Novel Terrain Integrated Navigation System using Neural Network aided Kalman Filter
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This document proposes a novel terrain integrated navigation system using a neural network aided Kalman filter. It combines SINS, DVL, and TAN sensors with a BP neural network and Kalman filter for underwater navigation. The neural network is trained offline to correct errors in the Kalman filter estimate arising from nonlinearities and colored noise underwater. Simulations show the approach substantially reduces AUV position error and improves underwater navigation precision.
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질문이 있으면 언제든지 연락주세요!
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Reverse Time Migration (RTM) is a powerful seismic imaging approach, widely used for migrating areas of complex structures of steep-dips and subsalt regions, despite its high computational cost. Advancing wave-field in time represents the main cost of the RTM as it is usually done by using Finite Difference (FD) to solve the wave-equation. Accuracy of the solution is subject to the approximation of the FD in both time and space.
Theoretically, waves propagate their extends to infinity or continue until vanishing. Unfortunately, this is not applicable in modelling a particular region since we truncate model to a computational grid modelling a region of interest. Absorbing all incoming energy at the boundaries of the computational grid mimics a real-life infinite media. Many approaches attempt to mimic different kinds of absorbing boundary conditions (ABC) e.g. Sponge, PML, random boundaries, etc. The objective of this study is to find the best compromise between geophysical and computational standpoint, and find the best quality of the attenuation with a minimum number of additional grid points.
We review 2 RTM implementations; the first one is using the standard approach (2 propagation with in-memory snapshots of the full wave-field with IPP compression) covering Sponge and CPML boundary conditions, while the second implementation uses random velocity boundaries that almost avoids IO but involves an extra propagation. Thereof we can balance the number of grid points in the damping area to find the best combination with respect to the computational efficiency of the RTM kernels.
Atmospheric Correction Algorithm_IGARSS.pptx
This document describes three atmospheric correction algorithms for the Geostationary Ocean Color Imager (GOCI): the Standard NASA algorithm, the Spectral Shape Matching Method (SSMM), and the Sun-Glint Correction Algorithm (SGCA). It outlines the processing steps for each algorithm, including radiometric calibration, removal of Rayleigh and aerosol scattering, and derivation of remote sensing reflectance. Validation results show SSMM and SGCA provide reasonable matches to NASA standard processing of MODIS data, though all three GOCI algorithms could be improved by updating aerosol and ocean models. The document concludes the algorithms capture the essential ocean color measurement but would benefit from further refinement.
Doppler Estimation Method of Using Frequency Channel Response for OFDM System...
This document proposes a new Doppler estimation method for OFDM systems that uses the frequency channel response (CFR) instead of the conventional method that uses the channel impulse response (CIR). The proposed method employs the autocorrelation of the estimated CFR, which can be accurately estimated even when zero-padding is used, unlike the CIR. A least squares method is then applied to the autocorrelation values to estimate the Doppler frequency. The document compares the proposed method to conventional methods through simulations, demonstrating better Doppler and C/N estimation accuracy, especially at higher Doppler spreads and lower C/N values.
UPLINK, DOWNLINK AND OVERALL LINK PERFORMANCE INTER-SATELLITE LINKS
The document discusses uplink, downlink, and intersatellite communication links. It covers key parameters like antenna configuration, gain, beamwidth, polarization, radiated power, and received signal power. The effective isotropic radiated power (EIRP) and power flux density are defined. Antenna gain is calculated using effective aperture area, which depends on the antenna diameter and efficiency. Beamwidth is specified as the 3dB width around maximum gain. Polarization is characterized by rotation, axial ratio, and ellipse inclination.
Temporal Superpixels Based on Proximity-Weighted Patch Matching
발표자: 이세호(고려대 박사과정)
발표일: 2018.4.
