On Enhanced GLM-Based Monitoring: An Application to Additive Manufacturing Process

Innovations in technology assist the manufacturing processes in producing high-quality products and, hence, become a greater challenge for quality engineers. Control charts are frequently used to examine production operations and maintain product quality. The traditional charting structures rely on a response variable and do not incorporate any auxiliary data. To resolve this issue, one popular approach is to design charts based on a linear regression model, usually when the response variable shows a symmetric pattern (i.e., normality). The present work intends to propose new generalized linear model (GLM)-based homogeneously weighted moving average (HWMA) and double homogeneously weighted moving average (DHWMA) charting schemes to monitor count processes employing the deviance residuals (DRs) and standardized residuals (SRs) of the Poisson regression model. The symmetric limits of HWMA and DHWMA structures are derived, as SR and DR statistics showed a symmetric pattern. The performance of proposed and established methods (i.e., EWMA charts) is assessed by using run-length characteristics. The results revealed that SR-based schemes have relatively better performance as compared to DR-based schemes. In particular, the proposed SR-DHWMA chart outperforms the other two, namely SR-EWMA and SR-HWMA charts, in detecting shifts. To illustrate the practical features of the study’s proposal, a real application connected to the additive manufacturing process is offered.

Research protocol for the implementation of management control tools in the operational areas of a logistics facility in the state of Veracruz

Management control tools are of great importance for any organization, therefore, in this research work, the study of management control tools will be carried out in the operational areas of a logistics facility in the state of Veracruz. , to later develop a measuring instrument. The study proposes to design a measurement instrument based on a Likert scale, converting qualitative information into quantitative data by the researcher, which allows visualization and clarity in determining the ideal tools for the control management of the studied area. The instrument will be applied to the company's experts, since they provide reliable information and provide a reliable scenario. The information is analyzed by the researcher, to later design and define a proposal, a proposal that allows the correct selection of control management tools and comprehensively improve the organization.

Using artificial intelligence in healthcare: Allocating liability and risks

Within the framework of this article, the author considers the features regarding the application and use of artificial intelligence (AI) in medical practice. This includes complex issues related to the personal liability of a doctor when making decisions on diagnostics and treatment based on an algorithm proposal (a system for supporting medical decisions), as well as possible options for the responsibility of the algorithm (AI) developer. The analysis provides an overview of the existing system for holding medical professionals accountable, as well as an assessment of possible options for the distribution of responsibility in connection with the widespread introduction of AI into the work of doctors alongside the possible introduction of AI into standard medical care. The author considers the possibility of establishing more serious requirements for the collection of information on the side effects of such devices for an AI registered as a medical device. Using the method of legal analysis and the comparative legal method, the author analyzes the current global trends in the distribution of responsibility for harm in such cases where there is an error and/or inaccuracy in making a medical decision; as a result of this, the author demonstrates possible options for the distribution of the roles of the healthcare professional and AI in the near future.

Standpoint Epistemology and Nursing Science

In this article, I propose that engagement in nursing practice affords an epistemic advantage and should be included in defining nursing science and as a warrant for scientific knowledge. I appeal to standpoint epistemology, a philosophical theory, to support my proposal. A new conception of objectivity, which aligns with the contemporary practice of science and standpoint theory, is discussed. The article presents a preliminary theory of nursing standpoint theory that explains epistemic advantage of a practicing nurse. Open questions about nursing science conclude the article.

RESEARCH OF THE SLP METHOD TO IMPROVE THE LAYOUT OF AN ICE CREAM FACTORY

The problems of physical arrangement for the organizations are relevant when have space and material movements limitations. Reviewing layouts is a way to improve the industrial production process. Therefore, the objective of this present academic work is to propose a layout for an ice cream factory's production, considering analysis of alternatives to increase productivity. The Systematic Layout Planning (SLP) Simplified method was used as the main tool for the construction of the layout proposal. A case study was carried out which investigates a phenomenon within a real context through an in-depth analysis of a study object. The method was used systematically and validated from the fifth step, where a qualitative comparation between the current layout and the alternative submitted. As a result, is achieved an optimized, complete, detailed layout plan that reduces 21,30% of the factory handling cost.

