1,449 research outputs found
Extending middleware frameworks for wireless sensor networks
No full textWe define sensor middleware as the binding code mainly running between the sensor OS and applications providing programming abstractions to bridge the gap between application developers and low-level hardware. Hence it serves the purpose of simplified integration of components developed by multiple technology vendors. Middleware for distributed systems is a relatively mature research area with a considerable amount of work done on the aforementioned topics. In this paper we explain why standard distributed systems middleware solutions are not suitable to address wireless sensor network (WSN) problems. Illustrated by a health monitoring use case, we propose an enhanced middleware framework that better addresses the needs of WSN applications.sponsorship: This research is partially funded by the Interuniversity Attraction Poles Programme Belgian State, Belgian Science Policy, and by the Research Fund K.U. Leuven.status: Publishe
Comparing Inception V3, VGG 16, VGG 19, CNN, and ResNet 50: A Case Study on Early Detection of a Rice Disease
No full textRice production has faced numerous challenges in recent years, and traditional methods are still being used to detect rice diseases. This research project developed an automated rice blast disease diagnosis technique based on deep learning, image processing, and transfer learning with pre-trained models such as Inception V3, VGG16, VGG19, and ResNet50. The public dataset consists of 2000 images; about 1200 images belong to the leaf blast class, and 800 to the healthy leaf class. The modified connection-skipping ResNet 50 had the highest accuracy of 99.75% with a loss rate of 0.33, while the other models achieved 98.16%, 98.47%, and 98.56%, respectively. Furthermore, ResNet 50 achieved a validation accuracy of 99.69%, precision of 99.50%, F1-score of 99.70, and AUC of 99.83%. In conclusion, the study demonstrated a superior performance and disease prediction using the Gradio web application
sj-docx-1-imj-10.1177_10815589221140597 – Supplemental material for Anemia prevalence time trends and disparities in the US population: examination of NHANES 1999–2020
No full textSupplemental material, sj-docx-1-imj-10.1177_10815589221140597 for Anemia prevalence time trends and disparities in the US population: examination of NHANES 1999–2020 by Yunjoo Hwang, Kripa R Ahuja, Syed M Haque, George F Jones, Adan Naseer, Oren Shechter, Simrah Siddiqui and Rehan Qayyum in Journal of Investigative Medicine</p
Estimating Passenger Car Equivalent Factors for Heterogeneous Traffic Using Occupancy-Density Linear Regression Model
No full textA variety of methods have been proposed in the existing literature for the estimation of passenger car equivalent (PCE) factors. These methods are based on the comparison of selected attributes of different vehicles. This research, for the first time, utilizes the basic notion of the linear relationship between road area occupancy and density for the estimation of PCE factors for different vehicle types in heterogeneous traffic. Aerial photographs obtained from an unmanned aerial vehicle (UAV) were analyzed to estimate the road area occupancy and the number of vehicles classified in seven selected groups. A linear least-squares regression model was developed between road area occupancy and classified vehicle count. The coefficients of the occupancy-density linear regression model were used to estimate PCE and motorcycle equivalent (MCE) factors. The comparison of the estimated set of PCE values with the values reported in the literature shows that PCE factors estimated using the proposed method are reasonable and produce a better occupancy-density relationship than the other studies. In comparison with the existing methods that rely on lane-based measurements, the proposed method is well suited for traffic with weak/no lane discipline, as it considers the entire road width and the dynamics of lateral movement of different types of vehicles. The proposed method does not need extensive traffic data of speeds, headways, flow rates, and so forth, and is applicable on aerial photographs obtained from other sources, such as satellites.Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported with funding from Exascale Open Data Analytics Lab, National Center for Big Data and Cloud Computing (NCBC) and the Higher Education Commission of Pakistan.
Acknowledgments
The authors are thankful to research students Syed Hassan Ali, Haseeb Ahmed, Zohaib Ahmed, Aqib Abbasi, Asad Rehan, Mirza Ali Haider, Syed Abbas Hasan Zaidi, and Omema for their help in this research
Mediapipe based Preprocessed VGGFace2 Dataset
No full textVGGFace2 Dataset and Face Mesh PreprocessingIntroductionThe VGGFace2 dataset is a large-scale face recognition dataset containing over 3.31 million images of 9,131 identities, with an average of 362 images per identity. The dataset is designed to include extensive variations in pose, age, illumination, ethnicity, and profession, making it one of the most diverse and challenging face recognition datasets available. For more details, please refer to the original publication:VGGFace2: A dataset for recognizing faces across pose and age - DOI: 10.48550/arXiv.1710.08092
Preprocessing Using MediaPipe 3D Face MeshOn this dataset, we applied the MediaPipe-based 3D face mesh algorithm to accurately detect faces while removing all background elements, including hair. Our preprocessing strictly retained facial landmarks, ensuring that only the essential facial features were preserved. This approach significantly enhanced the accuracy and generalization of our model, as the model was trained exclusively on landmark-based facial data.
Training and PerformanceThe preprocessed data was utilized to train Xception model, which resulted in remarkably accurate outcomes due to the strictly landmark-based facial representation. The model demonstrated robust performance including explainable-AI, proving that eliminating unnecessary background elements contributed positively to its efficiency and reliability.