슈퍼픽셀 알고리즘은 입력 영상을 다수의 의미 있는 영역으로 과분할하는 기법이다. 입력 영상을 픽셀 단위로 표현할 때와 비교하여, 슈퍼픽셀 단위의 표현은 입력 영상의 단위의 수를 크게 줄이는 장점이 있어, 여러 컴퓨터 비전 기법에 전처리로 이용된다. 또한 슈퍼픽셀 알고리즘을 동영상으로 확장한 동영상 슈퍼픽셀 (temporal superpixel) 알고리즘은 동영상 기반의 컴퓨터 비전 기법에 적용될 수 있다. 기존의 동영상 슈퍼픽셀 기법은 시간적 유사성을 유지하기 위하여 움직임 정보를 이용하는데, 움직임 정보의 추출에는 많은 계산 복잡도가 요구된다. 따라서 이를 보완하기 위해, 본 연구에서는 근접성 가중치 패치 정합 (proximity-weighted patch matching) 기반의 동영상 슈퍼픽셀 기법을 제안한다.
What's hot (18)
PR-214: FlowNet: Learning Optical Flow with Convolutional Networks
PR-214: FlowNet: Learning Optical Flow with Convolutional Networks
[PR12] Making Convolutional Networks Shift-Invariant Again
[PR12] Making Convolutional Networks Shift-Invariant Again
Boundary Conditions for Seismic Imaging: Computational and Geophysical Point...
Boundary Conditions for Seismic Imaging: Computational and Geophysical Point...
Doppler Estimation Method of Using Frequency Channel Response for OFDM System...
Doppler Estimation Method of Using Frequency Channel Response for OFDM System...
UPLINK, DOWNLINK AND OVERALL LINK PERFORMANCE INTER-SATELLITE LINKS
UPLINK, DOWNLINK AND OVERALL LINK PERFORMANCE INTER-SATELLITE LINKS
Temporal Superpixels Based on Proximity-Weighted Patch Matching
Temporal Superpixels Based on Proximity-Weighted Patch Matching
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Quantum Machine Learning for IBM AI
The document discusses various machine learning algorithms that have been implemented using quantum computing techniques, including linear regression, ridge regression, perceptron, support vector machines, k-means clustering, principal component analysis, autoencoders, restricted Boltzmann machines, deep neural networks, generative adversarial networks, reinforcement learning, and Monte Carlo sampling. It also describes common quantum algorithms like quantum phase estimation, quantum amplitude estimation, quantum Fourier transform, and variational quantum algorithms. Finally, it discusses approaches for encoding classical data onto quantum states for processing, including using basis states, amplitudes, and rotation angles.
Morocco2022_LocationProblem_Bondar.pptx
This document discusses methods for locating earthquakes based on analyzing arrival times of seismic phases at stations. Accurate event location is important for various applications but also challenging due to uncertainties from measurement errors, velocity model inaccuracies, and the non-linear nature of the problem. The document reviews classical methods like Geiger's linearized inversion and also discusses more advanced non-linear techniques and using multiple events to better constrain locations. It emphasizes picking higher quality phase arrival times and using reference ground truth events to validate new location methods and velocity models.
Hands on machine learning with scikit-learn and tensor flow by ahmed yousry
Introduction to Artificial Neural Networks.
Training Deep Neural Nets.
Convolutional Neural Networks.
Recurrent Neural Network.
Reinforcement Learning.
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.pptx
EfficientNet proposes a compound scaling method that uniformly scales the width, depth, and resolution of convolutional neural networks. Prior work scaled these dimensions independently without theoretical guidance. The paper finds that balancing the scaling of width, depth, and resolution yields more efficient models. EfficientNet models outperform existing state-of-the-art models with an order of magnitude fewer parameters and floating point operations while achieving better accuracy on ImageNet and other datasets.
Fractal Antenna
This document provides an overview of fractal antennas and their advantages for wireless communications. Fractal antennas can achieve multiband operation and miniaturization by utilizing fractal geometry which increases the effective antenna length while maintaining a small size. Specific fractal designs like the Koch loop and Sierpinski monopole and dipole are discussed. Fractal antennas have the potential to develop small, low profile antennas for applications like wireless communications.
