A sum rate optimization for a wireless network has been considered in this problem. In this wireless
network, each link will receive not only its desired signal but also interference from other links. Since
the original optimization problem is not a convex optimization problem, we propose several methods
to transform the original objective function into a concave form. Then, dual-based sub-gradient
methods have been proposed to deal with each transformations. The simulation results show that
our proposed algorithm can converge in an acceptable number of iterations. Besides, the comparison
between each proposed methods is discussed via simulation.
Genetic Algorithm for Solving the Economic Load DispatchSatyendra Singh
In this paper, comparative study of two approaches, Genetic Algorithm
(GA) and Lambda Iteration method (LIM) have been used to provide
the solution of the economic load dispatch (ELD) problem. The ELD
problem is defined as to minimize the total operating cost of a power
system while meeting the total load plus transmission losses within
generation limits. GA and LIM have been used individually for solving
two cases, first is three generator test system and second is ten
generator test system. The results are compared which reveals that GA
can provide more accurate results with fast convergence characteristics
and is superior to LIM.
Comparison between the Specific graph partitioning method
(kernighan-lin) and general method (simulated annealing) with consideration to certain criteria
Genetic Algorithm for Solving the Economic Load DispatchSatyendra Singh
In this paper, comparative study of two approaches, Genetic Algorithm
(GA) and Lambda Iteration method (LIM) have been used to provide
the solution of the economic load dispatch (ELD) problem. The ELD
problem is defined as to minimize the total operating cost of a power
system while meeting the total load plus transmission losses within
generation limits. GA and LIM have been used individually for solving
two cases, first is three generator test system and second is ten
generator test system. The results are compared which reveals that GA
can provide more accurate results with fast convergence characteristics
and is superior to LIM.
Comparison between the Specific graph partitioning method
(kernighan-lin) and general method (simulated annealing) with consideration to certain criteria
Many traditional optimization methods have been successfully used from years to deal with ELD problem. However these techniques have limitations in many aspects as they provide inaccurate results. The objective is to minimize total fuel cost of power generation so as to meet the power demands to satisfy all constraints. In present paper, the parameters of the fuzzy logic are tuned using genetic algorithms. By using GA with fuzzy logic leads to an intelligent dimension for ELD solution space to obtain an optimum solution for ELD
Economic Load Dispatch (ELD) is a process of scheduling the required load demand among available generation units such that the fuel cost of operation is minimized. The ELD problem is formulated as a non-linear constrained optimization problem with both equality and inequality constraints. In this paper, two test systems of the ELD problems are solved by adopting the Cuckoo Search (CS) Algorithm. A comparison of obtained simulation results by using the CS is carried out against six other swarm intelligence algorithms: Particle Swarm Optimization, Shuffled Frog Leaping Algorithm, Bacterial Foraging Optimization, Artificial Bee Colony, Harmony Search and Firefly Algorithm. The effectiveness of each swarm intelligence algorithm is demonstrated on a test system comprising three-generators and other containing six-generators. Results denote superiority of the Cuckoo Search Algorithm and confirm its potential to solve the ELD problem.
Predicting Drug Target Interaction Using Deep Belief NetworkRashim Dhaubanjar
With the advancement in AI field, machine learning methods are being used to train the classifier for separating intractable drug-target pair as it is difficult to classify dockable and non-dockable ligands due to non-linear nature of big-biological data. As deep learning has been shown to produce state-of-the-art results on various tasks, we propose a new approach to predict the interaction between drug and targets efficiently. The DBN is used to extract the high level features from 2D chemical substructure represented in fingerprint format. DBN is trained in a greedy layer-wise unsupervised fashion and the result from this pre-training phase is used to initialize the parameters prior to BP used for fine tuning. Similarly, logistic regression layer is staked as output layer. Then it is fine-tuned using BP of error derivative to build classification model that directly predict whether a drug interacts with a target of interest or not. In addition to this we too propose an approach to reduce the time complexity of training the learning method with the use of GPU which is highly parallel programmable processor featuring peak arithmetic and memory bandwidth that substantially outpaces its CPU counterpart.
Memory Polynomial Based Adaptive Digital PredistorterIJERA Editor
Digital predistortion (DPD) is a baseband signal processing technique that corrects for impairments in RF
power amplifiers (PAs). These impairments cause out-of-band emissions or spectral regrowth and in-band
distortion, which correlate with an increased bit error rate (BER). Wideband signals with a high peak-to-average
ratio, are more susceptible to these unwanted effects. So to reduce these impairments, this paper proposes the
modeling of the digital predistortion for the power amplifier using GSA algorithm.
