A new method for the detection of singular points in fingerprint images

Automatic biometric identification based on fingerprintsis still one of the most reliable identification method in criminaland forensic applications. A critical step in fingerprintanalysis without human intervention is to automatically andreliably extract singular points from the input fingerprintimages. These singular points (cores and deltas) not onlyrepresent the characteristics of local ridge patterns but alsodetermine the topological structure (i.e., fingerprint type)and largely influence the orientation field. Poincaré Indexbasedmethods are one of the most common for singularpoints detection. However, these methods usually result inmany spurious detections. Therefore, we propose an enhancedversion of the method presented by Zhou et al. [13]that introduced a feature called DORIC to improve the detection.Our principal contribution lies in the adoption of asmoothed orientation field and in the formulation of a newalgorithm to analyze the DORIC feature. Experimental resultsshow that the proposed algorithm is accurate and robust,giving better results than the best reported results sofar, with improvements in the range of 5% to 7%

Automatic nurse allocation based on a population algorithm for home health care

The provision of home health care services is becoming an important research area, mainly because in Portugal the population is ageing and it is necessary to perform home care services. Home care visits are organized taking into account the medical treatments and general support that elder/sick people need at home. This health service can be provided by nurses teams from Health Units, requiring some logistics for this purpose. Usually, the visits are manually planned and without computational support. The main goal of this work is to carry out the automatic nurse’s allocation of home care visits, of one Bragança Health Unit, in order to minimize the nurse’s workload balancing, spent time in all home care visits and, consequently, reduce the costs involved. The developed methodology was coded in MatLab Software and the problems were efficiently solved by the particle swarm optimization method. The nurse’s allocation solution of home care visits for the presented case study shows a significant improvement and reduction in the maximum time, in the nurse workload balancing, as well as the patients waiting time.This work has been supported by COMPETE:POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia within the project UID/CEC/00319/2019

Accuracy and simultaneous selection gains for grain yield and earliness in tropical maize lines

Winter maize is sown between January and March in Brazil. Although this maize is sown in unfavorable weather conditions, many farmers are successful, and winter maize has become an important crop. The sowing of early hybrids is a strategy to reduce the effects of stress on yield; however, low yields may result from earliness. Thus, the objectives in this study were to investigate tropical maize lines for the possibility of simultaneous selection for yield and earliness and to compare the differences among the simultaneous selection methods. Therefore, 64 lines were evaluated in two locations for grain yield, days to female flowering and grain moisture at harvest. The genotypic values for these traits were predicted using Restricted Maximum Likelihood/Best Linear Unbiased Predictor (REML/BLUP) single-trait (univariate) and multi-trait (multivariate) methods. Using three simultaneous selection methods (i.e., Additive index, Mulamba-Mock index and Independent culling levels) with two methods of prediction for genotypic values (single-trait and multi-trait), six simultaneous selection scenarios were considered and then compared for selection gains and accuracy. Because of the low correlation between these traits, the pre- dictions of genotypic values were similar for single-trait and multi-trait methods. Thus, single-trait analysis should be prioritized because of its practicality. The Additive index obtained the highest selection gain for grain yield and simultaneously achieved good gains for days to female flowering and grain moisture at harvest. Therefore, the Additive index, using the single-trait prediction method, is the best simultaneous selection method for yield and earliness in tropical maize lines

Multi-agent system specification for distributed scheduling in home health care

Nowadays, scheduling and allocation of resources and tasks becomes a huge and complex challenge to the most diverse industrial areas, markets, services and health. The problem with current scheduling systems is that their management is still done manually or using classical optimization methods (usually static, time-consuming) and centralized approaches. However, opportunities arise to decentralize solutions with smart systems, which enable the distribution of the computational effort, the flexibility of behaviours and the minimization of operating times and operational planning costs. The paper proposes the specification of a Multi-agent System (MAS) for the Home Health Care (HHC) scheduling and allocation. The MAS technology enables the scheduling of intelligent behaviours and functionalities based on the interaction of agents, and allows the evolution of current strategies and algorithms, as it can guarantee the fast response to condition changes, flexibility and responsiveness in existing planning systems. An experimental HHC case study was considered to test the feasibility and effectiveness of the proposed MAS approach, the results demonstrating promising qualitative and quantitative indicators regarding the efficiency and responsiveness of the HHC scheduling.This work has been supported by FCT—Fundação para a Ciência e a Tecnologia within the R&D Units Projects Scope: UIDB/00319/2020 and UIDB/05757/2020. Filipe Alves is supported by FCT Doctorate Grant Reference SFRH/BD/143745/2019

Corncob cellulose scaffolds: A new sustainable temporary implant for cartilage replacement

