Designing alternative scenarios for the provincial region development based on the scenario planning methodology

Subject. This article considers the issues of application of scenario planning techniques in the process of constructing alternative scenarios for the development of spatial socio-economic systems in the context of changes, complexity, and uncertainty. Objectives. The article aims to form a scenario planning algorithm for spatial socio-economic systems and its implementation in relation to the Mari El Republic. Methods. For the study, we used the systems approach and foresight techniques. Results. The article presents four alternative scenarios for the development of the provincial region: intensive, technological, moderately technological and pessimistic. The article presents four alternative scenarios for the development of the provincial region, namely, the intensive, technological, moderate technological, and worst-case ones. Conclusions and Relevance. The technological scenario for the provincial region’s development seems to be the most likely. It assumes moderately favorable prospects for attracting investment, which can stimulate the development of regional key industries. The proposed alternative scenarios can serve as a basis for the policy making by regional and municipal authorities.

Cam Mechanisms Reverse Engineering Based on Evolutionary Algorithms

Cam follower mechanisms are widely used in automated manufacturing machinery to transform a rotary stationary motion into a more general required movement. Reverse engineering of cams has been studied, and some solutions based on different approaches have been identified in the literature. This article proposes an innovative method based on the use of an evolutionary algorithm for the identification of a law of motion that allows for approximating in the best way the motion or the sampled profile on the physical device. Starting from the acquired data, through a genetic algorithm, a representation of the movement (and therefore of the cam profile) is identified based on a type of motion law traditionally used for this purpose, i.e., the modified trapezoidal (better known as modified seven segments). With this method it is possible to estimate the coefficients of the parametric motion law, thus allowing the designer to further manipulate them according to the usual motion planning techniques. In a first phase, a study of the method based on simulations is carried out, considering sets of simulated experimental measures, obtained starting from different laws of motion, and verifying whether the developed genetic algorithm allows for identifying the original law or approximating one. For the computation of the objective function, the Euclidean norm and the Dynamic Time Warping (DTW) algorithm are compared. The performed analysis establishes in which situations each of them is more appropriate. Implementation of the method on experimental data validates its effectiveness.

On Eventual Applicability of Plans in Dynamic Environments with Cyclic Phenomena

Planning and acting in dynamic environments deals with non-deterministic events that might change the state of the environment without consent of the agent. In the worst case, some events might cause the agent to become ``trapped'' in a dead-end state, which in practice might mean damage or destruction of the agent. Presence of non-deterministic events often considerably increases the number of alternatives that might occur in a single step and hence traditional non-deterministic planning techniques might not scale. In this paper, we address a class of problems where non-deterministic events represent ``cyclic phenomena''. If they interfere with the agent, they might be dangerous for it (e.g. ships cruising through the area of AUV operations). We present techniques that initially analyse the problem whether it falls within this class by considering the notion of event reversibility and if so, these techniques generate a plan such that encountered unsafe states, in which the ``cyclic phenomena'' might interfere with the agent, can be eventually crossed without any risk of ``falling'' into a dead-end state. Our approach is evaluated in the AUV and Perestroika domains.

An adaptive motion planning algorithm for obstacle avoidance in autonomous vehicle parking

In the recent era, machine learning-based autonomous vehicle parking and obstacle avoidance navigation have drawn increased attention. An intelligent design is needed to solve the autonomous vehicles related problems. Presently, autonomous parking systems follow path planning techniques that generally do not possess a quality and a skill of natural adapting behavior of a human. Most of these designs are built on pre-defined and fixed criteria. It needs to be adaptive with respect to the vehicle dynamics. A novel adaptive motion planning algorithm is proposed in this paper that incorporates obstacle avoidance capability into a standalone parking controller that is kept adaptive to vehicle dimensions to provide human-like intelligence for parking problems. This model utilizes fuzzy membership thresholds concerning vehicle dimensions and vehicle localization to enhance the vehicle’s trajectory during parking when taking into consideration obstacles. It is generalized for all segments of cars, and simulation results prove the proposed algorithm’s effectiveness.

Custom-Design of FDR Encodings: The Case of Red-Black Planning

Classical planning tasks are commonly described in PDDL, while most planning systems operate on a grounded finite-domain representation (FDR). The translation of PDDL into FDR is complex and has a lot of choice points---it involves identifying so called mutex groups---but most systems rely on the translator that comes with Fast Downward. Yet the translation choice points can strongly impact performance. Prior work has considered optimizing FDR encodings in terms of the number of variables produced. Here we go one step further by proposing to custom-design FDR encodings, optimizing the encoding to suit particular planning techniques. We develop such a custom design here for red-black planning, a partial delete relaxation technique. The FDR encoding affects the causal graph and the domain transition graph structures, which govern the tractable fragment of red-black planning and hence affects the respective heuristic function. We develop integer linear programming techniques optimizing the scope of that fragment in the resulting FDR encoding. We empirically show that the performance of red-black planning can be improved through such FDR custom design.

An Innovative VMAT Technique for Left-sided Breast Cancer Patients With Postmastectomy Radiotherapy (PMRT) Evaluated by Ratio of Heart Volume in Tangent Line (RHVTL)

For patients with left-sided breast cancer (LBC), postmastectomy radiotherapy (PMRT) has been shown to improve the overall survival and many advanced planning techniques was adopted in PMRT. We aim to use an innovative VMAT technique to enhance the conformity of PTV and reduce the scattering dose of surrounding OARs, thereby reducing the long-term toxicity of the heart as well as ipsilateral lung (IL). The study further analyzes the more appropriate treatment planning techniques for personalized LBC patients with PMRT. 35 LBC patients were retrospectively selected undergoing PMRT. The PTV included lymph nodes, chest walls, excluding internal mammary nodes, where 95% of PTV receiving the prescription dose of 50Gy (2Gy/fraction) with three different techniques, VMAT, IMRT, Hybrid VMAT. Furthermore, the ratio of Heart Volume in Tangent line and heart volume (RHVTL) was proposed to evaluate the relative antonymy position between patient's heart and PTV, which hypothetically represents the complexity of treatment planning. The data from this study showed that for LBC patients undergoing PMRT, the CI from VMAT was 0.85 (IMRT and H-VMAT were 0.77 and 0.83), the heart D mean was 502.9cGy (IMRT and H-VMAT were 675.6cGy and 687cGy) and the V20 of IL was 21.3 as the lowest of the three techniques, but the dose of the contralateral breast (CB) and contralateral lung increased noticeably. In H-VMAT and IMRT, the mean heart dose was significantly related to RHVTL, with R-values of 0.911 and 0.892 respectively, while the values in VMAT was 0.613, thus the VMAT technique was relatively unaffected by the difficulty of treatment plan. For RHVTL values exceed than 0.06, the mean heart dose under VMAT technique raised by 98.7cGy compared to the RHVTL value of less than 0.06, but H-VMAT and IMRT increased by 233cGy and 261.58cGy individually. This study illustrates that separated fields and adjacent fields in VMAT technique obtained the optimal conformality and lowest doses of heart in three techniques for LBC with PMRT. Thus, based on the results of our preliminary study, the VMAT technique is highly recommended when RHVTL is exceeded 0.06.