Technical Sessions A3 - E3

SESSION A3: Fault Detection

[20] A negative selection algorithm applied to helicopter actuator fault detection
Thomas Rakotomamonjy and Morgane Le Boulanger

In order to detect the failure of an actuator of a helicopter swashplate, a simple detection method based on a negative selection algorithm (NSA) is developed. This technique, inspired by existing rules found in the biological immunity, rely on a set of elemental detectors which have been trained in order to recognize only the non-self (i.e. faulty) behaviors of the system, without needing an explicit model of the system dynamics. A simple model for the actuator failure is developed and coupled with a helicopter flight dynamics model, and some trajectories for the algorithm training and validation are simulated. A procedure for improving the efficiency of the algorithm by introducing weighting coefficients to the detection function is proposed and successfully tested. Moreover, the performance of the algorithm is slightly improved by observing the covariance of the flight dynamics states, instead of the variables themselves.

[65] A Novel Fault Detection Index Using Principal Component Analysis And Mahalanobis Distance
Ines Jaffel, Okba Taouali, Hassani Messaoud and Mohamed-Faouzi Harakat

This paper proposes a new online index to detect a sensor fault based on principal component analysis (PCA) and Mahalanobis distance. This proposed index is entitled Principal Component Mahalanobis Distance . The main idea behind this index is to detect a disagreement between a PCA model that represent reference function and a PCA model that represent current operation by evaluation of the Mahalanobis distance between their principal components.

[66] On the application of recursive principal component analysis method to fault detection and isolation
Ines Jaffel, Okba Taouali, Hassani Messaoud and Ilyes Elaissi

This paper suggests an extension of a previous study in Recursive Singular Spectrum Analysis (RSSA) [1] to an online method for fault detection and isolation. This proposed method is titled Recursive Principal Component Analysis based on First Order Perturbation RPCA-FOP and it is based on first order perturbation theory (FOP) and partial PCA models where the eigenvalues and eigenvectors of the covariance matrix are updated taking into account the effect of new acquired data as a perturbation.

[84] Active fault diagnosis based on a framework of optimization for closed loop system
Jingwen Yang, Frédéric Hamelin and Dominique Sauter

This paper considers an approach about active fault diagnosis with a new framework for closed loop system. Firstly, a new framework of active fault diagnosis is proposed with a reference model for closed loop system. Secondly, different from the traditional design methods, peak of the amplitude of the responses from the auxiliary signal on the output, active duration of the auxiliary signal on the system and the effects of the auxiliary signal on the control signal are proposed to formulate the auxiliary signal. A constrained multi objective optimization problem is formulated to contain all the criteria. At last, a practical example about DC motor control system DR300 is illustrated to validate the effectiveness of the proposed method.

SESSION B3: Healthcare systems planning and optimization

[109] A linear mathematical model for patients’ activities scheduling on hospital resources
Nour El Houda Saadani, Zied Bahroun and Asma Bouras

Hospitals use very costly medical equipment like scanners, RMI, endoscopy equipment or operating rooms. In this paper, we propose a mixed integer model to schedule patients on different hospital resources they can need during their stay in a hospital. We study the case of multiple types of resources and for each type the existence of several parallel units. The objective is to minimize the sum of all patients’ stays. We used LINGO11 solver, along with our mathematical formulation, to solve the problem. The results showed that, as expected for an NP-hard problem, the computational times rise exponentially with the size of the instances.

[193] A Robust Assessment of Effective HealthCare Demand in the Pediatric Emergency Department
Wided Chandoul, Hervé Camus, Nesrine Zoghlami, Slim Hammadi and Alain Matinot