Review (1)
This document proposes a method for enhancing low-contrast satellite images using lifting wavelet decomposition, dominant brightness level analysis, and morphological edge-preserving filtering. The method decomposes input images into intensity layers, applies adaptive intensity transfer functions, performs wavelet soft thresholding on high-frequency subbands, and applies top-hat filtering to enhance edges. Performance is evaluated based on measures of enhancement and Gaussian distribution. The method aims to improve image quality with less distortion while preserving edges.
HiPEAC 2019 Workshop - Use Cases
The document describes three use cases implemented on the Tulipp embedded platform:
1) Pedestrian detection for ADAS achieving 15 frames/s with 2-3 frame latency.
2) Stereo depth estimation for UAVs performing in real-time with streaming optimization.
3) Medical image processing reducing radiation dose by 4x and enhancing images at 30 frames/s.
The Tulipp tools and SDSoc/Vivado HLS were used to implement algorithms from C/C++ onto the FPGA-based platform while addressing challenges of memory, streaming, and hardware-suitability. Overall, the Tulipp platform performed well across different applications with high-level development.
MAVMeetup - All About GPS
The document provides an overview of GPS (Global Positioning System) including:
- How GPS works using trilateration of signals from multiple satellites to determine position.
- Sources of error and techniques to improve accuracy like carrier phase tracking, real-time kinematics, and inertial navigation.
- Challenges including issues in urban areas with multipath and lack of satellite visibility, and potential interference or spoofing of signals.
- Common uses of GPS and factors affecting its accuracy.
Neural network for black-box fusion of underwater robot localization under un...
This document proposes a neural network architecture called B-PR-F for fusing redundant location estimates from sensors on underwater robots operating in unmodeled noise conditions. B-PR-F models the underwater environment and sensor behaviors, uses contextual anticipation to predict sensor deviations, evaluates sensor reliability, and fuses estimates with weighted sums. Simulations in Gazebo demonstrate how B-PR-F can eliminate noise from virtual sensors by incorporating behavioral context and ordered neighborhood relationships between estimates. Experimental results show B-PR-F outperforms Kalman filters for localizing an underwater robot using sonar and DGPS sensors.
[Q-tangled 22] Deconstructing Quantum Machine Learning Algorithms - Sasha Laz...
[Q-tangled 22] Deconstructing Quantum Machine Learning Algorithms - Sasha Laz...DataScienceConferenc1
Quantum machine learning is one of the promising application domains of quantum computing, which is expected to improve and accelerate the most resource-intensive machine learning calculations. This talk will explain how we implement quantum machine learning algorithms, what are the limits and challenges, and how these challenges can be addressed.EC6602 - AWP UNI-4
This document discusses different types of antennas and their characteristics, including whips, loops, helicals, Yagis, log periodic, horns, and parabolic antennas. It also covers topics like antenna radiation pattern measurement systems, gain and loss calculations, antenna design considerations, and the differences between EIRP and ERP.
SPECFORMER: SPECTRAL GRAPH NEURAL NETWORKS MEET TRANSFORMERS.pptx
This document presents Specformer, a novel Transformer-based spectral graph neural network. Specformer uses a Transformer to encode eigenvalues of the graph Laplacian into representations that capture magnitude and relative differences. It then applies self-attention to learn relationships between eigenvalues. Specformer decodes the eigenvalue representations using learnable bases to perform graph convolutions. Experiments show Specformer outperforms other GNNs on node and graph classification tasks and learns meaningful patterns in the graph spectrum.
SPICE-MATEX @ DAC15
1. The document proposes an algorithmic framework for large-scale circuit simulation using exponential integrators. It uses exponential Rosenbrock methods and an invert Krylov subspace approach to efficiently compute the matrix exponential-vector product to solve the circuit equations explicitly without needing Newton-Raphson iterations.
