Electric Circuits Class (Handout 12)
•
0 likes•65 views
This document outlines the terms and conditions for a home loan agreement between a lender and borrower. It details the loan amount, interest rate, repayment schedule, late fees, prepayment rules, default conditions, and insurance requirements to protect the property securing the loan. The borrower agrees to these terms by signing the document and understands that failure to abide by the terms could result in foreclosure on their home.
Report
Share
Report
Share
Download to read offline
Recommended
Morning tea 17 11-2016
The document provides a daily market summary and analysis for November 17th, 2016. It discusses the performance of the US, Asian, and Indian markets the previous day. It also provides technical analysis and recommendations for two Indian stocks, TECHM and SUNPHARMA, suggesting buy and sell signals. Additionally, it lists several corporate actions and an upcoming earnings calendar. The document is the daily morning tea report from Choice Broking research analysts.
Estimation Theory Class (Summary and Revision)
Summary of important theories and formulas in Estimation theory:
1) Cramer-Rao lower bound (CRLB)
2) Linear Model
3) Best Linear Unbiased Estimate (BLUE)
4) Maximum Likelihood Estimation (MLE)
5) Least Squares Estimation (LSE)
6) Bayesian Estimation and MMSE estimation
Properties of bivariate and conditional Gaussian PDFs
Properties of bi-variate Gaussian pdf
Properties of conditional Gaussian pdf
Effect of correlation on bi-variate and conditional Gaussian pdf
Analytic expressions of bivariate and conditional Gaussian pdfs
3-D and 2-D contour plots of Gaussian pdfs
Conditional mean and variance
Matlab code of density functions plots
Estimation Theory Class (Handout 12)
The document appears to be a scanned copy of a legal contract for the sale of a residential property located in California. The contract details the purchase price of $625,000, down payment terms, closing date, inclusion of household appliances, and procedural clauses around contingencies, possession, and risk of loss. The buyers and sellers signatures indicate they agree to the terms laid out in the contract for the purchase of the property.
Estimation Theory Class (Handout 11)
Bayesian Philosophy
Minimum Mean Square Error (MMSE) Estimation
MMSE derivation and motivation
Classical Estimation versus Bayesian Estimation
Review of probability theory
Estimation Theory Class (Handout 10)
- Least Squares Estimation (Part III)
- Constrained Linear Least Squares
- Reduced Model
- Examples: Non-linear device modeling using least squares - Sinusoidal parameters estimation using least squares, Numerical solution of non-linear least squares
- Ill-conditioned measurement matrix
- Regularized least squares
- SVD-based model modification
Estimation Theory Class (Handout 9)
- Least Squares Estimation (Part II)
- Linear Algebra background
- Geometrical interpretation of Linear Least Squares Estimation
- Vector subspace and space concepts
- Orthogonal subspaces
- Projection and orthogonal projection
- Properties of projection matrices
Estimation Theory Class (Handout 8)
- Least Squares Estimation (Part I)
- Linear Least Squares Estimation
- Weighted Least Squares
- Examples: Amplitude and frequency least squares estimation of sinusoidal in noise
Recommended
Morning tea 17 11-2016
The document provides a daily market summary and analysis for November 17th, 2016. It discusses the performance of the US, Asian, and Indian markets the previous day. It also provides technical analysis and recommendations for two Indian stocks, TECHM and SUNPHARMA, suggesting buy and sell signals. Additionally, it lists several corporate actions and an upcoming earnings calendar. The document is the daily morning tea report from Choice Broking research analysts.
Estimation Theory Class (Summary and Revision)
Summary of important theories and formulas in Estimation theory:
1) Cramer-Rao lower bound (CRLB)
2) Linear Model
3) Best Linear Unbiased Estimate (BLUE)
4) Maximum Likelihood Estimation (MLE)
5) Least Squares Estimation (LSE)
6) Bayesian Estimation and MMSE estimation
Properties of bivariate and conditional Gaussian PDFs
Properties of bi-variate Gaussian pdf
Properties of conditional Gaussian pdf
Effect of correlation on bi-variate and conditional Gaussian pdf
Analytic expressions of bivariate and conditional Gaussian pdfs
3-D and 2-D contour plots of Gaussian pdfs
Conditional mean and variance
Matlab code of density functions plots
Estimation Theory Class (Handout 12)
The document appears to be a scanned copy of a legal contract for the sale of a residential property located in California. The contract details the purchase price of $625,000, down payment terms, closing date, inclusion of household appliances, and procedural clauses around contingencies, possession, and risk of loss. The buyers and sellers signatures indicate they agree to the terms laid out in the contract for the purchase of the property.
