-related deaths and grows over time. A variety of alternative specifications, methods of inference, placebo tests, and sample definitions confirm our main result.

We derive the form of the variance-covariance matrix for any affine equivariant matrix-valued statistics when sampling from complex elliptical distributions. We then use this result to derive the variance-covariance matrix of the sample covariance matrix (SCM) as well as its theoretical mean squared error (MSE) when finite fourth-order moments exist. Finally, illustrative examples of the formulas are presented.

The sound fields generated by ultrasonic transducers are modeled using the quasi-Monte Carlo (QMC) method, which is found to overcome the conflict between accuracy and efficiency that occurs in existing wave field calculation methods. The RI equation, which is frequently used as a model equation in ultrasonic field calculation, is used here as an exact method and for comparison purposes. In the QMC method, the judgment sampling method and Halton sequence are used for pseudo-random sampling from the sound source, and then the sound field distributions are found by solving the integral solution using the sample mean. Numerical examples and results are presented when modeling unfocused, focused, and steered and focused beam fields. The accuracy and efficiency of the QMC method are discussed by comparing the results obtained using different modeling methods. The results show that the proposed method has a high level of efficiency due to the nature of the QMC algorithm and a high level of accuracy because no approximation is required. In addition, wave fields can be modeled with the QMC method as long as sound sources can be effectively pseudo-randomly sampled, allowing the proposed method to be applied to various types of transducers.

In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme noise using Deep Learning (DL). In particular, we introduce a Convolutional Neural Network (CNN) that predicts angular directions using the sample covariance matrix estimate. The network is trained from multi-channel data of the true array manifold matrix in the low signal-to-noise-ratio (SNR) regime. By adopting an on-grid approach, we model the problem as a multi-label classification task and train the CNN to predict DoAs across all SNRs. The proposed architecture demonstrates enhanced robustness in the presence of noise, and resilience to a relatively small number of snapshots. Moreover, it is able to resolve angles within the grid resolution. Experimental results demonstrate significant performance gains in the low-SNR regime compared to state-of-the-art methods and without the requirement of any parameter tuning in both cases of correlated and uncorrelated sources. Finally, we relax the assumption that the number of sources is known a priori and present a training method, where the CNN learns to infer their number and predict the DoAs with high confidence. The increased robustness of the proposed solution is highly desirable in challenging scenarios that arise in several fields, ranging from wireless array sensors to acoustic microphones or sonars.

Activities involving the use of several media simultaneously or alternately while working on a task are even better known as multitasking behavior in using media (media multitasking). This study aims to describe the behavior of multitasking in using media for students at the University of Nusa Cendana (Undana). The approach used is a quantitative approach with a descriptive research type. The data collection technique used the MMM-S Likert scale with the results of the measuring instrument trial showing the Cronbach alpha scale value of 0.856. The research respondents were 395 Undana students. The results of the study found that Undana students showed high multitasking behavior in using media because the empirical mean was greater than the hypothetical mean (40.17> 30), with a low category of 39 people, medium 132 people, and high as many as 224 people. Multitasking behavior in using the media is known to be 4.24 times more women respondents than men, in the age range 22-25 years, 1.64 times more than those aged 18-21 years, while based on where the respondents live in 1.32 times more households than living in a boarding house.

We consider a supercritical branching Lévy process on the real line. Under mild moment assumptions on the number of offspring and their displacements, we prove a second-order limit theorem on the empirical mean position.

In this article, a difference-coarray-based direction of arrival (DOA) method is introduced, which utilizes the uniform linear array (ULA) in a novel fashion to address the problem of DOA estimation for coherent signals. Inspired by the coarray-based estimators employed in cases of sparse arrays, we convert the sample covariance matrix of the observed signals into the difference coarray domain and process the signals using a spatial smoothing technique. The proposed method exhibits good accuracy and robustness in both the uncorrelated and coherent cases. Numerical simulations verify that the ULA difference coarray- (UDC-) based method can achieve good DOA estimation accuracy even when the SNR is very low. In addition, the UDC-based method is insensitive to the number of snapshots. Under extremely challenging conditions, the proposed UDC-ES-DOA method is preferred because of its outstanding robustness, while the UDC-MUSIC method is suitable for most moderate cases of lower complexity. Due to its demonstrated advantages, the proposed method is a promising and competitive solution for practical DOA estimation, especially for low-SNR or snapshot-limited applications.