Php project aim is to develop dynamic and attractive web application as per user requirement. you can easily develop web application with our guidance............
for more details..... contact us..........
softroniics
calicut || palakkad || coimbatore
9037061113 , 9037291113
www.softroniics.in
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat A...IDES Editor
This paper proposes application of BAT algorithm
for solving economic load dispatch problem. BAT
algorithmic rule is predicated on the localization
characteristics of micro bats. The proposed approach has
been examined and tested with the numerical results of
economic load dispatch problems with three and five
generating units with valve - point loading without
considering prohibited operating zones and ramp rate limits.
The results of the projected BAT formula are compared with
that of other techniques such as lambda iteration, GA, PSO,
APSO, EP, ABC and basic principle. For each case, the
projected algorithmic program outperforms the answer
reported for the existing algorithms. Additionally, the
promising results show the hardness, quick convergence
and potency of the projected technique.
VLSI Implementation of High Speed & Low Power Multiplier in FPGAIOSR Journals
Abstract : We known that different multipliers consume most of the power in DSP computations, FIR filters.
Hence, it is very important factor for modern DSP systems to built low-power multipliers to minimize the power
dissipation. In this paper, we presents high speed & low power Row Column bypass multiplier design
methodology that inserts more number of zeros in the multiplicand thereby bypass the number of zero in row &
Column as well as reduce power consumption. The bypassing of zero activity of the component used in the
process of multiplication, depends on the input bit data. This means if the input bit data is zero, corresponding
row and column of adders need not be addition & transfer bit in next row and column adder circuit. If
multiplicand having more zeros, higher power reduction can be achieved. At last stage of Row & column bypass
multiplier having ripple carry adder which are increase time to generate carry bit to transfer next adder
circuit. To reduce this problem by using Carry bypass adder in place of ripple carry adder, then new
modification of Row &column multiplier having high speed in comparison to simple row & column bypass
multiplier, , the experimental results show that our proposed multiplier reduces power dissipation & High
speed overhead on the average for 4x4, 8x8 and 16x16 multiplier.
Keywords: Low Power, Row & Column bypass Multiplier, Carry bypassing techniques, FPGA, Xilinx
Basic knowhow of several techniques commonly used in deep learning and neural networks -- activation functions, cost functions, optimizers, regularization, parameter initialization, normalization, data handling, hyperparameter selection. Presented as lecture material for the course EE599 Deep Learning in Spring 2019 at University of Southern California.
Many traditional optimization methods have been successfully used from years to deal with ELD problem. However these techniques have limitations in many aspects as they provide inaccurate results. The objective is to minimize total fuel cost of power generation so as to meet the power demands to satisfy all constraints. In present paper, the parameters of the fuzzy logic are tuned using genetic algorithms. By using GA with fuzzy logic leads to an intelligent dimension for ELD solution space to obtain an optimum solution for ELD
Economic Load Dispatch (ELD) is a process of scheduling the required load demand among available generation units such that the fuel cost of operation is minimized. The ELD problem is formulated as a non-linear constrained optimization problem with both equality and inequality constraints. In this paper, two test systems of the ELD problems are solved by adopting the Cuckoo Search (CS) Algorithm. A comparison of obtained simulation results by using the CS is carried out against six other swarm intelligence algorithms: Particle Swarm Optimization, Shuffled Frog Leaping Algorithm, Bacterial Foraging Optimization, Artificial Bee Colony, Harmony Search and Firefly Algorithm. The effectiveness of each swarm intelligence algorithm is demonstrated on a test system comprising three-generators and other containing six-generators. Results denote superiority of the Cuckoo Search Algorithm and confirm its potential to solve the ELD problem.
Predicting Drug Target Interaction Using Deep Belief NetworkRashim Dhaubanjar
With the advancement in AI field, machine learning methods are being used to train the classifier for separating intractable drug-target pair as it is difficult to classify dockable and non-dockable ligands due to non-linear nature of big-biological data. As deep learning has been shown to produce state-of-the-art results on various tasks, we propose a new approach to predict the interaction between drug and targets efficiently. The DBN is used to extract the high level features from 2D chemical substructure represented in fingerprint format. DBN is trained in a greedy layer-wise unsupervised fashion and the result from this pre-training phase is used to initialize the parameters prior to BP used for fine tuning. Similarly, logistic regression layer is staked as output layer. Then it is fine-tuned using BP of error derivative to build classification model that directly predict whether a drug interacts with a target of interest or not. In addition to this we too propose an approach to reduce the time complexity of training the learning method with the use of GPU which is highly parallel programmable processor featuring peak arithmetic and memory bandwidth that substantially outpaces its CPU counterpart.
