Parameter optimization of H∞ controller designed for tumor growth in the light of physiological aspects

According to the fact that cancer diseases are leading causes of death all around the world, development of cancer fighting therapies is necessary. Beside the medical knowledge, there is an extra need for engineering approach to solve this complex problem. The aim of this paper is to design controller for tumor growth under angiogenic inhibition, which on the one hand minimizes the input signal as far as possible (in order to have less side effects and greater cost-effectiveness) and on the other hand results in appropriately low tumor volume. Since the model contains uncertainties and measurement noise, the controller was designed using modern robust control methodology. Choosing of the ideal system and the weighting functions were done in the light of physiological aspects

Potential Benefits of Discrete-Time Controllerbased Treatments over Protocol-based Cancer Therapies

In medical practice, the effectiveness of fighting cancer is not only determined by the composition of the used drug, but determ ined by the administration method as well. As a result, having drugs with a suitable action profile is just a promising beginning, but without appropriate delivery method s , the therapy still can be ineffective. Finding the optimal biologic dose is an empir ical process in medical practice; however, using controllers, an automated optimal administration can be determined . In this paper , we evaluate the effectiveness of different drug delivery protocols; using in silico simulations (like bolus dose s, low - dose metron omic regimen and continuous infusion therapy ). In addition, we compare these results with discrete - time controller - based treatments containing state feedback, setpoint control, actual state observer and load estimation

Stable Hybrid Fuzzy Controller-based Architecture for Robotic Telesurgery Systems

Robotic surgery and remotely controlled teleoperational systems are on the rise. However, serious limitations arise on both the hardware and software side when traditional modeling and control approaches are taken. These limitations include the incomplete modeling of robot dynamics, tool–tissue interaction, human– machine interfaces and the communication channel. Furthermore, the inherent latency of long-distance signal transmission may endanger the stability of a robot controller. All of these factors contribute to the very limited deployment of real robotic telesurgery. This paper describes a stable hybrid fuzzy controller-based architecture that is capable of handling the basic challenges. The aim is to establish high fidelity telepresence systems for medical applications by easily handled modern control solution

Robust Fixed Point Transformations-based Control of Chaotic Systems

Nowadays, nonlinear control is a very important task because machines are playing more and more role in life. Lyapunov's 2nd method is a popular tool by the use of which various controllers can be designed like the adaptive Neural Networks, Fuzzy Controllers, and Neuro-Fuzzy solutions, or the Sliding Mode Controllers and the well-known PID feedback controllers. Robust Fixed Point Transformation is a procedure which can be built for almost any type of controller in case an approximate model is used to estimate the controlled system's behavior. In this paper a new approach to Robust Fixed Point Transformations (RFPT) is introduced by integrating a second controller in the system. Authors show that this additional, "recalculated" controller not just improves the original controller's results, but halves the tracking errors achieved by the previous RFPT methods

Imaging time series for the classification of EMI discharge sources

In this work, we aim to classify a wider range of Electromagnetic Interference (EMI) discharge sources collected from new power plant sites across multiple assets. This engenders a more complex and challenging classification task. The study involves an investigation and development of new and improved feature extraction and data dimension reduction algorithms based on image processing techniques. The approach is to exploit the Gramian Angular Field technique to map the measured EMI time signals to an image, from which the significant information is extracted while removing redundancy. The image of each discharge type contains a unique fingerprint. Two feature reduction methods called the Local Binary Pattern (LBP) and the Local Phase Quantisation (LPQ) are then used within the mapped images. This provides feature vectors that can be implemented into a Random Forest (RF) classifier. The performance of a previous and the two new proposed methods, on the new database set, is compared in terms of classification accuracy, precision, recall, and F-measure. Results show that the new methods have a higher performance than the previous one, where LBP features achieve the best outcome

Tumor Volume Estimation and Quasi- Continuous Administration for Most Effective Bevacizumab Therapy

Bevacizumab is an exogenous inhibitor which inhibits the biological activity of human VEGF. Several studies have investigated the effectiveness of bevacizumab therapy according to different cancer types but these days there is an intense debate on its utility. We have investigated different methods to find the best tumor volume estimation since it creates the possibility for precise and effective drug administration with a much lower dose than in the protocol.We have examined C38 mouse colon adenocarcinoma and HT-29 human colorectal adenocarcinoma. In both cases, three groups were compared in the experiments. The first group did not receive therapy, the second group received one 200 μg bevacizumab dose for a treatment period (protocol-based therapy), and the third group received 1.1 μg bevacizumab every day (quasi-continuous therapy). Tumor volume measurement was performed by digital caliper and small animal MRI. The mathematical relationship between MRI-measured tumor volume and mass was investigated to estimate accurate tumor volume using caliper-measured data. A two-dimensional mathematical model was applied for tumor volume evaluation, and tumor- and therapy-specific constants were calculated for the three different groups. The effectiveness of bevacizumab administration was examined by statistical analysis.In the case of C38 adenocarcinoma, protocol-based treatment did not result in significantly smaller tumor volume compared to the no treatment group; however, there was a significant difference between untreated mice and mice who received quasi-continuous therapy (p = 0.002). In the case of HT-29 adenocarcinoma, the daily treatment with one-twelfth total dose resulted in significantly smaller tumors than the protocol-based treatment (p = 0.038). When the tumor has a symmetrical, solid closed shape (typically without treatment), volume can be evaluated accurately from caliper-measured data with the applied two-dimensional mathematical model.Our results provide a theoretical background for a much more effective bevacizumab treatment using optimized administration

Design and Implementation of a Computer-Based Power Management System

Power supply is of great importance and interrupting its supply may impact negatively on our daily activities. With the application of power management systems, the vulnerability of energy is effectively managed, thereby ensuring a smooth flow of energy requirements for domestic and industrial operations. This also reconciles efficiency, safety, economic, health and environmental conditions. Therefore, this paper presents the design, construction and implementation of a computer-based power management system for household applications. It enables the user to transfer management of supply to appliances in the house to a real time monitoring, switching and control system. This is achieved by programming an Atmega 328 microcontroller, which coordinates the overall activities of the system from a central control unit through an ESP8266 module. This wireless fidelity (Wi-Fi) module is where internally processed result is being sent to the central control unit. System design shows that the interoperability of the power management system is hinged upon a Wi-Fi as the signals are sent as packets in ASCII format from the point harnessed by the GUI software. The design was tested for performance and results show that when the power up icon is clicked on the personal computer, the bulb glows and when the power down button is clicked, the bulb goes off. Also, the measured and actual current of the transformer used in the design, justifies the efficiency of the power management system. The system design was seen to be more scalable and flexible when compared with existing home automation systems, and the hardware interface module can be handled by one server when there is Wi-Fi coverage. In conclusion, it is seen that power can be effectively managed from the personal computer, thereby reducing the overall power consumption in the facility