Current Issue : January - March Volume : 2019 Issue Number : 1 Articles : 5 Articles
In recent years, weigh-in-motion systems based on embedded sensor networks have\nreceived a lot of attention. However, how to improve the accuracy of multi-sensor weigh-in-motion\n(WIM) systems while keeping costs low remains a challenge. In this paper, a numerical simulation\nmethod is presented to analyze the relationship between sensor location and the accuracy of static\nweight estimation. The finite element model of a WIM system is developed, which consists of\nthree parts: a pavement model, a moving load model and two types of sensor models. Analysis of\nsimulation results shows that the ability of sensing dynamic load is closely related to the installation\ndepth of sensors and pavement material. Moreover, the distance between the moving wheel and\nsensors has a great impact on estimating performance. Gaussian curve fitting could be used to reduce\nweighing error within a limited range. Our work suggests that much more attention should be paid\nto the design of the sensor layout of a WIM system....
Developing the formal model based on the Event-B design pattern is an excellent method to improve the development efficiency\nof the embedded control system and improve the reusability of the formal model. However, the instantiation of the Event-B design\npattern requires themanual writing of a large number of model codes, which brings a great deal of learning cost and coding burden\nto the engineering staff. In this paper, we propose a modelling approach for formal development of control systems based on the\napplication of iUML-B state machine patterns to model the four synchronization patterns of the typical control system. Then,we use\nthe instantiation of iUML-B pattern state machine to establish a typical multilevel control system's Event-B model.The simulation\nresults show that the event trace of the model obtained using our method is the same as that of the corresponding model obtained\nusing the traditional Event-B design pattern.Compared with the traditional Event-B design pattern method, our method can greatly\nreduce the manual coding burden in the modelling process. The system model expressed using the iUML-B pattern state machine\ncan be easily mapped to the labelled transition system so as to verify the behavioural properties of the model....
Diabetes has become a chronic metabolic disorder, and the growing diabetes population\nmakes medical care more important. We investigated using a portable and noninvasive contact lens as\nan ideal sensor for diabetes patients whose tear fluid contains glucose. The key feature is the reversible\ncovalent interaction between boronic acid and glucose, which can provide a noninvasive glucose\nsensor for diabetes patients. We present a phenylboronic acid (PBA)-based HEMA contact lens that\nexhibits a reversible swelling/shrinking effect to change its thickness. The difference in thickness can\nbe detected in a picture taken with a smartphone and analyzed using software. Our novel technique\noffers the following capabilities: (i) non-enzymatic and continuous glucose detection with the contact\nlens; (ii) no need for an embedded circuit and power source for the glucose sensor; and (iii) the use\nof a smartphone to detect the change in thickness of the contact lens with no need for additional\nphoto-sensors. This technique is promising for a noninvasive measurement of the glucose level and\nsimple implementation of glucose sensing with a smartphone....
In recent years, with an increase in the use of smartwatches among wearable devices,\nvarious applications for the device have been developed. However, the realization of a user interface\nis limited by the size and volume of the smartwatch. This study aims to propose a method to classify\nthe userâ??s gestures without the need of an additional input device to improve the user interface.\nThe smartwatch is equipped with an accelerometer, which collects the data and learns and classifies\nthe gesture pattern using a machine learning algorithm. By incorporating the convolution neural\nnetwork (CNN) model, the proposed pattern recognition system has become more accurate than the\nexisting model. The performance analysis results show that the proposed pattern recognition system\ncan classify 10 gesture patterns at an accuracy rate of 97.3%....
Smartphones are ubiquitously integrated into our home and work environment and users frequently use them as the portal to\ncloud-based secure services. Since smartphones can easily be stolen or coopted, the advent of smartwatches provides an intriguing\nplatform legitimate user identification for applications like online banking and many other cloud-based services. However, to\naccess security-critical online services, it is highly desirable to accurately identifying the legitimate user accessing such services and\ndata whether coming from the cloud or any other source. Such identification must be done in an automatic and non-bypassable\nway. For such applications, this work proposes a two-fold feasibility study; (1) activity recognition and (2) gait-based legitimate\nuser identification based on individual activity. To achieve the above-said goals, the first aim of this work was to propose\na semicontrolled environment system which overcomes the limitations of usersâ?? age, gender, and smartwatch wearing style. The\nsecond aim of this work was to investigate the ambulatory activity performed by any user. Thus, this paper proposes a novel system\nfor implicit and continuous legitimate user identification based on their behavioral characteristics by leveraging the sensors\nalready ubiquitously built into smartwatches. The design system gives legitimate user identification using machine learning\ntechniques and multiple sensory data with 98.68% accuracy....
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