Educational tool is one of the prominent solutions for aiding students to learn course material in Information Technology (IT) domain. However, most of them are not used in practice since they do not properly fit student necessity. This paper evaluates the impact of an educational tool, namely PythonTutor, for completing programming laboratory task regarding data structure materials. Such evaluation will be conducted in one semester by implementing a quasi-experimental design. As a result, six findings can be deducted which are: 1) PythonTutor might positively affect student performance when the students have used such tool before; 2) Sometimes, student perspective regarding the impact of educational tool is not always in-sync with actual laboratory result; 3) the impact of PythonTutor might be improved when similar data representation is used consequently for several weeks; 4) the correlation between the use of PythonTutor and student performance might not be significant when the control and intervened group share completely different characteristics; 5) the students might experience some difficulties when they are asked to handle a big task for the first time; and 6) the students might be able to complete a particular weekly task with a promising result if the students have understood the material well. Keywords—quasi-experimental design, empirical evaluation, program visualization, educational tool, laboratory session
Internet of Things (IOT) has found broad applications and has drawn more and more attention from researchers. At the same time, IOT also presents many challenges, one of which is node localization, i.e. how to determine the geographical position of each sensor node. Algorithms have been proposed to solve the problem. A popular algorithm is Particle Swarm Optimization (PSO) because it is simple to implement and needs relatively less computation. However, PSO is easily trapped into local optima and gives premature results. In order to improve the PSO algorithm, this paper proposes the EHPSO algorithm based on Novel Particle Swarm Optimization (NPSO) and Hybrid Particle Swarm Optimization (HPSO). The EHPSO algorithm applies the principle of best neighbor of each particle to the HPSO algorithm. Simulation results indicate that EHPSO outperforms HPSO and NPSO in evaluating accurate node positions and improves convergence by avoiding being trapped into local optima.
In Rechargeable Wireless Sensor Networks(R-WSNs), it is critical for data collection because a sensor has to operate in a very low and dynamic duty cycle owing to sporadic availability of energy. In this work, we propose a distribute maximum rate allocation based on data aggregation to compute an upper data generation rate by maximizing it as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. The resulting algorithms are guaranteed to converge to an optimal value with low computational complexity. Through extensive simulation and experiments, we demonstrate our algorithm is efficient to maximize data collection rate in rechargeable wireless sensor networks.
Energy is a key factor that affects the lifetime of wireless sensor network (WSN). This paper proposes an adaptive energy management model to improve the energy efficiency in WSN. Unlike existing clustering routing protocols, the overall performance indicators are introduced as the inputs of fuzzy logic control (FLC). Meanwhile, the probability adjustment value, as the out of FLC, is fed back to the network for the generation of new clusters. Since the design of membership functions (MFs) of FLC has a significant impact on system performance, a particle swarm optimization (PSO) algorithm is used to optimize MFs and its optimization goal is to reduce the number of dead nodes and increase the remaining energy level in WSN. Simulation experiments were conducted for the low energy adaptive clustering hierarchy protocol (LEACH), the conventional FLC, FLC using genetic algorithm (GA), and FLC using PSO. The results show that the proposed FLC-PSO has the best performance among the four protocols and it can be used efficiently in energy management of WSN.
To explore the security mechanism of the Internet of Things (IoT) perception environment, we perform a security research on the IoT on the basis of game algorithm. The dynamic game method of node cooperation is used in the experiments. Firstly, multiple report nodes are merged into a game party, and the dynamic game for two parties is established with the detection node. In the environment where the malicious nodes are dominant, the detection nodes collaborate, and the state of the unknown nodes is conjectured by the reputation value of the reporting nodes. The high trust reference report is used for the modification and reduction the weight of malicious nodes in the overall report, for node merging, and finally for bias equilibrium. The results show that cooperative game can significantly improve the success rate of incident monitoring and reduce the number of forged reports.
This paper aims to create a desirable positioning method for nodes in wireless sensor networks (WSNs). For this purpose, a source node positioning algorithm was developed based on time-of-arrival (TOA), in view of the nonlinear correlation between the measured values and unknown parameters in the observation equation of TOA source position. Several experiments were carried out to evaluate the performance of the proposed algorithm in terms of time measurement error, computing complexity, location error and Cramér–Rao lower bound (CRLB). The results show that the CRLB acquired by this algorithm can be used for WSN node positioning, provided that the independent zero mean Gauss measurement error is sufficiently small. The research findings lay a solid technical basis for optimal management, load balance, efficient routing, and automatic topology control of WSNs.
