Manhours estimation and automatic approval plays an important role in project scheduling and reducing the development cost for factory. Traditional approaches usually have some limitations, such as technical text form...
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Manhours estimation and automatic approval plays an important role in project scheduling and reducing the development cost for factory. Traditional approaches usually have some limitations, such as technical text formatting limitations and industry-specific limitations. This paper presents a software system that estimates the manhours and approves the technology texts that have been submitted. Firstly, we collect a technology texts dataset and complement the dictionaries. Secondly, the word2vec is used to extract the features implicated in the technology text, and a DNN (deep neural network) model is proposed to estimate the manhours. Finally, an Odoo-based software system is developed, which provides the estimation manhours and approves automatically of the submitted technology texts. The advantages of approach in which is proposed in this paper is that, it has less limitations on the format of submitted technology texts. And, it can be used for various production technology.
A novel multi-pulses technology with unequal space to enhance SNR of pulse laser radar is proposed in this letter. Traditional multi-pulses technology employing equal spaces multi-pulses always leads to many outputs o...
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ISBN:
(纸本)9781479973989
A novel multi-pulses technology with unequal space to enhance SNR of pulse laser radar is proposed in this letter. Traditional multi-pulses technology employing equal spaces multi-pulses always leads to many outputs once the time window has pulses no matter the number of pulses, which is difficult to identify which one is the main pulse we want to get. Thus we propose a method using unequal spaces multi-pulses to improve the poor performance of the equal space multi-pulses technology, which means our method will get only one pulse output when the time window has pulses input. Both simulation and experimental results show the validity of our algorithm.
We present an image registration algorithm based on the area-correlation method. Image registration is indispensable for moving target detection and tracking with the infra-red search and tracker (IRST). In our approa...
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We present an image registration algorithm based on the area-correlation method. Image registration is indispensable for moving target detection and tracking with the infra-red search and tracker (IRST). In our approach to image registration, displacements between frames are obtained using the area correlation, and then, the search image is rectified to the reference image by compensating displacements. Detection of a moving target is achieved by the frame difference method. The proposed algorithm has been tested with real image data, and we observe that the proposed algorithm is able to compensate the displacement of two images in that we get only a few detection points when we subtract two registered images.
The paper presents a new tracking scheme based on the object-strips color (OSC) feature. Firstly, the images captured by the camera are transformed into a format which is suitable for object tracking. Secondly, backgr...
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The paper presents a new tracking scheme based on the object-strips color (OSC) feature. Firstly, the images captured by the camera are transformed into a format which is suitable for object tracking. Secondly, background subtraction method is used to detect the moving object. Then the OSC feature is represented by dividing the detected object into several strips and integrating the mean hue of each strip into a one-dimensional vector. Finally, the detected object is tracked by matching the OSC features using correlation coefficient criteria. Since the OSC feature includes both color and spatial distribution information of the detected object, the proposed method is more reliable than traditional color-based tracking algorithms. Furthermore, the OSC feature, which is a one-dimensional vector, is so simple that can satisfy the real-time requirement in video surveillance easily. The experimental results show that the proposed method has a good performance for tracking objects.
Most area-defense formulations follow from the assumption that threats must first be identified and then neutralized. This is reasonable, but inherent to it is a process of labeling: threat A must be identified and th...
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Most area-defense formulations follow from the assumption that threats must first be identified and then neutralized. This is reasonable, but inherent to it is a process of labeling: threat A must be identified and then threat B, and then action must be taken. This manuscript begins from the assumption that such labeling (A & B) is irrelevant. The problem naturally devolves to one of Random Finite Set (RFS) estimation: we show that by eschewing any concern of target label we relax the estimation procedure, and it is perhaps not surprising that by such a removal of constraint (of labeling) performance (in terms of localization) is enhanced. A suitable measure for the estimation of unla-beled objects is the Mean OSPA (MOSPA). We derive a general algorithm which provided the optimal estimator which minimize the MOSPA. We call such an estimator a Minimum MOSPA (MMOSPA) estimator.
The paper focuses on a microprocessor implementation of the Hamming distance for binary correlation. It uses the fact that the binary correlation result can be derived from binary convolution (i.e., modeled with AND g...
