Healthcare’s Sustainable Resource Planning Using Neutrosophic Goal Programming

We develop neutrosophic goal programming models for sustainable resource planning in a healthcare organization. The neutrosophic approach can help examine the imprecise aspiration levels of resources. For deneutrosophication, the neutrosophic value is transformed into three intervals based on the truth, falsity, and indeterminacy-membership functions. Then, a crisp value is derived. Moreover, multi-choice goal programming is also used to get a crisp value. The proposed models seek to draw a strategic plan and long-term vision for a healthcare organization. Accordingly, the specific aims of the proposed flexible models are meant to evaluate hospital service performance and to establish an optimal plan to meet the growing patient needs. As a result, sustainability’s economic and social goals will be achieved so that the total cost would be optimized, patients’ waiting time would be reduced, high-quality services would be offered, and appropriate medical drugs would be provided. The simplicity and feasibility of the proposed models are validated using real data collected from the Al-Amal Center for Oncology, Aden, Yemen. The results obtained indicate the robustness of the proposed models, which would be valuable for planners who could guide healthcare staff in providing the necessary resources for optimal annual planning.

Subspace Detours Meet Gromov–Wasserstein

In the context of optimal transport (OT) methods, the subspace detour approach was recently proposed by Muzellec and Cuturi. It consists of first finding an optimal plan between the measures projected on a wisely chosen subspace and then completing it in a nearly optimal transport plan on the whole space. The contribution of this paper is to extend this category of methods to the Gromov–Wasserstein problem, which is a particular type of OT distance involving the specific geometry of each distribution. After deriving the associated formalism and properties, we give an experimental illustration on a shape matching problem. We also discuss a specific cost for which we can show connections with the Knothe–Rosenblatt rearrangement.

DESIGN OF THE TOURIST INFRASTRUCTURE OF THE CITY APPLICATION. PROBLEMS OF LEISURE PLANNING

The article considers the current problem of tourism development in Ukraine and in a particular city Kharkiv. This problem is especially relevant today, due to the spread of COVID-19 pandemic. Nowadays, in order to correct the situation in this sector of the economy, it is advisable to use specialized information support. There are many different resources on the Internet, with which one can get help or mark out a route, depending on the selected points of interest. Some of them specialize in working with the map, in particular in marking out routes, finding and displaying places of tourist infrastructure on the map. Others display information about events taking place in these places without cartographic reference. But each of these resources has only a part of the needs of a tourist or resident who wants to plan their leisure time. The proposed application will fill all the flaws of existing resources. It will meet the needs of navigation, information and planning functions. In other words this application will be the first application that combines the functions of finding and providing information about places of tourist attraction, marking out routes between them and creating an optimal plan for visiting them. The geographic information system ArcGIS was chosen to solve this problem. It contains the necessary modules for working with vectorized maps, layers and provides programming. An intuitive application interface was created using VBA. It contains the necessary forms for routing between points of interest and time planning. The article demonstrated the capabilities of geographic information systems in tourism business sphere It demonstrated a solution that allows with maximum convenience and minimum time not only to obtain the necessary information, but also to plan their leisure. It will help even during lockdowns and other anti-epidemic measures to prevent decline of tourist infrastructure.

Teenage Male with Cough and Recurrent Bruit

A general pediatrician is skilled at continuity; through longitudinal evaluation, they serve as front-line providers in the recognition and referral of unusual pathology. The majority of arteriovenous malformations (AVM) are diagnosed with history and physical examination. AVM are inherently progressive by nature; their expansion is what creates the risk of morbidity. With higher-risk vascular lesions, relative risk is important when discussing management with observation versus with invasive intervention. Size, location, and expected course of progression of the lesion help generate a timeline for action. Collaboration of physicians with diverse expertise generates optimal plan of therapy, particularly when faced with an unusual clinical finding. Genetics referral may be beneficial, as the body of literature on AVM is growing, and databases on associated syndromes are evolving. Establishing concrete follow-up is imperative to assess for recurrence of AVM or development of additional symptoms. This can be with the interventionalist or with the generalist.

