Behavioral modeling of DRACO : a peripheral interface ASIC

This paper describes the behavioral modeling of DRACO, a peripheral interface Application Specific Integrated Circuit (ASIC) developed by Rockwell International for numerical control applications. The behavioral model was generated from a data sheet of the fabricated chip, which primarily described the chip's input-output functionality, physical and operational characteristics, and a functional block diagram. The data sheet contained very little abstract behavioral information. This report describes the abstract behavioral model of the DRACO chip, and uses flowcharts and VHDL to capture the behavior. The behavioral model was developed through reverse engineering of the data sheet description, supplemented by further consultation with designers of the DRACO ASIC at Rockwell Intemational. The report describes typical behavioral test sequences that were applied to the DRACO VHDL model to verify its correctness. The appendices contain the original DRACO datasheet and the VHDL code used to capture DRACO's behavior

Moving beyond a limited follow-up in cost-effectiveness analyses of behavioral interventions

Background Cost-effectiveness analyses of behavioral interventions typically use a dichotomous outcome criterion. However, achieving behavioral change is a complex process involving several steps towards a change in behavior. Delayed effects may occur after an intervention period ends, which can lead to underestimation of these interventions. To account for such delayed effects, intermediate outcomes of behavioral change may be used in cost-effectiveness analyses. The aim of this study is to model cognitive parameters of behavioral change into a cost-effectiveness model of a behavioral intervention. Methods The cost-effectiveness analysis (CEA) of an existing dataset from an RCT in which an high-intensity smoking cessation intervention was compared with a medium-intensity intervention, was re-analyzed by modeling the stages of change of the Transtheoretical Model of behavioral change. Probabilities were obtained from the dataset and literature and a sensitivity analysis was performed. Results In the original CEA over the first 12 months, the high-intensity intervention dominated in approximately 58% of the cases. After modeling the cognitive parameters to a future 2nd year of follow-up, this was the case in approximately 79%. Conclusion This study showed that modeling of future behavioral change in CEA of a behavioral intervention further strengthened the results of the standard CEA. Ultimately, modeling future behavioral change could have important consequences for health policy development in general and the adoption of behavioral interventions in particular

Efektivitas Model Konseling Behavioral Teknik Modeling untuk Meningkatkan Efikasi Diri Siswa Kelas VIII SMP Negeri 2 Singaraja Tahun Pelajaran 2013/2014

Penelitian ini bertujuan untuk mengetahui efektivitas model konseling behavioral teknik modeling untuk meningkatkan efikasi diri siswa. Penelitian ini merupakan penelitian eksperimen dengan rancangan Pretest Posttest Control Group Design. Populasi penelitian adalah siswa kelas VIII SMP Negeri 2 Singaraja Tahun Pelajaran 2013/2014 berjumlah 573 orang. Penentuan sampel menggunakan teknik Purposive Sampling dengan jumlah 20 orang siswa. Jenis data yang dikumpulkan adalah data kuantitatif tentang peningkatan efikasi diri. Metode pengumpulan data yang digunakan adalah kuesioner. Data penelitian dianalisis dengan menggunakan analisis statistik independent sampel t-test.. Hasil penelitian menunjukkan bahwa model konseling behavioral teknik modeling efektif untuk meningkatkan efikasi diri siswa, hal ini dilihat dari hasil analisis nitai thitung lebih besar dari ttabel (6,51 > 1,734) dengan taraf signifikansi 0.05. Hal ini menunujukkan bahwa model konseling behavioral teknik modeling efektif untuk meningkatkan efikasi diri siswa.Kata Kunci : konseling behavioral, modeling, efikasi diri This study aim to determine the effectiveness of behavioral counseling models modeling techniques to improve students' self-efficacy. This study is a design experiment with pretest posttest control group design. The study population was a Junior High School 2 Singaraja eighth grade students in the Academic Year 2013/2014 numbered 573 people. Determination of the sample using purposive sampling technique the number of 20 students. The type of data that is collected quantitative data on the increase in self-efficacy. The data collection method used was a questionnaire. Data were analyzed by using statistical analysis of independent samples t-test. The results showed that the model of behavioral counseling effective modeling techniques to improve students' self-efficacy, it is seen from the results of the analysis of coefisien t count greater than t-table (6.51 > 1.734) with a significance level of 0.05. This research show that behavioral counseling models modeling techniques effective to improve students' self-efficacy. keyword : behavioral counseling, modeling, self-efficac