A new method for the realistic visualization of virtual cables in a 2D environment, which is representing a 3D virtual reality, is presented in this paper. They are described with two consecutive cubic Bezier curves, whose common point is movable. Experiment was carried out and the optimal proportions for the parameters of the curves were obtained in order to achieve a realistic representation of cables. The suggested method has been developed for and implemented in the Engine for Virtual Electrical Engineering Equipment. The obtained results show that it is easy to manipulate the route of the virtual cables in 2D space and that they look realistic for any position of the control point.
A new routing rule detection and identity authentication mechanism based on the path sequence is proposed to cope with the vulnerability problem of wireless sensor networks (WSNs) against various attacks, especially in unattended environments. Then, the great permutation encryption algorithm (G-PEC) for WSN is proposed. Finally, a signature scheme against pollution attack based on linear network coding is improved. The results show that the proposed path sequence-based authentication method with the Contiki simulation platform can significantly reduce the computing overhead of sensor nodes and decrease the energy consumption and delay of nodes to a greater extent than the traditional authentication method. The G-PEC can effectively resist eavesdropping attack, and the new signature scheme does not need additional secure channels. The proposed mechanism also provides source message authentication.
Model driven approach has been introduced to deal with challenges of business and technology. This approach provides tools and elements that permit defining high abstraction level models and metamodels with their transformation to automate code generation. Besides, emotional tests have been introduced to help managing behaviors and relationships between individuals through Emotional Quotient (EQ). In this paper, we propose a model driven approach to generate an emotional intelligence test platform by proposing new CIM metamodel and transformations to generate the PIM as a Class Diagram. We present also a case study that shows how our proposed approach helps generating a class diagram automatically starting from a single input model. This generated model can be easily used to generate the application code.
To study the application of wireless sensor in the ship dynamic positioning system, the distributed fusion function model and structure model of wireless sensor network were set up. Using the DJC model-based SVM prediction algorithm, the quadratic optimal performance index in ship dynamic positioning MPC control was solved and the optimal control thrust was obtained. According to the classic cluster routing protocol, a data fusion structure based on residual energy and dormancy scheduling mechanism was proposed. The results showed that the proposed routing protocol based on the residual energy and sleep scheduling mechanism data fusion structure was superior to the Leach protocol. It improved the real-time performance of data transmission. Thus, the network data fusion structure achieves the goal of energy balance. The energy consumption is reduced to a certain extent and the design is reasonable.
The evaluation of physical education (PE) multimedia teaching refers to the prediction of physical education multimedia teaching quality in the absence of initial multimedia teaching information. Therefore, the evaluation method of PE multimedia teaching based on unsupervised feature learning has achieved good performance. But, its quality prediction accuracy decreases significantly with the reduction of the feature dimension. In order to overcome this defect, the author combines the active learning strategy with the unsupervised feature learning and proposes a kind of data assimilation framework to improve the discriminability of the representation of teaching features. The results show that the proposed method can enhance the accuracy of teaching quality prediction by 8%. Experiments show that, when feature dimension is relatively low, the proposed method can improve the teaching quality prediction accuracy by 8% compared with the method based on unsupervised feature learning. At the same time, the performance of the proposed method is superior to that of the other physical education multimedia teaching evaluation methods at present.
A method based on improved fuzzy theory of evidence was presented to solve the problem that there exist all kinds of uncertainty in the process of information security risk assessment. The hierarchy model for the information systems risk assessment was established firstly, and then fuzzy sets were introduced into theory of evidence. The basic probability assignments were constructed using the membership function of fuzzy sets, and the basic probability assignments were determined. Moreover, weight coefficients were calculated using entropy weight and empirical factor, which combined the objective weights with the subjective ones, and improved the validity and reliability. An illustration example indicates that the method is feasible and effective, and provides reasonable data for constituting the risk control strategy of the information systems security.
With the resolution of remote sensing images is getting higher and higher, high-resolution remote sensing images are widely used in many areas. Among them, image information extraction is one of the basic applications of remote sensing images. In the face of massive high-resolution remote sensing image data, the traditional method of target recognition is difficult to cope with. Therefore, this paper proposes a remote sensing image extraction based on U-net network. Firstly, the U-net semantic segmentation network is used to train the training set, and the validation set is used to verify the training set at the same time, and finally the test set is used for testing. The experimental results show that U-net can be applied to the extraction of buildings.
