Computationally efficient model of the implanted knee for time-sensitive applications

2020 ◽  
Author(s):  
E Bori ◽  
A Navacchia ◽  
L Wang ◽  
L Duxbury ◽  
S McGuan ◽  
...  
Keyword(s):  
Computationally Efficient

Cloud-Based Multimedia Content Protection System

2020 ◽  
pp. 164-169
Author(s):  
B. Aparna ◽  
S. Madhavi ◽  
G. Mounika ◽  
P. Avinash ◽  
S. Chakravarthi
Keyword(s):  
Large Scale ◽  
Protection System ◽  
Multimedia Content ◽  
Computationally Efficient ◽  
Content Protection ◽  
Protection Systems ◽  
Multimedia Content Protection ◽  
High Scalability ◽  
Cloud Infrastructures ◽  
Rapid Deployment

We propose a new design for large-scale multimedia content protection systems. Our design leverages cloud infrastructures to provide cost efficiency, rapid deployment, scalability, and elasticity to accommodate varying workloads. The proposed system can be used to protect different multimedia content types, including videos, images, audio clips, songs, and music clips. The system can be deployed on private and/or public clouds. Our system has two novel components: (i) method to create signatures of videos, and (ii) distributed matching engine for multimedia objects. The signature method creates robust and representative signatures of videos that capture the depth signals in these videos and it is computationally efficient to compute and compare as well as it requires small storage. The distributed matching engine achieves high scalability and it is designed to support different multimedia objects. We implemented the proposed system and deployed it on two clouds: Amazon cloud and our private cloud. Our experiments with more than 11,000 videos and 1 million images show the high accuracy and scalability of the proposed system. In addition, we compared our system to the protection system used by YouTube and our results show that the YouTube protection system fails to detect most copies of videos, while our system detects more than 98% of them.

Full Optical Rotation Tensor at CCSD Level in the Modified Velocity Gauge

2020 ◽  
Author(s):  
Kaihua Zhang ◽  
Ty Balduf ◽  
Marco Caricato
Keyword(s):  
Electric Dipole ◽  
Optical Rotation ◽  
Electric Quadrupole ◽  
Polarizability Tensor ◽  
Dipole Polarizability ◽  
Difficult Case ◽  
Computationally Efficient ◽  
Rotation Tensor ◽  
Approximate Methods ◽  
Velocity Gauge

<div> <div> <p> </p><div> <div> <div> <p>This work presents the first simulations of the full optical rotation (OR) tensor at coupled cluster with single and double excitations (CCSD) level in the modified velocity gauge (MVG) formalism. The CCSD-MVG OR tensor is origin independent, and each tensor element can in principle be related directly to experimental measurements on oriented systems. We compare the CCSD results with those from two density functionals, B3LYP and CAM-B3LYP, on a test set of 22 chiral molecules. The results show that the functionals consistently overestimate the CCSD results for the individual tensor components and for the trace (which is related to the isotropic OR), by 10-20% with CAM-B3LYP and 20-30% with B3LYP. The data show that the contribution of the electric dipole-magnetic dipole polarizability tensor to the OR tensor is on average twice as large as that of the electric dipole-electric quadrupole polarizability tensor. The difficult case of (1S,4S)-(–)-norbornenone also reveals that the evaluation of the former polarizability tensor is more sensitive than the latter. We attribute the better agreement of CAM-B3LYP with CCSD to the ability of this functional to better reproduce electron delocalization compared with B3LYP, consistently with previous reports on isotropic OR. The CCSD-MVG approach allows the computation of reference data of the full OR tensor, which may be used to test more computationally efficient approximate methods that can be employed to study realistic models of optically active materials. </p> </div> </div> </div> </div> </div>

In the Quest for a Stable Triplet State in Small Polyaromatic Hydrocarbons : An In-Silico Tool for Rational Design and Prediction

2019 ◽  
Author(s):  
Madhumita Rano ◽  
Sumanta K Ghosh ◽  
Debashree Ghosh
Keyword(s):  
Triplet State ◽  
Small Molecules ◽  
In Silico ◽  
Qualitative Agreement ◽  
Rational Design ◽  
Polyaromatic Hydrocarbons ◽  
Spin Hamiltonian ◽  
Spin Frustration ◽  
Computationally Efficient ◽  
High Level

