8 Point DIT-FFT Algorithm Using Verilog

The importance of Digital Signal method (DSP) algorithms has increased drastically in recent times, the two very important techniques of DSP unit the Distinct Fourier rework (DFT) and thus the fast Fourier rework (FFT). DFT is mostly utilized within the applications sort of convolution, a linear filtering etc. Another algorithmic rule to reason DFT efficiently is that the fast Fourier remodels (FFT). Fast Fourier rework processor incorporates a vital role inside the sphere of communication system like audio broadcasting and digital video etc.

Video Steganography Based on Shi-Tomasi Corner Detection and Least Significant Bit Algorithm

Today, the digital and social media platforms are extremely trending, leading a demand to transmit knowledge very firmly. The information that is exchanged daily becomes ‘a victim’ to hackers. To beat this downside, one of the effective solutions is Steganography or Cryptography. In this paper, the video Steganography and cryptography thoughts are employed, where a key text is hidden behind a ‘certain frame’ of the video using Shi-Tomasi corner point detection and Least Significant Bit (LSB) algorithmic rule. Shi-Tomasi algorithmic rule is employed to observe, the corner points of the frame. In the proposed work, a ‘certain frame’ with large number of corner points is chosen from the video. Then, the secret text is embedded within the detected corner points using LSB algorithmic rule and transmitted. At the receiver end, decryption process is employed, in the reverser order of encryption to retrieve the secret data. As a technical contribution, the average variation of Mean Squared Error, Peak Signal to Noise Ratio, Structural Similarity Index are analysed for original and embedded frames and found to be 0.002, 0.016 and 0.0018 respectively.

Customer Segmentation Analysis and Visualization

Today’s world is all concerning Innovation and new concepts, where everybody desires to contend to measure higher than others. In the business world, it is crucial to know the client's desires and behavior patterns concerning buying merchandise. With the giant number of merchandise the businesses square measure confused to work out the potential customers to sell their merchandise to earn the large profits. To solve this real-time downside we tend to use machine learning techniques and algorithms. We can conclude the hidden patterns of knowledge. So that we can observe choices for earning a lot of profits. For this, we tend to take client information and divides the purchasers into totally different teams conjointly known as segmentation. segmentation permits businesses to create higher use of their selling budgets, gain a competitive edge over rival corporations, and, significantly, demonstrate much better information about your customer's desires and needs. In this project, we tend to square measure implementing k-means agglomeration algorithmic rule to analyze the results of clusters obtained from the algorithmic rule. A code is developed in python and it’s trained on an information set having 201 data samples that are taken from the native shopping center. All the offered data within the dataset is placed along to own a concept concerning client age, gender, annual financial gain, and outlay score(Expenditure) of mall customers dataset. Finally, this understanding information is analyzed to the simplest of our knowledge under the abled guidance of our mentor.

Image Edge Detection Based on Swarm Optimization Technique

Detecting of the edges in the image is used for highlighting sharp values of intensities and also which is used to extracted the relevant data. In the traditional methods of detection the results will be in broken edges and thereby there is loss of contours. The Ant Colony Optimization (AnCO) is originated to have faith in the detection problems wherever the aim is to extract the sting data which is present in the input picture, which is necessary to grab the information. Most procedures regarding Ant Colony Optimization is the inventions of fine explore regeneration over across the secretion upgraded by the army of ants. AnCO is galvanized from the actions of hunting the food displayed by hymenopteran community to seek out estimate results to the robust problems. An Ant Colony Optimization algorithmic rule is that the combination of previous information relating to the structure of an answer with the data relating to the arrangement of antecedent to acquire smart results. This methods uses 5 steps as initialization, construction, updation, decision and conceptualization method. Here the proposed methodology is carried with test images such as lena and cameraman. This method in finding the edges from a binary image by investigation results shows the successful outcomes. This proposed work can be applied in biomedical image processing in finding out the contour of tumor tissues.

Detection of Unhealthy Plant Leaves using Image Processing with Arduino

India is a cultivating country and as for seventy percentage of our people depends upon agribusiness. Third of our national compensation starts from agribusiness. Along these lines the illness disclosure of plants expects a critical activity inside the agricultural field. Larger piece of the plant contaminations are realized by the attack of bacterium, parasites, disease, etc. In the occasion that correct consideration isn't taken during this space, it should cause real impacts on plants and unfairly impacts the productivity and quality. To perceive, the plant ailments we'd like a snappy modified techniques. The most approach grasped in seek after for area and unmistakable verification of plant contaminations is eye observation through stars. the basic leadership limit of AN informed conjointly depends upon his/her adequacy, like exhaustion and vision, work weight air, etc subsequently this technique is time outstanding and more expensive. Here an endeavor is masterminded with a thought of police work plant diseases abuse picture process. Picture methodology instrument chest of Matlab is used for evaluating affected space of infection and to see the capability inside the shade of the illness impacted space. This idea may be loosened up to find the reactions of any variety of plant ailments that is affected on absolutely remarkable horticulture crops. The algorithmic rule may be wont to arrange the leaves and the gathered outcomes are detached abuse Arduino basically based vehicle system This decreases an essential task of watching of farms crops at starting period itself to find the sign of sicknesses show up on plant leaves.

Symmetric Transparent Online Bist and Repair of Memories

During regular testing Symmetric transparent BIST and Repair programme of RAM modules satisfy the memory contents conservation during similar time bouncing and signature prediction part is needed in transparent BIST programme which achieves considerable limiting in test time. In this study adders incorporated with binary addition is suggested for the utilization of accumulator modules. A symmetric Transparency march c primarily based algorithmic rule for constitutional self-repair (BISR) programme is recommended for multiple embedded reminiscences to realize best purpose of the performance of BISR for multiple embedded memories.

A New Hybrid Algorithm for Convex Nonlinear Unconstrained Optimization

In this study, we tend to propose a replacement hybrid algorithmic rule which mixes the search directions like Steepest Descent (SD) and Quasi-Newton (QN). First, we tend to develop a replacement search direction for combined conjugate gradient (CG) and QN strategies. Second, we tend to depict a replacement positive CG methodology that possesses the adequate descent property with sturdy Wolfe line search. We tend to conjointly prove a replacement theorem to make sure global convergence property is underneath some given conditions. Our numerical results show that the new algorithmic rule is powerful as compared to different standard high scale CG strategies.

Solution for optimal power flow problem in wind energy system using hybrid multi objective artificial physical optimization algorithm

<p class="Default">Normally, the character of the wind energy as a renewable energy sources has uncertainty in generation. To resolve the Optimal Power Flow (OPF) drawback, this paper proposed a replacement Hybrid Multi Objective Artificial Physical Optimization (HMOAPO) algorithmic rule, which does not require any management parameters compared to different meta-heuristic algorithms within the literature. Artificial Physical Optimization (APO), a moderately new population-based intelligence algorithm, shows fine performance on improvement issues. Moreover, this paper presents hybrid variety of Animal Migration Optimization (AMO) algorithmic rule to express the convergence characteristic of APO. The OPF drawback is taken into account with six totally different check cases, the effectiveness of the proposed HMOAPO technique is tested on IEEE 30-bus, IEEE 118-bus and IEEE 300-bus check system. The obtained results from the HMOAPO algorithm is compared with the other improvement techniques within the literature. The obtained comparison results indicate that proposed technique is effective to succeed in best resolution for the OPF drawback.</p>