This work aims to assess the effective demand of healthcare treatment load in the Pediatric Emergency Department (PED) as a treatment time requested and focus on the treatment time remained. So we defined a metrics assessing the Total Demand Load (TDL) of healthcare treatment in the PED which is more robust to reflect the whole patients’ healthcare demand than the simple attending patients count. In addition, we demonstrate that we have to avoid being limited on the physical presence of patients because a high occupancy rate does not necessarily mean that there is a high demand of healthcare treatment. This study was based on Length Of Stay (LOS) estimation according to the patient diagnostic and his number of additional tests. The patient process progression is modeled by a time buffer system allowing the instantly track of each patient. It is a way to improve the quality of service and information delivery. This method offers a priority mechanism, it is also a robust management and decision aided tool. Besides, the time buffers system will encourage physicians to respect the time needed for each patient profile suggested in order to maximize the objective of improving the performing. Such system will make them aware about three important points: The healthcare Treatment process progress, the eventual overflowing/ time excess, the eventual high acuity. From patients’ viewpoint, it will reassure parents who can follow the healthcare treatment progression of their children instantly.

[196] Solving Operating Theater Facility Layout Problem using a Multi-Agent System
Abdelahad Chraibi, Kharraja Saïd, Ibrahim Osman and Omar El Beqqali

Operating Theater Layout Problem (OTLP) has a great impact on the productivity and the efficiency of the health process. While solving OTLP, Real-life Operating Theater (OT) sizes are larger than exact methods capacity, this lead to explore other methods as heuristics, metaheuristics or parallel treatment looking for approximate solutions. In this paper we developed a novel approach using a Multi-Agent (MA) Decision Making System (DMS) based on Mixed Integer Linear Programming (MILP) for large-sized OTFLP with objective of minimizing total traveling costs. The DMS generates exact solutions in reasonable time and gives the final OT layout in a graphic interface.

[233] Multicriteria decision making for Medical equipment maintenance: Insourcing, outsourcing and service contract
Malek Masmoudi, Zeineb Ben Houria and Faouzi Masmoudi

Hospitals outsource several activities of support in order to focus on healthcare production. Maintenance is one of these support activities. Recently, faced with rising healthcare costs, governments have implemented new reforms to control costs and improve efficiency and quality. Hospitals became interested in minimizing the total cost of the activity, by minimizing both healthcare production activities and support activities. In developing countries, medical equipment maintenance is costly and partially mastered most of the time because it is usually managed by external service contracts. Reorganizing medical equipment maintenance service became a priority for hospital managers to reduce the cost and dependency while raising quality and reliability. In this paper, we propose an efficient procedure to take the appropriate decisions for medical equipment maintenance such as the maintenance strategy, to insource or outsource the type of contract and its content.

SESSION C3: Combinatorial Optimization and Logistics

[127] A Hybrid Large Neighborhood Search for the Pickup and Delivery Problem with Time Windows
Mhand Hifi, Laurent Moreau, Stephane Negre and Lei Wu

In this paper, we investigate the use of the large neighborhood search for solving the pickup and delivery problem with time windows. Such a problem may be viewed as a variant of the capacitated vehicle routing problem with time windows, where both precedence and coupling constraints are considered. The proposed method is based on the framework of the large neighborhood search combined with local search procedures. In order to evaluate the performance of the proposed method, it has been tested on Li et al. ’s benchmark instances. The obtained results are compared to those reached by the best method available in the literature. Encouraging results have been obtained.

[237] A contribution to solving the travelling salesman problem using ant colony optimization and web mapping platforms : Application to logistics in a urban context
Ahmed Haroun Sabry, Abdelkabir Bacha and Jamal Benhra

This article presents an easy to use system for solving the travelling salesman problem in a urban context, it uses an ant colony optimization metaheuristic for solving the combinatorial problem. The system assists the user to formulate, manage and rapidly solve complicated instances of the routing problem, delivering optimum or near-optimum solutions that can be used for improving the quality of modern urban transportation systems. The proposed model is simple and scalable and integrates a spatial data management service to communicate with the web mapping platform to be chosen. The system integrates Bing maps™ (Imagery and geographic network data) and an efficient ant colony optimization metaheuristic. It was tested with a moderately large instance of the problem in the complex urban environment of the city of Casablanca, Morocco.