For q-dimensional data, penalized versions of the sample covariance matrix are important when the sample size is small or modest relative to q. Since the negative log-likelihood under multivariate ...

The decline in Lake Urmia (LU) water level during the past two decades has been addressed by several studies. However, the conducted studies could not come across a practical solution by considering the sample mean in the lake water level time series. For this, the present study suggests a fresh look to the lake water level decline in LU by addressing the volatility changes instead. The Bayesian change-point detection method was used to define the major and critical change points during the study period from January 1966 to December 2016 on a daily scale. Results indicated that major changes occurred in early 2000, and the time series can be studied under the pre- and post-change point events. Afterward, several methods namely shift-track and mono- and multiple-trend line analyses were used to remove the trends associated with the lake water level time series. The de-trending approaches later were applied separately for the entire study period, before 2000 (i.e., 1966–1999) and afterward (i.e., 2000–2016). Then, the de-trended time series were used, and a generalized autoregressive conditional heteroscedasticity (GARCH) model was fitted to the de-trended time series to predict the volatility changes in the data run. Results indicated to descending and ascending changes, respectively, in short- and long-term persistence after 2000. The GARCH(1,1) model was found to be satisfactory to interpret the pre- and post-turn point events, while the changes in short- and the long-term persistence were calculated as 0.53 to 0.75 and 0.46 to 0.24, respectively. In addition, by considering the lake water level anomaly and coefficient of variation in LU and two neighboring cases of Lake Sevan and Lake Van, it is concluded that the changes are exclusive to LU, and the rate of changes was accelerated after 2006.

Stochastic simulation is beneficial when evaluating the performance of a complex system. When optimizing the system performance with the simulation, we need to make a final decision by considering various qualitative criteria neglected by the simulation as well as the simulation results. However, as simulations are expensive and time-consuming, in this paper, we propose a ranking and selection algorithm to make such optimization with the simulation efficient. The proposed algorithm selects a best-subset of designs expected to optimize the system performance from a finite set of alternatives. Furthermore, the algorithm identifies the ranking of designs within the subset. To maximize the accuracy of the selection under limited simulation resources, the algorithm selectively and gradually increases the precision of the sample mean of each design by allocating the resources heuristically based on the evaluated uncertainty. The selected subset allows decision makers to efficiently choose the best design that optimizes the performance while satisfying the qualitative criteria. We exhibit various experimental results, including a practical case study, to empirically demonstrate the efficiency and high noise robustness of the proposed algorithm.

Direct displacement-based design (DDBD) approach attempts to alleviate the shortcomings of force-based design (FBD) approach to achieve seismic resistance of structures. Many simplified procedures for DDBD proposed in the literature are conceptually similar, yet differ in their considerations for crucial parameters such as target displacement profile, equivalent viscous damping equation and base shear distribution pattern in the design process. Due to variation in the aforementioned parameters, seismic force, their distribution and element design differs, leading to significant changes in the inelastic behavior of the building. The present numerical study compares the performance of low, medium and high-rise RC frame buildings designed using six DDBD approaches for two drift levels. The seismic performance of the considered buildings has been deliberated by both nonlinear static pushover as well as nonlinear dynamic time-history methods. From analysis results, it is observed that the 84th percentile of the sample mean storey displacement of low-rise buildings designed for low storey drift exceeds the target profile, whereas, this behavior is contrary in high-rise buildings designed for higher storey drift. The analysis also highlighted that the parabolic displacement profile consideration for mid and high-rise buildings is rational than the linear displacement profile consideration. In the present case, it seems that equivalent viscous damping estimation and displacement spectra modification factors are conservative for all the DDBD approaches and needs modification to improve its rationality.

