2012 Iowa Drug Control Strategy

Drug use is a preventable behavior; drug addiction is a treatable disease; and a balanced approach of proven and promising prevention, treatment and enforcement is required to protect Iowans from drugs now and in the future. Drug abuse itself is a two-faceted problem, affected by both the available supply of and the demand for illegal drugs and other substances of abuse. Any strategy dealing with both the supply of and demand for drugs of abuse must be three-fold and involve these coordinated components: 1) Prevention strategies to discourage the initial human demand for drugs, 2) Treatment for those who already abuse or are addicted to drugs, in order to halt their drug-seeking behavior, and 3) Law enforcement actions to decrease the supply of illegal drugs and bring to treatment those who otherwise would not seek help. It is with these three approaches in mind that the Governor’s Office of Drug Control Policy presents the 2012 Iowa Drug Control Strategy. Mark J. Schouten Director, Governor’s Office of Drug Control Policy

Iowa’s Drug Control Strategy, 2008

The 2011 Iowa Drug Control Strategy is submitted in satisfaction of Chapter 80E.1 of the Code of Iowa which directs the Drug Policy Coordinator to monitor and coordinate all drug prevention, enforcement and treatment activities in the state. Further, it requires the Coordinator to submit an annual report to the Governor and Legislature concerning the activities and programs of the Coordinator, the Governor’s Office of Drug Control Policy and all other state departments with drug enforcement, substance abuse treatment, and prevention programs. Chapter 80E.2 establishes the Drug Policy Advisory Council (DPAC), chaired by the Coordinator, and consisting of a prosecuting attorney, substance abuse treatment specialist, law enforcement officer, prevention specialist, judge and representatives from the departments of corrections, education, public health, human services, public safety and human rights. This report and strategy was developed in consultation with the DPAC.

Iowa’s Drug Control Strategy, 2010

The 2011 Iowa Drug Control Strategy is submitted in satisfaction of Chapter 80E.1 of the Code of Iowa which directs the Drug Policy Coordinator to monitor and coordinate all drug prevention, enforcement and treatment activities in the state. Further, it requires the Coordinator to submit an annual report to the Governor and Legislature concerning the activities and programs of the Coordinator, the Governor’s Office of Drug Control Policy and all other state departments with drug enforcement, substance abuse treatment, and prevention programs. Chapter 80E.2 establishes the Drug Policy Advisory Council (DPAC), chaired by the Coordinator, and consisting of a prosecuting attorney, substance abuse treatment specialist, law enforcement officer, prevention specialist, judge and representatives from the departments of corrections, education, public health, human services, public safety and human rights. This report and strategy was developed in consultation with the DPAC.

Iowa’s Drug Control Strategy, 2012

The 2011 Iowa Drug Control Strategy is submitted in satisfaction of Chapter 80E.1 of the Code of Iowa which directs the Drug Policy Coordinator to monitor and coordinate all drug prevention, enforcement and treatment activities in the state. Further, it requires the Coordinator to submit an annual report to the Governor and Legislature concerning the activities and programs of the Coordinator, the Governor’s Office of Drug Control Policy and all other state departments with drug enforcement, substance abuse treatment, and prevention programs. Chapter 80E.2 establishes the Drug Policy Advisory Council (DPAC), chaired by the Coordinator, and consisting of a prosecuting attorney, substance abuse treatment specialist, law enforcement officer, prevention specialist, judge and representatives from the departments of corrections, education, public health, human services, public safety and human rights. This report and strategy was developed in consultation with the DPAC.

Iowa’s Drug Control Strategy, 2009

The 2011 Iowa Drug Control Strategy is submitted in satisfaction of Chapter 80E.1 of the Code of Iowa which directs the Drug Policy Coordinator to monitor and coordinate all drug prevention, enforcement and treatment activities in the state. Further, it requires the Coordinator to submit an annual report to the Governor and Legislature concerning the activities and programs of the Coordinator, the Governor’s Office of Drug Control Policy and all other state departments with drug enforcement, substance abuse treatment, and prevention programs. Chapter 80E.2 establishes the Drug Policy Advisory Council (DPAC), chaired by the Coordinator, and consisting of a prosecuting attorney, substance abuse treatment specialist, law enforcement officer, prevention specialist, judge and representatives from the departments of corrections, education, public health, human services, public safety and human rights. This report and strategy was developed in consultation with the DPAC.

