Today, with the exponential rise in the use of the internet, the trend of the massive use of mobile devices (tablets, laptops, computers, iPads etc...) the user has become inseparable from his smartphone, which facilitates the use of several services in different fields (work, research, commerce, etc.). Besides, with the proliferation of data, the needs of consumers are becoming increasingly complex. So the composition of web services remains a necessary process allowing to combine several atomic services aggregating different functionalities to answer a complex request. Several techniques in the literature like, AI planning, work flow, Agent, Mathematics and Semantic. These techniques are mainly involved in the automation and improvement of the composition process. In this article, we will survey several context aware web service composition approaches based on these techniques. Remember that the Mobile environment is characterized by software, hardware and space constraints and Web Service Composition in mobile environment must respect these conditions.

When dealing with the design of robotic fingers driven by tendons, one can be inspired by the human index finger tendon distribution. The structure of the designed robot finger has to minimize the number of tendons required without sacrificing either the actuated degree of freedom or the maximal output force produced at the fingertip. In this paper, a biomechanical study of the index finger under normal and abnormal conditions is developed. Under abnormal conditions, when some pathology affects the musculo-tendon units, the number of intact muscular actuators will be reduced. A three-dimensional biomechanical model for a static force analysis is developed through anatomical and kinematic studies. An optimization approach is then used to determine muscle force distributions corresponding to maximal fingertip strength when performing isometric force tasks. Further common cases of injured flexors and extensors are analyzed. The simulation method of such abnormalities is described and the results are reported. This investigation allows us to analyze the importance of the tendons distribution in order to enhance the robotic hands design process. In fact, the obtained force distributions are linked to the further required motor torques of the artificial robotic finger driven by tendons. Hence, the developed approach can be with great help whenever the motor sizing process is investigated.

In this work, a biomechanical model of the index finger is used to get an insight into the mechanism that controls the index musculoskeletal system. Our simulation is intended to determine how different muscles groups are acting on different joints in producing adequate static maximal fingertip forces and moments. The model is then modified to simulate injured fingers with extensor mechanism loss. We investigated two common pathologies that affect the extensor mechanism, i.e., Mallet and Boutonniere lacerations. We used a biomechanical model based on robotic principles and an optimization technique to solve the muscular redundant problem over the 3 joints of the forefinger system. The role of each tendon was quantified in the case of the healthy finger as well as in the pathological one. We showed, in particular, that the loss of strength in the finger can be regained by an increase of the tension in the interosseous tendons; however, this increase can be a source of instability in the pinch task.

In the paper a static analysis of key grip is presented. Objective deals with estimating maximal pinch force required to secure objects in the human hand system. A three- dimensional static computational biomechanical model was developed. This model is based on fingers anatomy, kinematics and numerical optimization technique. The optimization module permits to predict the optimal combination of tendon tensions that maximize pinch force for a given pinch posture. The key pinch output force is presented in the case of the healthy, the pathological and the reconstructed index and thumb fingers.

This paper extends a neural model for causal reasoning to mechanize the monotonic class. Hence, the resulting model is able to solve multiple, varied causal problems in the open, independent, incompatibility and monotonic classes. First, additivity between causes is formalized as a fuzzy AND-ing process. Second, an activation mechanism called the "softmin" is developed to solve additive interactions. Third, the softmin is implemented within a neural architecture. Experimental results on real-world and artificial problems reveal a good performance of the model and should stimulate future research.