2. The framework was shown to accurately simulate benchmark circuits while achieving speedups over traditional approaches. It can handle large-scale, strongly coupled circuits that traditional methods have difficulty with.
3. Future work includes exploring parallelization opportunities to further accelerate the method using multicore/many-core systems and developing additional tools based on the proposed derivatives-based approach.
Exploring Simple Siamese Representation Learning
This document discusses an unsupervised representation learning method called SimSiam. It proposes that SimSiam can be interpreted as an expectation-maximization algorithm that alternates between updating the encoder parameters and assigning representations to images. Key aspects discussed include how the stop-gradient operation prevents collapsed representations, the role of the predictor network, effects of batch size and batch normalization, and alternatives to the cosine similarity measure. Empirical results show that SimSiam learns meaningful representations without collapsing, and the various design choices affect performance but not the ability to prevent collapsed representations.
nural network ER. Abhishek k. upadhyay
Here is a Python program to train and simulate a neural network with 2 input nodes, 1 hidden layer with 3 nodes, and 1 output node to perform an XOR operation:
```python
import numpy as np
# Network parameters
num_input = 2 # Input nodes
num_hidden = 3 # Hidden layer nodes
num_output = 1 # Output node
# Training data
X = np.array([[0,0], [0,1], [1,0], [1,1]])
y = np.array([[0], [1], [1], [0]])
# Initialize weights randomly with mean 0
hidden_weights = 2*np.random.random((num_
Digial instrumentation fnal
Digital Instrumentation
The document discusses digital instrumentation and data acquisition systems. It covers topics like analog and digital signals, data sampling, the sampling theorem, anti-aliasing, sample and hold circuits, data acquisition systems, and interfacing with computers. Key points include:
- Analog signals are continuous while digital signals are discrete. Sampling converts a continuous signal to a discrete one.
- The sampling theorem states the sampling rate must be at least twice the highest frequency component to avoid aliasing.
- Sample and hold circuits create and store samples of an input voltage to digitize analog signals for data conversion.
- Data acquisition systems collect data from sensors, condition signals, convert to digital, and transfer to computers or
unit_5 ppt DIRECT BROADCAST SATELLITE.pptx
The document discusses satellite navigation systems and direct broadcast satellite technology. For satellite navigation, the key benefits are enhanced safety, increased capacity, and reduced delays. Direct broadcast satellites provide audio, video, television and internet services directly to homes. They operate in the Ku band and use techniques like MPEG compression, forward error correction, and circular polarization of signals to transmit multiple channels via each transponder.
Traversing Notes |surveying II | Sudip khadka
Traverse is a method in the field of surveying to establish control networks. It is also used in geodesy. Traverse networks involve placing survey stations along a line or path of travel, and then using the previously surveyed points as a base for observing the next point
ct image quality
Scanner B has a higher MTF curve across all spatial frequencies compared to Scanner A. This indicates that Scanner B is able to resolve higher spatial frequencies more accurately, meaning it has better spatial resolution than Scanner A.
Statistical learning approach for estimating water quality parameters
This document summarizes a study that used statistical learning methods to estimate water quality parameters like chlorophyll-a from remote sensing data. Support vector regression (SVR) with a radial basis function kernel performed best with a mean squared error of 0.14. Random forest and decision tree models also yielded good results. Multiple linear regression did not capture the nonlinear relationships in the data as well. The results demonstrate the potential of using satellite imagery and statistical learning to monitor water quality over large areas.