<div>Combining the roles of spin frustration and geometry of odd and even numbered rings in polyaromatic hydrocarbons (PAHs), we design small molecules that show exceedingly small singlet-triplet gaps and stable triplet ground states. Furthermore, a computationally efficient protocol with a model spin Hamiltonian is shown to be capable of qualitative agreement with respect to high level multireference calculations and therefore, can be used for fast molecular discovery and screening.</div>

Compressive Sensing Audio Watermarking dengan Metode LWT dan QIM

2018 ◽  
Vol 6 (3) ◽  
pp. 405
Author(s):  
IRMA SAFITRI ◽  
NUR IBRAHIM ◽  
HERLAMBANG YOGASWARA
Keyword(s):  
Wavelet Transform ◽  
Compressive Sensing ◽  
Audio Watermarking ◽  
Quantization Index Modulation ◽  
Computationally Efficient ◽  
Black And White ◽  
Additional Information ◽  
Audio Files ◽  
Index Modulation ◽  
Mp3 Compression

ABSTRAKPenelitian ini mengembangkan teknik Compressive Sensing (CS) untuk audio watermarking dengan metode Lifting Wavelet Transform (LWT) dan Quantization Index Modulation (QIM). LWT adalah salah satu teknik mendekomposisi sinyal menjadi 2 sub-band, yaitu sub-band low dan high. QIM adalah suatu metode yang efisien secara komputasi atau perhitungan watermarking dengan menggunakan informasi tambahan. Audio watermarking dilakukan menggunakan file audio dengan format *.wav berdurasi 10 detik dan menggunakan 4 genre musik, yaitu pop, classic, rock, dan metal. Watermark yang disisipkan berupa citra hitam putih dengan format *.bmp yang masing-masing berukuran 32x32 dan 64x64 pixel. Pengujian dilakukan dengan mengukur nilai SNR, ODG, BER, dan PSNR. Audio yang telah disisipkan watermark, diuji ketahanannya dengan diberikan 7 macam serangan berupa LPF, BPF, HPF, MP3 compression, noise, dan echo. Penelitian ini memiliki hasil optimal dengan nilai SNR 85,32 dB, ODG -8,34x10-11, BER 0, dan PSNR ∞.Kata kunci: Audio watermarking, QIM, LWT, Compressive Sensing. ABSTRACTThis research developed Compressive Sensing (CS) technique for audio watermarking using Wavelet Transform (LWT) and Quantization Index Modulation (QIM) methods. LWT is one technique to decompose the signal into 2 sub-bands, namely sub-band low and high. QIM is a computationally efficient method or watermarking calculation using additional information. Audio watermarking was done using audio files with *.wav format duration of 10 seconds and used 4 genres of music, namely pop, classic, rock, and metal. Watermark was inserted in the form of black and white image with *.bmp format each measuring 32x32 and 64x64 pixels. The test was done by measuring the value of SNR, ODG, BER, and PSNR. Audio that had been inserted watermark was tested its durability with given 7 kinds of attacks such as LPF, BPF, HPF, MP3 Compression, Noise, and Echo. This research had optimal result with SNR value of 85.32 dB, ODG value of -8.34x10-11, BER value of 0, and PSNR value of ∞.Keywords: Audio watermarking, QIM, LWT, Compressive Sensing.

Accurate Detection and Quantization of Leaf- Diseases through Soft Computing

2018 ◽  
Vol 1 (1) ◽  
pp. 236-247
Author(s):  
Divya Srivastava ◽  
Rajitha B. ◽  
Suneeta Agarwal
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Agricultural Production ◽  
Bacterial Blight ◽  
Early Stage ◽  
Second Phase ◽  
Computationally Efficient ◽  
Stage Of Disease ◽  
Accurate Detection ◽  
Two Phases

