Implementation Of Optimal Policies Research Articles

Questioning The Branding of Bandung Regency as a Religious and Prosperous District trough the Quranic Teacher Incentive Programme in 2021-2022

Along with the election of Dadang Supriatna-Sahrul Gunawan as the elected Regent and Vice Regent of Bandung, both prioritized Bandung Regency as a religious and prosperous area as stated in their vision. One of the manifestations of this vision is the Incentive program. Ngaji teachers in the Bandung Regency area. The Ngaji Teacher Incentive Program is in principle one of the flagship programs of Regent Dadang Supriatna, during his campaign for the candidacy for Regent of Bandung Regency, where when he was elected, the implementation of the policy was then fully submitted to the Bandung Regency Regional Government through the basis of Perbup No. 51 of 2021 concerning Guidelines for Providing Ngaji Teacher Incentives and specifically, the implementor is the Education Office. The Quranic Teacher Incentive Program is targeted at religious educators in Bandung Regency with the aim of improving the welfare of Quranic teachers as religious educators by providing monthly incentives in the form of non-cash transfer funds as well as funds for BPJS Health and BPJS Employment. 17,000 Koranic teachers in Bandung Regency in the process then became the target beneficiaries of the incentive money assistance. There are 23,000 Quranic teachers in Bandung district, and the government has budgeted Rp 109 billion for Quranic teacher incentive assistance. The results of the study show that the implementing committee officers involved in implementing the Koranic Teacher Incentive Program policy have not implemented the policy optimally. The lack of optimal policy implementation is motivated by the lack of selectivity of the sub-district and village parties in implementing the policy, resulting in pros and cons and social jealousy. In addition, there are also differences regarding the nominal incentive money given according to members of the Dinas and village officials. In this Quranic teacher incentive program, it can also be concluded that economic conditions are the most important influence in the implementation of the Quranic Teacher Incentive Program. Because if there is no financial resource support, the financial resources, the Quranic Teacher Incentive Program will not be implemented.

Influence of subsidy policies against insurances on controlling the propagation of epidemic security risks in networks

Subsidies are used to further control the propagation of epidemic security risks as they offer users incentives to practice security investment behaviors. However, previously proposed subsidy policies have typically been studied without insurance, and it is still challenging to build effective subsidy strategies when users can transfer some of the infection loss to the insurer by purchasing insurance, because these external incentives may alter users' decisions to purchase insurance. To this end, we designed three subsidy policies in a scenario where purchasing insurance is one of the available strategies to users: under SPIns and SPInsp, the subsidies are used as the insurance funds and the risk precaution aspect of the insurance funds, respectively, and under SPInsd, a fraction of the subsidies are used to support some free-riding users with high node importance in their purchase of insurance, and the remaining subsidies are used as the precaution aspect of the insurance funds. The subsidy policies are studied with a formulated security investment game model on scale-free networks from the perspectives of the public and insurer. The results show that SPInsd can always work effectively and outperforms others in limiting the extent of an epidemic outbreak with similar or lower social costs, and without a reduction in profit for the insurer. More importantly, an interesting phenomenon emerges in the SPInsp scenario: under specific insurance parameters, the increase in subsidy funding has a negative impact on preventing the risk spread, leading to larger final epidemic sizes. In addition, the effectiveness of SPInsd on scale-free networks with larger average degree or network size and random networks are also studied. We anticipate this work can provide useful insights for policy makers with respect to design and implementation of optimal subsidy policies related to the control of epidemic security risks under an insurance scenario.

Low-carbon transition of China's provincial power sector under renewable portfolio standards and carbon cap

Low-carbon transition of the power sector is an important measure to achieve carbon neutrality in China. Renewable portfolio standards (RPS) and carbon cap were implemented to promote energy transition since 2018. It is essential to evaluate influences of different policy mixes on provincial power systems and inter-provincial electricity transmissions for an optimal policy design and implementation under provincial heterogeneity. This study evaluates the effects of RPS targets and carbon cap on low-carbon transition of China's power system. It further analyzes how to achieve low-carbon transition of China's provincial power sectors with these two policies. Different mixes of RPS target and carbon cap were set to assess their impacts on energy structure change, CO2 emissions abatement, and compliance costs. Results show that the RPS policy can significantly promote investments in renewable energy power in China's resource-rich and high-demand provinces. Investment in nuclear power is important in meeting carbon cap constraints. RPS policy and carbon cap have an overlapping effect on low-carbon transition in China's power sector. Moreover, extensive inter-provincial electricity flows could balance the reverse distribution of energy resources and power loads for renewable energy in a cost-effective way.

