Ronald A. Perez

Controls laboratory program with an accent on discovery learning

A sequence of laboratories is presented that have been designed to maximize student involvement in the design as well as execution of the laboratory exercises. The first lab begins with the simplest possible model, and students explore fundamental ideas of sensing, actuation, and feedback. With the second lab, student-designed experiments are introduced. By the end of the sequence, students independently design and implement system identification, controller design, and performance assessment for high performance tracking with a motor servo. The education literature establishes the potential for discovery learning to increase learning outcomes in laboratory teaching.

A new system identification technique using Kaiman filtering and multilayer neural networks

Abstract The objective of this work is to use the back-propagation algorithm in conjunction with Kaiman filtering in order to establish a new self-learning technique of multilayer neural network (MNN). This new technique is developed by directly building a Kaiman filtering model for each perceptron in order to increase the adaptability of the MNN and to provide for on-line nonlinear system identification. We demonstrate that this new technique is faster and more stable than the classical back-propagation algorithm for training multilayer perceptrons. We also find that it is less sensitive to the initial weights and to the learning parameters.

The US Cancer Moonshot initiative

Correspondence avoid surgery in rapidly progressive or chemo-insensitive disease. 4 Genotyping of pancreatic tumours via fine needle aspiration could influence the clinical management of pancreatic cancer. Fine-needle aspiration sequencing was used to identify subgroups of patients with specific actionable mutations related to resectable or locally advanced tumours. 5 In patients with radiologically resectable or borderline resectable tumours, preoperative fine-needle aspiration sequencing could distinguish between patients with a genetic pattern associated with micrometastatic tumours, who should undergo neoadjuvant therapy, and those with a truly localised disease that would be amenable to a surgery-first strategy. Michele Reni has served as a consultant for or on the advisory boards of Celgene, Boehringer-Ingelheim, Lilly, Genentech, Baxalta, Novocure, Astra-Zeneca, Pfizer, and Merck-Serono, and has received honoraria from Celgene. Massimo Falconi has received honoraria from Celgene, Ipsen and Novartis. The other authors declare no competing interests. *Stefano Crippa, Michele Reni, Gianpaolo Balzano, Claudio Doglioni, Massimo Falconi crippa1.stefano@hsr.it Division of Pancreatic Surgery, IRCCS San Raffaele Hospital, Milan, Italy (SC, GB, MF); Medical Oncology Department, IRCCS San Raffaele Hospital , Milan, Italy (MR); Department of Pathology, IRCCS San Raffaele Hospital , Milan, Italy (CD); Clinical and Translational Research Program on Pancreatic Cancer, IRCCS San Raffaele Hospital, Milan, Italy (SC, MR, GB, CD, MF) e178 Barreto SG, Windsor JA. Justifying vein resection with pancreatoduodenectomy. Lancet Oncol 2016; 17: e118–24 Giovinazzo F, Turri G, Katz MH, Heaton N, Ahmed I. Meta-analysis of benefit of portal-superior mesenteric vein resection in pancreatic resection for ductal adenocarcinoma. Br J Surg 2016; 103: 179–91. Bapat AA, Hostetter G, Von Hoff DD, Han H. Perineural invasion and associated pain in pancreatic cancer. Nat Rev Cancer 2011; Sohal DP, Walsh RM, Ramanathan RK, Khorana AA. Pancreatic adenocarcinoma: treating a systemic disease with systemic therapy. J Natl Cancer Inst 2014; 106: dju011 Valero V, Saunders TJ, He J, et al. Reliable detection of somatic mutations in fine needle aspirates of pancreatic cancer with next-generation sequencing: implications for surgical management. Ann Surg 2016; Author’s reply Stefano Crippa and colleagues, in responding to our manuscript, 1 agree that increasing the radicality of surgery for pancreatic ductal adenocarcinoma, including synchronous vein resection, is suspect. Indeed, a recent meta-analysis 2 indicates that synchronous vein resection, as reported, increases mortality and decreases survival. Crippa and colleagues put forward two interesting ideas that warrant further discussion. The first is that the surgery-first