Estimation Theory Class (Handout 11)
Bayesian Philosophy
Minimum Mean Square Error (MMSE) Estimation
MMSE derivation and motivation
Classical Estimation versus Bayesian Estimation
Review of probability theory
Estimation Theory Class (Handout 10)
- Least Squares Estimation (Part III)
- Constrained Linear Least Squares
- Reduced Model
- Examples: Non-linear device modeling using least squares - Sinusoidal parameters estimation using least squares, Numerical solution of non-linear least squares
- Ill-conditioned measurement matrix
- Regularized least squares
- SVD-based model modification
Estimation Theory Class (Handout 9)
- Least Squares Estimation (Part II)
- Linear Algebra background
- Geometrical interpretation of Linear Least Squares Estimation
- Vector subspace and space concepts
- Orthogonal subspaces
- Projection and orthogonal projection
- Properties of projection matrices
Estimation Theory Class (Handout 8)
- Least Squares Estimation (Part I)
- Linear Least Squares Estimation
- Weighted Least Squares
- Examples: Amplitude and frequency least squares estimation of sinusoidal in noise
Estimation Theory Class (handout 7)
- Maximum Likelihood Estimation: Part II
- MLE for transformed parameters
- Invariance property of MLE and its proof
- Extension to vector parameter
- Examples: ML estimation of power of Gaussian noise in dB - ML estimation of tangent of sinusoidal phase - Joint ML estimation of mean and variance of Gaussian random variables - Equivalency between MLE and Efficient estimator in linear Gaussian model - Joint estimation of amplitude and phase of sinusoidal wave in Gaussian noise - Joint estimation of amplitude, phase and frequency of sinusoidal wave in Gaussian noise
Estimation Theory Class (handout 6)
- Maximum Likelihood Estimation: Part I
- ML philosophy
- Asymptotic property of MLE
- Consistency Property of MLE
- Proof that ML produces efficient estimators if they exist
- Examples: ML sinusoidal phase estimation - MLE of Gaussian variables parameters with equal mean and variance - Verification of the asymptotic property of MLE using Truncated Taylor series
Electric Circuits Class (Solved problem set E)
This document outlines the terms and conditions for a home loan agreement between a lender and borrower. It details the loan amount, interest rate, repayment schedule, late fees, prepayment options, default conditions, and foreclosure process if the borrower fails to meet the obligations of the loan. The lender and borrower must both sign agreeing to these terms to finalize the home loan contract.
Electric Circuits Class (Solved problem set D)
The document outlines the key details of a home purchase agreement between John Doe and Jane Smith for the sale of a residential property located at 123 Main St for the price of $250,000. The buyer will pay a $5,000 deposit and the remaining balance at closing within 30 days. Standard contingencies are included for inspections, financing and other customary terms.
Electric Circuits Class (Solved problem set F)
The document outlines the key details of a home sale including the purchase price of $450,000, a closing date of January 15, 2023, and contingencies requiring the home to pass inspection and the buyer to obtain financing by December 15, 2022.
Eectric Circuits Class (Revision problems set 2)
Solved revision problem set 2 - DC Circuits
Thevenin and Norton Theorems
Compensation theory
Superposition theory
Electric Circuits Class (Handout 10)
This document outlines the terms and conditions for a rental agreement between John Doe and Jane Smith for the property located at 123 Main St. It specifies the monthly rental rate of $1,000 due on the 1st of each month, the security deposit of $500, and responsibilities of the landlord and tenant regarding repairs, guests, noise, and more. The initial lease term is one year beginning January 1st.
Electric Circuits Class (Handout 11)
This document outlines the terms and conditions for a rental agreement between John Doe and Jane Smith for the property located at 123 Main St. It specifies the monthly rental rate of $1,000 due on the 1st of each month, the security deposit of $500, allows for pets with an additional $100 fee, and holds both parties accountable for repairs and damages that may occur during the lease period.
Estimation Theory Class (handout 5)
Best Linear Unbiased Estimator (BLUE)
Why and when BLUE is needed?
Derivation of BLUE for scalar parameter
Extension to vector parameter
Solved examples include DC estimation in additive colored noise of general distribution
Proof that BLUE is MVU and efficient if Noise is Gaussian and data is linear in the parameters
Estimation Theory Class (handout 4)
Cramer-Rao Lower Bound (CRLB), Fisher Information Matrix (FIM), and Efficient MVU estimator for linear data models in multivariate colored and white Gaussian noise.