The AC servo system of hydraulic excavator dynamic simulation test system is studied in this paper.The AC servo controller based on C8051F410 on-chip system is designed in this paper. The dynamic characteristics of AC servo are tested and the fault treatment measures of AC servo controller are improved. Comparison between traditional PID and improved PID algorithm in AC Servo Controller by dynamic Simulation Test system, the improved PID algorithm suitable for dynamic simulation test system is obtained, and the response characteristics of the improved PID algorithm to AC servo system are tested. At the same time, the reliability of AC servo controller is tested.
Due to low communication costs and convenient deployment, wireless sensor network has been widely applied in various fields. However, it still has some problems in the defence against selective forwarding attacks. To address these problems, this paper proposes a model against selective forwarding attacks, which is built on the threshold secret sharing mechanism and adopts the individualized path routing protocol. Through simulation test, this paper studies the effects of attack intensity on the successful transmission rate and communication load under the same network deployment and communication topology but at different node densities and average neighbourhood degrees. The results show that this model can effectively defend against forwarding attacks, also saves communication resource, offering a technical reference for similar studies.
A sensor-fusion wearable health-monitoring system with integrated haptic feedback was previously introduced by our research group. The system's components are the following: a chest-worn device with an embedded controller board, an electrocardiogram (ECG) sensor, a temperature sensor, an accelerometer, a vibration motor, a colour-changing light-emitting diode (LED) and a push-button. This multi-sensor device makes possible to collect biometric and medical monitoring data from its wearer. The data provide a real-time indication of the wearer's health state and can also be further analysed later for medical diagnosis. The embedded vibration motor can actuate distinctive haptic feedback patterns according to the wearer's health state. The embedded colour-changing LED provides the wearer with an additional intuitive visual feedback of the current health state, and the wearer can report a potential emergency condition by using the push-button. In this paper, a conceptual case study is presented concerning possible applications for the health monitoring of elderly people in smart cities. The proposed system aims at reducing risk by assessing individual and overall potentially-harmful situations. A data collection and analysis are also presented to demonstrate that the system can provide compelling vibrotactile feedback.
The traditional fire drill is difficult, high cost, poor effect etc. in variety of fire scene simulation; a new fire drill platform combined Somatosensory camera Kinect and VR can achieve self-construction and virtual simulation fire drill based on somatosensory interaction; the platform achieves interaction between human and the 3D objects in virtual simulation environment, 3D modeling, scene building with Unity, identified human skeletal by Kinect, and using Euclidean distance matching recognition algorithm for body movements, and finally realizes the evaluation of fire drills.; the platform shows that the system has important practical significance and use value in fire drills, fire safety teaching and other aspects.
This paper aims to accurately locate underground personnel in coal mines. For this purpose, an underground personnel positioning platform was established on the wireless sensor network (WSN). Specifically, the ultra-wide band (UWB) and the time difference of arrival (TDOA) positioning algorithm were introduced briefly, in view of the underground operation environment. Then, the underground operator monitoring platform was developed based on UWB-WSN and compared it with different positioning techniques through experiments. The results show that the proposed platform achieved a high positioning accuracy and satisfied the needs of real-time monitoring of underground personnel. The research findings shed new light on the mitigation of personnel and property losses in coal mine accidents.
The focus of this paper is to find a robust power control strategy with uncertain noise plus interference (NI) in cognitive radio networks (CRNs)in an under orthogonal frequency-division multiplexing (OFDM) framework. The optimization problem is formulated to maximize the data rate of secondary users (SUs) under the constraints of transmission power of each SU, probabilistic the transmit rate of each SU at each subcarrier and robust interference constraint of primary user. In consideration of the feedback errors from the quantization due to uniform distribution, the probabilistic constraint is transformed into closed forms. By using Lagrange relaxation of the coupling constraints method and subgradient iterative algorithm in a distributed way, we solve this dual problem. Numerical simulation results show that our proposed algorithm is superior to the robust power control scheme based on interference gain worst case approach and non-robust algorithm without quantization error in perfect channels in the improvement of data rate of each SU, convergence speed and computational complexity.
Researchers propose new algorithm to monitor fatigue of driver by tracking the movements of the eyes. This can classify the opening and closing eyes by using Haar-Like Features and Region of Interest techniques. The fatique can be classified by decision tree classification. The system works in real time and sends message to the mobile phone to alert the driver via Line Application. The results showed that the program can detect face and classify opening and closing eyes accurately at 99.93 percent in which it yielded higher accuracy than other algorithms.