Nuclear Energy, Economic Growth, and the Environment: Optimal policies in a model with endogenous technical change and environmental constraints

We use a model of endogenous growth with vertical innovations, in order to derive optimal energy policy under uncertainty. Innovation can be directed to dirty, green, or nuclear technologies, which in turn can be used to produce different types of energy. We show that, nuclear energy usage, is not only a necessary welfare maximizing condition, but also a crucial determinant of economic growth in the long run. Lastly, we find no evidence supporting the traditional Environmental Kuznets Curve hypothesis under optimal policy implementation.

Limited Visage-to-Visage Learning Program in Watersheds

The government conducted an evaluation and concluded that there is a need for visage-to-visage learning from students who even matter in implementing gap learning. The approach that will be used is a qualitative oncoming with a descriptive method in the shape of data that describes in detail the phenomenon that case in the field in a finite visage-to-visage learning program. The results showed that the optimal policy implementation process occurred in communication factors between organizations and the attitudes of implementers or implementors while the resource factor still needed improvement, especially in human resources because there were still some teachers who were still unable to maximize finite visage-to-visage learning due to finite preceptor time hours and lack of innovation in learning.

Secular trends of morbidity and mortality of prostate, bladder, and kidney cancers in China, 1990 to 2019 and their predictions to 2030

BackgroundProstate, bladder and kidney cancers are common age-related genitourinary cancers. China's population is aging at an increasing rate, so predicting the morbidity and mortality of prostate, bladder, and kidney cancer in China is of great significance to provide epidemiological evidence for forward planning and implementation of national health policies.MethodsNumbers of incidences and deaths by cancer (prostate, bladder and kidney), sex (male and female) and age groups from 1990 to 2019 were extracted from the Global Burden of Disease (GBD) Study. We applied Bayesian age-period-cohort models to predict incidences and deaths to 2030. We also calculated Age-standardized incidence rate (ASIR) and mortality rate (ASMR), their trends were quantified by estimated average percentage change (EAPC) and 95% confidence interval (CI).ResultsPredictions suggest that by 2030, there will be 315,310 prostate cancer cases, 192,390 bladder cancer cases and 126,980 kidney cancer cases. The ASIRs will increase to 25.54/100,000 for prostate cancer (EAPC: 2.88, 95% CI, 2.84, 2.93), 7.54/100,000 for bladder cancer (EAPC: 2.58, 95% CI, 2.54, 2.61) and 5.63/100,000 for kidney cancer (EAPC: 4.78, 95% CI, 4.54, 5.02). Number of deaths in 2030 will be 81,540, 61,220, and 41,940, respectively. Different ASMR changes are observed, the ASMR for prostate cancer will drop to 7.69/100,000 (EAPC: -0.29, 95% CI, -0.31, -0.27), the ASMR for bladder cancer will stabilize at 2.49/100,000 (EAPC: 0.00, 95% CI, -0.02, 0.03), the ASMR of kidney cancer will increase to 1.84/100,000 (EAPC: 3.45, 95% CI, 3.22, 3.67). From 1990 to 2030, higher numbers of cases and rates are reported among males and in the 60 plus age group, both ASIR and ASMR of bladder and kidney cancers presents progressively widening differences between both males and females and between the < 60 and the ≥ 60 age groups.ConclusionMorbidity and mortality of the three genitourinary cancers are predicted to increase further over the next decade. It highlights the need for timely development and implementation of optimal health policies to curb the epidemic trends.

Impact of ICT and Globalization on Educational Attainment: Evidence from the New EU Member States

Education is a critical factor underlying the social and economic development of countries and their citizens. Therefore, the specification of factors affecting educational attainment is crucial for the planning and implementation of optimal educational policies. The objective of the article is to research the influence of information and communication technology (ICT), proxied by the ICT index and globalization index on educational attainment in the new EU Member States over the term of 2000–2018 by means of the causality and cointegration test. The causality test points out a unilateral causality from ICT to educational attainment and a bidirectional causality between ICT and globalization. In other words, ICT has a significant effect on educational attainment, but globalization influences educational attainment by way of ICT in the short term. On the other hand, the cointegration test uncovers a positive effect of ICT on educational attainment at panel level and in Croatia, Czechia, Poland, and Slovakia in the long term, while globalization has a positive effect on educational attainment in Bulgaria, Hungary, Lithuania, and Poland. The findings of the cointegration test also support those of the causality test and denote that both ICT and globalization can be effective instruments for improving educational attainment, depending on countries’ current human and physical capital and education policies.

