Simulador de comportamiento de enjambre con Quorum Sensing bacteriano

One of the most useful tools in the design of path-planning solutions is simulators. Thanks to them, it is possible to predict the performance of certain control strategies. In this paper, a simulator is presented that implements a swarm of automatons, which perform a wild motion in a user-selected environment. The robots will have the quality to avoid collisions with different obstacles that affect their mobility since they are equipped with proximity sensors. The interface of this simulator was designed entirely with the Qt Designer software. Successful configurations that replicate the performance of the real prototype are presented.  Una de las herramientas más útiles en el diseño de soluciones de planificación de trayectorias son los simuladores. Gracias a ellos, es posible predecir el rendimiento de determinadas estrategias de control. En este trabajo se presenta un simulador que implementa un enjambre de autómatas que realizan un movimiento salvaje en un entorno seleccionado por el usuario. Los robots tendrán la cualidad de evitar colisiones con diferentes obstáculos que afecten a su movilidad ya que están equipados con sensores de proximidad. La interfaz de este simulador se ha diseñado íntegramente con el software Qt Designer. Se presentan configuraciones exitosas que replican el desempeño del prototipo real. &nbsp

An extensive search algorithm to find feasible healthy menus for humans.

Promoting healthy lifestyles is nowadays a public priority among most public entities. The ability to design an array of nutritious and appealing diets is very valuable. Menu Planning still presents a challenge which complexity derives from the problems’ many dimensions and the idiosyncrasies of human behavior towards eating. Among the difculties encountered by researchers when facing the Menu Planning Problem, being able of fnding a rich feasible region stands out. We consider it as a system of inequalities to which we try to fnd solutions. We have developed and implemented a two-phase algorithm -that mainly stems from the Randomized Search and the Genetic- that is capable of rapidly fnding an pool of solutions to the system with the aim of properly identifying the feasible region of the underlying problem and proceed to its densifcation. It consists of a hybrid algorithm inspired on a GRASP metaheuristic and a later recombination. First, it generates initial seeds, identifying best candidates and guiding the search to create solutions to the system, thus attempting to verify every inequality. Afterwards, the recombination of diferent promising candidates helps in the densifcation of the feasible region with new solutions. This methodology is an adaptation of other previously used in literature, and that we apply to the MPP. For this, we generated a database of a 227 recipes and 272 ingredients. Applying this methodology to the database, we are able to obtain a pool of feasible (healthy and nutritious) complete menus for a given D number of days.Open Access granted by Universidad de Málaga / CBUA. This work has been partially supported by the Spanish *Ministerio de Ciencia, Innovación y Universidades *(MCIU/AEI/FEDER, UE) with grant ref PID2019-104263RBC42; and Junta de Andalucía with grant refs. P18-RT-1566, (contract ref CI-21-228) UMA18-FEDERJA- 065. Funding for open access charge: Universidad de Málaga / CBU

Human Behavior-based Personalized Meal Recommendation and Menu Planning Social System

The traditional dietary recommendation systems are basically nutrition or health-aware where the human feelings on food are ignored. Human affects vary when it comes to food cravings, and not all foods are appealing in all moods. A questionnaire-based and preference-aware meal recommendation system can be a solution. However, automated recognition of social affects on different foods and planning the menu considering nutritional demand and social-affect has some significant benefits of the questionnaire-based and preference-aware meal recommendations. A patient with severe illness, a person in a coma, or patients with locked-in syndrome and amyotrophic lateral sclerosis (ALS) cannot express their meal preferences. Therefore, the proposed framework includes a social-affective computing module to recognize the affects of different meals where the person's affect is detected using electroencephalography signals. EEG allows to capture the brain signals and analyze them to anticipate affective toward a food. In this study, we have used a 14-channel wireless Emotive Epoc+ to measure affectivity for different food items. A hierarchical ensemble method is applied to predict affectivity upon multiple feature extraction methods and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is used to generate a food list based on the predicted affectivity. In addition to the meal recommendation, an automated menu planning approach is also proposed considering a person's energy intake requirement, affectivity, and nutritional values of the different menus. The bin-packing algorithm is used for the personalized menu planning of breakfast, lunch, dinner, and snacks. The experimental findings reveal that the suggested affective computing, meal recommendation, and menu planning algorithms perform well across a variety of assessment parameters

A study on an integrated observation and collision avoiding support system for merchant ships

東京海洋大学博士学位論文 平成23年度(2011) 応用環境システム学 課程博士 甲第253号指導教員: 大津皓平全文公表年月日: 2016-12-13東京海洋大学201

