Altran

About: Altran is a company organization based out in Neuilly-sur-Seine, France. It is known for research contribution in the topics: Software development & Formal verification. The organization has 488 authors who have published 512 publications receiving 6395 citations.

Towards a distributed computation platform tailored for educational process discovery and analysis

Abstract: Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EPM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform, under construction, which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Semantic Grid-Based Road Model Estimation for Autonomous Driving

Abstract: For autonomous driving, knowledge about the current environment and especially the driveable lanes is of utmost importance. Currently this information is often extracted from meticulously (hand-)crafted offline high-definition maps, restricting the operation of autonomous vehicles to few well-mapped areas and making it vulnerable to temporary or permanent environment changes. This paper addresses the issues of map-based road models by building the road model solely from online sensor measurements. Based on Dempster-Shafer theory and a novel frame of discernment, sensor measurements, such as lane markings, semantic segmentation of drivable and non-drivable areas and the trajectories of other observed traffic participants are fused into semantic grids. Geometrical lane information is extracted from these grids via an iterative path-planning method. The proposed approach is evaluated on real measurement data from German highways and urban areas.

Precise current matching charge pump for digital phase locked loop

Abstract: In digital phase locked loop cascode structured charge pump is proposed with current mismatch less than 0.01%. Steady state error in digital phase locked loop can be minimized by reducing current mismatch. The rail to rail operational amplifier and cascode current source circuit is employed to reduce the mismatch between charging and discharging current. The operational amplifier has high gain of 90dB. The proposed charge pump is designed, simulated and verified at power supply of 1.8V in TSMC 90nm CMOS technology.

Optimal sensor placement strategy for anomaly detection and isolation

Abstract: On-line detection and isolation of anomalies in process systems, devices, and instrument channels is an important issue in the nuclear power industry, addressing efficient and continuous operation of power plants. An approach for optimal sensor placement, based on directed graph (DG) and minimizing the maximum unobservability among all postulated faults, is described and illustrated with application to a nuclear desalination plant.