Fault-tolerance of a neural network solving the traveling salesman problem

This study presents the results of a fault-injection experiment that stimulates a neural network solving the Traveling Salesman Problem (TSP). The network is based on a modified version of Hopfield's and Tank's original method. We define a performance characteristic for the TSP that allows an overall assessment of the solution quality for different city-distributions and problem sizes. Five different 10-, 20-, and 30- city cases are sued for the injection of up to 13 simultaneous stuck-at-0 and stuck-at-1 faults. The results of more than 4000 simulation-runs show the extreme fault-tolerance of the network, especially with respect to stuck-at-0 faults. One possible explanation for the overall surprising result is the redundancy of the problem representation

What Is the Most Effective Management of the Primary Tumor in Men with Invasive Penile Cancer: A Systematic Review of the Available Treatment Options and Their Outcomes.

CONTEXT: The primary lesion in penile cancer is managed by surgery or radiation. Surgical options include penile-sparing surgery, amputative surgery, laser excision, and Moh's micrographic surgery. Radiation is applied as external beam radiotherapy (EBRT) and brachytherapy. The treatment aims to completely remove the primary lesion and preserve a sufficient functional penile stump. OBJECTIVE: To assess whether the 5-yr recurrence-free rate and other outcomes, such as sexual function, quality of life, urination, and penile preserving length, vary between various treatment options. EVIDENCE ACQUISITION: The EMBASE, MEDLINE, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL; Cochrane HTA, DARE, HEED), Google Scholar, and ClinicalTrials.gov were searched for publications from 1990 through May 2021. Randomized controlled trials, nonrandomized comparative studies (NRCSs), and case series (CSs) were included. EVIDENCE SYNTHESIS: The systematic review included 88 studies, involving 9578 men from 16 NRCSs and 72 CSs. The cumulative mean 5-yr recurrence-free rates were 82.0% for penile-sparing surgery, 83.9% for amputative surgery, 78.6% for brachytherapy, 55.2% for EBRT, 69.4% for lasers, and 88.2% for Moh's micrographic surgery, as reported from CSs, and 76.7% for penile-sparing surgery and 93.3% for amputative surgery, as reported from NRCSs. Penile surgery affects sexual function, but amputative surgery causes more appearance concerns. After brachytherapy, 25% of patients reported sexual dysfunction. Both penile-sparing surgery and amputative surgery affect all aspects of psychosocial well-being. CONCLUSIONS: Despite the poor quality of evidence, data suggest that penile-sparing surgery is not inferior to amputative surgery in terms of recurrence rates in selected patients. Based on the available information, however, broadly applicable recommendations cannot be made; appropriate patient selection accounts for the relative success of all the available methods. PATIENT SUMMARY: We reviewed the evidence of various techniques to treat penile tumor and assessed their effectiveness in oncologic control and their functional outcomes. Penile-sparing as well as amputative surgery is an effective treatment option, but amputative surgery has a negative impact on sexual function. Penile-sparing surgery and radiotherapy are associated with a higher risk of local recurrence, but preserve sexual function and quality of life better. Laser and Moh's micrographic surgery could be used for smaller lesions

Management of Lymph Node-positive Penile Cancer: A Systematic Review.

CONTEXT: Lymph node (LN) involvement in penile cancer is associated with poor survival. Early diagnosis and management significantly impact survival, with multimodal treatment approaches often considered in advanced disease. OBJECTIVE: To assess the clinical effectiveness of treatment options available for the management of inguinal and pelvic lymphadenopathy in men with penile cancer. EVIDENCE ACQUISITION: EMBASE, MEDLINE, the Cochrane Database of Systematic Reviews, and other databases were searched from 1990 to July 2022. Randomised controlled trials (RCTs), nonrandomised comparative studies (NRCSs), and case series (CSs) were included. EVIDENCE SYNTHESIS: We identified 107 studies, involving 9582 patients from two RCTs, 28 NRCSs, and 77 CSs. The quality of evidence is considered poor. Surgery is the mainstay of LN disease management, with early inguinal LN dissection (ILND) associated with better outcomes. Videoendoscopic ILND may offer comparable survival outcomes to open ILND with lower wound-related morbidity. Ipsilateral pelvic LN dissection (PLND) in N2-3 cases improves overall survival in comparison to no pelvic surgery. Neoadjuvant chemotherapy in N2-3 disease showed a pathological complete response rate of 13% and an objective response rate of 51%. Adjuvant radiotherapy may benefit pN2-3 but not pN1 disease. Adjuvant chemoradiotherapy may provide a small survival benefit in N3 disease. Adjuvant radiotherapy and chemotherapy improve outcomes after PLND for pelvic LN metastases. CONCLUSIONS: Early LND improves survival in nodal disease in penile cancer. Multimodal treatments may provide additional benefit in pN2-3 cases; however, data are limited. Therefore, individualised management of patients with nodal disease should be discussed in a multidisciplinary team setting. PATIENT SUMMARY: Spread of penile cancer to the lymph nodes is best managed with surgery, which improves survival and has curative potential. Supplementary treatment, including the use of chemotherapy and/or radiotherapy, may further improve survival in advanced disease. Patients with penile cancer with lymph node involvement should be treated by a multidisciplinary team

