scholarly journals An Efficient Machine Learning based Model for Classification of Wearable Clothing

2021 ◽  
Vol 3 (4) ◽  
pp. 317-329
Author(s):  
Judy Simon
Keyword(s):  
High Efficiency ◽  
Performance Metrics ◽  
Research Work ◽  
Evaluation Procedure ◽  
Classification Error ◽  
Fashion Industry ◽  
Starting Point ◽  
Benchmark Datasets ◽  
And Performance ◽  
Traditional Approaches

Computer vision research and its applications in the fashion industry have grown popular due to the rapid growth of information technology. Fashion detection is increasingly popular because most fashion goods need detection before they could be worn. Early detection of the human body component of the input picture is necessary to determine where the garment area is and then synthesize it. For this reason, detection is the starting point for most of the in-depth research. The cloth detection of landmarks is retrieved through many feature items that emphasis on fashionate things. The feature extraction can be done for better accuracy, pose and scale transmission. These convolution filters extract the features through many epochs and max-pooling layers in the neural networks. The optimized classification has been done using SVM in this study, for attaining overall high efficiency. This proposed CNN approach fashionate things prediction is combined with SVM for better classification. Furthermore, the classification error is minimized through the evaluation procedure for obtaining better accuracy. Finally, this research work has attained good accuracy and other performance metrics than the different traditional approaches. The benchmark datasets, current methodologies, and performance comparisons are all reorganized for each piece.

Multi Orientation Text Detection in Natural Imagery

2018 ◽  
Vol 8 (4) ◽  
pp. 41-56
Author(s):  
Deepak Kumar ◽  
Ramandeep Singh
Keyword(s):  
Performance Metrics ◽  
Research Work ◽  
Text Detection ◽  
Natural Images ◽  
Hard Copy ◽  
Future Perspective ◽  
Depth Study ◽  
Benchmark Datasets ◽  
And Performance ◽  
Curved Text

Constant advancement and growth in digital technology is swiftly changing the scenario of text detection from hard copy images to natural images. An in-depth study of the previous research work reveals that though a lot of research work has been done on text detection and recognition in natural scene images, but most of the researchers have concluded their survey either on a horizontal or near to horizontal texts. Their survey somewhat speaks about multi-orientation text detection, but the curved text detection in natural images escaped their attention. It has necessitated exploration on the vital aspect of text detection field where detailed study of horizontal, near to horizontal, multi-orientation, and curved text finds a place in a single cover. To achieve this goal, the present study will focus on fundamental understanding, existing challenges, and the proven algorithms for text detection in natural images. The authors discuss the future perspective of recent advances in text detection in natural images with various benchmark datasets and performance metrics.

Multiscale Nanoporous Structures for Sensing and Diagnostics

2009 ◽  
Vol 1236 ◽  
Author(s):  
Shalini Prasad
Keyword(s):  
Performance Metrics ◽  
Dynamic Range ◽  
Research Work ◽  
Serum Samples ◽  
Biomolecule Detection ◽  
Confined Spaces ◽  
And Performance ◽  
Hybrid Devices ◽  
Design And Manufacture ◽  
Analytical Tools

AbstractCurrent trends in sensing and diagnostics is towards developing hybrid devices that incorporate nanomaterial for enhancing device performance. These devices and systems have a broad impact ranging from personalized medicine in health care, environmental sensing and building multifunctional sensors for military applications. The overarching objective of the research work is to develop a new class of portable, bio-analytical tools with improved functionality and performance capabilities by utilizing the electrical effects on cellular and sub cellular species in micro and nanoscale domains.There are two key ideas underlying this research work. The first is to design and manufacture structures comprising of nanoscale-confined spaces integrated on to multi-scale architecture platforms. This model architecture has been engineered to harness the principle of macromolecular crowding for biomolecule binding and detection by monitoring perturbations in the electrical bi-layer in tailored nanoscale confined spaces. Enhanced performance metrics in biomolecule detection have been demonstrated in developing electrical immunoassays. We have demonstrated picogram/ml sensitivity in detection of specific cardiovascular disease biomarkers, cancer biomarkers from human serum samples with a dynamic range of response varying from pg/ml to g/ml and response time within 120 seconds.

scholarly journals Deliverology in Community Economic Development: Enhancing Results Frameworks and Performance Measurement