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Hands on machine learning with scikit-learn and tensor flow by ahmed yousry
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EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.pptx
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SPECFORMER: SPECTRAL GRAPH NEURAL NETWORKS MEET TRANSFORMERS.pptx
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Statistical learning approach for estimating water quality parameters
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8x3x8 Multi layer perceptron training using Python Code
The document describes implementing an 8x3x8 multilayer perceptron neural network in Python to classify 8 input patterns into 8 target classes, as the single perceptron cannot perform this non-linear separation. It presents the Python code to define the neural network architecture, initialize weights randomly, then train the network over 5000 iterations by propagating errors backwards to update the weights between the input, hidden, and output layers. After training, the network is tested on each input pattern and the resulting classification output is printed.
Perceptrons
Perceptrons are a type of artificial neural network where each unit is called a perceptron. Perceptrons take a vector of inputs and can only deal with linearly separable functions like AND and OR, but not XOR. The perceptron training rule modifies weights at each step according to the error between the target and actual output. If there is no error, the weights are not updated. Gradient descent was introduced to handle non-linearly separable functions by finding weights for the best fit without a threshold, by minimizing the squared error over all training examples through iterative weight updates in the direction of steepest descent. The delta rule for gradient descent is similar to the perceptron rule but uses the linear unit output rather than the
weights training of perceptron (using 3 training rules)
This document summarizes and provides code examples for 3 training algorithms for a single unit perceptron: 1) Perceptron training rule, 2) Gradient descent (delta) rule, and 3) Stochastic gradient descent rule. For each algorithm, it provides a brief description, Python code to implement the algorithm, and a conclusion. The code examples demonstrate how to train a perceptron on sample input data to classify it accurately according to given targets, for each of the 3 training algorithms.
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2) The basic structure of a power diode includes a diode chip and connections for series or parallel configurations.
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Novel Terrain Integrated Navigation System using Neural Network aided Kalman ...
This document compares different methods for predicting corrections for differential GPS (DGPS) positioning errors over time, including neural networks, fuzzy neural networks, and Kalman filters. It introduces DGPS and the need to model time-varying errors, describes the error sources in GPS positioning, and discusses using predictors trained on past errors to estimate future corrections. It then outlines three methods for correction prediction: recurrent neural networks, which can model dynamic systems; fuzzy neural networks, which combine fuzzy and neural network techniques; and Kalman filters. The document provides more detail on recurrent neural networks, describing their training process.
novel approach for charger of electrical vehicle
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IMU and LiDar vision system using Neural network
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why and where use Advance power electronics design
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一比一原版(uoft毕业证书)加拿大多伦多大学毕业证如何办理
原版一模一样【微信：741003700 】【(uoft毕业证书)加拿大多伦多大学毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
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校名:学校英文全称
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毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理(uoft毕业证书)加拿大多伦多大学毕业证【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
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Null Bangalore | Pentesters Approach to AWS IAM
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Applications of artificial Intelligence in Mechanical Engineering.pdf
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Accident detection system project report.pdf
The Rapid growth of technology and infrastructure has made our lives easier. The
advent of technology has also increased the traffic hazards and the road accidents take place
frequently which causes huge loss of life and property because of the poor emergency facilities.
Many lives could have been saved if emergency service could get accident information and
reach in time. Our project will provide an optimum solution to this draw back. A piezo electric
sensor can be used as a crash or rollover detector of the vehicle during and after a crash. With
signals from a piezo electric sensor, a severe accident can be recognized. According to this
project when a vehicle meets with an accident immediately piezo electric sensor will detect the
signal or if a car rolls over. Then with the help of GSM module and GPS module, the location
will be sent to the emergency contact. Then after conforming the location necessary action will
be taken. If the person meets with a small accident or if there is no serious threat to anyone’s
life, then the alert message can be terminated by the driver by a switch provided in order to
avoid wasting the valuable time of the medical rescue team.