Tissue engineering using scaffolds is a promising strategy to repair damaged articular cartilage, whose self-repair is inefficient. Cellulose properties have been recognized for their application in the biomedical field. The aim of this study was to fabricate and characterize novel scaffolds based on poly(E-caprolactone) (PCL) and sustainable cellulose. Thus, the performance of corncob-derived cellulose (CC) in scaffolds as an alternative to wood cellulose (WC) was also investigated to reduce the environmental footprint. Two concentrations of CC in scaffolds were tested, 1% and 2% (w/w), and commercial WC using the same concentrations, as a control. Morphologically, all the developed scaffolds presented pore sizes of ~300 m, 10 layers, a circular shape and well-dispersed cellulose. Thus, all of these characteristics and properties provide the manufactured scaffolds suitable for use in cartilage-replacement strategies. The use of 2% CC results in higher porosity (54.24%), which promotes cell infiltration/migration and nutrient exchange, and has similar mechanical properties to WC. As for the effects of enzymatic degradation of the scaffolds, no significant changes (p > 0.05) were observed in resistance over time. However, the obtained compressive modulus of the scaffold with 2% CC was similar to that of WC. Overall, our results suggest that the integration of 2% corncob cellulose in PCL scaffolds could be a novel way to replace wood-cellulose-containing scaffolds, highlighting its potential for cartilage-replacement strategies.info:eu-repo/semantics/publishedVersio

A multi-objective approach to the optimization of home care visits scheduling

Due to the increasing of life expectancy in the developed countries, the demand for home health care services is growing dramatically. Usually, home services are planned manually and lead to various optimization problems in their activities. In this sense, health units are confronted with appropriate scheduling which may contain multiple, often conflicting, objectives such as minimizing the costs related to the traveling distance while minimizing the traveling time. In order to analyze and discuss different trade-offs between these objectives, it is proposed a multi-objective approach to home health care scheduling in which the problem is solved using the Tchebycheff method and a Genetic algorithm. Different alternative solutions are presented to the decision maker that taking into account his/her preferences chooses the appropriate solution. A problem with real data from a home health care service is solved. The results highlight the importance of a multi-objective approach to optimize and support decision making in home health care services. Moreover, this approach provides efficient and good solutions in a reasonable time.Programa Operacional Temático Factores de Competitividade(POCI-01-0145-FEDER-007043

The sustainable home health care process based on multi-criteria decision-dupport

The increase in life expectancy has led to a growing demand for Home Health Care (HHC) services. However, some problems can arise in the management of these services, leading to high computational complexity and time-consuming to obtain an exact and/or optimal solution. This study intends to contribute to an automatic multi-criteria decision-support system that allows the optimization of several objective functions simultaneously, which are often conflicting, such as costs related to travel (distance and/or time) and available resources (health professionals and vehicles) to visit the patients. In this work, the HHC scheduling and routing problem is formulated as a multi objective approach, aiming to minimize the travel distance, the travel time and the number of vehicles, taking into account specific constraints, such as the needs of patients, allocation variables, the health professionals and the transport availability. Thus, the multi-objective genetic algorithm, based on the NSGA-II, is applied to a real-world problem of HHC visits from a Health Unit in Bragança (Portugal), to identify and examine the different compromises between the objectives using a Pareto-based approach to operational planning. Moreover, this work provides several efficient end-user solutions, which were standardized and evaluated in terms of the proposed policy and compared with current practice. The outcomes demonstrate the significance of a multi-criteria approach to HHC services.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020), SusTEC (LA/P/0007/2021) and ALGORITMI Research Centre / LASI (UIDB/00319/2020). Filipe Alves thanks the FCT for supporting its research with the Ph.D. grant SFRH/BD/143745/2019.info:eu-repo/semantics/publishedVersio

A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment

Manufacturing activities and production control are constantly growing. Despite this, it is necessary to improve the increasing variety of scheduling and layout adjustments for dynamic and flexible responses in volatile environments with disruptions or failures. Faced with the lack of realistic and practical manufacturing scenarios, this approach allows simulating and solving the problem of job shop scheduling on a production system by taking advantage of genetic algorithm and particle swarm optimization algorithm combined with the flexibility and robustness of a multi-agent system and dynamic rescheduling alternatives. Therefore, this hybrid decision support system intends to obtain optimized solutions and enable humans to interact with the system to properly adjust priorities or refine setups or solutions, in an interactive and user-friendly way. The system allows to evaluate the optimization performance of each one of the algorithms proposed, as well as to obtain decentralization in responsiveness and dynamic decisions for rescheduling due to the occurance of unexpected events.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

Periodic vehicle routing problem in a health unit

In logistics of home health care services in the Health Units, the managers and nurses need to carry out the schedule and the vehicles routes for the provision of care at the patients' homes. Currently, in Portugal, these services are increasingly used but the problem is still, usually, solved manually and without computational resources. The increased demand for home health care due to the boost of the elderly people number entails a high associated cost which, sometimes, does not guarantee the quality of the service. In this sense, the periodic vehicle routing problem is a generalization of the classical vehicle routing problem in which routes are determined for a time horizon of several days. In this work, it is provided a periodic vehicle routing problem applied in the Health Unit in Bragança. An integer linear programming formulation for the real database, allowed to solve the problem in an efficient and optimized way using the CPLEXR software.Programa Operacional Temático Factores de Competitividade(POCI-01-0145-FEDER-007043