The Pietra-Ricci index is often used in economic and social sciences as a measure of inequality. In this Correspondence, the index is adapted to the cooperative spectrum sensing scenario, yielding the Pietra-Ricci index detector (PRIDe). The PRIDe applies the index to distinguish the shapes of the received signal sample covariance matrices in the situations of presence and absence of the primary sensed signal. It is shown that the PRIDe is very simple, is robust against time-varying noise and received signal powers, exhibits the constant false alarm rate property, and outperforms state-of-the-art detectors in many situations.

Coprime array exhibits many advantages over the uniform linear array (ULA) with the same number of physical sensors in resolution performance and interference suppression capability. In this study, the authors take the advantages of coprime array to improve the robustness of adaptive beamformer. In the coprime virtual ULA (CV-ULA), they prove that a constructed Toeplitz matrix can be taken as the sample covariance matrix from the perspective of virtual signal characteristics. The CV-ULA Capon spectrum estimator is modified to obtain the directions and powers of all impinging signals. Since the real directions of all impinging signals are located at different angular sectors, they form independent signal subspace for each impinging signal. They also assign independent steering vector mismatches for different impinging signals to obtain their real steering vectors. The steering vector mismatch of each impinging signal is independently obtained by solving its own convex optimisation problem. They reconstruct the interference-plus-noise covariance matrix (INCM) with precise steering vectors and powers of interference signals. The proposed weight vector is computed by combining the desired signal steering vector and the reconstructed INCM. Extensive simulations show that the proposed algorithm provides robustness against many types of model mismatches.

This paper describes some proficient estimation procedures in the presence of multi-auxiliary variables to enhance the precision of estimates in two-occasion rotation sampling. Utilizing information on several auxiliary variables, which are considered to be a positive correlation with the study variables on both occasions, we have suggested some better estimation procedures. The behaviors of the proposed estimation strategies have been examined along with the discussion of optimum replacement strategies, and the results obtained in these estimation procedures are demonstrated numerically through empirical and simulation studies, which present the supremacy in efficiencies of the proposed estimation procedures over the sample mean estimator, natural successive sampling estimator and recently developed estimator.

The weighting subspace fitting (WSF) algorithm performs better than the multi-signal classification (MUSIC) algorithm in the case of low signal-to-noise ratio (SNR) and when signals are correlated. In this study, we use the random matrix theory (RMT) to improve WSF. RMT focuses on the asymptotic behavior of eigenvalues and eigenvectors of random matrices with dimensions of matrices increasing at the same rate. The approximative first-order perturbation is applied in WSF when calculating statistics of the eigenvectors of sample covariance. Using the asymptotic results of the norm of the projection from the sample covariance matrix signal subspace onto the real signal in the random matrix theory, the method of calculating WSF is obtained. Numerical results are shown to prove the superiority of RMT in scenarios with few snapshots and a low SNR.

Endogamy or intra-caste marriage is one of the most resilient of all the caste based practices in India. Even in 2011, the rate of inter caste marriages in India was as low as 5.82%. In this paper we explore whether education has any relationship with this age-old practice of marrying within one’s own caste. Using a nationally representative data set, the Indian Human Development Survey, we find that, in sharp contrast with the findings in the existing literature on out-marriages in the Western countries, education levels of the spouses themselves do not have any association with the likelihood of their own marriage being an inter caste one. However, couples with a more educated mother of the husband have a significantly higher probability of being in an inter caste marriage. One standard deviation increase in the years of education of the husband’s mother is associated with a 10.16% increase in the probability of inter caste marriage over the sample mean. Our analysis highlights the importance of recognizing the institution of arranged marriages in any analysis of Indian marriage markets.

This study aims to find The Correlation between Social Environment and Self-Esteem on Teenagers at Al Jam’iyatul Washliyah Orphanage in Binjai. The subject were 56 teenagers who lived in the orphanage. The sample was collected by using total sampling technique. The data was collected by using social environment and self-esteem scales. The data was analyzed by using correlation technique (rxy) in the amount of 0,792 with p = 0,000 < 0,050 which means there was a positive and significant relationship between social environment and self-esteem, it showed that the better the social environment, the higher self-esteem. Conversely, the worse the environment, the lower self-esteem. Social environment in this study was classified as high, due to (empirical mean = 111,32 > hypothetical mean = 90 where the difference exceeds the numbers of SD = 13,087). Self-esteem was also classified as high, due to (empirical mean = 120,68 > hypothetical mean = 95 where the difference exceeds the numbers of SD = 13,051). Coefficient of determination and correlation was r2 = 0,627 which means the social environment contributed 62,7% to self-esteem. Based on this study, there were still 37,3% influence of the other factors which weren’t revealed in this study.