Performance Analysis in the Segmentation of urban asphalted roads in RGB satellite images using K-Means++ and SegNet

The design and manual insertion of new terrestrial roads into geographic databases is a frequent activity in geoprocessing and their demand usually occurs as the most up-to-date satellite imagery of the territory is acquired. Continually, new urban and rural occupations emerge, for which specific vector geometries need to be designed to characterize the cartographic inputs and accommodate the relevant associated data. Therefore, it is convenient to develop a computational tool that, with the help of artificial intelligence, automates what is possible in this respect, since manual editing depends on the limits of user agility, and does it in images that are usually easy and free to access. To test the feasibility of this proposal, a database of RGB images containing asphalted urban roads is presented to the K-Means++ algorithm and the SegNet Convolutional Neural Network, and the performance of each was evaluated and compared for accuracy and IoU of road identification. Under the conditions of the experiment, K-Means++ achieved poor and unviable results for use in a real-life application involving tarmac detection in RGB satellite images, with average accuracy ranging from 41.67% to 64.19% and average IoU of 12.30% to 16.16%, depending on the preprocessing strategy used. On the other hand, the SegNet Convolutional Neural Network proved to be appropriate for precision applications not sensitive to discontinuities, achieving an average accuracy of 87.12% and an average IoU of 71.93%.

Management as a necessary tool for the prevention of violence against women

The chair "Women, family and Guantanamo society" in the Guantánamo province as part of its functions intends the following investigation that addresses the theme of the prevention of violence against women from its management. This has the purpose of contributing to the educational preparation of agencies and social agents as an effective response to the demands of today's Cuban society. The study assumes the methodological-materialist and historical dialectical conception with the use of general research methods, with references, aspects of historical and theoretical-methodological evolution in the sociological, psychological, pedagogical and legal areas. The diagnostic results of the study made it possible to design as a methodological proposal a management strategy for the prevention of violence against women, which is strengthened from the integration of agencies and social agents, which places the University as the most important educational agency of the community.

Uncertanties and Risk Analysis on Ports Construction Projects Considering Technological and Market Strategic Factors

This article appropriates a new methodology for evaluating port projects involving not only economic analysis, but also strategic factors, technological and market, wich provide greater security and assertiveness on the search for the development of a Hub Port model as an option to optimize the logistics of port operations. To achieve the objectives of the proposal, a technical and economic analysis model was developed to demonstrate the feasibility of the project with the inclusion of technological features (deep of ships, modes of transport linking the port to its region of land influence, expansion area) and market components (cargo demands, free trade zone, distance from the main centers of world trade) that decisively interfere in the attractiveness of the project. Linked to this proposal, a risk analysis was carried out, including uncertainties involving economic and strategic aspects, with market and technological variables. To achieve the objectives of the study, the Monte Carlo method operated by the software “@RiskTM” was used, where the analyzes of positive and negative interferences in the project were carried out. To evaluate the proposed methodology, it was applied in two cases studies of the feasibility of a new logistics platform in Brazil and Africa, with the implementation of an offshore cargo concentrator port. One was in the State of Pará, in northern Brazil, and the other in Dakar, Senegal, which can integrate the entire South America and Africa, respectivaly. The results of those analysis show very favorable indicators for the implementation of the proposed projects. Considering that, strategic factors introduced in the study, the greatest influences were: transport modes that link the port to the land influence zone and the draft of the ships. For the offshore port of Pará, strategic factors boosted the viability result by approximately 55% for a 95% probability of success and for Dakar, in Africa, the results were 100%, both for a 14% rate and a life span of 30 years showing that strategic factors are elements very importatants, as they produced almost 100% and 70% elasticity in the results, respectivaly, so they should be considered in feasibility studies of hub ports in addition to tradicioanl economic analysis.

A Shallow–Deep Feature Fusion Method for Pedestrian Detection

In this paper, a shallow–deep feature fusion (SDFF) method is developed for pedestrian detection. Firstly, we propose a shallow feature-based method under the ACF framework of pedestrian detection. More precisely, improved Haar-like templates with Local FDA learning are used to filter the channel maps of ACF such that these Haar-like features are able to improve the discriminative power and therefore enhance the detection performance. The proposed shallow feature is also referred to as weighted subset-haar-like feature. It is efficient in pedestrian detection with a high recall rate and precise localization. Secondly, the proposed shallow feature-based detection method operates as a region proposal. A classifier equipped with ResNet is then used to refine the region proposals to judge whether each region contains a pedestrian or not. The extensive experiments evaluated on INRIA, Caltech, and TUD-Brussel datasets show that SDFF is an effective and efficient method for pedestrian detection.