Paired Comparisons-based Interactive Differential Evolution

We propose Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are two big keys for reducing Interactive Evolutionary Computation (IEC) user fatigue. Unlike IGA and conventional IDE, users of the proposed IDE and tournament IGA do not need to compare whole individuals each other but compare pairs of individuals, which largely decreases user fatigue. In this paper, we design a pseudo-IEC user and evaluate another factor, IEC convergence performance, using IEC simulators and show that our proposed IDE converges significantly faster than IGA and tournament IGA, i.e. our proposed one is superior to others from both user interface and convergence performance points of view

Comparing Evolutionary Operators, Search Spaces, and Evolutionary Algorithms in the Construction of Facial Composites

Facial composite construction is one of the most successful applications of interactive evolutionary computation. In spite of this, previous work in the area of composite construction has not investigated the algorithm design options in detail. We address this issue with four experiments. In the first experiment a sorting task is used to identify the 12 most salient dimensions of a 30-dimensional search space. In the second experiment the performances of two mutation and two recombination operators for interactive genetic algorithms are compared. In the third experiment three search spaces are compared: a 30-dimensional search space, a mathematically reduced 12-dimensional search space, and a 12-dimensional search space formed from the 12 most salient dimensions. Finally, we compare the performances of an interactive genetic algorithm to interactive differential evolution. Our results show that the facial composite construction process is remarkably robust to the choice of evolutionary operator(s), the dimensionality of the search space, and the choice of interactive evolutionary algorithm. We attribute this to the imprecise nature of human face perception and differences between the participants in how they interact with the algorithms. Povzetek: Kompozitna gradnja obrazov je ena izmed najbolj uspešnih aplikacij interaktivnega evolucijskega ra?cunanja. Kljub temu pa do zdaj na podro?cju kompozitne gradnje niso bile podrobno raziskane možnosti snovanja algoritma. To vprašanje smo obravnavali s štirimi poskusi. V prvem je uporabljeno sortiranje za identifikacijo 12 najbolj izstopajo?cih dimenzij 30-dimenzionalnega preiskovalnega prostora. V drugem primerjamo u?cinkovitost dveh mutacij in dveh rekombinacijskih operaterjev za interaktivni genetski algoritem. V tretjem primerjamo tri preiskovalne prostore: 30-dimenzionalni, matemati?cno reducirani 12-dimenzionalni in 12-dimenzionalni prostor sestavljen iz 12 najpomembnejših dimenzij. Na koncu smo primerjali uspešnost interaktivnega genetskega algoritma z interaktivno diferencialno evolucijo. Rezultati kažejo, da je proces kompozitne gradnje obrazov izredno robusten glede na izbiro evolucijskega operatorja(-ev), dimenzionalnost preiskovalnega prostora in izbiro interaktivnega evolucijskega algoritma. To pripisujemo nenatan?cni naravi percepcije in razlikam med interakcijami uporabnikov z algoritmom

A Review on Humanized Computational Intelligence

Computational Intelligence (CI) has three main foundations: Neural Networks, Evolutionary Computation (EC) and Fuzzy Systems (FS). Collaborating systems based on these models have been built and installed in prototypes and successful consumer products. However, creativity still is a main human task, in great part due to the presence of subjective values and psychological / emotional responses in the evaluation of the created objects. In this context the Interactive Evolutionary Computation (IEC), a paradigm in which humans directly intervene in fitness evaluation, is a new direction for CI research. Art, education and engineering are some examples of IEC application domains.N/

Improvement of Speech Perception for Hearing-Impaired Listeners

Hearing impairment is becoming a prevalent health problem affecting 5% of world adult populations. Hearing aids and cochlear implant already play an essential role in helping patients over decades, but there are still several open problems that prevent them from providing the maximum benefits. Financial and discomfort reasons lead to only one of four patients choose to use hearing aids; Cochlear implant users always have trouble in understanding speech in a noisy environment. In this dissertation, we addressed the hearing aids limitations by proposing a new hearing aid signal processing system named Open-source Self-fitting Hearing Aids System (OS SF hearing aids). The proposed hearing aids system adopted the state-of-art digital signal processing technologies, combined with accurate hearing assessment and machine learning based self-fitting algorithm to further improve the speech perception and comfort for hearing aids users. Informal testing with hearing-impaired listeners showed that the testing results from the proposed system had less than 10 dB (by average) difference when compared with those results obtained from clinical audiometer. In addition, Sixteen-channel filter banks with adaptive differential microphone array provides up to six-dB SNR improvement in the noisy environment. Machine-learning based self-fitting algorithm provides more suitable hearing aids settings. To maximize cochlear implant users’ speech understanding in noise, the sequential (S) and parallel (P) coding strategies were proposed by integrating high-rate desynchronized pulse trains (DPT) in the continuous interleaved sampling (CIS) strategy. Ten participants with severe hearing loss participated in the two rounds cochlear implants testing. The testing results showed CIS-DPT-S strategy significantly improved (11%) the speech perception in background noise, while the CIS-DPT-P strategy had a significant improvement in both quiet (7%) and noisy (9%) environment