Identification of Internal and External Factors Affecting the Optimal Implementation of Government Policies

The purpose of this study was to identify the internal and external factors associated with the implementation of the organization's policies. It was an applied-descriptive study conducted through a survey method using a questionnaire. For the purpose of this study, after reviewing the literature and theoretical foundations, we tried to identify the most important internal and external factors affecting optimal policy implementation. Therefore, seven factors and their indices were selected based on frequency and importance. In the form of seven hypotheses, the relationship between these factors and optimized policy implementation was evaluated. The statistical population included 120 employees of the Department of Natural Resources and Watershed Management of Khorasan Razavi province. The sample size was calculated using the Morgan formula to be 92 people. Regarding the fact that the policy implementation had an abnormal distribution, the nonparametric single t-test was used to test the hypotheses. The results indicated a positive and significant relationship between all internal and external organizational factors identified by optimal policy implementation in the organization.

A retrospective analysis of policy development on compliance with World Health Organization\u2019s physical activity recommendations between 2002 and 2005 in European Union adults: closing the gap between research and policy

BackgroundPhysical inactivity (PIA) is a mortality risk factor defined as performing lower levels of physical activity than recommended by the World Health Organization (WHO). After 2002, the WHO released the WHA55.23 Resolution and the Global Strategy which produced several changes in policymaking, but with no subsequent analyses of the impact of these changes in European Union (EU) policymaking while examining PIA prevalence.MethodsPIA of 31,946 adults as a whole sample and country-by-country were analyzed in the 2002 and 2005 EU Special Eurobarometers. PIA prevalence between countries was performed with the χ2 test and PIA between both years and between genders was analyzed with the Z-Score test for two population proportions. A retrospective analysis of national plans was performed to interpret the suitability of such policy documents, considering changes in PIA prevalence.ResultsDifferences in PIA prevalence were observed between countries (p < 0.001) and years (p < 0.001) for the whole sample and men and women separately. Within-country samples showed no differences for Denmark, Finland, Ireland, Italy, Luxemburg, Portugal, and Spain (p > 0.05). When considering gender, there were no gender reductions in subsamples for Denmark, Finland, Ireland, Portugal, Spain, and United Kingdom, neither in Luxemburg for men, nor in France and Italy for women. When analyzing gender differences across the entire sample, PIA was higher in women than men for both years (p < 0.001). Greece and Luxemburg did not release national plans for promoting physical activity.ConclusionsWhile large differences in PIA prevalence between EU countries prevailed, the overall PIA descended between both years for the whole sample, men, and women. While this points out a general suitability of policymaking for reducing PIA, not all countries reported reductions in PIA for men, women, or both genders. Also, PIA levels were higher for women in both years, suggesting a less than optimal policy implementation, or lack of women-specific focus across the EU. This analysis helps to identify the strengths and weaknesses of PIA policymaking in the EU and provides researchers with targeted intervention areas for future development.

Strengthening mental health system governance in six low- and middle-income countries in Africa and South Asia: challenges, needs and potential strategies.

Poor governance has been identified as a barrier to effective integration of mental health care in low- and middle-income countries. Governance includes providing the necessary policy and legislative framework to promote and protect the mental health of a population, as well as health system design and quality assurance to ensure optimal policy implementation. The aim of this study was to identify key governance challenges, needs and potential strategies that could facilitate adequate integration of mental health into primary health care settings in low- and middle-income countries. Key informant qualitative interviews were held with 141 participants across six countries participating in the Emerging mental health systems in low- and middle-income countries (Emerald) research program: Ethiopia, India, Nepal, Nigeria, South Africa, and Uganda. Data were transcribed (and where necessary, translated into English) and analysed thematically using framework analysis, first at the country level, then synthesized at a cross-country level. While all the countries fared well with respect to strategic vision in the form of the development of national mental health policies, key governance strategies identified to address challenges included: strengthening capacity of managers at sub-national levels to develop and implement integrated plans; strengthening key aspects of the essential health system building blocks to promote responsiveness, efficiency and effectiveness; developing workable mechanisms for inter-sectoral collaboration, as well as community and service user engagement; and developing innovative approaches to improving mental health literacy and stigma reduction. Inadequate financing emerged as the biggest challenge for good governance. In addition to the need for overall good governance of a health care system, this study identifies a number of specific strategies to improve governance for integrated mental health care in low- and middle-income countries.