Computing iterative roots with second order training methods

Iterative roots are a valuable tool for modeling and analyzingdynamical systems. They provide a natural way toconstruct a continuous time model from discrete time data.However, they are in most cases extremely difficult tocompute analytically. Previously we have demonstratedhow to use neural networks to calculate the iterativeroots and fractional iterations of functions. We used aspecial topology of MLPs together with weight sharing.This paper shows how adding a regularization term to theerror function can direct any backpropagation basedtraining method to the same result but in a fraction of epochswhen using advanced 2-nd order learning rules

Physics without laws - Making exact predictions with data based methods

The mathematical method of fractional or continuous iteration can be used to model a dynamical system exactly from limited experimental data. However, mathematics is complicated and exact solutions - even if proven to exist - can rarely be found analytically. We have shown previously that neural networks can be utilized to numerically compute fractional iterates of mathematical functions. In this paper we demonstrate the application of this method to the fundamental experiment of physics: The free fall

Reverse Parking of a Model Car with Fuzzy Control

. To demonstrate the application of fuzzy control for rapid prototyping and robust performance, we use a 1/10 scaled model car with an onboard microcontroller and sensors for the task of autonomous parking. There is no precise mathematical model of the car's kinematics and the controller has to cope with heavy sensor uncertainty, imprecise actuators, and a very sketchy world model. We deliberately do not use any learning approaches, but express the knowledge on how to park a car in the form of fuzzy rules. To solve the parking problem, the system architecture has to handle the interaction of several fuzzy as well as conventional modules performing various subtasks. 1. Introduction The problem of reverse parking has been the subject of several research projects in the field of classical control as well as Fuzzy Control theory. Classical approaches as in [1], [3] and [6] are based on an exact mathematical model of the system to be controlled, i.e. the car or the truck-trailer combinatio..

Bringing robotics closer to students - a threefold approach

In this paper, we present our threefold concept of "bringing robotics closer to students". Our efforts begin with motivating high-school students to study engineering sciences by increasing their interest in technical issues. This is achieved by a national robotics contest. Besides our work with high-school students, we also focus on projects for undergraduate university students. Several robotics projects and competitions are included into the curriculum of electrical and mechanical engineering and computer science. These projects offer chances to do special assignments and student research projects. It may be important to point out that most of the work described in this paper, including inventing and specifying the projects and organizing the events, has been done by undergraduate and graduate student

RoboKing - Bringing robotics closer to pupils

In this paper, we introduce RoboKing, a national contest of mobile autonomous robots, dedicated to teams of high school students. RoboKing differs from similar contests by supporting the participating teams with a 250 Euro voucher and by not restricting the kind of materials the robots can be build with. Its task is manageable for students without previous knowledge in robotics but offers enough complexity to be challenging for advanced participants. The first RoboKing contest with 12 participating teams from different parts of Germany took place at the Hannover Messe in 2004. Because of its great success, RoboKing will be held annually. RoboKing 2005 has been extended to 20 teams of pupils and offers a new challenging task. More pictures and video files can be found under www. roboking. de

A Comparison of Different Neural Methods for Solving Iterative Roots

Finding iterative roots is the inverse problem of iteration.Iteration itself plays a major role in numerous theoriesand applications. So far it is hardly realized how manyproblems can be related to its counterpart. This may bedue to the difficulty of the mathematics involved: Thereare no standard methods available for computing thesefractional iterations.Previously we have shown how neural networks can beutilized to perform calculations of iterative roots by addinga weight coupling mechanism to backpropagationlearning. Here we show that an easier implementation ofthis functionality can be achieved by a simple weightcopy function. Introducing second order methods likequasi Newton learning on the other hand can significantlyreduce training times and improve the reliability of themethod. It also overcomes some limitations in the complexityof the problems the method can be applied to