2019 ◽  
Vol 18 ◽  
pp. 1
Author(s):  
Trevin S. Stratton
Keyword(s):  
Economic Development ◽  
Service Delivery ◽  
Performance Measurement ◽  
Performance Metrics ◽  
Community Economic Development ◽  
Delivery Model ◽  
Measurement Framework ◽  
And Performance ◽  
Traditional Approaches ◽  
Development Service

<p> </p><p><span> </span>This paper will assess the viability of implementing an alternative delivery model and performance measurement framework – commonly known as ‘deliverology’ – at the level of community economic development. First, a review of relevant literature on traditional economic development delivery models and performance metrics is conducted to determine strengths and weaknesses. Next, a deliverology approach is defined and analyzed to determine whether such a model can address the weaknesses of more traditional approaches. The results indicate that a deliverology approach has many potential advantages for economic development service delivery and addresses many of the weaknesses of current models and frameworks. Since deliverology remains rather new compared to more traditional approaches, further research in terms of a case study in a large urban municipality is recommended as a way to test the applicability of deliverology to community economic development. </p><p><strong>Keywords: </strong>deliverology, performance measurement, results and delivery framework, community economic development, service delivery model</p>

scholarly journals Simulation and Performance Enhancement of High Efficiency Video Coding Standard for Video Compression

2019 ◽  
Vol 8 (11) ◽  
pp. 4311-4315
Keyword(s):  
Wireless Communication ◽  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Performance Enhancement ◽  
Research Work ◽  
High Efficiency Video Coding ◽  
And Performance

In the era of modern communication, the transmission of video is the most demanded feature and that makes the bandwidth issues crucial. The only solution to fight with is the video compression techniques/ standards.The High efficiency video coding standard(H.265/ HEVC) is newly evolved standard that is popularly used. this standard is better in saving bandwidth giving more compression. This research work deals with narrates the steps of implementation, simulation with MATLAB and the results obtained. from the obtained results, the 4G technique for wireless communication has been obtained in an enhanced way from the compression perspective

Piezoelectric β-polymorph formation of new textiles by surface modification with coating process based on interfacial interaction on the conformational variation of poly (vinylidene fluoride) (PVDF) chains

2020 ◽  
Vol 91 (3) ◽  
pp. 31301
Author(s):  
Nabil Chakhchaoui ◽  
Rida Farhan ◽  
Meriem Boutaldat ◽  
Marwane Rouway ◽  
Adil Eddiai ◽  
...  
Keyword(s):  
High Efficiency ◽  
Vinylidene Fluoride ◽  
Research Work ◽  
Research Area ◽  
Interfacial Interaction ◽  
Tetraethyl Orthosilicate ◽  
Poly Vinylidene Fluoride ◽  
Carbon Nanofillers ◽  
The Impact ◽  
Advanced Applications

Novel textiles have received a lot of attention from researchers in the last decade due to some of their unique features. The introduction of intelligent materials into textile structures offers an opportunity to develop multifunctional textiles, such as sensing, reacting, conducting electricity and performing energy conversion operations. In this research work nanocomposite-based highly piezoelectric and electroactive β-phase new textile has been developed using the pad-dry-cure method. The deposition of poly (vinylidene fluoride) (PVDF) − carbon nanofillers (CNF) − tetraethyl orthosilicate (TEOS), Si(OCH2CH3)4 was acquired on a treated textile substrate using coating technique followed by evaporation to transform the passive (non-functional) textile into a dynamic textile with an enhanced piezoelectric β-phase. The aim of the study is the investigation of the impact the coating of textile via piezoelectric nanocomposites based PVDF-CNF (by optimizing piezoelectric crystalline phase). The chemical composition of CT/PVDF-CNC-TEOS textile was detected by qualitative elemental analysis (SEM/EDX). The added of 0.5% of CNF during the process provides material textiles with a piezoelectric β-phase of up to 50% has been measured by FTIR experiments. These results indicated that CNF has high efficiency in transforming the phase α introduced in the unloaded PVDF, to the β-phase in the case of nanocomposites. Consequently, this fabricated new textile exhibits glorious piezoelectric β-phase even with relatively low coating content of PVDF-CNF-TEOS. The study demonstrates that the pad-dry-cure method can potentially be used for the development of piezoelectric nanocomposite-coated wearable new textiles for sensors and energy harvesting applications. We believe that our study may inspire the research area for future advanced applications.

