Image Retrieval Algorithm based on Incremental CBIR using Color Histogram

Waqas Rasheed,Nishat Ahmad,Ilhoe Jeung(정일회),SungKwan Kang(강성관),Jongan Park(박종안) 한국정보기술학회 2007 Proceedings of KIIT Conference Vol.2007 No.-

An incremental Content Based Image Retrieval (CBIR) method is proposed in this paper based on color histogram. Standard histograms, because of their efficiency and insensitivity to small changes, are widely used for content based image retrieval. But the main disadvantage of histograms is that many images of different appearances can have similar histograms because histograms provide coarse characterization of an image. We define an algorithm that utilizes the concept of Histogram Refinement [l] and we call it Color Refinement Method.

Dual-mode highly selective colorimetric and smartphone-based paper sensors utilizing silver nanoparticles for ultra-trace level omeprazole detection in complex matrices

Sufian Rasheed,Naseer Ahmad,Muhammad Anwar Ul Haq,Waqas Ahmad,Dilshad Hussain,Sirajuddin 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.128 No.-

The present work focuses on the synthesis and optimization of highly stable, bare silver nanoparticles(AgNPs) as colorimetric sensor for trace-level detection of omeprazole. A novel approach combiningAgNPs-based paper sensor and smartphone technology enables real-time analysis of omeprazole. Thecolor change observed by the naked eye and shift in localized surface plasmon resonance (LSPR) wereused to construct calibration curves. Both LSPR-based colorimetric sensing and paper-based sensingapproaches were utilized for omeprazole detection in complex matrices. The limits of detection (LODs)were determined as 15 nM and 240 nM, with linear dynamic ranges of 0.05–40 lM and 0.1–50 lM,respectively. Recovery studies demonstrated % recoveries within the acceptable range of 90–110% andrelative standard deviation (RSD) below 2%. Detailed characterizations including Fourier-TransformInfrared - (FTIR) Spectroscopy, Dynamic Light Scattering (DLS), zeta potential, Atomic ForceMicroscopy (AFM), and Field-Emission Scanning Electron Microscopy (FE-SEM) provided insights intosensing mechanism. This work offers a promising and practical solution for real-time omeprazole analysiswith potential applications extending beyond pharmaceutical formulations. The developed colorimetricsensor based on AgNPs demonstrates high stability, sensitivity, and versatility, making it suitable foron-site and point-of-care omeprazole detection in various samples, including serum, plasma, urine, seawater, and tap water.

학계와 산업계의 정보 대중성 변동과 인용 정보에 기반한 최신 기술 동향 식별 시스템

김선호,이준규,Waqas Rasheed,여운동 한국기술혁신학회 2011 한국기술혁신학회 학술대회 발표논문집 Vol.2011 No.11

An Emerging Technology Trend Identifier Based on the Citation and the Change of Academic and Industrial Popularity

김선호,이준규,Waqas Rasheed,여운동 한국기술혁신학회 2011 기술혁신학회지 Vol.14 No.S

Identifying Emerging Technology Trends is crucial for decision makers of nations and organizations in order to use limited resources, such as time, money, etc., efficiently. Many researchers have proposed emerging trend detection systems based on a popularity analysis of the document, but this still needs to be improved. In this paper, an emerging trend detection classifier is proposed which uses both academic and industrial data, SCOPUS and PATSTAT. Unlike most pre-vious research, our emerging technology trend classifi-er utilizes supervised, semi-automatic, machine learning techniques to improve the precision of the results. In addition, the citation information from among the SCOPUS data is analyzed to identify the early signals of emerging technology trends. Identifying Emerging Technology Trends is crucial for decision makers of nations and organizations in order to use limited resources, such as time, money, etc., efficiently. Many researchers have proposed emerging trend detection systems based on a popularity analysis of the document, but this still needs to be improved. In this paper, an emerging trend detection classifier is proposed which uses both academic and industrial data, SCOPUS and PATSTAT. Unlike most pre-vious research, our emerging technology trend classifi-er utilizes supervised, semi-automatic, machine learning techniques to improve the precision of the results. In addition, the citation information from among the SCOPUS data is analyzed to identify the early signals of emerging technology trends.

Defining a new feature set for content-based image analysis using histogram refinement

Park, Jongan,An, Youngan,Kang, Gwangwon,Rasheed, Waqas,Park, Seungjin,Kwon, Goorak Wiley Subscription Services, Inc., A Wiley Company 2008 INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHN Vol.18 No.2

<P>The proposed method is based on color histogram. A new set of features are proposed for content-based image retrieval (CBIR) in this article. The selection of the features is based on histogram analysis. Standard histograms, because of their efficiency and insensitivity to small changes, are widely used for CBIR. But the main disadvantage of histograms is that many images of different appearances can have similar histograms because histograms provide coarse characterization of an image. We define an algorithm that utilizes the concept of Histogram Refinement (Pass and Zabih, IEEE Workshop on Applications of Computer Vision (1996), 96–102) and we call it color refinement method. Color refinement method splits the pixels in a given bucket into several classes just like histogram refinement method. The classes are all related to colors and are based on color coherence vectors. After the calculation of clusters using color refinement method, inherent features of each of the cluster is calculated. These inherent features include size, mean, variance, major axis length, minor axis length, and angle between x-axis and major axis of ellipse for various clusters. These inherent features are finally used for image retrieval using Euclidean distance. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 86–93, 2008</P>

Dietary Practices, Addictive Behavior and Bowel Habits and Risk of Early Onset Colorectal Cancer: a Case Control Study

Khan, Naveed Ali,Hussain, Mehwish,Rahman, Ata ur,Farooqui, Waqas Ahmed,Rasheed, Abdur,Memon, Amjad Siraj Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.17

Background: The abrupt rise of colorectal cancer in developing countries is raising concern in healthcare settings. Studies on assessing relationships with modifiable and non-modifiable risk factors in the Pakistani population have been limited. The present investigation was designed to examine associations of dietary practices, addictive behavior and bowel habits in developing colorectal cancer (CRC) among patients in a low-resource setup. Materials and Methods: An age-gender matched case control study was conducted from October 2011 to July 2015 in Karachi, Pakistan. Cases were from the surgical oncology department of a public sector tertiary care hospital, while their two pair-matched controls were recruited from the general population. A structured questionnaire was used which included questions related to demographic characteristics, family history, dietary patterns, addictive behavior and bowel habits. Results: A family history of cancer was associated with a 2.2 fold higher chance of developing CRC. Weight loss reduced the likelihood 7.6 times. Refraining from a high fat diet and consuming more vegetables showed protective effects for CRC. The risk of CRC was more than twice among smokers and those who consumed Asian specific addictive products as compared to those who avoid using these addictions (ORsmoking: 2.12, 95% CI: 1.08 - 4.17, ORpan: 2.92, 95% CI: 1.6 - 5.33, ORgutka: 2.13, 95% CI: 1.14 - 3.97). Use of NSAID attenuated risk of CRC up to 86% (OR: 0.14, 95% CI: 0.07 - 0.31). Conclusions: Most of the findings showed concordance with the literature elucidating protective effects of consuming vegetables and low fat diet while documenting adverse associations with family history, weight loss, constipation and hematochezia. Moreover, this study highlighted Asian specific indigenous addictive products as important factors. Further studies are needed to validate the findings produced by this research.