Linking unlearning with innovation through organizational memory and technology

While the information technologies provide organizational members with explicit concepts, such as writing instruction manuals, the ‘organizational memory’ provides individuals with tacit knowledge, such as systematic sets, routines and shared visions. This means that individuals within an organization learn by using both the organizational memory and the information technologies. They interact to reduce organizational information needs contributing to improve organizational innovativeness. However, the utilization of the organization memory or the technology infrastructure does not guarantee that appropriate information is used in appropriate circumstances or that information is appropriately updated. In other words, previous memories reflect a world that is only partially understood and assimilated, which might lead individuals to doing the wrong things right or the right things wrong. This paper examines the relative importance and significance of the existence of unlearning to the presence and nature of ‘organizational memory and technology’. We further examine the effect of the existence of organizational memory and information technology on conditions that promote organizational innovativeness. These relationships are examined through an empirical investigation of 291 large Spanish companies. Our analysis found that if the organization considers the establishment of an unlearning culture as a prior step in the utilization of organization memory or the technology infrastructure through organizational innovativeness, then organization memory and technology have a positive influence on the conditions that stimulate organizational innovativeness

Analyzing an absorptive capacity : unlearning context and information system capabilities as catalysts for innovativeness

This study examines the impact of a company’s unlearning context and information system (IS) capabilities on the company’s ability to challenge of basic beliefs and to implement processes that are explicitly or tacitly helpful in the reception of new ideas (absorptive capacity). We also examine the relationship between absorptive capacity and the existence and enhancement of innovativeness. These relationships are examined through an empirical investigation of 286 large Spanish companies. Our results show that absorptive capacity is an important dynamic determinant for developing a company’s innovativeness. Moreover, this relationship is best explained with two related constructs. Firstly, the company’s unlearning context plays a key role in managing the tension between potential absorptive capacity and realised absorptive capacity. Secondly, the results also shed light on a tangible means for managers to enhance their company’s innovativeness through IS capabilities

Analyzing an absorptive capacity: unlearning context and information sistem capabilities as catalysts for innovativeness

This study examines the impact of a company’s unlearning context and information system (IS) capabilities on the company’s ability to challenge of basic beliefs and to implement processes that are explicitly or tacitly helpful in the reception of new ideas (absorptive capacity). We also examine the relationship between absorptive capacity and the existence and enhancement of innovativeness. These relationships are examined through an empirical investigation of 286 large Spanish companies. Our results show that absorptive capacity is an important dynamic determinant for developing a company’s innovativeness. Moreover, this relationship is best explained with two related constructs. Firstly, the company’s unlearning context plays a key role in managing the tension between potential absorptive capacity and realised absorptive capacity. Secondly, the results also shed light on a tangible means for managers to enhance their company’s innovativeness through IS capabilities

Deep Neural Networks for the Recognition and Classification of Heart Murmurs Using Neuromorphic Auditory Sensors

Auscultation is one of the most used techniques for detecting cardiovascular diseases, which is one of the main causes of death in the world. Heart murmurs are the most common abnormal finding when a patient visits the physician for auscultation. These heart sounds can either be innocent, which are harmless, or abnormal, which may be a sign of a more serious heart condition. However, the accuracy rate of primary care physicians and expert cardiologists when auscultating is not good enough to avoid most of both type-I (healthy patients are sent for echocardiogram) and type-II (pathological patients are sent home without medication or treatment) errors made. In this paper, the authors present a novel convolutional neural network based tool for classifying between healthy people and pathological patients using a neuromorphic auditory sensor for FPGA that is able to decompose the audio into frequency bands in real time. For this purpose, different networks have been trained with the heart murmur information contained in heart sound recordings obtained from nine different heart sound databases sourced from multiple research groups. These samples are segmented and preprocessed using the neuromorphic auditory sensor to decompose their audio information into frequency bands and, after that, sonogram images with the same size are generated. These images have been used to train and test different convolutional neural network architectures. The best results have been obtained with a modified version of the AlexNet model, achieving 97% accuracy (specificity: 95.12%, sensitivity: 93.20%, PhysioNet/CinC Challenge 2016 score: 0.9416). This tool could aid cardiologists and primary care physicians in the auscultation process, improving the decision making task and reducing type-I and type-II errors.Ministerio de Economía y Competitividad TEC2016-77785-

Spike-based control monitoring and analysis with Address Event Representation

Neuromorphic engineering tries to mimic biological information processing. Address-Event Representation (AER) is a neuromorphic communication protocol for spiking neurons between different chips. We present a new way to drive robotic platforms using spiking neurons. We have simulated spiking control models for DC motors, and developed a mobile robot (Eddie) controlled only by spikes. We apply AER to the robot control, monitoring and measuring the spike activity inside the robot. The mobile robot is controlled by the AER-Robot tool, and the AER information is sent to a PC using the USBAERmini2 interface.Junta de Andalucía P06-TIC-01417Ministerio de Educación y Ciencia TEC2006-11730-C03-0

An AER-Based Actuator Interface for Controlling an Anthropomorphic Robotic Hand

Bio-Inspired and Neuro-Inspired systems or circuits are a relatively novel approaches to solve real problems by mimicking the biology in its efficient solutions. Robotic also tries to mimic the biology and more particularly the human body structure and efficiency of the muscles, bones, articulations, etc. Address-Event-Representation (AER) is a communication protocol for transferring asynchronous events between VLSI chips, originally developed for neuro-inspired processing systems (for example, image processing). Such systems may consist of a complicated hierarchical structure with many chips that transmit data among them in real time, while performing some processing (for example, convolutions). The information transmitted is a sequence of spikes coded using high speed digital buses. These multi-layer and multi-chip AER systems perform actually not only image processing, but also audio processing, filtering, learning, locomotion, etc. This paper present an AER interface for controlling an anthropomorphic robotic hand with a neuro-inspired system.Unión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C03-0

NAVIS: Neuromorphic Auditory VISualizer Tool

This software presents diverse utilities to perform the first post-processing layer taking the neuromorphic auditory sensors (NAS) information. The used NAS implements in FPGA a cascade filters architecture, imitating the behavior of the basilar membrane and inner hair cells and working with the sound information decomposed into its frequency components as spike streams. The well-known neuromorphic hardware interface Address-Event-Representation (AER) is used to propagate auditory information out of the NAS, emulating the auditory vestibular nerve. Using the information packetized into aedat files, which are generated through the jAER software plus an AER to USB computer interface, NAVIS implements a set of graphs that allows to represent the auditory information as cochleograms, histograms, sonograms, etc. It can also split the auditory information into different sets depending on the activity level of the spike streams. The main contribution of this software tool is that it allows complex audio post-processing treatments and representations, which is a novelty for spike-based systems in the neuromorphic community and it will help neuromorphic engineers to build sets for training spiking neural networks (SNN).Ministerio de Economía y Competitividad TEC2012-37868-C04-0