[203] A Mathematical formulation and a lower bound for the three-dimensional multiple-bin-size bin packing problem (MBSBPP): A Tunisian industrial case
Mariem Baazaoui, Saïd Hanafi and Hichem Kamoun

In our research, we are interested in the three-dimensional multiple-bin-size bin packing problem (MBSBPP). We deal with the real word application of cutting mousse blocks proposed by a Tunisian industrial company. First, we present the general context related to our optimization problem. Second we formulate it as a mathematical problem without considering the guillotine constraint, and then we tested it on a small instance taken from the industry. Thereafter, we propose and test a lower bound for a large instance from the same industrial company. Finally, some computational results are presented.

[187] A Hybrid Metaheuristic for the Vehicle Routing Problem with Time Windows
Mhand Hifi and Lei Wu

In this paper we propose to solve the Vehicle Routing Problem with Time Windows (VRPTW) using a hybrid metaheuristic. The VRPTW is a bi-objective optimization problem where both the number of vehicles and the distance of the travel to use should be minimized. Because it is often difficult to optimize both objectives, we propose an approach that optimizes the distance traveled by a fleet of vehicles. Such a strategy has been already used by several authors in the domain. Herein, an instance of VRPTW is considered as the composition of the Assignment Problem and a series of Traveling Salesman Problems with Time Windows (TSPTW). Both AP and TSPTW are solved by using an ant colony optimization system. Furthermore, in order to enhance the quality of the current solution, a large neighborhood search is introduced. Finally, a preliminary experimental part is presented where the proposed method is evaluated on a set of benchmark instances and its results are compared to the best results obtained by the methods available in the literature. Our preliminary results show that the proposed hybrid method remains competitive and it is able to reach new minimum distances for some tested instances.

SESSION D3: Biomedical Engineering & Clinical Applications (BECA)

[35] Low-Noise Transimpedance Amplifier Dedicated to Biomedical Devices: Near Infrared Spectroscopy System
Ahmad Chaddad and Camel Tanougast

This paper concerns the design and the implementation of a transimpedance amplifier (TIA) dedicated to detector of Near Infrared spectroscopy (NIRS). To reduce the effect of the input capacitance on the bandwidth, a bias circuit with low input impedance is connected to input stage. A single ended common source common gate input stage based on a cascode structure is used to get a higher gain bandwidth closed loop transimpedance amplifier. In addition, a higher open loop gain is got by adding second active load. To increase noise circuit performance, a feedback single transistor technique is considered. The TIA is implemented in 0.18 µm CMOS process. Simulation results show a transimpedance gain of 104.2 dBΩ, -3dB bandwidth of 19 MHz and an equivalent input noise current spectral density of 446 fA/√Hz. A comparative study confirms the feasibility of our proposal.

[36] Quantitative Texture Analysis for Glioblastoma Phenotypes Discrimination
Ahmad Chaddad, Pascal O. Zinn and Rivka R. Colen

A quantitative texture analysis for discriminating GBM phenotypes in brain magnetic resonance (MR) images is proposed. GBM phenotypes captured using semi-automatic segmentation based on 3D Slicer Scripts. Segmentation was applied on the registered images considered the T1-Weighted and FLAIR sequence. Texture feature has been extracted from the gray level co-occurrence matrix (GLCM) based on GBM phenotypes. Feature vectors are then used in training a minimum distance classifier based on Mahalanobis distance metric. Simulation results for 13 patients show the highest accuracy of 67% based on the feature extraction from GLCM with offset =1 a nd 8 phases. Preliminary texture analysis demonstrated that the texture feature based on the GLCM is promising to distinguish GBM phenotypes.

[51] Survival Analysis of Pre-Operative GBM Patients by Using Quantitative Image Features
Pattana Wangaryattawanich, Jixin Wang, Ginu A. Thomas, Ahmad Chaddad, Pascal O. Zinn and Rivka R. Colen

This paper concerns a preliminary study of the relationship between survival time of both overall and progression free survival, and multiple imaging features of patients with glioblastoma. Simulation results showed that specific imaging features were found to have significant prognostic value to predict survival time in glioblastoma patients.