Examples include: Line fitting, Curve fitting, Fourier analysis, System identification, DC estimation
Electric Circuits Class (Solution of Problem set A)
Solved problems about:
Loop current method
Node voltage method
Circuit simplification methods
Delta-Star (Pi-Tee) transformation
Electric Circuits Class (Problem set A)
Problems about:
Loop current method
Node voltage method
Circuit simplification methods
Delta-Star (Pi-Tee) transformation
Electric Circuits Class (project specifications)
Using circuit theories, analysis tools, and simplification methods presented in this course, the student is required to write a computer program that can do the following:
1. Accept the elements and connections
2. Compute the required circuit response (Current, Voltage, Power, …) at any arbitrary location specified by the program user. The computer program is required to be completed without any call or use of any circuit simulation tool (e.g. PSpice).
Electric Circuits Class (Solution of Problem set C)
Solution of problems about
Network theorems
Thevenin Theorem
Norton Theorem
Maximum Power transfer Theorem
Reciprocity Theorem
Compensation Theorem
Electric Circuits Class (Revision problems with solurtions)
Solved problems in Electric Circuits (DC part)
Thevenin theory
Norton theory
Superposition theory
Delta-star transformation
Loop-current method
Node voltage method
Electric Circuits Class (Solution of Problem set B)
Solved problems about:
Loop current method
Node voltage method
Circuit simplification methods
Delta-Star (Pi-Tee) transformation
Electric Circuits Class (Problem set B)
Problems about:
Loop current method
Node voltage method
Circuit simplification methods
Delta-Star (Pi-Tee) transformation
Electric Circuits Class (Problem set C)
Problems about:
Network theorems
Thevenin Theorem
Norton Theorem
Maximum Power transfer Theorem
Reciprocity Theorem
Compensation Theorem
Electric Circuits Class (Handout 9)
General notes on Electric Circuits
Calculation of Input resistance
Power efficiency in maximum power transfer theorem
Electric Circuits Class (Handout 8)
The document discusses the benefits of meditation for reducing stress and anxiety. Regular meditation practice can help calm the mind and body by lowering heart rate and blood pressure. Studies have shown that meditating for just 10-20 minutes per day can have significant positive impacts on both mental and physical health over time.
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Recycled Concrete Aggregate in Construction Part III
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
More Related Content
More from Ahmad Gomaa
Estimation Theory Class (handout 7)
- Maximum Likelihood Estimation: Part II
- MLE for transformed parameters
- Invariance property of MLE and its proof
- Extension to vector parameter
- Examples: ML estimation of power of Gaussian noise in dB - ML estimation of tangent of sinusoidal phase - Joint ML estimation of mean and variance of Gaussian random variables - Equivalency between MLE and Efficient estimator in linear Gaussian model - Joint estimation of amplitude and phase of sinusoidal wave in Gaussian noise - Joint estimation of amplitude, phase and frequency of sinusoidal wave in Gaussian noise
Estimation Theory Class (handout 6)
- Maximum Likelihood Estimation: Part I
- ML philosophy
- Asymptotic property of MLE
- Consistency Property of MLE
- Proof that ML produces efficient estimators if they exist
- Examples: ML sinusoidal phase estimation - MLE of Gaussian variables parameters with equal mean and variance - Verification of the asymptotic property of MLE using Truncated Taylor series
Electric Circuits Class (Solved problem set E)
This document outlines the terms and conditions for a home loan agreement between a lender and borrower. It details the loan amount, interest rate, repayment schedule, late fees, prepayment options, default conditions, and foreclosure process if the borrower fails to meet the obligations of the loan. The lender and borrower must both sign agreeing to these terms to finalize the home loan contract.
Electric Circuits Class (Solved problem set D)
The document outlines the key details of a home purchase agreement between John Doe and Jane Smith for the sale of a residential property located at 123 Main St for the price of $250,000. The buyer will pay a $5,000 deposit and the remaining balance at closing within 30 days. Standard contingencies are included for inspections, financing and other customary terms.
Electric Circuits Class (Solved problem set F)
The document outlines the key details of a home sale including the purchase price of $450,000, a closing date of January 15, 2023, and contingencies requiring the home to pass inspection and the buyer to obtain financing by December 15, 2022.
Eectric Circuits Class (Revision problems set 2)
Solved revision problem set 2 - DC Circuits
Thevenin and Norton Theorems
Compensation theory
Superposition theory
Electric Circuits Class (Handout 10)
This document outlines the terms and conditions for a rental agreement between John Doe and Jane Smith for the property located at 123 Main St. It specifies the monthly rental rate of $1,000 due on the 1st of each month, the security deposit of $500, and responsibilities of the landlord and tenant regarding repairs, guests, noise, and more. The initial lease term is one year beginning January 1st.
Electric Circuits Class (Handout 11)
This document outlines the terms and conditions for a rental agreement between John Doe and Jane Smith for the property located at 123 Main St. It specifies the monthly rental rate of $1,000 due on the 1st of each month, the security deposit of $500, allows for pets with an additional $100 fee, and holds both parties accountable for repairs and damages that may occur during the lease period.
