Comparison of the Effectiveness of Contextual Therapy fair- centered and Emotion-Focused Therapy on Marital Intimacy and Marital Burnout among Couples

The aim of the present study was to compare and evaluate the effectiveness of Contextual Therapy fair-centered (CT) (based on Ivan Böszörményi-Nagy) and Emotion-Focused Therapy (EFT) on increasing Marital Intimacy and reducing Marital Burnout in couples. The method was semi-experimental with a pretest-posttest design with a control group. The statistical population included all couples who in 2017-2018 referred to the Sanam private office of counseling and psychological services (under the supervision of the Psychology and Counseling Organization of Iran) in the city of Urmia. Among them, 24 couples who have referred to this center due to marital conflicts, after matching the subjects and the criteria for entering and leaving the research, were purposefully selected and randomly assigned to three groups (Eight pairs in each group), which are two experimental groups and one control group. After performing the pretest, the Contextual Therapy group were performed 10 sessions and Emotion-Focused Therapy was 9 for each pair. The questionnaires used included Walker and Thompson's intimacy scale and Pines 's Burnout Scale. To analyze the data and hypotheses, the statistical test method of “repeated measurement variance analysis” and SPSS software were used. Findings showed that the effectiveness of Emotion-Focused Therapy in increasing intimacy was significantly (p < 0.001) than the Contextual. But there is no significant difference between the two approaches in reducing “marital boredom”, Also, the findings showed that, over time, the effectiveness of the Contextual Therapy approach to the Emotion-Focused Therapy in “marital burnout” is more stable. Conclusion: In comparison Emotion-Focused Therapy a more effective effect in increasing intimacy and the effectiveness of the two approaches in reducing marital burnout is the same,but in the long run, the Contextual approach has shown better therapeutic stability in improving Marital burnout.

Measuring the Burden of Intimate Partner Violence by Sex and Sexual Identity: Results From a Random Sample in Toronto, Canada

Debates on how sex, gender, and sexual identity relate to intimate partner violence (IPV) are longstanding. Yet the role that measurement plays in how we understand the distribution of IPV has been understudied. We investigated whether people respond differently to IPV items by sex and sexual identity and the implications this has for understanding differences in IPV burdens. Our sample was 2,412 randomly selected residents of Toronto, Canada, from the Neighborhood Effects on Health and Well-being (NEHW) study. IPV was measured using short forms of the Physical and Nonphysical Partner Abuse Scales (20 items). We evaluated the psychometric properties of this measure by sex and sexual identity. We examined whether experiences of IPV differed by sex and sexual identity (accounting for age and neighborhood clustering) and the impacts of accounting for latent structure and measurement variance. We identified differential item functioning by sex for six items, mostly related to nonphysical IPV (e.g., partner jealousy). Males had higher probabilities of reporting five of the six items compared to females with the same latent IPV scores. Being female and identifying as lesbian, gay, or bisexual were positively associated with experiencing IPV. However, the association between female sex and IPV was underestimated when response bias was not accounted for and outcomes were dichotomized as “any IPV.” Common practices of assuming measurement invariance and dichotomizing IPV can underestimate the association between sex or gender and IPV. Researchers should continue to attend to gender-based and intersectional differences in IPV but test for measurement invariance prior to comparing groups and analyze scale (as opposed to binary) measures to account for chronicity or intensity.

Inter-sentential Code-switching and Language Dominance in Cantonese–English Bilingual Children

This paper examines the relationship between language dominance and the under-investigated topic of inter-sentential code-switching in Hong Kong Cantonese–English bilingual children. Longitudinal data for six children showing different dominance patterns were analysed. MLU differentials (Yip & Matthews, 2006) were adopted to measure dominance based on five criteria: methodological compatibility, typological comparability, gradient measurement, variance validity, and multifaceted compatibility. Our results showed that bilingual children produced more inter-sentential code-switching in the context of their non-dominant language and less in their dominant-language context. We account for this asymmetry in relation to mechanisms of inhibitory control (Gross & Kaushanskaya, 2015). Further, we propose that intrasentential and inter-sentential code-switching each have a different status in bilingual children’s developing grammar, underlining the methodological importance of separating the two constructs in future investigations. We also suggest that, in societies where intra-sentential code-switching is a social norm, inter-sentential code-switching could serve as signs of early bilinguals’ dominance status.