Single and Multi-Piece Behavioral Models of IC Output Buffers

This paper discusses the switching properties of the behavioral models of integrated circuit output buffers. Present behavioral models are based on a two-piece structure defined by a linear combination of two submodels for the two logic states. These models are very accurate in the two logic states, but their state switching is sensitive to the driven loads. The analysis carried out in this paper shows that this load sensitivity stems from the linear combination defining the two-piece model. A new single-piece behavioral model is proposed, that solves this problem and has efficiency and complexity levels comparable to those of two-piece model

A Behavioral Model of Cyclical Dieting

This paper presents a behavioral economics model with bounded rationality to describe an individual¡¯s food consumption choices that lead to weight gain and dieting. Using a physiological relationship determining calories needed to maintain weight, we simulate the food consumption choices of a representative female over a 30 year period. Results show that a diet will reduce weight only temporarily. Recurrence of weight gain leads to cyclical dieting, which reduces the trend rate of weight increase. Dieting frequency is shown to depend on decision period length, dieting costs, and habit persistence.Dieting, Behavioral economics, Weight cycles,

Persuasion in Finance

Persuasion is a fundamental part of social activity, yet it is rarely studied by economists. We compare the traditional economic model, in which persuasion is communication of objectively valuable information, with a behavioral model, in which persuasion is an effort to fit the message into the audience's already held beliefs. We present a simple formalization of the behavioral model, and compare the two models using data on financial advertising in Money and Business Week magazines over the course of the internet bubble. The evidence on the content of the persuasive messages is broadly consistent with the behavioral model of persuasion.

Integrating Behavioral Health & Primary Care in New Hampshire: A Path Forward to Sustainable Practice & Payment Transformation

New Hampshire residents face challenges with behavioral and physical health conditions and the interplay between them. National studies show the costs and the burden of illness from behavioral health conditions and co-occurring chronic health conditions that are not adequately treated in either primary care or behavioral health settings. Bringing primary health and behavioral health care together in integrated care settings can improve outcomes for both behavioral and physical health conditions. Primary care integrated behavioral health works in conjunction with specialty behavioral health providers, expanding capacity, improving access, and jointly managing the care of patients with higher levels of acuity In its work to improve the health of NH residents and create effective and cost-effective systems of care, the NH Citizens Health Initiative (Initiative) created the NH Behavioral Health Integration Learning Collaborative (BHI Learning Collaborative) in November of 2015, as a project of its Accountable Care Learning Network (NHACLN). Bringing together more than 60 organizations, including providers of all types and sizes, all of the state’s community mental health centers, all of the major private and public insurers, and government and other stakeholders, the BHI Learning Collaborative built on earlier work of a NHACLN Workgroup focused on improving care for depression and co-occurring chronic illness. The BHI Learning Collaborative design is based on the core NHACLN philosophy of “shared data and shared learning” and the importance of transparency and open conversation across all stakeholder groups. The first year of the BHI Learning Collaborative programming included shared learning on evidence-based practice for integrated behavioral health in primary care, shared data from the NH Comprehensive Healthcare Information System (NHCHIS), and work to develop sustainable payment models to replace inadequate Fee-for-Service (FFS) revenues. Provider members joined either a Project Implementation Track working on quality improvement projects to improve their levels of integration or a Listen and Learn Track for those just learning about Behavioral Health Integration (BHI). Providers in the Project Implementation Track completed a self-assessment of levels of BHI in their practice settings and committed to submit EHR-based clinical process and outcomes data to track performance on specified measures. All providers received access to unblinded NHACLN Primary Care and Behavioral Health attributed claims data from the NHCHIS for provider organizations in the NH BHI Learning Collaborative. Following up on prior work focused on developing a sustainable model for integrating care for depression and co-occurring chronic illness in primary care settings, the BHI Learning Collaborative engaged consulting experts and participants in understanding challenges in Health Information Technology and Exchange (HIT/HIE), privacy and confidentiality, and workforce adequacy. The BHI Learning Collaborative identified a sustainable payment model for integrated care of depression in primary care. In the process of vetting the payment model, the BHI Learning Collaborative also identified and explored challenges in payment for Substance Use Disorder Screening, Brief Intervention and Referral to Treatment (SBIRT). New Hampshire’s residents will benefit from a health care system where primary care and behavioral health are integrated to support the care of the whole person. New Hampshire’s current opiate epidemic accentuates the need for better screening for behavioral health issues, prevention, and treatment referral integrated into primary care. New Hampshire providers and payers are poised to move towards greater integration of behavioral health and primary care and the Initiative looks forward to continuing to support progress in supporting a path to sustainable integrated behavioral and primary care