ANTECEDENTS AND CONSEQUENCES OF ORGANIZATIONAL JUSTICE

2016 ◽  
Vol 12 (02) ◽  
Author(s):  
Reeta Yadav
Keyword(s):  
Job Satisfaction ◽  
Organizational Justice ◽  
Organizational Citizenship ◽  
Organizational Citizenship Behavior ◽  
Turnover Intentions ◽  
Research Work ◽  
Citizenship Behavior ◽  
Future Research ◽  
Antecedents And Consequences ◽  
And Performance

Employee’s perception regarding fairness in the organization is termed as organizational justice. The objective of this paper is to study the antecedents and consequences of organizational justice on the basis of earlier relevant studies from the period ranging from 1964 to 2015. Previous research identified employee participation, communication, justice climate as the antecedents and trust, job satisfaction, commitment, turnover intentions, organizational citizenship behavior and performance as the consequences of organizational justice. Finding reveals the gaps existing in the literature and gives suggestions for future research work.

scholarly journals ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Xujun Zhang ◽  
Chao Shen ◽  
Xueying Guo ◽  
Zhe Wang ◽  
Gaoqi Weng ◽  
...  
Keyword(s):  
High Efficiency ◽  
Low Cost ◽  
Pearson Correlation ◽  
Scoring Function ◽  
Web Server ◽  
Scoring Functions ◽  
Protein Ligand Interactions ◽  
Prediction Module ◽  
Ligand Interactions ◽  
Benchmark Datasets

AbstractVirtual screening (VS) based on molecular docking has emerged as one of the mainstream technologies of drug discovery due to its low cost and high efficiency. However, the scoring functions (SFs) implemented in most docking programs are not always accurate enough and how to improve their prediction accuracy is still a big challenge. Here, we propose an integrated platform called ASFP, a web server for the development of customized SFs for structure-based VS. There are three main modules in ASFP: (1) the descriptor generation module that can generate up to 3437 descriptors for the modelling of protein–ligand interactions; (2) the AI-based SF construction module that can establish target-specific SFs based on the pre-generated descriptors through three machine learning (ML) techniques; (3) the online prediction module that provides some well-constructed target-specific SFs for VS and an additional generic SF for binding affinity prediction. Our methodology has been validated on several benchmark datasets. The target-specific SFs can achieve an average ROC AUC of 0.973 towards 32 targets and the generic SF can achieve the Pearson correlation coefficient of 0.81 on the PDBbind version 2016 core set. To sum up, the ASFP server is a powerful tool for structure-based VS.

scholarly journals On Performance of Sparse Fast Fourier Transform Algorithms Using the Aliasing Filter

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1117
Author(s):  
Bin Li ◽  
Zhikang Jiang ◽  
Jie Chen
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
High Efficiency ◽  
Theory And Practice ◽  
Long Time ◽  
And Performance ◽  
Binary Tree Search ◽  
The One ◽  
Sparse Fast Fourier Transform ◽  
L1 And L2

Computing the sparse fast Fourier transform (sFFT) has emerged as a critical topic for a long time because of its high efficiency and wide practicability. More than twenty different sFFT algorithms compute discrete Fourier transform (DFT) by their unique methods so far. In order to use them properly, the urgent topic of great concern is how to analyze and evaluate the performance of these algorithms in theory and practice. This paper mainly discusses the technology and performance of sFFT algorithms using the aliasing filter. In the first part, the paper introduces the three frameworks: the one-shot framework based on the compressed sensing (CS) solver, the peeling framework based on the bipartite graph and the iterative framework based on the binary tree search. Then, we obtain the conclusion of the performance of six corresponding algorithms: the sFFT-DT1.0, sFFT-DT2.0, sFFT-DT3.0, FFAST, R-FFAST, and DSFFT algorithms in theory. In the second part, we make two categories of experiments for computing the signals of different SNRs, different lengths, and different sparsities by a standard testing platform and record the run time, the percentage of the signal sampled, and the L0, L1, and L2 errors both in the exactly sparse case and the general sparse case. The results of these performance analyses are our guide to optimize these algorithms and use them selectively.

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