Semantic segmentation is one of the main steps in the processing chain for Airborne Laser Scanning (ALS) point clouds, but it is also one of the most labour intensive steps, as it requires many labelled examples to train a classifier. National mapping agencies (NMAs) have to acquire nationwide ALS data every couple of years for their duties. Having point clouds cover different terrains such as flat or mountainous regions, a classifier often requires a refinement using additional data from those specific terrains. In this study, we present an algorithm, which is able to classify point clouds of similar terrain types without requiring any additional training data and which is still able to achieve overall F1-Scores of over 90% in most setups. Our algorithm uses up to two height distributions within a single cell in a rasterized point cloud. For each distribution, the empirical mean and standard deviation are calculated, which are the input for a Convolutional Neural Network (CNN) classifier. Consequently, our approach only requires the geometry of point clouds, which enables also the usage of the same network structure for point clouds from other sensor systems such as Dense Image Matching. Since the mean ground level varies with the observed area, we also examined five different normalisation methods for our input in order to reduce the ground influence on the point clouds and thus increase its transferability towards other datasets. We test our trained networks on four different tests sets with the classes’ ground, building, water, non-ground and bridge.

Although issues about the economic spillovers from transport infrastructure have been discussed and debated for decades, a great deal of controversy concerning the direction and magnitude of the economic effects of transport infrastructure remains, and the empirical evidence of those effects in emerging economies is still insufficient. In this study, based on a sample of Chinese manufacturing firms during the period 1998–2007, we employed a method combining the difference‐in‐differences approach with the propensity scoring matching technique to research the effects of improvements in transport infrastructure on firm productivity. With highways used as a typical example of transport infrastructure, the results suggested that a connection to highways boosted firm productivity by an average of 0.043, or approximately 0.74% of the sample mean. Moreover, this study provided evidence that the effects of improvements in transport infrastructure on firm productivity were stronger in industries producing nondurable goods and driven by an increase in firm innovation. This study’s findings contribute to a reconciliation of the controversy concerning the economic effects of transport infrastructure and enrich the empirical evidence of that effect in emerging economies.

Objective:Sleep deprivation is common among both college students and athletes and has been correlated with negative health outcomes, including worse cognition. As such, the current study sought to examine the relationship between sleep difficulties and self-reported symptoms and objective neuropsychological performance at baseline and post-concussion in collegiate athletes.Method:Seven hundred seventy-two collegiate athletes completed a comprehensive neuropsychological test battery at baseline and/or post-concussion. Athletes were separated into two groups based on the amount of sleep the night prior to testing. The sleep duration cutoffs for these group were empirically determined by sample mean and standard deviation (M= 7.07,SD= 1.29).Results:Compared with athletes getting sufficient sleep, those getting insufficient sleep the night prior to baseline reported significantly more overall symptoms and more symptoms from each of the five symptom clusters of the Post-Concussion Symptom Scale. However, there were no significant differences on objective performance indices. Secondly, there were no significant differences on any of the outcome measures, except for sleep symptoms and headache, between athletes getting insufficient sleep at baseline and those getting sufficient sleep post-concussion.Conclusion:Overall, the effect of insufficient sleep at baseline can make an athlete appear similar to a concussed athlete with sufficient sleep. As such, athletes completing a baseline assessment following insufficient sleep could be underperforming cognitively and reporting elevated symptoms that would skew post-concussion comparisons. Therefore, there may need to be consideration of prior night’s sleep when determining whether a baseline can be used as a valid comparison.

