Business Model Generation: A handbook for visionaries, game changers and challengers

The book entitled “Business Model Generation: A Handbook for visionaries, game changers and challengers” though written by Osterwalder and Pigneur (2010) was also co-created by 470 practitioners from 45 countries. The book is thus a good example of how a global creative collaboration effort can contribute positively to the business and management literature and subsequently to the advancement of society. The book "Business Model Generation" has both narrative and visual detail. Before proceeding to do an in-depth review of “Business Model Generation” we first looked at other publications by the authors which led up to the book

Producing innovation: Comments on Lee and Yu (2010)

The purpose of the article being reviewed (Lee and Yu, 2010), a survey by questionnaire with 182 valid responses, is to analyze “how different relationship styles of employees in the hi-tech industry influence innovation performance” and indeed its conclusions are that “the relationship style of an organization has a significant positive effect on innovation performance”. We see Lee and Yu (2010) as being similar to another highly cited article by Morgan and Hunt in so far as both articles are about relationships, cooperation and trust

Facilitating qualitative research in business studies - Using the business narrative to model value creation

This is a conceptual paper supported by empirical research giving details of a new Business Narrative Modelling Language (BNML). The need for BNML arose given a growing dissatisfaction with qualitative research approaches and also due to the need to bring entrepreneurs, especially those with little training in management theory, closer to the academic (as well as practitioner) discussion of innovation and strategy for value creation. We aim primarily for an improved communication process of events which can be described using the narrative, in the discussion of the value creation process. Our findings, illustrated through a case study, should be of interest to both researchers and practitioners alike

Relatório de acompanhamento do projecto RHEUMUS (sistema de análise de imagens de ecografia para reumatologia): QREN - Projecto Nº 38505

O projeto RHEUMUS tem como principal objetivo o desenvolvimento de um sistema de processamento e análise de imagens de ecografia para a área da reumatologia. A solução em desenvolvimento será composta por um conjunto de ferramentas computacionais capazes de identificar, segmentar e quantificar estruturas anatómicas normais/patológicas do sistema músculo-esquelético da mão e do joelho, baseadas na tecnologia de visão por computador.projecto RHEUMUSQREN - Projecto Nº 3850

Tracking system using texture cue based on wavelet transform

This paper presents an approach for tracking objects whose principal discriminate characteristic is its texture. The presented system extracts texture features based on the wavelet transform and uses a fuzzy grammar classifier. The feature vector consists of 6 characteristics extracted from the wavelet detail images. The overall system was integrated on the platform developed by sony – AIBO robot. This application ensures a real time tracking approach and can be parameterized in order to be flexible in face of different types of texture

Two vision-guided vehicles : temporal coordination using nonlinear dynamical systems

This article addresses the problem of generating timed trajectories and temporally coordinated movements for two wheeled vehicles, when relatively low-level, noisy sensorial information is used to steer action. The generated trajectories have controlled and stable timing (limit cycle type solutions). Incoupling of sensory information enables sensor driven termination of movement. We build on a previously proposed solution in which timed trajectories and sequences of movements were generated as attractor solutions of dynamic systems. We present a novel system composed of two coupled dynamical architectures that temporally coordinate the solutions of these dynamical systems. The coupled dynamics enable synchronization of the different components providing an independence relatively to the specification of their individual parameters. We apply this architecture to generate temporally coordinated trajectories for two vision-guided mobile robots in a non-structured simulated environment, whose goal is to reach a target within a certain time independently of the environment configuration or the distance to the target. The results illustrate the robustness of the proposed decision-making mechanism and show that the two vehicles are temporal coordinated: if a robot movement is affected by the environment configuration such that it will take longer to reach the target, the control level coordinates the two robots such that they terminate approximately simultaneousl