SCHOOLTHY: Automatic Menu Planner for Healthy and Balanced School Meals

SCHOOLTHY: Automatic Menu Planner for Healthy and Balanced School Meals is a decision support tool that addresses the multi-objective menu planning problem in order to automatically produce meal plans for school canteens. Malnutrition is a widespread problem nowadays and is particularly serious when it affects children. In our environment, nutrition experts design healthy and balanced meal plans for children manually, which leaves significant room for improvement in terms of convenience and efficiency. SCHOOLTHY is presented herein as a proposal to improve and facilitate the work of these professionals. We focus on offering healthy and balanced meal plans that not only satisfy the recommended energy and nutrient intakes, but that also have a minimum cost and maximum variety of courses and food groups. Quantitative analyses that compare the meal plans yielded by SCHOOLTHY for meal plans designed by experts at hand and served in regional schools demonstrate the suitability of the proposal. Finally, we note that, thanks to its flexibility, SCHOOLTHY might be easily adapted to deal with other environments, such as hospitals, prisons and retirement homes, among others

Desenvolvimento de algoritmo para otimização de linhas de montagem

O balanceamento de uma linha de produção tem como objetivo anular o “gargalo” de produção, promovendo o máximo de produtividade e eficiência, mantendo o ritmo de trabalho adequado do processo produtivo. Desta forma, o presente projeto foca-se na identificação e eliminação de desperdícios, melhorando os processos de montagem, mediante o estudo dos tempos de ciclo dos postos de trabalhos e as tarefas executadas por cada operador. Na análise feita à linha, é descrito o processo com todas as tarefas inerentes à montagem da cadeira porta-bebé, bem como as fotografias da instrução de trabalho e controlo que auxiliam a montagem da cadeira. De igual forma são apresentados os dados recolhidos inicialmente e a proposta de melhoria. Posto isto, foi criada uma interface com o Excel, que indica qual o número teórico de operadores necessários, dado o nº de encomendas requeridas para um determinado período de tempo. Esta interface recorre a um problema de otimização, que é resolvido com recurso do Solver para efetuar a afetação das diferentes tarefas aos operadores. A análise feita, se for implementada, poderá ter um impacto positivo na produção final das cadeiras porta-bebés, no que diz respeito à diminuição de filas de espera entre postos, diminuição dos tempos de inatividade e aumento da eficiência da linha. Este modelo proposto pode ser ajustado às restantes linhas de montagem com vista à sua otimização.Balancing a production line aims to eliminate the production “bottleneck”, promoting maximum productivity and efficiency, maintaining the proper work rhythm of the production process. In this way, the present project focuses on the identification and elimination of waste, improving the assembly processes, by studying the cycle times of the workstations and the tasks performed by each operator. In the analysis carried out on the line, the process is described with all the tasks inherent to the assembly of the baby seat, as well as the photographs of the work and control instructions that help the assembly of the chair. Likewise, the data collected initially and the improvement proposal are presented. Thus said, an interface was created with Excel, which indicates the theoretical number of operators needed, given the number of orders required for a certain period of time. This interface uses an optimization problem, which is solved using Solver to allocate the different tasks to the operators. The analysis carried out, if implemented, could have a positive impact on the final production of baby seats, in terms of reducing queues between stations, reducing downtime and increasing the efficiency of the line. This proposed model can be adjusted to the remaining assembly lines with a view to its optimization

Intelligent optimisation of analogue circuits using particle swarm optimisation, genetic programming and genetic folding