This study aims to determine and analyze the differences and the effect of production on the income of plasma palm oil farmers who are independently managed and managed in the core of PT. Pinago Utama. This research method uses a quantitative approach, the type of research is a survey. The sample was determined by 60 stratified random sampling methods. Data were analyzed using the independent sample mean difference test and simple linear regression. The results showed that there was an insignificant difference in the production of oil palm smallholdings managed by nucleus and those managed independently by farmers. However, there are significant differences in farmers' incomes, production costs and the cost of production of plasma oil palm estates managed by the nucleus and those managed by farmers independently. The cost of production of the nucleus estate managed by the nucleus is Rp. 576.65 / kg 39.17% lower than smallholdings which are managed independently by farmers (Rp. 947.95 / kg). Changes in production obtained by farmers have a significant effect on changes in income, both for estates managed by the nucleus and those managed independently by farmers. Thus there is a difference in the effect of production on farmers' income by almost 50% (49.88%)

It is proved that a sign network with an elliptical distribution with known shift parameter is equivalent to a sign network with elliptical distribution with unknown shift parameter estimated by sample mean. This result is proved for the case of independent identically distributed observations and for the case of sample from a matrix elliptically contoured distribution with any dependence between observations.

The aim of the study is to find out the relationship emotional Intelligence with Conflict Management in Employees of Pt. Aspacindo Kedaton Motor. The research approach used in this study is a quantitative approach using correlation or relationship tests. Correlation research is research that aims to investigate the extent to which variations in one variable are related to variations in one or more other variables. The result of research on employees who have high conflict management and emotional intelligence are also classified as high. This can be seen from the SD results of 6.056, the hypothetical mean value of conflict management at 62.5, and the empirical mean of 74.66. Furthermore, the results of elementary emotional emotional intelligence amounted to 10.38, the mean hypothetical value was 72.5 and the empirical mean was 88.82.

With the emerging of sparsely spaced sensor arrays, the study on underdetermined direction-of-arrival (DOA) estimation methods has drawn much attention. In most of the existing methods, the vectorized sample covariance matrix was considered as circularly symmetric Gaussian by default. However, the sample covariance vector is in fact noncircular, and its pseudo covariance matrix has not yet been utilized for underdetermined DOA estimation. On account of the wide usage of wideband signals nowadays, in this letter, the underdetermined DOA estimation problem for wideband signals is addressed, where the noncircularity of the sample covariance vectors is exploited. Moreover, a hierarchical Bayesian model is established, modeling the noncircular sample covariance vectors, the nonnegative group-sparse signal variance vectors, the auto-estimated regularization parameter and the off-grid difference, which were not considered simultaneously in the existing methods. A sparse Bayesian learning algorithm is derived via expectation-maximization, and numerical simulations show that the proposed method outperforms the methods that do not consider the noncircularity of sample covariance vectors.

We estimate the causal impact of criminal activity nuisance ordinances on tenant evictions and eviction filings. These ordinances penalize property owners when certain types of illegal activity occur on or near their property, reported primarily through 911 calls. We exploit the staggered implementation of laws by municipalities and estimate the treatment effect on eviction outcomes using a difference-in-difference framework. The results show that criminal activity nuisance ordinances increase eviction filing rates by about 16 percent of the sample mean and court ordered evictions by 14 percent of the sample mean.

Robust estimation of location for data on the unit sphere Sp−1 is an important problem in directional statistics even though the influence functions of the sample mean direction and other location ...

This study aims to determine the differences in academic procrastination between active and non-active students in student organizations in the Faculty of Psychology, University of Medan Area. The scale of academic procrastination in this study is based on the characteristics of academic procrastination according to Ferrari, Johnson, and McCown. The results shows that There is no difference in academic procrastination between students who are active and not active in participating the organizational activities by looking at the value or coefficient of difference in anava F = 0.200 with P> 0.05. There is significant differences in academic procrastination between male and female students. These results are known by looking at the value or coefficient of difference in anava F = 14.137 with P

Rounding errors are an important factor in many statistical problems; therefore, statistical analysis of rounded data has recently received growing interest. In this paper we obtain an estimate of accuracy of the sample mean as an estimator of location parameter from rounded data. In contrast to earlier works, where usually asymptotic properties of such estimators have been studied, here the bounds are obtained for finite samples.

