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  • A Multi-Modal Approach to Cognitive Training and Assistance in Minimally Invasive Surgery
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-08-06
    Tina Vajsbaher; Tim Ziemer; Holger Schultheis

    Minimally-invasive surgery (MIS) offers many benefits to patients, but is considerably more difficult to learn and perform than is open surgery. One main reason for the observed difficulty is attributable to the visuo-spatial challenges that arise in MIS, taxing the surgeons’ cognitive skills. In this contribution, we present a new approach that combines training and assistance as well as the visual

  • Review for Cognitive Systems Research of the book The Brain and AI, by authors Karl Schlagenhauf and Fanji Gu
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-07-23
    Hans Liljenström

    The human brain is often considered the most complex system known. It has a fantastic capacity to learn and remember, to recognize patterns in space and time, solve problems of all kinds, innovate tools and machines, create beautiful art and science. Is it reasonable to believe that we, in a foreseeable future, will be able to understand all the wonders of our own brain, enough to be able to mimic

  • Role of the secondary visual cortex in HMAX model for object recognition
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-07-24
    Hiwa Sufikarimi; Karim Mohammadi

    The models inspired by visual systems of life creatures (e.g., human, mammals, etc.) have been very successful in addressing object recognition tasks. For example, Hierarchical Model And X (HMAX) effectively recognizes different objects by modeling the V1, V4, and IT regions of the human visual system. Although HMAX is one of the superior models in the field of object recognition, its implementation

  • Integrating a cognitive assistant within a critique-based recommender system
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-07-24
    Marc Güell; Maria Salamó; David Contreras; Ludovico Boratto

    Recommender systems are cognitive computing systems designed to support humans in their decision-making processes through convincing, timely product suggestions. In the field of recommender systems, critique-based recommenders have been widely applied as an effective approach for guiding users through a product space in pursuit of suitable products. To date, no critique-based approach has included

  • Planet Braitenberg: Experiments in Virtual Psychology
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-08-01
    Paul R. Smart

    Braitenberg vehicles are simple robotic platforms, equipped with rudimentary sensor and motor components. Such vehicles have typically featured as part of thought experiments that are intended to show how complex behaviours are apt to emerge from the interaction of inner control mechanisms with aspects of bodily structure and features of the wider (extra-agential) environment. The present paper describes

  • Fuzzy rough sets: survey and proposal of an enhanced knowledge representation model based on automatic noisy sample detection
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-07-10
    Abdelkhalek Hadrani; Karim Guennoun; Rachid Saadane; Mohammed Wahbi

    Fuzzy Rough Set (FRS) theory, which has been emerged thanks to unifying Rough Set and Fuzzy Set ones, is a powerful mathematical tool for handling and processing real data of imprecise, incomplete, inconsistent and uncertain nature. It has drawn attention of many researchers, scientists and industrials in various domains over the last three decades. However, different studies have showed that its classical

  • Safe and optimal navigation for autonomous multi-rotor aerial vehicle in a dynamic known environment by a decomposition-coordination method
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-06-02
    Imane Nizar; Youssef Illoussamen; Hala El Ouarrak; El Hossein Illoussamen; Manuel Grana (Graña); Mohammed Mestari

    In this paper, we present a new solution for the Autonomous navigation problem, using a Decomposition-Coordination Method (DCM) 1. The main purpose of this work is to compute an optimal and safe path for the multi-rotor Unmanned Aerial Vehicle (UAV) in a dynamic environment, moving from an initial location to the desired state. We assume that the flight environment is totally known to a supervisory

  • ELM-HTM guided bio-inspired unsupervised learning for anomalous trajectory classification
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-05-23
    Arif Ahmed Sekh; Debi Prosad Dogra; Samarjit Kar; Partha Pratim Roy; Dilip K. Prasad

    Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeling or exhaustive training. In this paper, we propose

  • Hierarchical growing grid networks for skeleton based action recognition
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-05-23
    Zahra Gharaee

    In this paper, a novel cognitive architecture for action recognition is developed by applying layers of growing grid neural networks. Using these layers makes the system capable of automatically arranging its representational structure. In addition to the expansion of the neural map during the growth phase, the system is provided with a prior knowledge of the input space, which increases the processing

  • Measuring text similarity based on structure and word embedding
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-05-06
    Mamdouh Farouk

    The problem of finding the similarity between natural language sentences is crucial for many applications in Natural Language Processing (NLP). An accurate calculation of similarity between sentences is highly needed. Many approaches depend on word-to-word similarity to measure sentence similarity. This paper proposes a new approach to improve the accuracy of the sentence similarity calculation. The

  • Neuroevolution-based autonomous robot navigation: A comparative study
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-04-29
    Seyed Mohammad Jafar Jalali; Sajad Ahmadian; Abbas Khosravi; Seyedali Mirjalili; Mohammad Reza Mahmoudi; Saeid Nahavandi

    The field of neuroevolution has achieved much attention in recent years from both academia and industry. Numerous papers have reported its successful applications in different fields ranging from medical domain to autonomous systems. However, it is not clear which evolutionary optimization techniques lead to the best results. In this paper, multilayer perceptron (MLP) neural networks (NNs) are trained

