This letter describes a developed wireless sensor network based on a proposed algorithm for monitoring the environmental parameters in healthcare intentions. This proposed algorithm contains a frame with different pac...
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This letter describes a developed wireless sensor network based on a proposed algorithm for monitoring the environmental parameters in healthcare intentions. This proposed algorithm contains a frame with different packets that are implemented on the developed wireless sensor network. The developed wireless sensor network consists of one central node as well as four sensor node that has been equipped with various sensors such as temperature, humidity, CO, CO2, and passive infrared sensor. In order to test the presented algorithm and the developed wireless sensor network, the sensor nodes are situated in four different rooms in a hospital for recording essential parameters of the environment while the central node is put in the nurse station for warning to nurses. The obtained result of the proposed sensor nodes in comparison to gold standards shows root mean square error 1.1%, 0.35 degrees C, 0.98% for humidity, temperature and gas, respectively. Also, the obtained results illustrate that the system gives accurate feedback from environmental temperature, humidity, and CO, and CO2 to the nurse station in order to increases the possibility of a healthy environment condition for patients.
This article reports a method for the estimation of parameters of a 3D Hindmarsh Rose neural model under a noisy measurement. Estimation procedure is based on reparametrization of the 3D model in a linear form. Method...
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This article reports a method for the estimation of parameters of a 3D Hindmarsh Rose neural model under a noisy measurement. Estimation procedure is based on reparametrization of the 3D model in a linear form. Method of least square has been used to estimate the biophysical parameters of the model. It is known that the presence of unavoidable noise effects the estimation procedure. To reduce the influence of noise to a certain extent, a denoising algorithm based on local projection is considered. Estimation procedure has been derived both in noisy and denoised condition to present the effectiveness of the algorithm. The denoising technique has been applied to reduce the influence of noisy stimuli in an experimentally collected EEG data set and the results are presented in terms of reduction in variance level. The effectiveness of the method is presented using analytical/mathematical and simulation results.
In digital forensics, image tamper detection and localization have attracted increased attention in recent days, where the standard methods have limited description ability and high computational costs. As a result, t...
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In digital forensics, image tamper detection and localization have attracted increased attention in recent days, where the standard methods have limited description ability and high computational costs. As a result, this research introduces a novel picture tamper detection and localization model. Feature extraction, tamper detection, as well as tamper localization are the three major phases of the proposed model. From the input digital images, a group of features like "Scale-based Adaptive Speeded Up Robust Features (SA-SURF), Discrete Wavelet Transform (DWT) based Patched Local Vector Pattern (LVP) features, HoG feature with harmonic mean based PCA and MBFDF" are extracted. Then, with this extracted feature strain the "optimized Convolutional Neural Network (CNN)" will be trained in the tamper detection phase. Since it is the key decision-maker about the presence/absence of tamper, its weighting parameters are fine-tuned via a novel improved Sea-lion Customized Firefly algorithm (ISCFF) model. This ensures the enhancement of detection accuracy. Once an image is recognized to have tampers, then it is essential to identify the tamper localization. In the tamper localization phase, the copy-move tampers are localized using the SIFT features, splicing tampers are localized using the DBN and the noise inconsistency is localized with a newly introduced threshold-based tamper localization technique. The simulation outcomes illustrate that the adopted model attains better tamper detection as well as localization performance over the existing methods.
Due to the rapid increase in images and image data, research examining the visual analysis of such unstructured data has recently come to be actively conducted. One of the representative image caption models the Dense...
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Due to the rapid increase in images and image data, research examining the visual analysis of such unstructured data has recently come to be actively conducted. One of the representative image caption models the DenseCap model extracts various regions in an image and generates region-level captions. However, since the existing DenseCap model does not consider priority for region captions, it is difficult to identify relatively significant region captions that best describe the image. There has also been a lack of research into captioning focusing on the core areas for story content, such as images in movies and dramas. In this study, we propose a new image captioning framework based on DenseCap that aims to promote the understanding of movies in particular. In addition, we design and implement a module for identifying characters so that the character information can be used in caption detection and caption improvement in core areas. We also propose a core area caption detection algorithm that considers the variables affecting the area caption importance. Finally, a performance evaluation is conducted to determine the accuracy of the character identification module, and the effectiveness of the proposed algorithm is demonstrated by visually comparing it with the existing DenseCap model.
Compact high frequency (HF) radar using small antenna has been widely accepted in ocean surface current mapping, but is challenging in measurement of wave height, particularly wave height field, due to its broad beam....