Current Concepts in Humeral Component Design for Anatomic and Reverse Shoulder Arthroplasty

The history of humeral component design has evolved from prostheses with relatively long stems and limited anatomic head options to a contemporary platform with short stems and stemless implants with shared instrumentation and the ability to provide optimal shoulder reconstruction for both anatomic and reverse configurations. Contemporary humeral components aim to preserve the bone, but they are potentially subject to malalignment. Modern components are expected to favorably load the humerus and minimize adverse bone reactions. Although there will likely continue to be further refinements in humeral component design, the next frontiers in primary shoulder arthroplasty will revolve around designing an optimal plan, including adequate soft tissue tension and providing computer-assisted tools for the accurate execution of the preoperative plan in the operating room.

Devising methods for planning a multifactorial multilevel experiment with high dimensionality

This paper considers the task of planning a multifactorial multilevel experiment for problems with high dimensionality. Planning an experiment is a combinatorial task. At the same time, the catastrophically rapid growth in the number of possible variants of experiment plans with an increase in the dimensionality of the problem excludes the possibility of solving it using accurate algorithms. On the other hand, approximate methods of finding the optimal plan have fundamental drawbacks. Of these, the main one is the lack of the capability to assess the proximity of the resulting solution to the optimal one. In these circumstances, searching for methods to obtain an accurate solution to the problem remains a relevant task. Two different approaches to obtaining the optimal plan for a multifactorial multilevel experiment have been considered. The first of these is based on the idea of decomposition. In this case, the initial problem with high dimensionality is reduced to a sequence of problems of smaller dimensionality, solving each of which is possible by using precise algorithms. The decomposition procedure, which is usually implemented empirically, in the considered problem of planning the experiment is solved by employing a strictly formally justified technique. The exact solutions to the problems obtained during the decomposition are combined into the desired solution to the original problem. The second approach directly leads to an accurate solution to the task of planning a multifactorial multilevel experiment for an important special case where the costs of implementing the experiment plan are proportional to the total number of single-level transitions performed by all factors. At the same time, it has been proven that the proposed procedure for forming a route that implements the experiment plan minimizes the total number of one-level changes in the values of factors. Examples of problem solving are given

Hierarchical planning in a supervisory control context with compositional abstraction

Hierarchy is a tool that has been applied to improve the scalability of solving planning problems modeled using Supervisory Control Theory. In the work of Hill and Lafortune (2016), the notion of cost equivalence was employed to generate an abstraction of the supervisor that, with additional conditions, guarantees that an optimal plan generated on the abstraction is also optimal when applied to the full supervisor. Their work is able to improve their abstraction by artificially giving transitions zero cost based on the sequentially-dependent ordering of events. Here, we relax the requirement on a specific ordering of the dependent events, while maintaining the optimal relationship between upper and lower levels of the hierarchy. This present paper also extends the authors’ work (Vilela and Hill 2020) where we developed a new notion of equivalence based on cost equivalence and weak bisimulation that we term priced-observation equivalence. This equivalence allows the supervisor abstraction to be generated compositionally. This helps to avoid the explosion of the state space that arises from having to first synthesize the full supervisor before the abstraction can be applied. Here, we also show that models with artificial zero-cost transitions can be created compositionally employing the new relaxed sequential dependence definition. An example cooperative robot control application is used to demonstrate the improvements achieved by the compositional approach to abstraction proposed by this paper.

Application of a Similarity Measure Using Fuzzy Sets to Select the Optimal Plan for an Air-Assisted Rice Seeder

Air-assisted rice seeders were designed to perform sowing while ensuring the alignment and depth of seeds within the allowable standard range of 5–10 mm. Their performance varies on the basis of different specifications; thus, it is necessary to evaluate them to select the best one. Fuzzy set theory allows us to flexibly handle practical problems, especially applied problems in engineering. In this paper, a new similarity measure using fuzzy sets is proposed, and its advantages were tested using the technique for order preference by similarity to ideal solution (TOPSIS) method to select technical parameters for the sowing machines. The experiments allowed identifying the best results. The correlations between input attributes and decision variables were determined on the basis of their correlation coefficients with technical factors. The influence of technical factors on output results was also examined to determine the technical factors providing superior product quality.

DELIVERY MANAGEMENT ALGORITHMS AND THEIR APPLICATIONS

In this article optimization problem of product delivery problems in modern business has been investigated.Desition-making problems to manage network sales strategy is solved.The dynamical model of multistage graph has been constructed. The algorithms to find optimal plan of products salsment is performed. The tools applied in this development based on the generalized dynamical programming methods and graph theory applications.Javascript programming language for software implementation is used.