A Variance Inequality for Meromorphic Functions Under Exterior Probability

The problem of measuring an unbounded system attribute near a singularity has been discussed. Lenses have been introduced as formal objects to study increasingly precise measurements around the singularity and a specific family of lenses called Exterior probabilities have been investigated. It has been shown that under such probabilities, measurement variance of a measurable function around a 1st order pole on a complex manifold, consists of two separable parts - one that decreases with diminishing scale of the lenses, and the other that increases. It has been discussed how this framework can lend mathematical support to ideas of non-deterministic uncertainty prevalent at a quantum scale. In fact, the aforementioned variance decomposition allows for a minimum possible variance for such a system irrespective of how close the measurements are. This inequality is structurally similar to Heisenberg uncertainty relationship if one considers energy/momentum to be a meromorphic function of a complex spacetime.

Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm

Targeted information sources include radar and ADS (Automatic Dependent Surveillance) for civil ATM (Air Traffic Management) systems, and the new navigation system based on satellites has the capability of global coverage. In order to solve the surveillance problem in mid-and-high altitude airspace and approaching airspace, this paper proposes a filter-based covariance matrix weighting method, measurement variance weighting method, and measurement-first weighted fusion method weighting integration algorithm to improve the efficiency of data integration calculation under fixed accuracy. Besides this, this paper focuses on the technology of the integration of a multi-radar surveillance system and automated related surveillance system in the ATM system and analyzes the constructional method of a multigeneration surveillance data integration system, as well as establishing the targeted model of sensors and the target track and designing the logical structure of multi-radar and ADS data integration.

Improving bearings-only target state estimation tracking problem by using adaptive and nonlinear kalman algorithms

<p><span style="font-family: 'Times New Roman'; font-size: 9pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Finding the best estimate of the process state from noisy data is the main problem in tracking systems, many efforts and researches have been done to remove this noise. More useful information about the target’s state can be extracted from observations by using a more appropriate model for the target’s motion or using additional sensors. In this paper, we will introduce two methods to improve the estimation of bearing-only target tracking problem in two dimensions (2D). The first method is by adding a third sensor and making a good alignment of those sensors, and at the same time an extended Kalman filter (EKF), unscented Kalman filter (UKF) and cubature Kalman filter (CKF) are implemented. The second method is by applying an adaptive nonlinear Kalman filter (ANKF) for two sensors to solve the problem of measurement variance uncertainty.</span></p>

Use of the Earth’s Surface as a Reference to Correct Airborne Nadir-Looking Radar Radial Velocity Measurements for Platform Motion

A technique for correcting radar radial velocity Vr in airborne, nadir-pointing radar data using the surface of Earth as a reference is proposed and tested. Operating airborne Doppler radars requires correcting the radial velocity for platform motion. This can be accomplished with accurate beam-pointing and platform motion measurements. However, there are often residual pointing errors due to drift in inertial navigation systems (INS) and/or errors in platform-relative pointing. The technique proposed here takes advantage of the fact that the surface is stationary and the mean of the measured Vr at the surface should be 0 m s−1. Therefore, if a good estimate of the mean is made, it can be subtracted from the measured Vr to correct for errors due to residual pointing errors. The data contain many independent deviations from 0 m s−1 due to various causes, including measurement variance and large deviations due to surface features. These deviations must be filtered out of before the surface reference can be applied to correct the Vr data. A two-step filtering process was developed and tested. The first step removes large deviations in and the second step removes the measurement noise. The technique was examined using data from three field campaigns and was found to improve the quality of Vr in all cases. The Vr bias was removed and the variance was substantially reduced. The approach is generally applicable to nadir-pointing airborne radar data.

Towards a Model Based Sensor Measurement Variance Input for Extended Kalman Filter State Estimation

In this paper, we present an alternate method for the generation and implementation of the sensor measurement variance used in an Extended Kalman Filter (EKF). Furthermore, it demonstrates the limitations of a conventional EKF implementation and postulates an alternate form for representing the sensor measurement variance by extending and improving the characterisation methodology presented in the previous work. As presented in earlier work, the use of surveying grade optical measurement instruments allows for a more effective characterisation of Ultra-Wide Band (UWB) localisation sensors; however, in cluttered environments, the sensor measurement variance will change, making this method not robust. To compensate for the noisier readings, an EKF using a model based sensor measurement variance was developed. This approach allows for a more accurate representation of the sensor measurement variance and leads to a more robust state estimation system. Simulations were run using synthetic data in order to test the effectiveness of the EKF against the originally developed EKF; next, the new EKF was compared to the original EKF using real world data. The new EKF was shown to function much more stably and consistently in less ideal environments for UWB deployment than the previous version.