approach for pancreatic ductal adenocarcinoma might ultimately be retired, given that pancreatic ductal adenocarcinoma is usually systemic at presentation, local treatments have little effect, and neoadjuvant therapy has possible benefits. For now, the absence of high-level evidence for neoadjuvant therapy leaves largely theoretical benefits; namely that neoadjuvant therapy will reveal the biology (ie, those patients that can progress on neoadjuvant therapy will avoid futile surgery), or alter the biology (ie, those patients that are downstaged will become resectable). The preliminary results of the ALLIANCE trial 3 damages the lustre of these purported benefits with no improvement in the number of resections (10 [50%] of 20 patients who completed all preoperative therapy), and no rescue of aggressive tumour biology. This leads to the second idea, in which Crippa and colleagues suggest a biological (rather than radiological) basis for selecting patients for neoadjuvant therapy with a view to reduce the number of synchronous vein resections. Endoscopic ultrasonography- guided genotyping is a possible way to select subgroups of patients with heterogenous pancreatic ductal adenocarcinoma 4 who will benefit from neoadjuvant therapy. In support of this method, Hruban and colleagues 5 suggested that an intact SMAD4/DPC4 gene might be used to select surgery because there is lesser risk of distant metastases for this genotype. 6 In the future, we hope to more accurately select a subgroup of patients in whom a surgery-first approach, and even synchronous vein resection, is justified, but it is much more likely that precision neoadjuvant therapy will ultimately result in less radical surgery and the introduction of non-surgical techniques to support the response to neoadjuvant therapy. We declare no competing interests. Savio G Barreto, *John A Windsor j.windsor@auckland.ac.nz Department of Gastrointestinal Surgery, Gastrointestinal Oncology, and Bariatric Surgery, Medanta Institute of Digestive and Hepatobiliary Sciences, Medanta, The Medicity, Gurgaon, India (SGB); Hepatobiliary Pancreatic and Upper GI Unit, Department of General Surgery, Auckland City Hospital, Auckland, New Zealand (JAW) Barreto S, Windsor J. Justifying vein resection with pancreatoduodenectomy. Lancet Oncol 2016; 17: e118–24. Giovinazzo F, Turri G, Katz MH, Heaton N, Ahmed I. Meta-analysis of benefits of portal-superior mesenteric vein resection in pancreatic resection for ductal adenocarcinoma. Br J Surg 2016; Varadhachary G, Fleming J, Crane C, et al. Phase II study of preoperation mFOLFIRINOX and chemoradiation for high-risk resectable and borderline resectable pancreatic adenocarcinoma. Proc Am Soc Clin Oncol 2015; 33 (suppl 3): abstr 362. Killock D. Pancreatic cancer: a problem quartered—new subtypes, new solutions? Nat Rev Clin Oncol 2016; 13: 201. Hruban RH, Adsay NV. Molecular classification of neoplasms of the pancreas. Hum Pathol Iacobuzio-Donahue CA, Fu B, Yachida S, et al. DPC4 gene status of the primary carcinoma correlates with patterns of failure in patients with pancreatic cancer. J Clin Oncol 2009; The US Cancer Moonshot initiative We recently sent the following letter to Vice President of the USA, Joe Biden, to state that we, as Deans and Directors of Public Health schools and programmes around the USA, strongly support the goals of the Cancer Moonshot initiative to www.thelancet.com/oncology Vol 17 May 2016

A novel application of artificial neural networks to structural analysis

Abstract In this work we use the continuous Hopfield network and the continuous bidirectional associative memory system (BAM) in order to develop two novel methods for structural analysis. The development of these techniques is based on the analogous relationship that results from comparing the energy functions of the above two models with that of the structural displacement method (i.e. the socalled stiffness matrix method) and it takes advantage of the fact that classical numerical methods do not have the characteristics of parallel computation that artificial neural networks have. Several examples related to structural deformation are used to illustrate the superiority of the BAM-based neural networks over other traditional numerical methods and the Hopfield model, especially for the case of large dimensional stiffness matrices.

