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This study aims to examine the role of ta’awun in reducing voluntary turnover intention. The authors defined ta’awun as the willingness to help colleagues without being asked and expecting rewards as promised by Islam. Also, the antecedent variables of organizational identification and job embeddedness are used to predict ta’awun.

This study used 216 respondents from Islamic Universities in Indonesia. Structural equation model was used to analyze data and test the empirical model.

Job embeddedness and organizational identification can improve ta’awun behavior. Ta’awun behavior has also been proven to be able to reduce voluntary turnover intention as well as successfully mediating the relationship between job embeddedness and organizational identification with voluntary turnover intention.

Ta’awun enriches organizational citizenship behavior (OCB) studies which are intervened with Islamic values. The questionnaire given to respondents are very susceptible for self-response bias so that this type of bias influences the conclusion. Thus, consistency of results can be retested in several different objects.

Organizations need to consider the factor of religiosity when recruiting employees. HRM practices need to be encouraged to create organizational identification through pride in the organization to reduce voluntary turnover intention through ta’awun behavior.

The Ta’awun concept is a refinement of the previously existing concept, which is OCB. Orientation in the world and the hereafter that underlies this ta’awun behavior is more effective in reducing the intention of voluntary displacement.

In order to improve working methods, this study proposes a method for the analysis of medication incidents and the systematic planning of error‐proofing (EP) countermeasures, in the hope that it might contribute to a reduction in medication incidents.

In order to simplify the process of planning EP countermeasures, the following approaches are employed in this study. Improvement elements are extracted in order to plan EP countermeasures. The improvement elements that caused the error‐factor are called improvement objects, and the authors designed the extraction set of improvement objects. The authors correlated the improvement objects with recommended EP solutions. Finally, these parameters are collated. Moreover, these tools are summarized as a procedure for analysis of such incidents and for the creation of appropriate EP countermeasures.

Using this approach, this paper suggests four steps to reduce medical incidents. The proposed procedure can facilitate the planning of EP countermeasures and can reduce the rate of medical incidents.

It can be surmised that the proposed method can serve as a useful means for planning EP countermeasures and reducing the number of medication incidents. On the other hand, there are various countermeasures which can be planned for one incident by applying the proposed method.

The relationship between Error factors and improvement objects were then clarified through utilizing maps. Furthermore, a list that clearly indicates which EP solutions should be adopted for the improvement objects were suggested. There is, therefore, a significant difference between the proposed and the conventional method, and this makes it possible to plan the EP countermeasures easily.

The purpose of this paper is to present an integrated cost of quality ‐ activity‐based costing (COQ‐ABC) framework for measuring quality costs under ABC. The main deficiencies of most COQ systems are: (1) no consensus method to allocate overhead costs to COQ elements, (2) the failure to trace quality costs to their sources, and (3) the lack of information about how indirect workers spend their time on various activities. These deficiencies can be easily overcome under ABC together with work sampling. The cost and nonfinancial information achieved from the integrated COQ‐ABC system can be used to identify the magnitude of the quality improvement opportunities, to identify where the quality improvement opportunities exist, and to continuously plan the quality improvement programs and control quality costs. The ultimate goal of the integrated COQ‐ABC system will be to continuously improve processes/activities/quality so that no defects at all are produced and quality cost measurement ultimately becomes unnecessary.

Multi-domain convolutional neural network (MDCNN) model has been widely used in object recognition and tracking in the field of computer vision. However, if the objects to be tracked move rapid or the appearances of moving objects vary dramatically, the conventional MDCNN model will suffer from the model drift problem. To solve such problem in tracking rapid objects under limiting environment for MDCNN model, this paper proposed an auto-attentional mechanism-based MDCNN (AA-MDCNN) model for the rapid moving and changing objects tracking under limiting environment.

First, to distinguish the foreground object between background and other similar objects, the auto-attentional mechanism is used to selectively aggregate the weighted summation of all feature maps to make the similar features related to each other. Then, the bidirectional gated recurrent unit (Bi-GRU) architecture is used to integrate all the feature maps to selectively emphasize the importance of the correlated feature maps. Finally, the final feature map is obtained by fusion the above two feature maps for object tracking. In addition, a composite loss function is constructed to solve the similar but different attribute sequences tracking using conventional MDCNN model.

