The Effects of Errorless Compliance Training Interventions on Compliance Behavior on Students in the Home and Generalization in the School Setting

Errorless Compliance Training (ECT) is a procedure used to lessen disruptive behavior using a gradual and noncorecive approach. In this study, parents of three school-aged children who demonstrated high levels of disruptive behavior in the home and the classroom were trained on the ECT procedure. ECT sessions took place in the home, with parents delivering requests. Generalized effects of ECT were assessed in the school setting. Baseline data were used to arrange requests into grouped Levels, ranging from Level 1 (requests of which individual is typically compliant) to Level 4 (requests in which individual is typically noncompliant). Using the ECT procedure, request levels were faded over time in a gradual fashion to ensure the highest probability of compliance. Results yielded increased compliance for all participants and both the home and school environments in all four levels of ECT

CLOSER: A Collaborative Locality-aware Overlay SERvice

Current Peer-to-Peer (P2P) file sharing systems make use of a considerable percentage of Internet Service Providers (ISPs) bandwidth. This paper presents the Collaborative Locality-aware Overlay SERvice (CLOSER), an architecture that aims at lessening the usage of expensive international links by exploiting traffic locality (i.e., a resource is downloaded from the inside of the ISP whenever possible). The paper proves the effectiveness of CLOSER by analysis and simulation, also comparing this architecture with existing solutions for traffic locality in P2P systems. While savings on international links can be attractive for ISPs, it is necessary to offer some features that can be of interest for users to favor a wide adoption of the application. For this reason, CLOSER also introduces a privacy module that may arouse the users' interest and encourage them to switch to the new architectur

Data Management Study, Volume 5. Appendix H - Contractor Data Package Logistics and Support /LS/ Final Report

Contractor data package for Voyager logistics and support in transportation, communications, supply, and maintenanc

Data management study, volume 5. Appendix F - Contractor data package test /TE/ and mission operations /MP/ Final report

Test and mission operations contractor data package for Voyager spacecraf

State v. Stone Clerk\u27s Record v. 3 Dckt. 34571

https://digitalcommons.law.uidaho.edu/idaho_supreme_court_record_briefs/2675/thumbnail.jp

Deep Reinforcement Learning for Real-Time Optimization in NB-IoT Networks

NarrowBand-Internet of Things (NB-IoT) is an emerging cellular-based technology that offers a range of flexible configurations for massive IoT radio access from groups of devices with heterogeneous requirements. A configuration specifies the amount of radio resource allocated to each group of devices for random access and for data transmission. Assuming no knowledge of the traffic statistics, there exists an important challenge in "how to determine the configuration that maximizes the long-term average number of served IoT devices at each Transmission Time Interval (TTI) in an online fashion". Given the complexity of searching for optimal configuration, we first develop real-time configuration selection based on the tabular Q-learning (tabular-Q), the Linear Approximation based Q-learning (LA-Q), and the Deep Neural Network based Q-learning (DQN) in the single-parameter single-group scenario. Our results show that the proposed reinforcement learning based approaches considerably outperform the conventional heuristic approaches based on load estimation (LE-URC) in terms of the number of served IoT devices. This result also indicates that LA-Q and DQN can be good alternatives for tabular-Q to achieve almost the same performance with much less training time. We further advance LA-Q and DQN via Actions Aggregation (AA-LA-Q and AA-DQN) and via Cooperative Multi-Agent learning (CMA-DQN) for the multi-parameter multi-group scenario, thereby solve the problem that Q-learning agents do not converge in high-dimensional configurations. In this scenario, the superiority of the proposed Q-learning approaches over the conventional LE-URC approach significantly improves with the increase of configuration dimensions, and the CMA-DQN approach outperforms the other approaches in both throughput and training efficiency

Buildings LCA and digitalization: Designers\u27 toolbox based on a survey

In a context of digitalization and increasing quality requirements, the building sector is facing an increasing level of complexity regarding its design process. This results in a growing number of involved actors from different domains, a multitude of tasks to be completed and a higher degree of needed expertise. New buildings are also required to reach higher performances in terms of environmental quality. To that regard, the exploitation of the full potential of digital tools can facilitate the integration of environmental aspects in the planning process, limit productivity shortcomings and reduce environmental impacts, which can result from an unaware decision making. Building environmental assessment can be performed through several Life Cycle Assessment (LCA)-based tools. “Pure calculation” tools quantify final buildings\u27 environmental potential, while “complex tools” additionally support decision making during the planning process. It is often difficult to choose the best suitable tool, which strongly depends on the user\u27s needs. Within the IEA EBC Annex 72, a survey was realized with the main objective of creating a comprehensive overview of the existing tools dedicated to buildings LCA. The questionnaire included the usability, functionality, compliance, data reliability and interoperability of the analysed tools. Lastly, based on the survey outcomes and their critical assessment, a procedure for the identification and selection of a tool has been proposed based on user\u27s needs. As a result, this work outlines main features of currently available building LCA tools, for which there is a harmonized status in terms of usability and overall applied LCA methodology. Despite the need for more automatized workflows, tools\u27 embedding is mostly not yet applicable in system chains or limited to a restricted number of tools

TINJAUAN PELAKSANAAN VISUM ET REPERTUM DARI ASPEK TEORI HUKUM KESEHATAN DAN PROSEDUR TETAPDI RSUD TIDAR MAGELANG TAHUN 2015

RSUD Tidar Magelang adalah salah satu rumah sakit yang melayani permintaan visum et repertum. Dalam pelaksanaan pelayanan visum et repertum sudah menggunakan prosedur tetap. Namun prosedur tetap yang ada belum spesifik menjelaskan tentang alur pelayanan yang terinci. Dari permasalahan tersebut penelitian ini dilakukan dengan tujuan mengetahui pelaksanaan visum et repertum dari aspek teori hukum kesehatan dan prosedur tetap di RSUD Tidar Magelang tahun 2015. Jenis penelitian ini adalah penelitian deskriptif evaluatif dengan pendekatan retrospektif.Metode yang digunakan adalah observasi dan wawancara. Penelitian ini menggunakan populasi pelayanan pelaksanaan visum et repertum Triwulan I tahun 2015 dengan subjek 2 orang petugas meliputi petugas unit rekam medis yang melayani visum dan Kepala Instalasi Rekam Medis dan objek jumlah pemintaan pelayanan visum et repertum Triwulan I tahun 2015 sejumlah 21 kasus. Pelaksanaan visum et repertum di RSUD Tidar Magelang sudah sesuai dengan teori hukum kesehatan namun belum sesuai dengan prosedur tetap. Dalam prosedur tetap belum mencantumkan penjelasan tentang tata cara permintaan visum et repertum, jenis kasus yang dimintakan visum et repertum, pihak peminta visum et repertum, pembuat visum et repertum, peranan petugas rekam medis dalam melayani visum et repertum, pengangendaan visum et repertum, dan penyerahan visum et repertum.Saran yang diberikan adalah perlu dilakukan pengkajian ulang dan revisi pada prosedur tetap (protap) mengingat pentingnya prosedur tetap sebagai pedoman petugas dalam menjalankan tugasnya