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This paper explores and analyses the actions of users on an e-commerce website after they have watched TV-advertising. The analysis considers factors such as month, day and time of the website visit. This article utilises visualization tools for the analysis of the frequency ratios (probabilities) of searches, conversions, bookings made by new visitors on the website.
Image saliency detection is one of the most active research topics in the field of computer vision. It focus on how to detect significant objects under the complex background, and to reduce the computational cost for getting high-resolution, clear boundary, the overall uniform significant objects. First, in this paper the state-of-the-art research on image saliency detection is analyzed and presented...
In this paper, we propose a constraint-based model for the combination of a course timetabling problem and a course allocation problem for secondary schools in Switzerland. Course timetabling has been widely studied for Universities, but for schools, solutions have only been proposed for specific countries or even for specific schools. In fact, timetabling problems presents the difficulty to be case-specific...
The work described in this paper is about building a general model capable of simulating human behaviour and emotions using virtual characters. To make the simulation realistic enough, virtual characters need to express emotions according to the environment and deal with those emotions in a parallel way where an emotional experience can be triggered at the same time as another emotional response....
The Campbell group uses protein engineering to develop fluorescent protein-based reporters for cell imaging. I will describe our most recent efforts to engineer an improved generation of reporters for calcium ion, membrane potential, and neurotransmitters.
A bio-inspired model for head pose recognition is described in this paper. The bio-inspired model recognizes the head by using gray scale information as well as the silhouette of the person. A set of descriptors is generated from this analysis by a hierarchical model based on the visual cortex. Then the descriptors are classified by a multilayer perceptron artificial neural network to identify the...
Where-What Networks (WWNs) is a series of developmental networks for the recognition and attention of complex visual scenes. One of the most critical challenges of autonomous development is task non-specificity, namely, the network is meant to learn a variety of open-ended task skills without pre-defined tasks. Then how does a brain-like network develop skills for object relation that can generalize...
Modelling aspects of the human vision system, including the retina, is difficult due to insufficient knowledge about the internal components, organisation and complexity of the interactions within the system. Retinal ganglion cells are considered a core component of the human visual system as they convey the accumulated data as action potentials onto the optic nerve. Current techniques capable of...
Being sustainable is now a source of competitive advantage and a question of survival for the supply chains. Indeed, several researches were conducted about this topic by covering several aspects such as the design of the supply chains, their optimization and the evaluation of their performance. However, concerning the performance evaluation of the sustainable supply chain, the models suggested are...
Animated movies are a popular way to communicate complex phenomena in cell biology to the broad audience. Animation artists apply sophisticated illustration techniques to communicate a story, while trying to maintain a realistic representation of a complex dynamic environment. Since such hand-crafted animations are time-consuming and cost-intensive to create, our goal is to formalize illustration...
Scientific visualization is an application area for virtual reality environments like stereoscopic displays or CAVEs. Especially interactive molecular visualizations that show the complex threedimensional structures found in structural biology are often investigated using such environments. In contrast to VR applications like simulators, molecular visualization typically lacks auditory output. Nevertheless,...
Carsharing has emerged as an alternative to vehicle ownership and is a rapidly expanding global market. Particularly through the flexibility of free-floating models, car sharing complements public transport since customers do not need to return cars to specific stations. We present a novel data analytics approach that provides decision support to car sharing operators -- from local start-ups to global...
Visual motion perception in biological vision systems is typically modeled via a set of elementary motion detectors (EMDs) forming a spatially distributed network. This paper addresses the problem of estimating the weights of such an EMD construct from a linear combination of their output signals. This challenge arises in e.g. mathematical modeling of animal motion perception. In particular, the spatial...
Biological systems span several orders of magnitude in space and time from intracellular pathways to tissue-level processes. Many studies focus on molecular level events while other studies focus on cellular level and tissue level interactions. The immune system is highly complex and dynamic, encompassing hierarchical interactions with dimensions ranging from nanometers to meters and time scales from...
Many species of flying insects detect and chase prey or conspecifics within a visually cluttered surround, e.g. for predation, territorial or mating behavior. We modeled such detection and pursuit for small moving targets, and tested it within a closed-loop, virtual reality flight arena. Our model is inspired directly by electrophysiological recordings from 'small target motion detector' (STMD) neurons...
A broad challenge facing scientists today is the availability of huge amounts of data from various sources. Computers are required to store, analyze, explore and represent these data in order to extract useful information. With UnityMol, we pursue the ambitious goal to create an interactive virtual laboratory enabling researchers in biology to visualize biomolecular systems, run simulations and interact...
Most sophisticated mammals, in particular primates, interact with the world to acquire knowledge and skills later exploitable to obtain biologically relevant resources. These interactions are driven by intrinsic motivations. Recent research on brain is revealing the system of neural structures, pivoting on superior colliculus, underlying trial-and-error learning processes guided by movement-detection,...
Inspired by the extraordinary ability of young infants to learn how to grasp and manipulate objects, many works in robotics have proposed developmental approaches to allow robots to learn the effects of their own motor actions on objects, i.e., the objects affordances. While holding an object, infants also promote its contact with other objects, resulting in object-object interactions that may afford...
Vision is an active process involving different kinds of eye movements. How are these movements controlled? And how are they learned and calibrated during development? Biomechanical simulations of eye movements can help us to better understand the underlying problems of visual perception and motor control. Here we introduce OpenEyeSim, a detailed three-dimensional biomechanical model of the human...
It appears that the mirror neuron system plays a crucial role when learning by imitation. However, it remains unclear how mirror neuron properties develop in the first place. A likely prerequisite for developing mirror neurons may be the capability to transform observed motion into a sufficiently self-centered frame of reference. We propose an artificial neural network (NN) model that implements such...
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