Estimation Theory Class (handout 5)
Best Linear Unbiased Estimator (BLUE)
Why and when BLUE is needed?
Derivation of BLUE for scalar parameter
Extension to vector parameter
Solved examples include DC estimation in additive colored noise of general distribution
Proof that BLUE is MVU and efficient if Noise is Gaussian and data is linear in the parameters
Estimation Theory Class (handout 4)
Cramer-Rao Lower Bound (CRLB), Fisher Information Matrix (FIM), and Efficient MVU estimator for linear data models in multivariate colored and white Gaussian noise.
Examples include: Line fitting, Curve fitting, Fourier analysis, System identification, DC estimation
Electric Circuits Class (Solution of Problem set A)
Solved problems about:
Loop current method
Node voltage method
Circuit simplification methods
Delta-Star (Pi-Tee) transformation
Electric Circuits Class (Problem set A)
Problems about:
Loop current method
Node voltage method
Circuit simplification methods
Delta-Star (Pi-Tee) transformation
Electric Circuits Class (project specifications)
Using circuit theories, analysis tools, and simplification methods presented in this course, the student is required to write a computer program that can do the following:
1. Accept the elements and connections
2. Compute the required circuit response (Current, Voltage, Power, …) at any arbitrary location specified by the program user. The computer program is required to be completed without any call or use of any circuit simulation tool (e.g. PSpice).
Electric Circuits Class (Solution of Problem set C)
Solution of problems about
Network theorems
Thevenin Theorem
Norton Theorem
Maximum Power transfer Theorem
Reciprocity Theorem
Compensation Theorem
Electric Circuits Class (Revision problems with solurtions)
Solved problems in Electric Circuits (DC part)
Thevenin theory
Norton theory
Superposition theory
Delta-star transformation
Loop-current method
Node voltage method
Electric Circuits Class (Solution of Problem set B)
Solved problems about:
Loop current method
Node voltage method
Circuit simplification methods
Delta-Star (Pi-Tee) transformation
Electric Circuits Class (Problem set B)
Problems about:
Loop current method
Node voltage method
Circuit simplification methods
Delta-Star (Pi-Tee) transformation
Electric Circuits Class (Problem set C)
Problems about:
Network theorems
Thevenin Theorem
Norton Theorem
Maximum Power transfer Theorem
Reciprocity Theorem
Compensation Theorem
Electric Circuits Class (Handout 9)
General notes on Electric Circuits
Calculation of Input resistance
Power efficiency in maximum power transfer theorem
Electric Circuits Class (Handout 8)
The document discusses the benefits of meditation for reducing stress and anxiety. Regular meditation practice can help calm the mind and body by lowering heart rate and blood pressure. Studies have shown that meditating for just 10-20 minutes per day can have significant positive impacts on both mental and physical health over time.
More from Ahmad Gomaa (20)
Electric Circuits Class (Solution of Problem set A)
Electric Circuits Class (Solution of Problem set A)
Electric Circuits Class (Solution of Problem set C)
Electric Circuits Class (Solution of Problem set C)
Electric Circuits Class (Revision problems with solurtions)
Electric Circuits Class (Revision problems with solurtions)
Electric Circuits Class (Solution of Problem set B)
Electric Circuits Class (Solution of Problem set B)
Recently uploaded
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Recycled Concrete Aggregate in Construction Part III
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Understanding Inductive Bias in Machine Learning
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
[JPP-1] - (JEE 3.0) - Kinematics 1D - 14th May..pdf
Kinematics 11th jpp- 01. ( Solved ) unacademy namo kaul on 14th may...
Advanced control scheme of doubly fed induction generator for wind turbine us...
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
bank management system in java and mysql report1.pdf
truth is high but higher still is truth full living
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
原版一模一样【微信：741003700 】【(csu毕业证书)查尔斯特大学毕业证硕士学历】【微信：741003700 】学位证，留信认证（真实可查，永久存档）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。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：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、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
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
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Recently uploaded (20)
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
Recycled Concrete Aggregate in Construction Part III
Recycled Concrete Aggregate in Construction Part III
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
[JPP-1] - (JEE 3.0) - Kinematics 1D - 14th May..pdf
[JPP-1] - (JEE 3.0) - Kinematics 1D - 14th May..pdf
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...
ACRP 4-09 Risk Assessment Method to Support Modification of Airfield Separat...
bank management system in java and mysql report1.pdf
bank management system in java and mysql report1.pdf
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
2. Operations Strategy in a Global Environment.ppt
2. Operations Strategy in a Global Environment.ppt
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMS