Non-linear model predictive control for autonomous vehicles

With the advent of faster computer processors and better optimization algorithms, Model Predictive Control (MPC) systems are more readily used for real-time applications. This research focuses on the application of MPC to trajectory generation of autonomous vehicles in an online manner. The operating environment is assumed to be unknown with various different types of obstacles. Models of simplified 2-D dynamics of the vehicle are developed, discretized and validated against a nonlinear CarSim vehicle model. The developed model is then used to predict future states of the vehicle. The relationship of the weight transfer to the tire slip angle is investigated. The optimal trajectory tracking problem is formulated in terms of a cost function minimization with constraints. Initially, a gradient descent method is used to minimize the cost function. A MATLAB based MPC controller is developed and interfaced with CarSim in order to test the controller on a vehicle operating in a realistic environment. The effects of varying MPC look-ahead horizon lengths on the computation time, simulation cost and the tracking performance are also investigated. Simulation results show that the new MPC controller provides satisfactory online obstacle avoidance and tracking performance. Also, a trajectory tracking criterion with goal point information is found to be superior to traditional trajectory tracking methods since they avoid causing the vehicle to retreat once a large obstacle is detected on the desired path. It is further demonstrated that at a controller frequency of 20Hz, the implementation is real-time implementable only at shorter horizon lengths

SAW Filter Modelling in Matlab for GNSS Receivers

Satellite navigation has enabled a great amount of new application for many users, but a lot of limitations have been observed regarding precision and integrity of navigation signals. Overall signals of different navigation systems (GPS, GALILEO, GLONASS signals) compose Global Navigation Satellite Systems (GNSS) Signal. Each of the satellite system has separate signal characteristics, but each signal needs to be compatible with the others to prevent interferences and attenuations between signals. The processing of all the signals is performed in same receiver. Hence, complex receiver design is required. In GNSS signals different frequencies are used for different satellite navigation systems such as GPS, Galileo and Glonass. When the group delay response is observed in SAW filters it shows that the signals lie on different frequencies have different delays. Manufacturers carried out measurements with respect to carrier wave but they have ignored the spreading codes or modulation. In this research, we will design a model for GNSS SAW filter in Matlab. This model can be use to obserce the delay of the signals. This model will allow the manufacturers to address these problems in the SAW filter software to optimise slope and magnitude of the design which will benefit the users of GNSS all over the world to get more precise positioning.DOI:http://dx.doi.org/10.11591/ijece.v3i5.364

Evaluation of High Speed Hardware Multipliers - Fixed Point and Floating point

There is a huge demand in high speed arithmetic blocks, due to increased performance of processing units. For higher frequency clocks of the system, the arithmetic blocks must keep pace with greater requirement of more computational power. Area and speed are usually conflicting constraints so that improving speed results mostly in larger areas. In our research we will try to determine the best solution to this problem by comparing the results of different multipliers. Different sized of two algorithms for high speed hardware multipliers were studied and implemented ie. Parallel multiplier, Bit serial multiplier. The workings of these two multipliers were compared by implementing each of them separately in VHDL. A number of high speed adder designs are developed and algorithm and design of these adders are discussed. The result of this research will help us to choose the better option between serial and parallel multipliers for both fixed point and floating point multipliers to fabricate in different systems. As multipliers form one of the most important components of many systems, analysing different multipliers will help us to frame a better system with area and better speed.DOI:http://dx.doi.org/10.11591/ijece.v3i6.418

Comparison of Erythropoietin alone with Erythropoietin plus oral Ascorbic Acid in the Treatment of Anemia in Chronic Kidney Disease Patients

Objective Of the Study:   To compare efficacy of “Oral ascorbic acid in combination with Erythropoietin”  with “standard dose of erythropoietin alone” in renal anemia in terms of mean hemoglobin rise. Introduction: Recombinant human erythropoietin (rhEPO) has a vital role in management of anemia in CKD (chronic kidney disease) patients. In the last decade, Ascorbic acid (AA) has emerged as a potential therapy to improve anemia probably by enhancing iron mobilization. We have conducted this study to compare the mean hemoglobin rise after treatment with standard dose erythropoietin alone with standard dose erythropoietin plus Oral ascorbic acid in CKD patients who were suffering from anemia. Materials & Methods: A total of 70 patients of CKD with anemia, 18 to 70 years of age of both genders were included. Patients with laboratory proven iron deficiency anemia, obvious blood loss, pernicious anemia, hyperparathyroidism and contraindications for erythropoietin or ascorbic acid treatment were excluded. The patients which were selected randomly placed in two groups. Group A (erythropoietin alone) & Group B (erythropoietin plus oral ascorbic acid), by using lottery method. Outcome variable like hemoglobin was measured at 2, 4 and 6 months. Results: Mean age was 48.90 ± 13.53 years. Male to female ratio was 1.6:1 with 43 (61.43%) males and 27 (38.57%) females. Mean pre-therapy hemoglobin  was 9.40 ± 1.03 g/dl in the Group A while it was 9.42 ± 0.98 g/dl (p-value = 0.901) in Group B and  mean post-therapy hemoglobin in the Group A was 9.34 ± 1.06 g/dl while in the Group B was 10.37 ± 1.16 g/dl with p value of 0.0002 which is statistically significant. Conclusion: The study concluded that standard dose erythropoietin plus Oral ascorbic acid in CKD anemia is more effective  as compared to erythropoietin alone. Keywords: Chronic kidney disease, Erythropoietin, Ascorbic acid, Anemia

Automatic neonatal sleep stage classification:A comparative study

Sleep is an essential feature of living beings. For neonates, it is vital for their mental and physical development. Sleep stage cycling is an important parameter to assess neonatal brain and physical development. Therefore, it is crucial to administer newborn's sleep in the neonatal intensive care unit (NICU). Currently, Polysomnography (PSG) is used as a gold standard method for classifying neonatal sleep patterns, but it is expensive and requires a lot of human involvement. Over the last two decades, multiple researchers are working on automatic sleep stage classification algorithms using electroencephalography (EEG), electrocardiography (ECG), and video. In this study, we present a comprehensive review of existing algorithms for neonatal sleep, their limitations and future recommendations. Additionally, a brief comparison of the extracted features, classification algorithms and evaluation parameters is reported in the proposed study

Development of gliclazide matrix tablets from pure and blended mixture of glyceryl monostearate and stearic acid

The present study was undertaken to evaluate the effect of glyceryl monostearate (GMS) and stearic acid (SA) on the release profile of gliclazide from the matrix. Matrix tablets for the controlled delivery of gliclazide were prepared by hot melt method using pure and blended mixture of glyceryl monostearate and stearic acid in different drug to polymer and polymer to polymer ratios. In vitro release characteristics of gliclazide from these hydrophobic matrices were studied over 8 h in phosphate buffer media of pH 7.4. The release kinetics of drug was evaluated for zero order, first order, Higuchi and Peppas kinetic models. It was observed that the release of drug from the matrix was greatly retarded by GMS and retarding effect increased with increasing polymer to drug ratios. On the other hand SA appeared to channel the drug from the wax matrix and release was greatly increased with increasing polymer to drug ratios. The kinetic evaluation of release profile indicated that the Higuchi model was the most appropriate model for describing the release profile of gliclazide. The application of Peppas biexponential equation indicated that non-Fickian release was the predominant mechanism of drug release. The FTIR results showed no interaction between the drug and the polymers and DSC results indicated that both the drug and polymers are in amorphous state and no significant complexes were formed. The results indicated that proper selection of drug to polymer and polymer to polymer ratios were important in order to achieve the desired dissolution profile in these matrix tablets.Colegio de Farmacéuticos de la Provincia de Buenos Aire

ZnO Nano-Flowers Assembled on Carbon Fiber Textile for High-Performance Supercapacitor’s Electrode

Herein, a crystalline nano-flowers structured zinc oxide (ZnO) was directly grown on carbon fiber textile (CFT) substrate via a simple hydrothermal process and fabricated with a binder-free electrode (denoted as ZnO@CFT) for supercapacitor (SC) utilization. The ZnO@CFT electrode revealed a 201 F·g−1 specific capacitance at 1 A·g−1 with admirable stability of >90% maintained after 3000 cycles at 10 A·g−1. These impressive findings are responsible for the exceedingly open channels for well-organized and efficient diffusion of effective electrolytic conduction via ZnO and CFT. Consequently, accurate and consistent structural and morphological manufacturing engineering is well regarded when increasing electrode materials’ effective surface area and intrinsic electrical conduction capability. The crystalline structure of ZnO nano-flowers could pave the way for low-cost supercapacitors

A New Ensemble-Based Intrusion Detection System for Internet of Things

The domain of Internet of Things (IoT) has witnessed immense adaptability over the last few years by drastically transforming human lives to automate their ordinary daily tasks. This is achieved by interconnecting heterogeneous physical devices with different functionalities. Consequently, the rate of cyber threats has also been raised with the expansion of IoT networks which puts data integrity and stability on stake. In order to secure data from misuse and unusual attempts, several intrusion detection systems (IDSs) have been proposed to detect the malicious activities on the basis of predefined attack patterns. The rapid increase in such kind of attacks requires improvements in the existing IDS. Machine learning has become the key solution to improve intrusion detection systems. In this study, an ensemble-based intrusion detection model has been proposed. In the proposed model, logistic regression, naive Bayes, and decision tree have been deployed with voting classifier after analyzing model’s performance with some prominent existing state-of-the-art techniques. Moreover, the effectiveness of the proposed model has been analyzed using CICIDS2017 dataset. The results illustrate significant improvement in terms of accuracy as compared to existing models in terms of both binary and multi-class classification scenarios