Abstract:According to the characteristics of the large time delay, nonlinearity and the great inertia of temperature control system in biomass pyrolysis reactor, a two-degree-of-freedom Smith internal model controller based on fuzzy control is proposed. Firstly, the mathematical model of the temperature control system is established by using the step response method, and then the two-degree-of-freedom Smith internal model controller is designed, and the good tracking per-formance and disturbance suppression performance can be obtained by designing the set value tracking controller and interference rejection capability. Secondly, the fuzzy control algorithm is used to realize the on-line tuning of the control parameters of the two-degree-of-freedom Smith internal model algorithm. The simulation results show that, compared with the traditional internal model control, fuzzy internal model PID control and two-degree-of-freedom Smith internal model control, the algorithm proposed in this paper improves the influence of lag time on the control system, realizes the separation control of set point tracking and anti-jamming performance and the self-tuning of control parameters, and improves the control performance of the system.

Abstract:At present online shopping is very popular as it is very convenient for the customers. However, selecting smartphones from online shops is bit difficult only from the pictures and a short description about the item, and hence, the customers refer user reviews and star rating. Since user reviews are represented in human languages, sometimes the real semantic of the reviews and satisfaction of the customers are different than what the star rating shows. Also, reading all the re-views are not possible as typically, a smartphone gets thousands of reviews in popular online shopping platform like Amazon. Hence, this work aims to develop a recommended system for smartphones based on aspects of the phones such as screen size, resolution, camera quality, battery life etc. reviewed by users. To that end we apply hybrid approach, which includes three lexicon-based methods and three machine learning modals to analyze specific aspects of user reviews and classify the reviews into six categories--best, better, good or somewhat for positive comments and for negative comments bad or not recommended--. The lexicon-based tool called AFINN together with Random Forest prediction model provides the best classification F1-score 0.95. This system can be customized according to the required aspects of smartphones and the classification of reviews can be done accordingly.

Abstract:Image registration is an important research topic in the field of computer vision, in which the registration and mosaic of side-scan sonar images is the keypoints of underwater navigation. However, the image registration method of keypoints is not suitable for sonar images which do not have obvious feature points. Therefore, a method of sonar-image regis-tration and mosaic based on line segment extraction and triangle matching is proposed in this paper. Firstly, in order to extract features from sonar image, the LSD method is introduced to detect line feature from images, and line segments are filtered by the principle of attention; after that, triangles are formed from line segments, an image transformation matrix can be calculated through the heuristic greedy algorithm from these triangles; finally, images are merged based on the transformation information. On the basis of practical tests, it is found that, the feature extraction method used in this paper can better describe the outline of underwater terrain, and there is no obvious stitching gap between the result of sonar images stitched. Experimental results show that the proposed method is effective than the keypoints method of the registration and mosaic of sonar images.

Abstract:Wearable health-monitoring devices are novel and integral developments based on smart-textiles. Conventional wearable technology consists of micro-controllers and a variety of electronic devices embedded on the skin, or in-corporated into the apparels, where they act as signal receptors, analytical devices and transmitters of the signals generated from the human body. Invasive methods are currently more commonly practiced where biofluids are obtained by penetrating the body by incision or injection, while in non-invasive methods no such penetrations take place. A critical review of current non-invasive wearable technology, including colorimetric, enzymatic, pH based, electrochemical and conductivity sensors, is presented in this paper along with the challenges and limitations they pose. Additionally, novel techniques of analysis have been explored concluding that a textile-based medium offers higher compatibility for in-tegration of such sensors in comparison to other existing substrates.

Abstract:A finite-time stabilization controller for the heating furnace temperature control system is proposed. Based on the ex-tended Lyapunov finite-time stability theory and power integral method, a finite-time stable condition of the heating furnace temperature control system is given. The temperature of the heating furnace is directed by the finite-time sta-bilization controller to make it stable in finite time. And the quality and quantity of slabs is improved. The simulation example is presented to illustrate the applicability of the developed results.

Abstract:Digital PreDistortion (DPD) is a very useful method to improve the linearity of Power Amplifiers (PAs) for LTE and upcoming 5G networks. As the spectrum resources are becoming more and more crowded, and the communications bandwidth are broader, the ACPR (Adjacent Channel Leakage Ratio) is very important to communication systems. DPD is one of the useful means for PA to reduce ACPR. This article demonstrates what DPD is and how DPD is achieved, the measurement of the Digital Distortion of a PA using a vector generator and vector analyzer, and the measurement results has been discussed.