Null-space method for optimal operation of transient processes

We consider batch process optimization and robust implementation of optimal control policies. The dynamic optimization of such processes is in most cases model based, and therefore subject to uncertainties. This may lead to sub-optimal control trajectories with significant economical losses. In this paper we extended the concept of self-optimizing control for the optimal operation of transient processes. The main idea is to find a function of the measurements whose trajectory is optimally invariant to disturbances, and then track the trajectory using standard feedback controllers. Doing so results in near-optimal economic operation in spite of varying disturbances without the need for re-optimization. We show that the invariant trajectories can be computed as linear combinations of the measurement vector, where the combination matrix is easily obtained from optimal sensitivities. We illustrate the application of the proposed method in a semi-batch reactor case study.

Optimal Control Policy Tuning and Implementation for a Hybrid Electric Race Car

The Formula 1 car is a state-of-the-art hybrid electric vehicle. Its power unit is composed by a turbocharged gasoline engine and two electric motor/generator units connected to the traction system and to the turbocharger. Such a powertrain offers an additional degree of freedom and therefore requires an energy management system. This supervisory controller has a significant influence on the vehicle’s fuel consumption and on the achievable lap-time. Therefore, a thorough, systematic optimization of the energy management system is a crucial prerequisite to win a race. The complexity of the system and the strict regulations make the time-optimal energy management problem non-trivial to solve and an effective implementation of its solution on the car difficult to achieve. In Ebbesen, S. et al. (2016) and Salazar, M. et al. (2016) a convex numerical solver was designed and the optimal strategies were derived analytically using a non-smooth version of Pontryagin’s Minimum Principle, respectively. Building on these results, we design a nonlinear program to tune an efficient version of the optimal control policy, in order to precisely match various boundary conditions on the fuel consumption and on the battery usage. This allows a simple and robust implementation of the time-optimal control strategies on the vehicle, and guarantees compatibility with the FIA rules. A simulator is then used to test the obtained feedforward controls on one race lap in Barcelona. The results stand comparison with the optimal solutions obtained with the numerical solver and validate the effectiveness of this strategy.

Assessing the accessibility impact of transport policy by a land-use and transport interaction model – The case of Madrid

Accessibility is an essential concept widely used to evaluate the impact of transport and land-use strategies in urban planning and policy making. Accessibility is typically evaluated by using separately a transport model or a land-use model. This paper embeds two accessibility indicators (i.e., potential and adaptive accessibility) in a land use and transport interaction (LUTI) model in order to assess transport policies implementation. The first aim is to define the adaptive accessibility, considering the competition factor at territorial level (e.g. workplaces and workers). The second aim is to identify the optimal implementation scenario of policy measures using potential and adaptive accessibility indicators. The analysis of the results in terms of social welfare and accessibility changes closes the paper.Two transport policy measures are applied in Madrid region: a cordon toll and increase bus frequency. They have been simulated through the MARS model (Metropolitan Activity Relocation Simulator, i.e. LUTI model). An optimisation procedure is performed by MARS for maximizing the value of the objective function in order to find the optimal policy implementation (first best). Both policy measures are evaluated in terms of accessibility.Results show that the introduction of the accessibility indicators (potential and adaptive) influence the optimal value of the toll price and bus frequency level, generating different results in terms of social welfare. Mapping the difference between potential and adaptive accessibility indicator shows that the main changes occur in areas where there is a strong competition among different land-use opportunities.

An Economic Analysis of Maritime Piracy and its Control

AbstractModern‐day piracy on the high seas poses a serious threat to international shipping. This paper develops an economic of model of piracy that emphasizes the strategic interaction between the efforts of pirates to locate potential targets, and shippers to avoid contact. Implementation of optimal enforcement policies is complicated by the need for international cooperation in the apprehension and prosecution of pirates. Free riding and other problems therefore impede the effectiveness of current international laws against piracy.

Dynamic Packet Scheduler Optimization in Wireless Relay Networks

In this work, we investigate the optimal dynamic packet scheduling policy in a wireless relay network (WRN). We model this network by two sets of parallel queues, that represent the subscriber stations (SS) and the relay stations (RS), with random link connectivity. An optimal policy minimizes, in stochastic ordering sense, a cost function of the SS and RS queue sizes. We prove that, in a system with symmetrical connectivity and arrival distributions, a policy that tries to balance the lengths of all the system queues, at every time slot, is optimal. We use stochastic dominance and coupling arguments in our proof. We also provide a low-overhead algorithm for optimal policy implementation.