Memory Polynomial Based Adaptive Digital PredistorterIJERA Editor
Digital predistortion (DPD) is a baseband signal processing technique that corrects for impairments in RF
power amplifiers (PAs). These impairments cause out-of-band emissions or spectral regrowth and in-band
distortion, which correlate with an increased bit error rate (BER). Wideband signals with a high peak-to-average
ratio, are more susceptible to these unwanted effects. So to reduce these impairments, this paper proposes the
modeling of the digital predistortion for the power amplifier using GSA algorithm.
Php project aim is to develop dynamic and attractive web application as per user requirement. you can easily develop web application with our guidance............
for more details..... contact us..........
softroniics
calicut || palakkad || coimbatore
9037061113 , 9037291113
www.softroniics.in
Economic Load Dispatch Problem with Valve – Point Effect Using a Binary Bat A...IDES Editor
This paper proposes application of BAT algorithm
for solving economic load dispatch problem. BAT
algorithmic rule is predicated on the localization
characteristics of micro bats. The proposed approach has
been examined and tested with the numerical results of
economic load dispatch problems with three and five
generating units with valve - point loading without
considering prohibited operating zones and ramp rate limits.
The results of the projected BAT formula are compared with
that of other techniques such as lambda iteration, GA, PSO,
APSO, EP, ABC and basic principle. For each case, the
projected algorithmic program outperforms the answer
reported for the existing algorithms. Additionally, the
promising results show the hardness, quick convergence
and potency of the projected technique.
VLSI Implementation of High Speed & Low Power Multiplier in FPGAIOSR Journals
Abstract : We known that different multipliers consume most of the power in DSP computations, FIR filters.
Hence, it is very important factor for modern DSP systems to built low-power multipliers to minimize the power
dissipation. In this paper, we presents high speed & low power Row Column bypass multiplier design
methodology that inserts more number of zeros in the multiplicand thereby bypass the number of zero in row &
Column as well as reduce power consumption. The bypassing of zero activity of the component used in the
process of multiplication, depends on the input bit data. This means if the input bit data is zero, corresponding
row and column of adders need not be addition & transfer bit in next row and column adder circuit. If
multiplicand having more zeros, higher power reduction can be achieved. At last stage of Row & column bypass
multiplier having ripple carry adder which are increase time to generate carry bit to transfer next adder
circuit. To reduce this problem by using Carry bypass adder in place of ripple carry adder, then new
modification of Row &column multiplier having high speed in comparison to simple row & column bypass
multiplier, , the experimental results show that our proposed multiplier reduces power dissipation & High
speed overhead on the average for 4x4, 8x8 and 16x16 multiplier.
Keywords: Low Power, Row & Column bypass Multiplier, Carry bypassing techniques, FPGA, Xilinx
Basic knowhow of several techniques commonly used in deep learning and neural networks -- activation functions, cost functions, optimizers, regularization, parameter initialization, normalization, data handling, hyperparameter selection. Presented as lecture material for the course EE599 Deep Learning in Spring 2019 at University of Southern California.
ECONOMIC LOAD DISPATCH USING PARTICLE SWARM OPTIMIZATIONMln Phaneendra
In this ppt particle swarm optimization (PSO) is applied to allot the active power among the generating stations satisfying the system constraints and minimizing the cost of power generated.The viability of the method is analyzed for its accuracy and rate of convergence. The economic load dispatch problem is solved for three and six unit system using PSO and conventional method for both cases of neglecting and including transmission losses. The results of PSO method were compared with conventional method and were found to be superior.
Design high gain dc dc boost converter with coupling inductor and simulation ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
VOLTAGE PROFILE IMPROVEMENT AND LINE LOSSES REDUCTION USING DG USING GSA AND ...Journal For Research
In recent years, the power industry has experienced significant changes on the power distribution systems primarily due to the implementation of smart-grid technology and the incremental implementation of distributed generation. Distributed Generation (DG) is simply defined as the decentralization of power plants by placing smaller generating units closer to the point of consumption, traditionally ten mega-watts or smaller. The distribution power system is generally designed for radial power flow, but with the introduction of DG, power flow becomes bidirectional. Therefore this thesis focuses on testing various indices and using effective techniques for the optimal placement and sizing of the DG unit by minimizing power losses and voltage deviation. A 14-bus radial distribution system has been taken as the test system. The feasibility of the work lies on the fast execution of the programs as it would be equipped with the real time operation of the distribution system and it is seen that execution of the DG placement is quite fast and feasible with the optimization techniques used in this work.