  • Facial expression recognition in the wild, by fusion of deep learnt and hand-crafted features
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-04-26
    G. Viswanatha Reddy; C.V.R. Dharma Savarni; Snehasis Mukherjee

    In spite of the recent advancements in the field of deep learning based techniques for facial expression recognition, the efficiency of the state-of-the-art recognition methods in the wild scenarios, remains a challenge. The main reason behind the less efforts made for handling wild scenarios is two-folds: very less and varying levels of cues available to identify the distinguishable patterns of features

  • A pseudo-dynamic search ant colony optimization algorithm with improved negative feedback mechanism
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-03-05
    Jun Li; Yuan Xia; Bo Li; Zhigao Zeng

    To solve low convergence precision and slow convergence speed, a pseudo-dynamic search ant colony optimization algorithm with improved negative feedback mechanism (PACON) is proposed. Firstly, the algorithm introduces an angle in the pheromone transfer rule. Through the rule for calculating the angle, multiple cities with smaller angles are also included in the next candidate city list. It affects

  • Robust supervised sparse representation for face recognition
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2020-02-26
    Jian-Xun Mi; Yueru Sun; Jia Lu; Heng Kong

    Sparse representation based classification (SRC) has become a popular methodology in face recognition in recent years. One widely used manner is to enforce minimum l1-norm on coding coefficient vector, which is considered as an unsupervised sparsity constraint and usually requires high computational cost. On the other hand, supervised sparsity representation based method (SSR) realizes sparse representation

  • Effects of Task Constraint on Action Dynamics.
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2019-02-06
    Patric C Nordbeck,Laura K Soter,Johan S Viklund,Emily A Beckmann,Rachel W Kallen,Anthony P Chemero,Michael J Richardson

    The actualization of action possibilities (i.e., affordances) can often be accomplished in numerous ways. For instance, an individual could walk over to a rubbish bin to drop an item in or throw the piece of rubbish into the bin from some distance away. The aim of the current study was to investigate the action dynamics that emerge from such under-constrained task or action spaces using an object transportation

  • Robot-Enabled Support of Daily Activities in Smart Home Environments.
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2018-11-15
    Garrett Wilson,Christopher Pereyda,Nisha Raghunath,Gabriel de la Cruz,Shivam Goel,Sepehr Nesaei,Bryan Minor,Maureen Schmitter-Edgecombe,Matthew E Taylor,Diane J Cook

    Smart environments offer valuable technologies for activity monitoring and health assessment. Here, we describe an integration of robots into smart environments to provide more interactive support of individuals with functional limitations. RAS, our Robot Activity Support system, partners smart environment sensing, object detection and mapping, and robot interaction to detect and assist with activity

  • Packing: A Geometric Analysis of Feature Selection and Category Formation.
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2011-03-29
    Shohei Hidaka,Linda B Smith

    This paper presents a geometrical analysis of how local interactions in a large population of categories packed into a feature space create a global structure of feature relevance. The theory is a formal proof that the joint optimization of discrimination and inclusion creates a smooth space of categories such that near categories in the similarity space have similar generalization gradients. Packing

  • On Strong Anticipation.
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2010-03-02
    N Stepp,M T Turvey

    We examine Dubois's (2003) distinction between weak anticipation and strong anticipation. Anticipation is weak if it arises from a model of the system via internal simulations. Anticipation is strong if it arises from the system itself via lawful regularities embedded in the system's ordinary mode of functioning. The assumption of weak anticipation dominates cognitive science and neuroscience and in

  • Fragile X syndrome: Neural network models of sequencing and memory.
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2009-10-06
    Mina C Johnson-Glenberg

    A comparative framework of memory processes in males with fragile X syndrome (FXS) and Typically Developing (TYP) mental age-match children is presented. Results indicate a divergence in sequencing skills, such that males with FXS recall sequences similarly to TYP children around five and a half years of age, but eth males with FXS recall significantly worse when compared to TYP children around seven

    Cogn. Syst. Res. (IF 1.902) Pub Date : 2009-03-04
    Gerald L Clore,Janet E Palmer

    Emotions and moods color cognition. In this article, we outline how emotions affect judgments and cognitive performance of human agents. We argue that affective influences are due, not to the affective reactions themselves, but to the information they carry about value, a potentially useful finding for creators of artificial agents. The kind of influence that occurs depends on the focus of the agent

  • BICA for AGI
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2019-09-24
    Piotr Bołtuć; Marta Boltuc

    BICAs for AI have been happening for decades, realized within multiple cognitive architectures. What is a BICA for AGI? It requires AI to go beyond the limitations of predicative human language, and of predicative logic based on it; also, above human reportable consciousness, to the subconscious/non-conscious level of human (and machine) mind; and then still beyond it. Within machine cognition this

  • The pattern theory of self in artificial general intelligence: A theoretical framework for modeling self in biologically inspired cognitive architectures
    Cogn. Syst. Res. (IF 1.902) Pub Date : 2019-09-17
    Kevin Ryan; Pulin Agrawal; Stan Franklin

    In an attempt to provide a unified account for a vast literature discussing a multiplicity of selves, Gallagher (2013) has proposed a pattern theory of self. Subsequent discussion on this account has led to a concern that the pattern theory, as originally presented, stands as a mere list of aspects that fails to explain how they are related in real-time. We suggest that one way to address these criticisms

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