Optimal, heuristic and Q‐learning based DSA policies for cellular networks with coordinated access band

AbstractDue to the increasing demands for higher data rate applications, also due to the actual spectrum crowd situation, Dynamic Spectrum Access (DSA) turned into an active research topic. In this paper, we analyse DSA in cellular networks context, where a Coordinated Access Band (CAB) is shared between Radio Access Networks (RANs). We propose a Semi‐Markov Decision Process (SMDP) approach to derive the optimal DSA policies in terms of operator reward. In order to overcome the limitations induced by optimal policy implementation, we also propose two simple, though sub‐optimal, DSA algorithms: a Q‐learning (QL) based algorithm and a heuristic algorithm. The achieved reward using the latter is shown to be very close to the optimal case and thus to significantly exceed the reward obtained with Fixed Spectrum Access (FSA). The rewards achieved by using the QL‐based algorithm are shown to exceed those obtained by using FSA. Higher rewards and better spectrum utilisation with DSA optimal and heuristic methods are, however, obtained at the price of a reduced average user throughput. Copyright © 2010 John Wiley &amp; Sons, Ltd.

Online model-based control of an emulsion terpolymerisation process

A multivariable constrained model predictive control was formulated and implemented to control online an emulsion terpolymerisation process. A generic multilayer control architecture for real-time implementation of optimal control policies for particulate processes was also developed. The methodology was implemented within a multi-tiered software environment for real-time implementation of model-based control strategies. A full mechanistic dynamic model for emulsion terpolymerisation, developed in our previous work, is used as a real-time soft-sensor and incorporated within the MPC strategy. The simultaneous control of key polymer properties such as the particle size distribution (PSD), average molecular weight (Mn) and terpolymer composition were investigated using case studies involving manipulation of flow rates of monomers (styrene, MMA, MA), surfactant and initiator, and the reactor temperature. Although some offsets were observed with a degree of model mismatch, the experimental results agreed well with predictions.

IMPLEMENTATION OF OPTIMAL OPERATION USING OFF-LINE COMPUTATIONS

The computational effort involved in the solution of real-time optimization problems can be very demanding. Hence, simple but effective implementation of optimal policies are attractive. The main idea is to use off-line calculations and analysis to determine the structure and properties of the optimal solution. This will be used to determine alternate representations of the optimal solution that are more suitable for implementation.

CacheFlow: Cache Optimizations for Data Driven Multithreading

Data-Driven Multithreading is a non-blocking multithreading model of execution that provides effective latency tolerance by allowing the computation processor do useful work, while a long latency event is in progress. With the Data-Driven Multithreading model, a thread is scheduled for execution only if all of its inputs have been produced and placed in the processor's local memory. Data-driven sequencing leads to irregular memory access patterns that could affect negatively cache performance. Nevertheless, it enables the implementation of short-term optimal cache management policies. This paper presents the implementation of CacheFlow, an optimized cache management policy which eliminates the side effects due to the loss of locality caused by the data-driven sequencing, and reduces further cache misses. CacheFlow employs thread-based prefetching to preload data blocks of threads deemed executable. Simulation results, for nine scientific applications, on a 32-node Data-Driven Multithreaded machine show an average speedup improvement from 19.8 to 22.6. Two techniques to further improve the performance of CacheFlow, conflict avoidance and thread reordering, are proposed and tested. Simulation experiments have shown a speedup improvement of 24% and 32%, respectively. The average speedup for all applications on a 32-node machine with both optimizations is 26.1.

Closed-loop optimal operation of batch distillation columns

Often, the main source of disturbance for a batch distillation system is an upset in the feed to the process. If the operation of a batch column is carried out on the basis of the nominal value of the feed composition, a high degree of uncertainty in the initial conditions to the batch may lead to run the column suboptimally, with a possibly large economic penalty. In this paper, a three-step strategy is proposed for the closed-loop implementation of optimal operating policies for batch rectifiers. First, the optimal reflux rate is calculated off-line for several feed compositions. Then, a correlation is developed off-line between the optimal reflux rate and the composition profile in the column at the end of the startup phase. Finally, the detection of the composition profile is performed on-line during the startup phase, so that the optimal reflux rate can be calculated and implemented in a closed-loop fashion. This allows operating the column optimally even though the actual feed composition is not known. Since the calculations to be performed on-line are straightforward, the computational demand is kept to a minimum. Results for binary and ternary systems indicate that, by using the proposed procedure, the column performance can be improved by as much as 30% with respect to a conventional open-loop optimal strategy.