Iowa Drug Control Strategy, 2013

The Governor’s Office of Drug Policy Control offers the 2013 Drug Control Strategy pursuant to Iowa Code §80E.1. The purpose of the strategy is to describe the activities of the office and other state departments related to drug enforcement, substance abuse treatment and prevention. This report also highlights trends in respect to substance abuse within the state and sets out innovative approaches to reduce drug abuse and its associated damage to society. Finally, the Strategy shows the state funding levels for the various agencies working in this area, as divided among the three areas of emphasis: prevention, treatment and enforcement.

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Mobile Robot Local Predictive Control under Perception Constraints

This research extends a previously developed work concerning about the use of local model predictive control in mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The platformused is a differential driven robot with a free rotating wheel. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are also introduced. In this sense, monocular image data provide an occupancy grid where safety trajectories are computed by using goal attraction potential fields

Iowa Drug Control Strategy, 2014

The Governor’s Office of Drug Policy Control offers the 2014 Drug Control Strategy pursuant to Iowa Code §80E.1. The purpose of the strategy is to describe the activities of the office and other state departments related to drug enforcement, substance abuse treatment and prevention. This report also highlights trends in respect to substance abuse within the state and sets out innovative approaches to reduce drug abuse and its associated damage to society. Finally, the Strategy shows the state funding levels for the various agencies working in this area, as divided among the three areas of emphasis: prevention, treatment and enforcement.

Iowa Drug Control Strategy, 2015

The purpose of the strategy is to describe the activities of the office and other state departments related to drug enforcement, substance abuse treatment and prevention. This report also highlights trends in respect to substance abuse within the state and sets out innovative approaches to reduce drug abuse and its associated damage to society. Finally, the Strategy shows the state funding levels for the various agencies working in this area, as divided among the three areas of emphasis: prevention, treatment and enforcement.

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Local model predictive control for navigation of a wheeled mobile robot using monocular information

Aquesta tesi està inspirada en els agents naturals per tal de planificar de manera dinàmica la navegació d'un robot diferencial de dues rodes. Les dades dels sistemes de percepció són integrades dins una graella d'ocupació de l'entorn local del robot. La planificació de les trajectòries es fa considerant la configuració desitjada del robot, així com els vértexs més significatius dels obstacles més propers. En el seguiment de les trajectòries s'utilitzen tècniques locals de control predictiu basades en el model, amb horitzons de predicció inferiors a un segon. La metodologia emprada és validada mitjançant nombrosos experiments.

Failure of a control strategy for a hybrid air-conditioning and wind catchers/towers system at Bluewater shopping malls in Kent

Purpose – To evaluate the control strategy for a hybrid natural ventilation wind catchers and air-conditioning system and to assess the contribution of wind catchers to indoor air environments and energy savings if any. Design/methodology/approach – Most of the modeling techniques for assessing wind catchers performance are theoretical. Post-occupancy evaluation studies of buildings will provide an insight into the operation of these building components and help to inform facilities managers. A case study for POE was presented in this paper. Findings – The monitoring of the summer and winter month operations showed that the indoor air quality parameters were kept within the design target range. The design control strategy failed to record data regarding the operation, opening time and position of wind catchers system. Though the implemented control strategy was working effectively in monitoring the operation of mechanical ventilation systems, i.e. AHU, did not integrate the wind catchers with the mechanical ventilation system. Research limitations/implications – Owing to short-falls in the control strategy implemented in this project, it was found difficult to quantify and verify the contribution of the wind catchers to the internal conditions and, hence, energy savings. Practical implications – Controlling the operation of the wind catchers via the AHU will lead to isolation of the wind catchers in the event of malfunctioning of the AHU. Wind catchers will contribute to the ventilation of space, particularly in the summer months. Originality/value – This paper demonstrates the value of POE as indispensable tool for FM professionals. It further provides insight into the application of natural ventilation systems in building for healthier indoor environments at lower energy cost. The design of the control strategy for natural ventilation and air-conditioning should be considered at the design stage involving the FM personnel.

Application of constrained predictive control on a 3D crane system

This paper describes the SIMULINK implementation of a constrained predictive control algorithm based on quadratic programming and linear state space models, and its application to a laboratory-scale 3D crane system. The algorithm is compatible with Real Time. Windows Target and, in the case of the crane system, it can be executed with a sampling period of 0.01 s and a prediction horizon of up to 300 samples, using a linear state space model with 3 inputs, 5 outputs and 13 states.