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Emmaline Sasportas
We work hard to help people with neurological conditions to gain functional skills so they can increase their independence. We concentrate on the practical needs of each patient by incorporating exercises and practices that facilitate physical and psychological well-being.
We perform physical evaluations to determine the location and level of your pain, and to analyze the weak areas of your body. We will focus on areas that have limited range of motion and help identify the underlying cause of your discomfort to find the pain relief you need and deserve.
Balance issues don't need to control or limit your life anymore. We will help you improve your balance and walking so you can live a more independent life. Our rehabilitation therapists are dedicated to providing exceptional care in a professional atmosphere.
Lea Sternbach is a very dedicated and gifted practitioner. She treated my back that had been hurting me for a week. I was pain free after one session. She really cares about her patients and will go the extra mile to make sure you are getting proper care.
Our mission is to miraculously transform your disability through empowerment, joy and belonging. Because everyone knows that just like flowers blossom in the sun, people also shine brightly and grow strong with the right kind of support, delivered with genuine warmth and fun. We are passionate about providing support to help so you can reach your goals and restore your quality of life.
There is a need for methods and tools that facilitate the systematic exploration of novel artificial neural network models. While significant progress has been made in developing concise artificial neural networks that implement basic models of neural activation, connectivity and plasticity, limited success has been attained in creating neural networks that integrate multiple diverse models to produce highly complex neural systems. From a problem-solving perspective, there is a need for effective methods for combining different neural-network-based learning systems in order to solve complex problems. Different models may be more appropriate for solving different subproblems, and robust, systematic methods for combining those models may lead to more powerful machine learning systems. From a neuroscience modelling perspective, there is a need for effective methods for integrating different models to produce more robust models of the brain. These needs may be met through the development of meta-model languages that represent diverse neural models and the interactions between different neural elements. A meta-model language based on attribute grammars, the Network Generating Attribute Grammar Encoding, is presented, and its capability for facilitating automated search of complex combinations of neural components from different models is discussed.
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