Time series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return and is the focus of several recent influential studies. This paper shows that asset-by-asset time series regressions reveal little evidence of TSM, both in- and out-of-sample. While the t-statistic in a pooled regression appears large, it is not statistically reliable as it is less than the critical values of parametric and nonparametric bootstraps. From an investment perspective, the TSM strategy is profitable, but its performance is virtually the same as that of a similar strategy that is based on historical sample mean and does not require predictability. Overall, the evidence on TSM is weak, particularly for the large cross section of assets.

Objective The objective of the study was to assess level of knowledge and attitudes of SUDEP among people living with epilepsy (PLWE) and healthcare workers providing epilepsy care in Uganda. Methods This cross‐sectional study of 48 PLWE and 19 epilepsy care providers used a tailored questionnaire to evaluate epilepsy and SUDEP knowledge, frequency of SUDEP discussion, reasons for not discussing SUDEP, timing of SUDEP discussions, and perceived patient reactions to being provided information on SUDEP. Results Median PLWE sample age was 25 (IQR; 19‐34) years, 10 (20.8%) were male, median age of onset of epilepsy 12 (IQR; 6‐18) years. Half of the PLWE reported that they had never heard of SUDEP. Most PLWE desired detailed information regarding SUDEP and preferred this information during the subsequent visits. Healthcare provider sample mean age was 35.7 (22.8) years, 12 (63.2%) were male and composed of 4 physicians (21.1%). Only 15% (3/20) of providers discussed SUDEP with their patients while 85% (17/20) have never discussed it. The main reasons for not discussing SUDEP were not knowing enough about SUDEP (89.5%) and no adequate support network available (30%). Providers that discussed SUDEP (100%) reported that negative reactions were the most common patient response. Significance In this Ugandan sample, most PLWE are not aware of SUDEP and epilepsy care providers rarely discuss SUDEP with their patients or patient caregivers. Negative reactions to SUDEP discussions are common but not universal. There is an urgent need for epilepsy educational programs in clinics and targeted communities addressing SUDEP.

In the Monte Carlo method for criticality calculation, the convergence-in-distribution check of the sample mean of tallies can be approached in terms of the influence range of autocorrelation compa...

espanolEl objetivo de la presente investigacion es evaluar la gestion educativa que desarrollan los directores de las instituciones publicas de educacion basica regular en el distrito de Trujillo en el periodo 2016. Es una investigacion descriptiva con variable multidimensional de diseno no experimental. La muestra estuvo conformada por 10 instituciones educativas de gestion publica en los niveles de inicial, primaria y secundaria ubicadas en el distrito de Trujillo que estan registradas en la Gerencia Regional de Educacion La Libertad y que quisieron formar parte de la investigacion. La recoleccion de los datos se hizo usando la tecnica de analisis de contenido y su instrumento la rubrica de evaluacion, se hizo ademas analisis documentario para verificar los documentos de gestion utilizados y como fueron elaborados. La prueba de hipotesis se hizo comparando el promedio del puntaje alcanzado versus el deseado con la prueba T de Student de una media muestral. Se concluyo que, solo un director logra el nivel medio en la evaluacion de competencias gerenciales, 3 directores logran el nivel minimo necesario en desarrollo de competencias gerenciales requeridas y los 6 directores restantes tienen un nivel insuficiente en desarrollo de competencias gerenciales. En terminos generales ningun director desarrolla las competencias gerenciales requeridas para gestionar la institucion que dirigen EnglishThe objective of this research was to assess the educational management developed by the directors of public regular basic education institutions in the district of Trujillo in the 2016 period. It was a descriptive research with multidimensional variable of non-experimental design. The sample was made up of 10 publicly managed educational institutions at pre-school, primary and secondary levels located in the district of Trujillo that were registered with the La Libertad Regional Office of Education and wanted to be part of the research. The data collection was done using the content analysis technique and its instrument the evaluation rubric; documentary analysis was also done to verify the management documents used and how they were elaborated. The hypothesis test was done by comparing the average score achieved versus the desired score with the Student T test of a sample mean. It was concluded that only one director achieved the average level in the evaluation of managerial skills, 3 directors achieved the minimum necessary level in development of required managerial skills and the remaining 6 directors had an insufficient level in development of managerial skills. In general terms, no director developed the managerial skills required to manage the institution they were directing