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering PROJECT REPORT ON SUMMER VOCATIONAL TRAINING
AT MBB AIRPORT
Blood finder application project report (1).pdf
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
一比一原版(USF毕业证)旧金山大学毕业证如何办理
原件一模一样【微信：95270640】【旧金山大学毕业证USF学位证成绩单】【微信：95270640】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：95270640】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：95270640】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份【微信：95270640】
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
办理旧金山大学毕业证毕业证学位证USF学位证【微信：95270640 】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理旧金山大学毕业证USF学位证毕业证学位证【微信：95270640 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理旧金山大学毕业证毕业证学位证USF学位证【微信：95270640 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理旧金山大学毕业证毕业证学位证USF学位证【微信：95270640 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
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Call For Paper -3rd International Conference on Artificial Intelligence Advan...
* Registration is currently open *
Call for Research Papers!!!
Free – Extended Paper will be published as free of cost.
3rd International Conference on Artificial Intelligence Advances (AIAD 2024)
July 13 ~ 14, 2024, Virtual Conference
Webpage URL: https://aiad2024.org/index
Submission Deadline: June 22, 2024
Submission System URL:
https://aiad2024.org/submission/index.php
Contact Us:
Here's where you can reach us : aiad@aiad2024.org (or) aiadconference@yahoo.com
WikiCFP URL: http://wikicfp.com/cfp/servlet/event.showcfp?eventid=180509©ownerid=171656
#artificialintelligence #softcomputing #machinelearning #technology #datascience #python #deeplearning #tech #robotics #innovation #bigdata #coding #iot #computerscience #data #dataanalytics #engineering #robot #datascientist #software #automation #analytics #ml #pythonprogramming #programmer #digitaltransformation #developer #promptengineering #generativeai #genai #chatgpt #artificial #intelligence #datamining #networkscommunications #robotics #callforsubmission #submissionsopen #deadline #opencall #virtual #conference
Unit -II Spectroscopy - EC I B.Tech.pdf
Chemical engineering and electronics engineering and chemical development of the day of the almighty paw paw paw
Assistant Engineer (Chemical) Interview Questions.pdf
These are interview questions for the post of Assistant Engineer (Chemical)
Bituminous road construction project based learning report
Road construction is not as easy as it seems to be, it includes various steps and it starts with its designing and
structure including the traffic volume consideration. Then base layer is done by bulldozers and levelers and after
base surface coating has to be done. For giving road a smooth surface with flexibility, Asphalt concrete is used.
Asphalt requires an aggregate sub base material layer, and then a base layer to be put into first place. Asphalt road
construction is formulated to support the heavy traffic load and climatic conditions. It is 100% recyclable and
saving non renewable natural resources.
With the advancement of technology, Asphalt technology gives assurance about the good drainage system and with
skid resistance it can be used where safety is necessary such as outsidethe schools.
The largest use of Asphalt is for making asphalt concrete for road surfaces. It is widely used in airports around the
world due to the sturdiness and ability to be repaired quickly, it is widely used for runways dedicated to aircraft
landing and taking off. Asphalt is normally stored and transported at 150’C or 300’F temperature
This study Examines the Effectiveness of Talent Procurement through the Imple...
In the world with high technology and fast
forward mindset recruiters are walking/showing interest
towards E-Recruitment. Present most of the HRs of
many companies are choosing E-Recruitment as the best
choice for recruitment. E-Recruitment is being done
through many online platforms like Linkedin, Naukri,
Instagram , Facebook etc. Now with high technology E-
Recruitment has gone through next level by using
Artificial Intelligence too.