Diseases in leaves can cause the significant reduction in both quality and quantity of agricultural production. If early and accurate detection of disease/diseases in leaves can be automated, then the proper remedy can be taken timely. A simple and computationally efficient approach is presented in this paper for disease/diseases detection on leaves. Only detecting the disease is not beneficial without knowing the stage of disease thus the paper also determine the stage of disease/diseases by quantizing the affected of the leaves by using digital image processing and machine learning. Though there exists a variety of diseases on leaves, but the bacterial and fungal spots (Early Scorch, Late Scorch, and Leaf Spot) are the most prominent diseases found on leaves. Keeping this in mind the paper deals with the detection of Bacterial Blight and Fungal Spot both at an early stage (Early Scorch) and late stage (Late Scorch) on the variety of leaves. The proposed approach is divided into two phases, in the first phase, it identifies one or more disease/diseases existing on leaves. In the second phase, amount of area affected by the disease/diseases is calculated. The experimental results obtained showed 97% accuracy using the proposed approach.

Efficient Computing in Image Processing and DSPs with ASIP Based Multiplier

2019 ◽  
Vol 13 (2) ◽  
pp. 174-180
Author(s):  
Poonam Sharma ◽  
Ashwani Kumar Dubey ◽  
Ayush Goyal
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Computation Time ◽  
Digital Signal ◽  
Instruction Set ◽  
Computationally Efficient ◽  
Specific Instruction ◽  
Processor Core ◽  
Speed Performance ◽  
Application Specific

Background: With the growing demand of image processing and the use of Digital Signal Processors (DSP), the efficiency of the Multipliers and Accumulators has become a bottleneck to get through. We revised a few patents on an Application Specific Instruction Set Processor (ASIP), where the design considerations are proposed for application-specific computing in an efficient way to enhance the throughput. Objective: The study aims to develop and analyze a computationally efficient method to optimize the speed performance of MAC. Methods: The work presented here proposes the design of an Application Specific Instruction Set Processor, exploiting a Multiplier Accumulator integrated as the dedicated hardware. This MAC is optimized for high-speed performance and is the application-specific part of the processor; here it can be the DSP block of an image processor while a 16-bit Reduced Instruction Set Computer (RISC) processor core gives the flexibility to the design for any computing. The design was emulated on a Xilinx Field Programmable Gate Array (FPGA) and tested for various real-time computing. Results: The synthesis of the hardware logic on FPGA tools gave the operating frequencies of the legacy methods and the proposed method, the simulation of the logic verified the functionality. Conclusion: With the proposed method, a significant improvement of 16% increase in throughput has been observed for 256 steps iterations of multiplier and accumulators on an 8-bit sample data. Such an improvement can help in reducing the computation time in many digital signal processing applications where multiplication and addition are done iteratively.

Simulation and Performance Analysis of Tilted Time Window and Support Vector Machine Based Learning Object Ranking Method

2020 ◽  
Vol 13 (2) ◽  
pp. 153-164
Author(s):  
Narina Thakur ◽  
Deepti Mehrotra ◽  
Abhay Bansal ◽  
Manju Bala
Keyword(s):  
Support Vector Machine ◽  
Classification Accuracy ◽  
Time Window ◽  
Optimal Solution ◽  
Similarity Score ◽  
Learning Objects ◽  
Retrieval Algorithm ◽  
Support Vector ◽  
Computationally Efficient ◽  
User Query

Objective: Since the adequacy of Learning Objects (LO) is a dynamic concept and changes in its use, needs and evolution, it is important to consider the importance of LO in terms of time to assess its relevance as the main objective of the proposed research. Another goal is to increase the classification accuracy and precision. Methods: With existing IR and ranking algorithms, MAP optimization either does not lead to a comprehensively optimal solution or is expensive and time - consuming. Nevertheless, Support Vector Machine learning competently leads to a globally optimal solution. SVM is a powerful classifier method with its high classification accuracy and the Tilted time window based model is computationally efficient. Results: This paper proposes and implements the LO ranking and retrieval algorithm based on the Tilted Time window and the Support Vector Machine, which uses the merit of both methods. The proposed model is implemented for the NCBI dataset and MAT Lab. Conclusion: The experiments have been carried out on the NCBI dataset, and LO weights are assigned to be relevant and non - relevant for a given user query according to the Tilted Time series and the Cosine similarity score. Results showed that the model proposed has much better accuracy.

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