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The paper focuses on a microprocessor implementation of the Hamming distance for binary correlation. It uses the fact that the binary correlation result can be derived from binary convolution (i.e., modeled with AND gates instead of XOR); as a result, convolution of multiple bits with multiple bits can be computed by a single multiplication instruction. This follows from a general proof for base-n convolution that is presented. Furthermore, using a hierarchical shift-addition approach, we can also reduce the number of additions in the subsequent step. The paper also shows that this approach can also be used in the frequency domain where an N/spl times/N point binary circular convolution can be modeled using an N/spl times/M double precision FFT, where M is a sub-multiple of N depending on the kernel size. Comparison of the time/frequency approaches is presented for different kernel/image sizes, with the help of benchmarking results.
This paper studies the physical layer performance of a lean carrier with reduced reference symbols and reduced control channel overhead as a possible candidate for a new 5G air interface. Specifically, we will show th...
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ISBN:
(纸本)9781479980895
This paper studies the physical layer performance of a lean carrier with reduced reference symbols and reduced control channel overhead as a possible candidate for a new 5G air interface. Specifically, we will show that, with minor modifications and optimizations, competitive link level performance can be achieved even in extreme use case scenarios using synchronization and channel estimation algorithms already employed in LTE-A. Further, we propose a set of enhancements to the broadcast channel and to the common search space configurations to fully dispense with cell specific reference symbols and legacy control channels.
The DC-DC conversion principle is a part of many electronics devices and is a subject of many research projects which are looking for the best control. In the search for the best control of a buck converter control li...
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The DC-DC conversion principle is a part of many electronics devices and is a subject of many research projects which are looking for the best control. In the search for the best control of a buck converter control line regulation should be considered in addition to load regulation. With ordinary PI controllers the dynamic response of the buck converter output voltage caused by load change is slow and exhibits large dynamic deviations from the desired steady state output value. With state space controller the dynamic response of the buck converter exhibits fast load response with small dynamic deviations from the desired steady state output value. Unfortunately dynamic response of state space controller to input voltage step change (line regulation) does not meet desired performance. It exhibits steady state error. Therefore an approach with outer PI controller in addition to the internal state space controller and disturbance observer based control approach have been considered.
This paper presents the Dual In-line Package Intelligent Power Module (DIPIPM(exp TM)) family that dedicated for Electric Vehicle (EV) and Hybrid Electric Vehicle (HEV) air-conditioner inverter drive application. The ...
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ISBN:
(纸本)9781509038442
This paper presents the Dual In-line Package Intelligent Power Module (DIPIPM(exp TM)) family that dedicated for Electric Vehicle (EV) and Hybrid Electric Vehicle (HEV) air-conditioner inverter drive application. The DIPIPM(exp TM) product family that targeted for automotive applications adopted the advanced CSTBT(exp TM) power chip technology and embedded into Mitsubishi Electric's unique insulation-sheet type transfer mold package that is capable to provide the excellent electrical characteristics and superior reliability for automotive application. By using the optimized wafer and assembly process, the DIPIPM(exp TM) achieved a package size that small enough to be able to dramatically shrink the compressor mounting space. Examples of DIPIPM(exp TM) in air-conditioner inverter drive application for electric vehicle that targeted for long drive range and heavy passenger load are introduced.
A major challenge in applying machine learning methods to Brain-Computer Interfaces (BCIs) is to overcome the on-line non-stationarity of the data blocks. An effective BCI system should be adaptive to and robust again...
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A major challenge in applying machine learning methods to Brain-Computer Interfaces (BCIs) is to overcome the on-line non-stationarity of the data blocks. An effective BCI system should be adaptive to and robust against the dynamic variations in brain signals. One solution to it is to adapt the model parameters of BCI system online. However, CSP is poor at adaptability since it is a batch type algorithm. To overcome this, in this paper, we propose the Incremental Common Spatial Pattern (ICSP) algorithm which performs the adaptive feature extraction on-line. This method allows us to perform the online adjustment of spatial filter. This procedure helps the BCI system robust to possible non-stationarity of the EEG data. We test our method to data from BCI motor imagery experiments, and the results demonstrate the good performance of adaptation of the proposed algorithm.
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