Key Words : Talent Management, Talent Acquisition , E-
Recruitment , Artificial Intelligence Introduction
Effectiveness of Talent Acquisition through E-
Recruitment in this topic we will discuss about 4important
and interlinked topics which are
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
CalArts毕业证学历书【微信95270640】CalArts毕业证’圣力嘉学院毕业证《Q微信95270640》办理CalArts毕业证√文凭学历制作{CalArts文凭}购买学历学位证书本科硕士,CalArts毕业证学历学位证【实体公司】办毕业证、成绩单、学历认证、学位证、文凭认证、办留信网认证、（网上可查，实体公司，专业可靠）
(诚招代理)办理国外高校毕业证成绩单文凭学位证,真实使馆公证（留学回国人员证明）真实留信网认证国外学历学位认证雅思代考国外学校代申请名校保录开请假条改GPA改成绩ID卡
1.高仿业务:【本科硕士】毕业证,成绩单（GPA修改）,学历认证（教育部认证）,大学Offer,,ID,留信认证,使馆认证,雅思,语言证书等高仿类证书；
2.认证服务: 学历认证（教育部认证）,大使馆认证（回国人员证明）,留信认证（可查有编号证书）,大学保录取,雅思保分成绩单。
3.技术服务：钢印水印烫金激光防伪凹凸版设计印刷激凸温感光标底纹镭射速度快。
办理加利福尼亚艺术学院加利福尼亚艺术学院毕业证文凭证书流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）
-办理真实使馆公证（即留学回国人员证明）
-办理各国各大学文凭（世界名校一对一专业服务,可全程监控跟踪进度）
-全套服务：毕业证成绩单真实使馆公证真实教育部认证。让您回国发展信心十足！
（详情请加一下 文凭顾问+微信:95270640）欢迎咨询！子小伍玩小伍比山娃小一岁虎头虎脑的很霸气父亲让山娃跟小伍去夏令营听课山娃很高兴夏令营就设在附近一所小学山娃发现那所小学比自己的学校更大更美操场上还铺有塑胶跑道呢里面很多小朋友一班一班的快快乐乐原来城里娃都藏这儿来了怪不得平时见不到他们山娃恍然大悟起来吹拉弹唱琴棋书画山娃都不懂却什么都想学山娃怨自己太笨什么都不会斟酌再三山娃终于选定了学美术当听说每月要交元时父亲犹豫了山娃也说爸算了吧咱学校一学期才转
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Novel Terrain Integrated Navigation System using Neural Network aided Kalman Filter
- 1. Novel Terrain Integrated Navigation System using Neural Network aided Kalman Filter umair ali
- 2. Previous and this work • SINS/DVL • INS/GPS • SINS/GPS/DVL • SINS/TAN/DVL/MCP implemented in this paper
- 3. Why NN with KF • Kalman filter diverge from estimate and can not deal colured noise underwater • Neural Network are good with dealing non linearity (main point is always inertial measurement with external global fixes)
- 4. Configuration of system • SINS has no substansive plateform so acceleration and angular velocity are there pose, position and velocity are calculated at 100Hz • Dvl provid velocity relative to sea bottom • heading is found by Dvl • position fixes are by TAN
- 5. Filter equation - Mathematical model • east-north-vertical coordinate and state vector is vilocity errors attitude angle errors lattitude longtude and high errors accelerometer biases gyro drifts real postion position obtrained from TAN SINS TAN
- 6. BP neural network (intro) • Main functions are adapation, generation and powerful fault tolerance • Neural network uses non- linearity and differential function to train weights.
- 7. BP NN algorithm • input(x) and output(y) with connection wij and wjk • Training process: w and b small random values, determine actual output(for x, y), lastly weights are adjusted to minimize errors, gives us result followed by gradient descent of cost function iterate until the cost function smaller the e(set value)
- 8. USE OF BP NN in this paper • Recall phase correction by NN(sample with enough percision) are added to Kalman filter input of NN is highly error producing sensors • Observation and prediction vector as one input 300 samples to train network offline
- 9. Simulations • Matlab 6.5 and VC++6.0 tool is used • flat plane under certain depth with some coditions • linear velocity is 4kn, heading 45, longitude and latitude 165 and 32, drift 5/h and noise 10/h, random constant bias 50ug and error 50ug, dvl covariance error 0.5m/s, compass 3 and TAN 50m
- 10. conclusion • In this approach, the errors in • the classical federated Kalman filter estimation are corrected by • the BP neural network which is trained off line. AUV position • error is substantially reduced and the precision of the • underwater navigation is greatly improved.