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ISBN:
(纸本)9781538616543
Compact high frequency (HF) radar using small antenna has been widely accepted in ocean surface current mapping, but is challenging in measurement of wave height, particularly wave height field, due to its broad beam. First-order Bragg scattering theory has been explored to estimate sea state, including wind speed and wave height, from the first-order ocean echo, which provides a capability of distinguishing waves information over different directions. However, this method is troubled by the calibration of direction dependent spreading factor. A new approach is proposed by adopting a dual-frequency compact radar, and the ratio of power of Bragg resonant waves associated with two frequencies, rather than that of a single frequency, is utilized to simultaneously eliminate the effect of spreading factor and estimate wave height. In addition, direction finding algorithm such as multiple signal classification (MUSIC) is employed to obtain wave field information. Preliminary results are presented to verify the effectiveness of the proposed algorithm.
This paper presents a hybrid control approach for grasping objects by multiple agents without rebounding. When multiple agents grasp an object cooperatively, the motion of the agents is constrained due to the geometri...
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This paper presents a hybrid control approach for grasping objects by multiple agents without rebounding. When multiple agents grasp an object cooperatively, the motion of the agents is constrained due to the geometrical and frictional conditions at the contact points. In this paper, each agent acting on an object of interest is controlled by a hybrid controller which includes a position controller, a force controller, and some logic to coordinate grasping. The proposed approach provides a method to steer the agents to grasping positions on an object along appropriate directions and to asymptotically exert stabilizing forces at each contact point. The stability properties induced by the hybrid controller can be asserted using Lyapunov stability tools for hybrid systems. The set of allowed initial conditions guaranteed is characterized using sublevel sets of Lyapunov functions. The proposed algorithm is verified in simulations.
This paper presents a cuckoo search algorithm to minimize makespan for a semiconductor final testing scheduling problem. Each solution is a two-part vector consisting of a machine assignment and an operation sequence....
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This paper presents a cuckoo search algorithm to minimize makespan for a semiconductor final testing scheduling problem. Each solution is a two-part vector consisting of a machine assignment and an operation sequence. In each iteration, a parameter feedback control scheme based on reinforcement learning is proposed to balance the diversification and intensification of population, and a surrogate model is employed to reduce computational cost. According to the Rechenberg's 1/5 Criterion, reinforcement learning uses the proportion of beneficial mutation as feedback. As a result, the surrogate modeling only needs to evaluate the relative ranking of solutions. A heuristic approach based on the smallest position value rule and a modular function is proposed to convert continuous solutions obtained from Lévy flight into discrete ones. The computational complexity analysis is presented, and various simulation experiments are performed to validate the effectiveness of the proposed algorithm.
We propose a joint design of beamforming and power allocation in a downlink multiple-input multiple-output multiuser system which employs non-orthogonal multiple access (NOMA). We address a new scenario where the user...
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ISBN:
(纸本)9781509024834
We propose a joint design of beamforming and power allocation in a downlink multiple-input multiple-output multiuser system which employs non-orthogonal multiple access (NOMA). We address a new scenario where the users are divided into two groups by their quality of service (QoS) requirements, rather than the location information, such that the users in Group 1 expect to be served with the best efforts whereas the users in Group 2 require to reach target rates. For this scenario, The aim is to maximize the sum rate of the users in Group 1 while guarantee the minimum rates of the users in Group 2. We first apply the semidefinite relaxation (SDR) approach to linearize the quadratic forms of beamforming vectors, and then successively approximate the nonconvex constraints based on the arithmeticgeometric mean inequality to jointly design the beamforming matrices and power allocation. Finally, we show that the proposed algorithm achieves a profound sum rate advantage over the existing ones, and examine the impact of parameters on the convergence rate of the proposed algorithm.
It is very challenging to capture images via cell phone cameras in low-lighting conditions due to possible motion blur, especially for a high dynamic range (HDR) scene. In this paper, a new single image brightening al...
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ISBN:
(纸本)9781479999897
It is very challenging to capture images via cell phone cameras in low-lighting conditions due to possible motion blur, especially for a high dynamic range (HDR) scene. In this paper, a new single image brightening algorithm is introduced to support capturing an image with a small exposure time and a small ISO value for a low-lighting scene. There are negligible motion blur and over-exposed pixels in the captured image while both details in the darkest regions and the brightness of the image are reduced. The proposed algorithm is applied to brighten the under-exposed regions and to enhance details of the under-exposed regions with negligible increment on the brightness of the brightest areas. The proposed algorithm can also be adopted to brighten an image captured for an HDR scene at day time but with dark objects.
This paper studies the joint optimization problem of two-way relay beamforming, the receiver power splitting (PS) ratio as well as the transmit power at the sources to maximize the achievable sum-rate of a simultaneou...
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ISBN:
(纸本)9781509024834
This paper studies the joint optimization problem of two-way relay beamforming, the receiver power splitting (PS) ratio as well as the transmit power at the sources to maximize the achievable sum-rate of a simultaneous wireless information and power transfer (SWIPT) system with a full-duplex (FD) multipleinput multiple-output (MIMO) amplify and forward (AF) relay, assuming perfect channel state information (CSI). In particular, our contribution is an iterative algorithm based on the difference of convex programming (DC) and one dimensional searching to achieve the joint solution. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm.
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