Ball catching by a puma arm : a nonlinear dynamical systems approach

We present an attractor based dynamics that autonomously generates temporally discrete movements and movement sequences stably adapted to changing online sensory information. Autonomous differential equations are used to formulate a dynamical layer with either stable fixed points or a stable limit cycle. A neural competitive dynamics switches between these two regimes according to sensorial context and logical conditions. The corresponding movement states are then converted by simple coordinate transformations into spatial positions of a robot arm. Movement initiation and termination is entirely sensor driven. In this article, the dynamic architecture was changed in order to cope with unreliable sensor information by including this information in the vector field. We apply this architecture to generate timed trajectories for a Puma arm which must catch a moving ball before it falls over a table, and return to a reference position thereafter. Sensory information is provided by a camera mounted on the ceiling over the robot. We demonstrate that the implemented decisionmechanism is robust to noisy sensorial information. Further, a flexible behavior is achieved. Flexibility means that if the sensorial context changes such that the previously generated sequence is no longer adequate, a new sequence of behaviors, depending on the point at which the changed occurred and adequate to the current situation emerges

Control of an industrial desktop robot using computer vision and fuzzy rules

Desktop robots are suitable for various production line systems in industrial applications like dispensing, soldering, screw tightening, pick’n place, welding or marking. Despite their capabilities to meet diverse requirements, they have to be programmed off-line using waypoints and path information. Misalignments in the workspace location during loading cause injuries in the workpiece and tool. Further, in modern flexible industrial production, machinery must adapt to changing product demands, both to the simultaneous production of different types of workpieces and to product styles with short life cycles. In this paper, visual data processing concepts on the basis of fuzzy logic are applied to enable an industrial desktop robot to raise its flexibility and address these problems that limit the production rate of small industries. Specifically, a desktop robot performing dispensing tasks is equipped with a CCD camera. Visual information is used to autonomously change previously off-line stored robot programs for known workpieces or to call worker’s attention for unknown/misclassified workpieces. A fuzzy inference classifier based on a fuzzy grammar, is used to describe/identify workpieces. Fuzzy rules are automatically generated from features extracted from the workpiece under analysis. Regarding the evaluation of the system performance, different types of workpieces were tested and a good rate performance, higher than 90%, was achieved. The obtained results illustrate both the flexibility and robustness of the proposed solution as well as its capabilities for good classification of workpieces. The overall system is being implemented in an industrial environment

Timed trajectory generation using dynamical systems : application to a puma arm

We present an attractor based dynamics that autonomously generates trajectories with stable timing (limit cycle solutions), stably adapted to changing online sensory information. Autonomous differential equations are used to formulate a dynamical layer with either stable fixed points or a stable limit cycle. A neural competitive dynamics switches between these two regimes according to sensorial context and logical conditions. The corresponding movement states are then converted by simple coordinate transformations and an inverse kinematics controller into spatial positions of a robot arm. Movement initiation and termination is entirely sensor driven. In this article, the dynamic architecture was changed in order to cope with unreliable sensor information by including this information in the vector field. We apply this architecture to generate timed trajectories for a Puma arm which must catch a moving ball before it falls over a table, and return to a reference position thereafter. Sensory information is provided by a camera mounted on the ceiling over the robot. A flexible behavior is achieved. Flexibility means that if the sensorial context changes such that the previously generated sequence is no longer adequate, a new sequence of behaviors, depending on the point at which the changed occurred and adequate to the current situation emerges. The evaluation results illustrate the stability and flexibility properties of the dynamical architecture as well as the robustness of the decision-making mechanism implemented

Simulated visually-guided paw placement during quadruped locomotion

Autonomous adaptive locomotion over irregular terrain is one important topic in robotics research. In this article, we focus on the development of a quadruped locomotion controller able to generate locomotion and reaching visually acquired markers. The developed controller is modeled as discrete, sensory driven corrections of a basic rhythmic motor pattern for locomotion according to visual information and proprioceptive data, that enables the robot to reach markers and only slightly perturb the locomotion movement. This task involves close-loop control and we will thus particularly focus on the essential issue of modeling the interaction between the central nervous system and the peripheral information in the locomotion context. This issue is crucial for autonomous and adaptive control, and has received little attention so far. Trajectories are online modulated according to these feedback pathways thus achieving paw placement. This modeling is based on the concept of dynamical systems whose intrinsic robustness against perturbations allows for an easy integration of sensory-motor feedback and thus for closed-loop control. The system is demonstrated on a simulated quadruped robot which online acquires the visual markers and achieves paw placement while locomotes