Internal Change Mechanism of Integrated Reporting: A Field Study

Integrated reporting has a considerable impact on the decision-making of all stakeholders in firms. Moreover, the increasing importance of integrated reporting has brought about changes in the reporting process. The purpose of this study is to analyze the internal changes in the integrated reporting process in Turkish business entities. To achieve this purpose, a semi-structured interview with managers of these entities was conducted. The data obtained from the interviews were analyzed then the results were evaluated. We find that entities undergo a structural internal change that affects all components of firms in their reporting process, due to the impact of integrated reporting implementation and expectations.

Macroeconomic Image Analysis and GDP Prediction Based on the Genetic Algorithm Radial Basis Function Neural Network (RBFNN-GA)

The prediction of gross domestic product (GDP) is a research hotspot, and its importance is self-evident. Its complex internal change mechanism also increases the difficulty of analyzing GDP data. The genetic algorithm (GA) is applied to the parameter design of the radial basis function neural network (RBFNN) based on genetic algorithm optimization (RBFNN-GA). An economic zone GDP image prediction model is proposed, which realizes the optimal design of the center vector, the base width vector of the RBFNN node function, and the weight between the hidden layer and output layer. Based on the GDP data over the years, this paper uses the RBFNN-GA prediction model to analyze and predict the GDP image and compares the image prediction results. The results show that the genetic algorithm is used to optimize RBFNN, which gives full play to the advantages of the two algorithms. The relative error of the RBFNN-GA prediction model is only 3.52%. Compared with the prediction results, the prediction accuracy is significantly higher than the ARIMA time series model and GM (1,1) model.

In-Session Reflective Functioning: Relationship With the Presence and Depth of Work on Conflict or Personality Functioning

Mentalizing, conceived as the capacity to attribute intentional mental states as implicit or underlying behavior of an individual or others, has gained interest within psychodynamic clinical research due to its potential as a change mechanism. Variations and qualities of mentalization have been studied through reflective functioning (RF). But only few studies are analyzing it throughout the psychotherapeutic interaction, identifying its level for therapists and patients. In contrast, brief psychodynamic therapy has a long tradition for establishing a focus to be worked upon. Lately, a multischematic focus has arisen, considering both conflict and personality functioning focuses as key elements on successful psychotherapies. This study aimed to identify mentalizing manifestations of patients and therapists through change episodes of one successful brief psychodynamic therapy and establish the relationship between these mentalizing manifestations and the type and depth of the therapeutic focus being worked on (conflict or personality functioning). Only 37.5% of speaking turns were able to be coded with RF; 77% of these had moderate to high RF and 22% had low or failure RF. The patient had 91% of low or failure RF, while the therapist only had 9% of low or failure RF. As for moderate to high RF, patients had 39%, while therapists had 61%. The patient showed a similar number of low or failure RF interventions and moderate to high RF interventions in conflict episodes. Meanwhile, the therapist only performs moderate to high-level RF interventions. In episodes in which personality functioning is worked on, both patient and therapist show a greater presence of interventions of moderate to high levels of RF. Finally, mentalizing interactions and non-mentalizing interactions were found on segments with conflict, and only mentalizing interactions were found on personality functioning segments.

RMAC

One knows that smart transport is also an integrated part of healthcare technologies. To minimize the pollution for benefiting the healthcare, the traffic throughput on roundabout intersection has to be increased which will reduce wasted time and will also enhance passenger comfort. This paper presents a new approach by use of cooperative vehicular control utilizing VANET without compromising the safety of vehicles. This intersection side unit (ISU)-based system use lane change mechanism. The modular use of lane with lane change in newly designed protocol CARA (collision avoidance at roundabout algorithm) will greatly enhance the capacity utilization of roundabout. A new simulator ‘RoundSim' was also developed exclusively for simulation in roundabout. A new MAC protocol RMAC (roundabout MAC) is also designed which will suit the roundabout management utilizing lane change to minimize sudden jerk to passengers, thus enhancing healthcare of people. This RMAC utilizes message set with different prioritization scheme which results in better utilization of allotted frequency spectrum.