[100] Effectiveness of combined time-frequency image- and signal-based features for improving the detection and classification of epileptic seizure activities in EEG signals
Larbi Boubchir, Somaya Al-Maadeed and Ahmed Bouridane

This paper presents new time-frequency (T-F) features to improve the detection and classification of epileptic seizure activities in EEG signals. Most previous methods were based only on signal features derived from the instantaneous frequency and energies of EEG signals generated from different spectral sub-bands. The proposed features are based on T-F image descriptors, which are extracted from the T-F representation of EEG signals, are considered and processed as an image using image processing techniques. The idea of the proposed feature extraction method is based on the application of Otsu's thresholding algorithm on the T-F image in order to detect the regions of interest where the epileptic seizure activity appears. The proposed T-F image related-features are then defined to describe the statistical and geometrical characteristics of the detected regions. The results obtained on real EEG data suggest that the use of T-F image based-features with signal related-features improve significantly the performance of the EEG seizure detection and classification by up to 5% for 120 EEG signals, using a multi-class SVM classifier.

SESSION E3: Modelling, Simulation and Performance Evaluation

[24] Simulation and Performance Evaluation of an Intermodal Terminal using Petri Nets
Mariagrazia Dotoli, Nicola Epicoco, Marco Falagario, Graziana Cavone and Biagio Turchiano

This paper focuses on modelling and performance evaluation of an Intermodal Freight Transport Terminal (IFTT), the rail-road inland terminal of a leading Italian intermodal logistics company. The IFTT is regarded as a discrete event system and is modelled in a timed Petri net framework. By means of suitable performance indices, we simulate the Petri net model and evaluate the operational performance of the transport system. This allows assessing the efficiency level of the terminal and identifying its criticalities and bottlenecks. Further, the model allows evaluating different solutions to the recognized criticalities under alternative scenarios (e.g., when inflow traffic increases and congestion may occur).

[47] Diagnosis of Dynamic Systems by Timed Automata and Interval Constrained Petri Nets
Lobna Belgacem, Dhouibi Hedi, Mhamdi Lotfi, Zineb Simeu-Abazi and Hassani Messaoud

The purpose of the following article is a new approach to modeling, diagnosing and controlling of discrete-event systems. This approach is using a model which combines Interval Constrained Petri Nets and Timed Automata to describe the diagnosed system. The Petri net is used for modelling the system which needs controlling and the timed automata is being used for the controller. This article is a description of a case study, which is a cigarette production system where the tobacco density must be held in an interval.

[40] Numerical Research of High Viscosity Phosphor Flow Field Distribution of High-power LED Phosphor Coating Process
Qiwei Guo, Yueming Hu and Zhifu Li

In this paper, the transportation and atomization of phosphor glue flowing in high-power LED (Light Emitting Diode) phosphor coating process were investigated via CFD (Computational Fluid Dynamics) and numerical simulations, and the 3D flow field models as well as the mathematical models of phosphor were established to describe the velocity distribution of phosphor glue’s flow field between two different spraying guns. Moreover, spraying experiments were carried out, and the consistency of simulated results with experimental ones was proved. It is found that numerical simulation helps accurately predict the phosphor droplets trajectories and the velocity distribution in LED phosphor coating process without establishing any models of atomization process; and that, within the same spray distance, small phosphor droplet and high droplet velocity may result in short acceleration and deceleration distance.

[55] Detection and localization of Faults using Bond Graph and Timed Automata
Maaref Bochra, Dhouibi Hedi, Hassani Messaoud and Zineb Simeu-Abazi

The problem of fault diagnosis involves detecting, locating and identifying the considered faults occurring in the dynamical system. The aim of this paper is to explain the use of hybrid tool which combines Bond Graph and Timed Automata. These tools allow us, respectively, to detect the fault and find the cause of a system dysfunction. Due to the structural and causal properties of the bond graph tool, we use it to detect the incorrect behavior and then to isolate faults which can affect the physical process. But sometimes, some failures of the system components can not be identified by the Bond Graph model. Therefore, we use, in this case, the timed model (timed automata) in order to locate and identify these faults. And subsequently, the performances of the phase of fault location will be improved thanks to the use of these tools (Bond Graph and Timed Automata). The proposed approach is then validated through simulation tests to a level regulation system.