This work shows the design and tuning procedure of a discrete PID controller for regulating buck boost converter circuits. The buck boost converter model is implemented using Simscape Matlab library without having to derive a complex mathematical model. A new tuning process of digital PID controllers based on identification data has been proposed. Simulation results are introduced to examine the potentials of the designed controller in power electronic applications and validate the capability and stability of the controller under supply and load perturbations. Despite controller linearity, the new approach has proved to be successful even with highly nonlinear systems. The proposed controller has succeeded in rejecting all the disturbances effectively and maintaining a constant output voltage from the regulator.
Small Signal Modelling and Controller Design of Boost Converter using MATLABPremier Publishers
Designing a controller for pulse width modulation (PWM) power converters is a real challenge owing to nonlinear and time-variant nature of switching power converters. PID con- trollers based on classical control theory is the simplest controller design approach. Nevertheless, the approach is valid only for linear system and hence the converter has to be linearized. The trial and error method of tuning the controller parameters may not give satisfactory results for advanced converters. Hence a systematic software aided controller design is required. This paper presents a systematic approach for controller design of a dc-dc converter using MATLAB. A simple converter like boost converter is taken as an example to illustrate the approach. Small signal modeling of a boost converter is derived theoretically. This is compared with MATLAB generated small signal model and resultant converter transfer functions. The controller design of the linearised converter is done using MATLAB. Finally, the performance of the controller is verified for line and load variations.
PID Tuning using Ziegler Nicholas - MATLAB ApproachWaleed El-Badry
This is an unreleased lab for undergraduate Mechatronics students to know how to practice Ziegler Nicholas method to find the PID factors using MATLAB.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Correlative Study on the Modeling and Control of Boost Converter using Advanc...IJSRD
DC-DC converters are switched power converters. The converters are most widely used in research and industrial applications. The DC-DC Boost Converters are used to step-up the supply voltage given to the plant model. The main advantage of using the Boost Converters is that it works in the low voltage according to the design specifications. In order to regulate the uncontrolled supply of voltage, a controller has to be designed and modeled to stabilize the output voltage. Since the convectional controllers cannot work under dynamic operating conditions, advanced controllers are to be designed to overcome the problems. In this article, the advanced controllers such as NARMA-L2, Fuzzy Logic (FLC) and Sliding Mode Controllers (SMC) are implemented and their responses are compared using MATLAB.
Similar to Power Control for Wireless Interference Network (20)
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Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
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This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
9. Prove concave
Difference of convex -> non-concave[1]
Simple model
Assume that , data rate is approximated to
Define , the original objective function can be
transformed into
The log-sum-exp function is concave [2], so the transformed
object function is concave
10. The solution to the dual problem provides
an upper bound to the solution of the primal
(maximization) problem
Joseph-Louis Lagrange
11. How to solve
Primal problem is hard to solve, so we
need to turn it into dual problem
Primal problem
In dual problem, we can solve the
maximum P which lead us to get the
minimum of dual problem
Dual problem
After getting minimum value of dual
problem, we need to update Lagrange
multiplier to make dual gap lower
Update Lagrange multiplier
14. Complicate model
No crash connection
Low throughput of any connection is not practical, so modify the objective
function as below
15. Complicate model
NO approximation
We assume previously so that the objective function is concave.
Now, we introduce two parameter to calculate the optimization problem
The Lower bound of the data rate can be expressed as
Transformed optimization problem
19. Simple model
Initial parameters
Update Pi
Update λ
Plot
Initial G, P, λ, Ϛ
Update λ and Ϛ by
Lagrange multiplier
update function
Update Pi by
power allocation
formula
Plot optimization
value vs iteration
index
Loop
20. Outer loop
Complicate model
Initial parameters
Update α,β
Update Pi
Update λ
Plot
Initial
G, P, λ, Ϛ, μ
Update Pi by
power allocation
formula
Plot optimization
value vs iteration
index
Update α, β by
the newest SINR
Update λ, μ and
Ϛ by Lagrange
multiplier
update function
Inner loop
27. [1] G. Tychogiorgos, A. Gkelias and K. K. Leung, “Utility-Proportional Fairness in
Wireless Networks,” in IEEE PIMRC, 2012
[2] Q. Chen, G. Yu, R. Yin, and G. Y. Li, “Energy-Efficient User Association and
Resource Allocation for Multistream Carrier Aggregation,” IEEE Transactions on
Wireless Communications, vol. 65, no. 8, Aug. 2016
[3] G. Tychogiorgos, A. Gkelias and K. K. Leung, “Towards a Fair Non-convex
Resource Allocation in Wireless Networks,” in IEEE PIMRC, 2011
Reference