MLP bilinear separation

In this paper, we present a thorough mathematical analysis of the use of neural networks to solve a specific classification problem consisting of a bilinear boundary. The network under consideration is a three-layered perceptron with two hidden neurons having the sigmoid serving as the activation function. The analysis of the hidden space created by the outputs of the hidden neurons will provide results on the network’s capacity to isolate two classes of data in a bilinear fashion, and the importance of the value of the sigmoid parameter is highlighted. We will obtain an explicit analytical function describing the boundary generated by the network, thus providing information on the effect each parameter has on the network’s behavior. Generalizations of the results are obtained with additional neurons, and a theorem concerned with analytical reproducibility of the boundary function is established.     

Characterization of renal tumours based on Raman spectra classification

In this study, we propose to evaluate the potential of Raman spectroscopy (RS) to assess renal tumours at surgery. Different classes of Raman renal spectra acquired during a clinical protocol are discriminated using support vector machines classifiers. The influence on the classification scores of various preprocessing steps generally involved in RS are also investigated and evaluated in the particular context of renal tumour characterization. Encouraging results show the interest of RS to evaluate kidney cancer and suggest the potential of this technique as a surgical assistance during partial nephrectomy.     

Exploring the relationship between Internet ethics in university students and the big five model of personality

The widespread use of the Internet and the convenient mechanism it provides, such as easy access, easy downloads, and easy copy and paste functions have made many types of unethical behaviors easier, particularly those involving students in academic settings. Among the issues in ethics within the academic environment that can be triggered by the Internet are fraudulence, plagiarism, falsification, delinquency, unauthorized help, and facility misuse. Given these issues, the study seeks to investigate the extent to which students at a public university in Malaysia engage in such unethical behavior and their relationship with the big five personality model. This study was conducted using a survey method of 252 students in three different academic faculties. The results of factor analyses confirm and refine the reliability of the scales for both big five personality variables and unethical Internet behaviors as conceptualized through Internet triggered academic dishonesty (ITADS). The findings indicate that personality traits such as (1) agreeableness, (2) conscientiousness and (3) emotional stability are significantly and negatively correlated with unethical Internet behavior in university students. Significant differences in facility misuse are also observed between the three academic faculties investigated. This research should provide significant contributions to educators in designing the computer ethics curriculum and in allowing for educational institutions as well as other organizations in developing relevant policies and guidelines on matters pertaining to academic conduct, utilization of computers and Internet, and recruitment exercises.     

A Learning Behavior Based Controller for Maintaining Balance in Robotic Locomotion

The Behavior Based Locomotion Controller (BBLC) extends the applicability of the behavior based control (BBC) architecture to redundant systems with multiple task-space motions. A set of control behaviors are attributed to each task-space motion individually and a reinforcement learning algorithm is used to select the combination of behaviors which can achieve the control objective. The resulting behavior combination is an emergent control behavior robust to unknown environments due to the added learning capability. Hence, the BBLC is applicable to complex redundant systems operating in unknown environments, where the emergent control behaviors can satisfy higher level control objectives such as balance in locomotion. The balance control problem of two robotic systems, a bipedal robot walker and a mobile manipulator, are used to study the performance of this controller. Results show that the BBLC strategy can generate emergent balancing strategies capable of adapting to new unknown disturbances from the environment, using only a small fixed library of balancing behaviors.     

Multi-contact vertical ladder climbing with an HRP-2 humanoid

We describe the research and the integration methods we developed to make the HRP-2 humanoid robot climb vertical industrial-norm ladders. We use our multi-contact planner and multi-objective closed-loop control formulated as a QP (quadratic program). First, a set of contacts to climb the ladder is planned off-line (automatically or by the user). These contacts are provided as an input for a finite state machine. The latter builds supplementary tasks that account for geometric uncertainties and specific grasps procedures to be added to the QP controller. The latter provides instant desired states in terms of joint accelerations and contact forces to be tracked by the embedded low-level motor controllers. Our trials revealed that hardware changes are necessary, and parts of software must be made more robust. Yet, we confirmed that HRP-2 has the kinematic and power capabilities to climb real industrial ladders, such as those found in nuclear power plants and large scale manufacturing factories (e.g. aircraft, shipyard) and construction sites.     

A sliding mode observer for uncertain nonlinear systems based on multiple models approach

This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters’ variations of the nonlinear system. Linear matrix inequalities (LMIs) have been established in order to ensure the stability conditions of the multiple observer which lead to determine the estimation gains. A sliding mode gain has been added in order to compensate the uncertainties. Numerical simulations through a state space model of a real process have been realized to show the robustness of the synthesized observer.     

Rational method for 3D manufacturing tolerancing synthesis based on the TTRS approach “R3DMTSyn”

During the production of new part in an industrial environment, it results in a high percentage of scrap if manufacturing planning is not carried out properly. One of the major factors responsible for this phenomenon is tolerance synthesis. In this paper, we deal with tolerance synthesis, and especially tolerance type identified after transfer. An algorithmic Rational method for 3D Manufacturing Tolerancing Synthesis (R3DMTSyn), which is based on the use of the Technologically and Topologically Related Surface (TTRS) rules, is developed. The TTRS concept helps to generate only the necessary manufacturing specification needed to guarantee the respect of the functional specification studied.The manufacturing project is modeled by a graphical representation called the SPIDER GRAPH. With the SPIDER GRAPH, all active surfaces can be detected (machined and positioning surfaces), so it is possible to identify the location of the functional surfaces used in each functional specification. The construction or the determination of the tolerancing torsor, belonging to each active surface, contributes to the selection of the adequate case of associations. A semantic study is already done to identify all possible combinations or associations needed to locate surfaces during each phases.Finally, referring to the developed TTRS_Cars_Process and in every phase, one or more manufacturing specifications are generated until finishing the treatment of all surfaces (surface belonging to the functional condition, or intermediate surfaces).     

A heuristic method for the vehicle routing problem with mixed deliveries and pickups

The vehicle routing problem with deliveries and pickups is a challenging extension to the vehicle routing problem that lately attracted growing attention in the literature. This paper investigates the relationship between two versions of this problem, called “mixed” and “simultaneous”. In particular, we wish to know whether a solution algorithm designed for the simultaneous case can solve the mixed case. To this end, we implement a metaheuristic based on reactive tabu search. The results suggest that this approach can yield good results.