Unsteady Pressure Field Investigation of an Axial Fan—Inlet and Outlet Unsteady Pressure Field Measurement

The unsteady pressure characteristics at inlet and outlet of an axial fan were measured in this study. A 1.829 m (6 ft) diameter axial fan was operated at 1770 rpm in a laboratory. The unsteady pressure field was obtained at three axial positions each with seven radial locations. The results showed that there was a relatively long response time for pressure drop both in the inlet and outlet during fan start-up. The measurements also showed that, due to the vortex shedding from the trailing edge of each fan blade, the fan outlet pressure oscillation frequency was related to the fan operating frequency. A theoretical analysis was also conducted in order to understand the measurements. The unsteady pressure measurements helped improve the fan performance and contributed to the understanding of the vibrational behavior of the fan unit. The complete set of the measurements obtained can be used as a database for computational fluid dynamics (CFD) codes validation and modeling.

A novel robust algorithm for controlling robotic manipulators

Abstract The purpose of this paper is to present a new technique for controlling complex non-linear dynamical systems. This algorithm is based on Lyapunov stability theory and it guarantees that the trajectories will converge globally-uniformly-asymptotically-stable to their respective equilibrium points. This new controller is shown to be insensitive to unmodeled dynamics and robust with respect to bounded uncertainties. This control law is applied through computer simulations to a robotic manipulator and it promises to be a very useful tool for realtime applications.

Using Symbolic Algebra to Enhance the Learning Environment of Dynamic Systems

Abstract In this paper we present the use of symbolic algebra to enhance the teaching and learning of dynamic systems. We illustrate concepts such as: Laplace transform; Root Locus; Bode diagrams; Nyquist diagrams; etc. We believe that a more efficient use of the available computing resources would free the students from some of the more tedious algebraic manipulations. Allowing them to channel their energies into creative processes that will sharpen their analytical skills.

Near-Minimum Time Controller for Robotic Manipulators

Abstract A near-minimum time feedback controller for robotic manipulators with bounded input torques is developed in this paper which applies a time scaling method to move a manipulator in near-minimum time using the allowable input torques efficiently. This new feedback controller algorithm adapts to an uncertain environment and automatically adjusts the desired speed along a specified path to be as fast as possible while avoiding the velocity saturation condition. Numerical examples of the near-minimum time feedback controller are provided using a two-link SCARA manipulator.

Local minimum-time trajectory planning for five-axis machining with and without tool tip deviation

This paper presents the algorithms to achieve local minimum-time trajectory planning for the motors of a five-axis milling machine with and without the tool tip deviation. The forward and inverse kinematics are first applied to obtain the kinematic relation between the planned path for the tool-workpiece system and the motion of the five motors. The path trajectory of the machine can be obtained by a CAM software a priori. With the constraints of the feed rate, velocity, acceleration and jerk of each motor, the trajectory planning algorithms are developed to obtain the local minimum-time trajectory for every interval in the tool path through the quintic polynomial with or without the tool tip deviation. The bisecting-plane (BP) algorithm is applied to obtain the minimum-time trajectory for each interval, and the potential field method is used to find the projection of tool tip deviation on the reference path. The proposed algorithms are verified through simulation study.

A Method to Improve the Illumination Effect in an Underwater Environment

There are some innate shortcomings for traditional underwater observation system due to camera/light’s rigid-fixed connection with carrier vehicle such as ROV (Remotely Operated Vehicle)/AUV (Autonomous Underwater Vehicle). One of these is that the clearance of video image is seriously corrupted since the backscatter of water/particles is not overcome using fixed light source. To make up the deficiency, multi-light sources have to be adopted as a traditional approach. In this paper, a Master-Slave coordinated architecture was created and developed to provide a solvable scheme for improving illumination consequence. The illumination geometry between a camera and a light can dynamically be coordinated so that the backscatter which is the culprit blurring the target observed can be greatly decreased. The light source can follow up the moving target which the camera captures based on the numerical simulation results. The proposed observation system is especially suitable for our research purpose, where an agile system is needed for the observation of small range in Lake Michigan. The dynamic and hydrodynamic models used in this paper can be found in [1]. The control algorithms to be employed to evaluate this proposed method in this paper can be referred to [2–3].Copyright