Interactivité efficace pour les algorithmes évolutionnaires interactifs. Application au débruitage multifractal d'images

Les algorithmes évolutionnaires interactifs pâtissent souvent de ce que l'on peut appeler le « goulot d'étranglement de l'utilisateur », autrement dit une perte d'efficacité de l'algorithme due à la fatigue de l'utilisateur (qui n'apprécie évidemment pas des interactions répétitives et/ou inintéressantes). Nous proposons et analysons dans ce papier une méthode de gestion de l'interaction-utilisateur permettant à la fois de glaner les informations utiles au bon déroulement de l'algorithme d'optimisation évolutionnaire, tout en limitant le nombre d'interactions. Cette méthode a été développée dans le cadre d'une application en débruitage multifractal d'images : le débruitage multifractal est adapté aux images complexes, mais dépend d'un jeu de paramètres délicats à ajuster. Une approche évolutionnaire interactive simple a été élaborée dans des travaux précédents pour l'ajustement de ces paramètres. Nous étudions ici l'emploi d'un module d'approximation du jugement de l'utilisateur, par le biais d'une « carte de fitness, » afin de réduire le nombre d'interactions avec l'utilisateur. La méthode peut être étendue facilement à d'autres applications évolutionnaires, interactives ou calculatoirement coûteuses

Aerospace Medicine and Biology: A continuing bibliography (supplement 160)

This bibliography lists 166 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1976

Crossover Method for Interactive Genetic Algorithms to Estimate Multimodal Preferences

We apply an interactive genetic algorithm (iGA) to generate product recommendations. iGAs search for a single optimum point based on a user’s Kansei through the interaction between the user and machine. However, especially in the domain of product recommendations, there may be numerous optimum points. Therefore, the purpose of this study is to develop a new iGA crossover method that concurrently searches for multiple optimum points for multiple user preferences. The proposed method estimates the locations of the optimum area by a clustering method and then searches for the maximum values of the area by a probabilistic model. To confirm the effectiveness of this method, two experiments were performed. In the first experiment, a pseudouser operated an experiment system that implemented the proposed and conventional methods and the solutions obtained were evaluated using a set of pseudomultiple preferences. With this experiment, we proved that when there are multiple preferences, the proposed method searches faster and more diversely than the conventional one. The second experiment was a subjective experiment. This experiment showed that the proposed method was able to search concurrently for more preferences when subjects had multiple preferences

Applying lean principles and set-based approaches in product development

The research described in this thesis addresses the problem of transformation to lean product development (LPD) and how to introduce and support the use of set-based design (SBD) in the concept development process. The original description of SBD does not define how to generate, evaluate and reduce a set of design solutions. Evaluation of solution candidates, which are too complex to be analytically verified, or are driven by qualitative criteria, has here been given special attention, particularly in cases when methods utilising human judgment may be needed. For some products, the solution space can consist of both principally different alternatives and parameterised variants of these. The question here is if established methods can be combined and introduced in an efficient way to support an SBD process for development of such products, when driven by both quantitative and qualitative criteria.The research approaches used are:-\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 a two-case study (Yin, 2009), -\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 the design research methodology (Blessing and Chakrabarti, 2009), and -\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0\ua0 the scientific work paradigm (J\uf8rgensen, 1992), the last two combined with multiple case studies. Also, elements of action research (Oosthuizen, 2002) are used. The results show that the principles and introduction of LPD were experienced as positive by participating practitioners in the conducted case studies. It was furthermore shown that SBD can be introduced and applied in a workshop at team level within a time frame of one or two working days if the design problem at hand is not too complex. Another result is that SBD can be combined with and supported by established methods such as creative and systematic methods for synthesis, enhanced function-means modelling, axiomatic design, extended causal diagrammes, interactive evolutionary algorithms (IEA) and Pugh matrices for generation, analysis, evaluation and reduction of a solution space of design alternatives and variants of these. Both qualitative and quantitative requirements can be handled. The conclusions are that a transformation to LPD is facilitated by information about good examples and internal support by management. Also, the existence of a lean enthusiast in the organization and an appropriate implementation plan supports a transformation to LPD. A function to maintain the LPD system as well as influence of the lean principles are valuable guides on how to use LPD.\ua0 Also concluded is that a seamless, efficient process, applying set-based principles, for synthesis, evaluation, and reduction of a solution space of design alternatives can be created by combining enhanced function-means modelling, morphological matrices, axiomatic design, causal diagrammes and Pugh matrices. Such a compound of methods can be introduced and applied in a workshop at team level within a time frame of one to two days when solving well-known and not too complex design problems. The workshop should be facilitated by an expert on the methods used and initiated and surveyed by a team manager. Furthermore, a solution space of parameterised design variants, with criteria that are either qualitative or too complicated to be numerically defined, can be generated, evaluated and reduced in such a process. By using a defined set of functional and constraining criteria, and applying axiomatic design and IEA, a variant solution space can be generated and refined. A set-up of the IEA that does not overburden the user should be preferred