THE ROLE OF STRUCTURAL ENGAGEMENT IN INTER-RELIGIOUS DIALOGUE: IN THE CASE OF THE INTER-RELIGIOUS CONFLICT IN GPDI SEMANU, GUNUNGKIDUL

The case of expulsion of a pastor at Semanu Gunungkidul GPdI church was resolved through mediation by the regional assistant. The conflict was triggered by the issue of Christianization by the pastor of GPdI Semanu. Today the conflict has ended, but it still leaves prejudice among religious leaders and structural officials in the area. The main data were interviews with those who directly involved in conflict and in efforts to resolve it. They were Muslim and Christian religious leaders, FKUB, sections of local government that were directly dealt with conflict, local communities, and community organizations accompanying the conflict resolution process. The Indonesian government was one of the important factors in the process of conflict and its resolution. The recent research on interfaith conflict and dialogue emphasized the role and influence of grassroots communities.

The Role of Family Counseling in Overcoming Juvenile Delinquency

Juvenile delinquency is one of the deviant behaviors that requires special attention and good understanding and proper handling of the resolution process because it is an important factor for the success of adolescents in the next life, considering that the teenage transition period is the most decisive period. There are several roles that parents can do in overcoming juvenile delinquency, including the process of fostering and guidance carried out by the family. Parents try to create a harmonious, communicative and comfortable family for adolescents and help adolescents in their social and adjustment processes. Family counseling is a training process that is focused on the client's parents as the most influential person in determining the system in the family. This is done not to change the personality or character of the family members involved but to change the family through changing the behavior of the parents. If the behavior of the parents changes, it will affect the members in the family.

PROCEDURE FOR RESOLVING CONSUMER DISPUTES THROUGH CONSUMER DISPUTE SETTLEMENT AGENCY (BPSK)

The establishment of the Consumer Dispute Settlement Agency (here and after, we will use the acronym BPSK) is to protect consumers and entrepreneurs by designing a Consumer Protection system that contains legal certainty and transparency. The purpose of this study was to determine the procedure for resolving consumer disputes through BPSK. This research uses doctrinal and non-doctrinal approaches. The result of the research is that the procedure for resolving consumer disputes carried out by BPSK is through 2 (two) processes or paths that must be passed if consumers want to resolve consumer disputes with business actors, namely: Dispute Resolution outside the court, namely the process of making a complaint or claim for losses carried out by business actors to BPSK or Non-Governmental Consumer Protection Agency (LPKSM). From these complaints, BPSK is obliged to issue a decision no later than 21 (twenty-one) working days after the claim is received and Dispute Settlement Through the court, namely the process Consumers who feel aggrieved report to the authorities, namely to the police for follow-up as in the dispute resolution process in court. There are 3 (three) ways to settle consumer disputes, namely conciliation, arbitration, and mediation.

A Regularized Procedure to Generate a Deep Learning Model for Topology Optimization of Electromagnetic Devices

The use of behavioral models based on deep learning (DL) to accelerate electromagnetic field computations has recently been proposed to solve complex electromagnetic problems. Such problems usually require time-consuming numerical analysis, while DL allows achieving the topologically optimized design of electromagnetic devices using desktop class computers and reasonable computation times. An unparametrized bitmap representation of the geometries to be optimized, which is a highly desirable feature needed to discover completely new solutions, is perfectly managed by DL models. On the other hand, optimization algorithms do not easily cope with high dimensional input data, particularly because it is difficult to enforce the searched solutions as feasible and make them belong to expected manifolds. In this work, we propose the use of a variational autoencoder as a data regularization/augmentation tool in the context of topology optimization. The optimization was carried out using a gradient descent algorithm, and the DL neural network was used as a surrogate model to accelerate the resolution of single trial cases in the due course of optimization. The variational autoencoder and the surrogate model were simultaneously trained in a multi-model custom training loop that minimizes total loss—which is the combination of the two models’ losses. In this paper, using the TEAM 25 problem (a benchmark problem for the assessment of electromagnetic numerical field analysis) as a test bench, we will provide a comparison between the computational times and design quality for a “classical” approach and the DL-based approach. Preliminary results show that the variational autoencoder manages regularizing the resolution process and transforms a constrained optimization into an unconstrained one, improving both the quality of the final solution and the performance of the resolution process.

A novel partial ambiguity method for multi-GNSS real-time kinematic positioning

Recent progress in using real-time kinematic (RTK) positioning has motivated the exploration of its application due to its high accuracy and efficiency. However, poorly-observed satellite data will cause unfixed ambiguities and markedly biased solutions. A novel partial ambiguity resolution method, named the irrespective of integer ambiguity resolution (IIAR) model, is proposed and applied to improve the reliability of ambiguity resolution. The proposed method contains initial ambiguity resolution and irrespective of integer ambiguity processes. The initial ambiguity resolution process applies an iterative partial ambiguity resolution method to obtain an approximate solution. The irrespective of integer ambiguity process transforms the approximate solution to a high-precision solution. Experiments show that the approximate solution is unreliable when the initial ambiguity resolution process has small redundancy, and the proposed method can obtain better results for those cases. The IIAR method showed about a 40% improvement of multi-GNSS ambiguity success rate and about a 25% improvement of standard deviation. Therefore, these results show that the proposed IIAR method can improve the results of multi-GNSS RTK positioning significantly.

Advocating for the use of Restorative Justice Practices: Examining the Overlap Between Restorative Justice and Behavior Analysis

Broadly defined, Restorative Justice (RJ) is a set of procedures based in Indigenous peacemaking practices that reduces recidivism and guides the effective reparation of harm. RJ practices provide harm-affected parties an opportunity for engagement in the resolution process, which theoretically enhances community well-being. RJ practices overlap significantly with behavior-analytic principles. Implementing RJ practices from a context-focused, appetitive-based approach that focuses on classes of behaviors may address harmful behaviors within police organizations. RJ practices may also facilitate changes in contexts that support behaviors valued by the community. The current review discusses criminal and Restorative Justice, RJ processes and practices, the effectiveness of RJ in various contexts, how RJ overlaps with behavior-analytic principles and existing behavior science models more generally, research suggestions, and recommendations for behavior analysts implementing RJ within police organizations and communities to address officer misconduct.