In order to validate the effectiveness and feasibility of the proposed AA-MDCNN model, this paper used ImageNet-Vid dataset to train the object tracking model, and the OTB-50 dataset is used to validate the AA-MDCNN tracking model. Experimental results have shown that the augmentation of auto-attentional mechanism will improve the accuracy rate 2.75% and success rate 2.41%, respectively. In addition, the authors also selected six complex tracking scenarios in OTB-50 dataset; over eleven attributes have been validated that the proposed AA-MDCNN model outperformed than the comparative models over nine attributes. In addition, except for the scenario of multi-objects moving with each other, the proposed AA-MDCNN model solved the majority rapid moving objects tracking scenarios and outperformed than the comparative models on such complex scenarios.

This paper introduced the auto-attentional mechanism into MDCNN model and adopted Bi-GRU architecture to extract key features. By using the proposed AA-MDCNN model, rapid object tracking under complex background, motion blur and occlusion objects has better effect, and such model is expected to be further applied to the rapid object tracking in the real world.

The purpose of this paper is to contribute to the understanding of Swedish school leaders’ relational and management work orientation, in terms of both techno and socio structure dimensions. The background is the neoliberal policy regime, underpinned by OECD and PISA, and an increased focus on school leaders’ management work.

In total, 26 school leaders in a Swedish municipality were interviewed, and their responses were analysed to score their expressed orientations in terms of techno structure (object and formal) and socio structure (person and symbolic) dimensions.

The school leaders had predominantly formal work orientations, expressed in comments about organising teams, scheduling teacher meetings, shaping working routines in meetings, making plans and (in some cases) creating an infrastructure. Scores for object (goal and result) and symbolic dimensions of their management orientation were low.

The results suggest a need to increase Swedish school leaders’ attention to object aspects, and both person and symbolic aspects of the formal or organising dimension, of their work. They also indicate the importance of establishing and communicating core symbols in compulsory schooling, like democracy and equity, to avoid external accountability pressures instrumentally shaping schools’ management.

In contrast to previous research, the analysis indicates that Swedish school leaders have a predominantly formal and organising work orientation, frequently with little clear goal and results orientation, or attention to professional needs and motivations of the teachers (important aspects of person orientation).

To provide original knowledge for graduate students, research workers and specialists in ability maintenance system of engineering systems in range of improving their diagnostic susceptibility in order to improve of credibility of worked out diagnosis, genesis and forecast.

In this work are methodological guidelines to realize a process of improving of diagnostic susceptibility of engineering systems, which can be approached as an automatics system. It can be hydraulic, pneumatic and fuel systems, oil and gas pipelines, etc.

It was noticed and next theoretically and experimentally confirmed that signals of weak interactions, which can excite between a tested object (hydraulic system) and a adjoined testing object (a corrector), are an additional piece of diagnostic information. This information allows for an increase of reliability of diagnosis, which is working out.

The signals of weak interactions can arise, when a tested object can be approached as an automatic control system (ACS), in which can be distinguished a controlled system (e.g. installation) and a control unit (e.g. pump). Experimental research was realized on a physical model of the airplane hydraulic installation. Other object requires similar investigations.

The development of functional (parametric and signal‐based) diagnosing methods. The proposition of “signal‐based diagnostics” based on the indicators of quality of course signal. These indicators result from the principles of the automatics, and from parametric diagnostics, resulting from the principles of the static and dynamic identification of diagnosing objects.

The proposition of receiving diagnostic information, also during observation of phenomena, which occur in a feedback path of automatics systems, in which operates a specially adjoined corrector (a testing object). Such approach allows by means of change of corrector's parameters to determine optionally a required sensitivity of measuring system, and to control a set value into the corrector, which is an output signal in the occurring in the past.

This paper aims to design a deep neural network for object instance segmentation and six-dimensional (6D) pose estimation in cluttered scenes and apply the proposed method in real-world robotic autonomous grasping of household objects.

A novel deep learning method is proposed for instance segmentation and 6D pose estimation in cluttered scenes. An iterative pose refinement network is integrated with the main network to obtain more robust final pose estimation results for robotic applications. To train the network, a technique is presented to generate abundant annotated synthetic data consisting of RGB-D images and object masks in a fast manner without any hand-labeling. For robotic grasping, the offline grasp planning based on eigengrasp planner is performed and combined with the online object pose estimation.