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.This research presents various intelligent optimisation methods which are: genetic algorithm (GA), particle swarm optimisation (PSO), artificial bee colony algorithm (ABCA), firefly algorithm (FA) and bacterial foraging optimisation (BFO). It attempts to minimise analogue electronic filter and amplifier circuits, taking a cascode amplifier design as a case study, and utilising the above-mentioned intelligent optimisation algorithms with the aim of determining the best among them to be used. Small signal analysis (SSA) conversion of the cascode circuit is performed while mesh analysis is applied to transform the circuit to matrices form. Computer programmes are developed in Matlab using the above mentioned intelligent optimisation algorithms to minimise the cascode amplifier circuit. The objective function is based on input resistance, output resistance, power consumption, gain, upperfrequency band and lower frequency band. The cascode circuit result presented, applied the above-mentioned existing intelligent optimisation algorithms to optimise the same circuit and compared the techniques with the one using Nelder-Mead and the original circuit simulated in PSpice. Four circuit element types (resistors, capacitors, transistors and operational amplifier (op-amp)) are targeted using the optimisation techniques and subsequently compared to the initial circuit. The PSO based optimised result has proven to be best followed by that of GA optimised technique regarding power consumption reduction and frequency response. This work modifies symbolic circuit analysis in Matlab (MSCAM) tool which utilises Netlist from PSpice or from simulation to generate matrices. These matrices are used for optimisation or to compute circuit parameters. The tool is modified to handle both active and passive elements such as inductors, resistors, capacitors, transistors and op-amps. The transistors are transformed into SSA and op-amp use the SSA that is easy to implement in programming. Results are presented to illustrate the potential of the algorithm. Results are compared to PSpice simulation and the approach handled larger matrices dimensions compared to that of existing symbolic circuit analysis in Matlab tool (SCAM). The SCAM formed matrices by adding additional rows and columns due to how the algorithm was developed which takes more computer resources and limit its performance. Next to this, this work attempts to reduce component count in high-pass, low-pass, and all- pass active filters. Also, it uses a lower order filter to realise same results as higher order filter regarding frequency response curve. The optimisers applied are GA, PSO (the best two methods among them) and Nelder-Mead (the worst method) are used subsequently for the filters optimisation. The filters are converted into their SSA while nodal analysis is applied to transform the circuit to matrices form. High-pass, low-pass, and all- pass active filters results are presented to demonstrate the effectiveness of the technique. Results presented have shown that with a computer code, a lower order op-amp filter can be applied to realise the same results as that of a higher order one. Furthermore, PSO can realise the best results regarding frequency response for the three results, followed by GA whereas Nelder- Mead has the worst results. Furthermore, this research introduced genetic folding (GF), MSCAM, and automatically simulated Netlist into existing genetic programming (GP), which is a new contribution in this work, which enhances the development of independent Matlab toolbox for the evolution of passive and active filter circuits. The active filter circuit evolution especially when operational amplifier is involved as a component is of it first kind in circuit evolution. In the work, only one software package is used instead of combining PSpice and Matlab in electronic circuit simulation. This saves the elapsed time for moving the simulation between the two platforms and reduces the cost of subscription. The evolving circuit from GP using Matlab simulation is automatically transformed into a symbolic Netlist also by Matlab simulation. The Netlist is fed into MSCAM; where MSCAM uses it to generate matrices for the simulation. The matrices enhance frequency response analysis of low-pass, high-pass, band-pass, band-stop of active and passive filter circuits. After the circuit evolution using the developed GP, PSO is then applied to optimise some of the circuits. The algorithm is tested with twelve different circuits (five examples of the active filter, four examples of passive filter circuits and three examples of transistor amplifier circuits) and the results presented have shown that the algorithm is efficient regarding design.Tertiary Education Trust Fund (TETFUND) through University of Calabar, Nigeria

Nutriční asistent

Název práce: Nutriční asistent Autor: Matúš Maďar Katedra / Ústav: Katedra softwarového inženýrství Vedoucí bakalářské práce: RNDr. Michal Kopecký, Ph.D. Abstrakt: Práca sa zaoberá skúmaním a implementovaním adaptívneho generovania jedálnička do mobilnej aplikácie pre platformu Android. Aplikácia pomôže používateľovi dosiahnuť cielenú hmotnosť nastavením jeho jedálnička presne na mieru, pričom dovoľuje vychýliť sa od stanoveného plánu. V prípade vychýlenia a skonzumovania nenavrhovaného jedla aplikácia dokáže reagovať v reálnom čase a adaptívne toto vychýlenie vyriešiť podľa voľby používateľa. Aplikácia taktiež zohľadňuje stravovanie v reštauráciách a implementuje možnosť vyhľadávania a zápisu reštauračných jedál z okolia užívateľa. Návrh a implementácia aplikácie umožňuje jej jednoduché rozšírenie vďaka modulárneho návrhu. UI a modul ktorý generuje jedálničky fungujú oddelene, preto môžeme jednoducho meniť UI s ktorým pracuje používateľ, bez toho, aby to spôsobilo nefunkčnosť aplikácie. Modul generujúci jedálničky je rovnako modulárny a je možné použiť v aplikácii vlastné algoritmy na generovanie jedálničkov alebo iné dáta než sú použité v tejto práci. Klíčová slova: Android, Výživa, HeuristikaTitle: Nutrition assistant Author: Matúš Maďar Department: Department of Software Engineering Supervisor: RNDr. Michal Kopecký, Ph.D. Abstract: This thesis explores and implements the options for adaptive generation of meal plans. We implement our approach as a mobile application for the Android operating system. The application aims to help the user to achieve the desired weight loss or weight gain results by custom made recommendations and, at the same time, allowing small deviations from the meal plan. In case of this deviation from the proposed meal plan, the application adapts to such cases with respect to user preference. The additional feature of the application is built-in support for exploring the meal options in nearby restaurants. Our application design is modular. The implementation of the user interface is separate from the logic behind the meal plan generation. The module for meal plan generation can also be easily extended to support new meal plan generation approaches. Also, the data we currently use can be easily replaced by any other data source for food information. Keywords: Android, Nutrition, HeuristicDepartment of Software EngineeringKatedra softwarového inženýrstvíMatematicko-fyzikální fakultaFaculty of Mathematics and Physic