The experiments on the standard pose benchmarking data sets showed that the method achieves better pose estimation and time efficiency performance than state-of-art methods with depth-based ICP refinement. The proposed method is also evaluated on a seven DOFs Kinova Jaco robot with an Intel Realsense RGB-D camera, the grasping results illustrated that the method is accurate and robust enough for real-world robotic applications.

A novel 6D pose estimation network based on the instance segmentation framework is proposed and a neural work-based iterative pose refinement module is integrated into the method. The proposed method exhibits satisfactory pose estimation and time efficiency for the robotic grasping.

This article takes into account object identification, enhanced visual feature optimization, cost effectiveness and speed selection in response to terrain conditions. Neither supervised machine learning nor manual engineering are used in this work. Instead, the OTV educates itself without instruction from humans or labeling. Beyond its link to stopping distance and lateral mobility, choosing the right speed is crucial. One of the biggest problems with autonomous operations is accurate perception. Obstacle avoidance is typically the focus of perceptive technology. The vehicle's shock is nonetheless controlled by the terrain's roughness at high speeds. The precision needed to recognize difficult terrain is far higher than the accuracy needed to avoid obstacles.

Robots that can drive unattended in an unfamiliar environment should be used for the Orbital Transfer Vehicle (OTV) for the clearance of space debris. In recent years, OTV research has attracted more attention and revealed several insights for robot systems in various applications. Improvements to advanced assistance systems like lane departure warning and intelligent speed adaptation systems are eagerly sought after by the industry, particularly space enterprises. OTV serves as a research basis for advancements in machine learning, computer vision, sensor data fusion, path planning, decision making and intelligent autonomous behavior from a computer science perspective. In the framework of autonomous OTV, this study offers a few perceptual technologies for autonomous driving in this study.

One of the most important steps in the functioning of autonomous OTVs and aid systems is the recognition of barriers, such as other satellites. Using sensors to perceive its surroundings, an autonomous car decides how to operate on its own. Driver-assistance systems like adaptive cruise control and stop-and-go must be able to distinguish between stationary and moving objects surrounding the OTV.

One of the most important steps in the functioning of autonomous OTVs and aid systems is the recognition of barriers, such as other satellites. Using sensors to perceive its surroundings, an autonomous car decides how to operate on its own. Driver-assistance systems like adaptive cruise control and stop-and-go must be able to distinguish between stationary and moving objects surrounding the OTV.

The purpose of this paper is to examine faculty members' perceptions over time with respect to the concept of quality assurance; the evaluation objects and the rationale for choosing them; and attitudes toward the application of this process in the college and in its academic units.

This a qualitative longitudinal case study of one veteran college of education in the center of Israel. The leading faculty members under study comprised 17 subject‐matter department heads specializing in the humanities, science and in education. All of them implemented an internal evaluation in their departments as part of a quality assurance process. The study involved two rounds of semi‐structured interviews: at the beginning of the process and two‐and‐a‐half years later, using categorical content analysis.

The results indicate that time is required for the process to mature, for process objection level to decline and for assertive leadership to evolve. Positive attitudes emerge when faculty members are given the opportunity to act in an autonomous atmosphere, when organizational learning frameworks are established and when variety is legitimized. Furthermore, faculty members take responsibility and understand that the process improves the quality of their work. Overall, perceptions of processes changed from quality assurance as external supervision imposed on the institution, to quality enhancement emerging from the academic faculty and from the needs of the institution.

For decision makers and practitioners in higher education, this case study represents one stage in building an organizational culture, that can contribute in the future to external quality assurance processes when required by stakeholders.

This article aims to explore how objects function in integration efforts in health and social care contexts.

The article draws on boundary object theory and empirical data collected from a range of health and social care integration initiatives in Wales to illustrate the value of the focus on objects and to identify the potential implications of this approach for studies in other national contexts.

Attention to objects can shed light on the dynamics of integration, its potential and limits, offering insights that conventional analysis might otherwise miss.

The data drawn on in this paper are illustrative. Exploring the role of objects in integration requires more focused studies.

The results suggest that integration designers and managers need to pay closer attention to the attachments that practitioners develop to objects.

This is a highly original paper in view of its innovative use of boundary object theory in the context of integration, and its contribution to theory, research and practice.