CitationIf you use this dataset or the preprocessed version in your work, please cite both of the following:
VGGFace2 Dataset:
@article{Cao2018VGGFace2, title={VGGFace2: A dataset for recognizing faces across pose and age}, author={Cao, Qiong and Shen, Li and Xie, Weidi and Parkhi, Omkar M and Zisserman, Andrew}, journal={arXiv preprint arXiv:1710.08092}, year={2018}}
DOI: [10.48550/arXiv.1710.08092](https://doi.org/10.48550/arXiv.1710.08092) Preprocessed Dataset using MediaPipe:@dataset{Shah2025_MediaPipe_FaceMesh, title={MediaPipe-based 3D Face Mesh Preprocessed VGGFace2 Dataset}, author={Shah, Syed Taimoor Hussain and Shah, Syed Adil Hussain and Zamir, Ammara and Qayyum, Kainat and Shah, Syed Baqir Hussain and Fatima, Syeda Maryam and Deriu, Marco Agostino}, year={2025}, doi={10.5281/zenodo.15078557}} DOI: [10.5281/zenodo.15078557](https://doi.org/10.5281/zenodo.15078557)
ContactFor any questions or further details, please feel free to contact us.Syed Taimoor Hussain ShahPolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, ItalyEmail: [email protected]: 0000-0002-6010-677
Comparative analysis of Eosin-based fluorescence microscopy of non-neoplastic breast tissue and fibroadenoma
No full textFibroadenoma (FA) is one of the most frequently diagnosed benign neoplasm in
women. Various researches have reported increased risk of breast cancer in females with FA. It
stems from the proliferation of epithelial and stromal contents of the terminal duct lobular units
(TDLU`S) of breast tissue, that are the primary sites for the histopathologic assessment which is
the gold standard for the diagnosis of disease. However, this method is subjective and possess
interobserver variability. Therefore, new quantitative methods are required to aid in diagnosis.
Hence we evaluated fluorescence light intensity and its use in histopatholgic evaluation.
Aim: The goal of this research was to compare and quantify red and green fluorescence light
intensities of ductal cells and stroma of non-neoplastic breast tissue with fibroadenomatous tissue.
Method: A cross-sectional study was done in the Cell biology and histology lab of Ziauddin
University. 44 slides of normal breast tissue and 44 slides of diagnosed fibroadenomatous tissue
were taken from Dr Ziauddin Hospital, North Campus. Hematoxylin and eosin (H&E) staining of the slides were done following standard protocols. On microscopic examination, the changes in light
intensities of ductal cells and stroma of normal breast tissue and fibroadenoma were quantified
using dual channel fluorescence microscopy using Nikon NIS imaging software.
Results: The results demonstrated statistically significant increase (p-value <0.05) in mean red
(37.22±5.9) and green (22.47±6.6) light intensity of stroma in FA when compared with red (32.71±
6.7) and green (17.01±4.3) light intensity of normal breast tissue. Whereas, R/G ratio for normal
tissue was higher (1.95±0.11) than R/G for FA (1.74±0.37) with a p value of <0.05. Similarly, for
ductal cells; statistically significant (p value <0.05) increase in mean red (38.86±5.4) and green
(15.54±2.51) light intensity for FA was found when compared with red (29.62±1.89) and green
(12.60±1.67) intensity of normal tissue. R/G ratio for FA (2.5±0.24) was compared to be higher than
normal tissue (2.36±0.3) with a p value of <0.05.
Conclusion: The study suggests that fluorescence microscopy combined with quantitative
assessment fluorescence light intensities may may be a helpful tool for histomorphic evaluation of
the breast tissue
CSD 1982696: Experimental Crystal Structure Determination
No full textRelated Article: Kanwar Rehan, Maliha Asma, Colin D. McMillen, Andrei Sokolov, Manzar Sohail, Muhammad Sher, Munib Ahmed Shafique, Naheed Bukhari, Syed Ahmad Tirmizi|2020|Inorg.Chim.Acta|509|119690|doi:10.1016/j.ica.2020.119690,An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures
Hydraulic simulations to evaluate and predict design and operation of the Chashma Right Bank Canal
No full textIrrigation systems / Irrigation canals / Flow control / Velocity / Canal regulation techniques / Hydraulics / Simulation models / Design / Operations / Crop-based irrigation / Distributary canals / Water delivery / Policy / Protective irrigation / Water allocation / Water requirements / Sedimentation / Water distribution / Equity / Water conveyance / Pakistan / Chashma Right Bank Canal
Syed Manzoorul Islam’s Postmodern Tales: A Study
No full textThe paper brings into focus how Syed Manzoorul Islam, in his three-decade-long literary career, has mastered a narrative style that sets him apart from many of his Bengali contemporaries. It demonstrates all the traits unique to his storytelling: blurring of boundaries between dream and reality, self-reflexivity, irony, and humor. The research also encapsulates how Syed Islam is different from his contemporary short story writers in terms of constructing plot and character. It foregrounds the author’s capability of developing a diction which is completely his own. The paper discusses the postmodern features prevailing in his stories. It shows us how the author invites the readers to be a part of his discourses. It summarizes the author’s surrealist imagination which creates a world that is strangely familiar and unfamiliar at the same time. Overall, the research analyzes how the postmodern elements relate to the major themes of Syed Manzoorul Islam’s short stories.Keywords: Post-modernism, magic-realism, realism, psychoanalysis, political degeneratio
ICT to enhance the triangle of life : the soil, the seed, and the life-giver farmer
No full textThis paper reports on the outcomes of an ICT enabled social sustainability project “Green Lanka1” trialled in the Wilgamuwa village, which is situated in the Dambulla district of Sri Lanka. The main goals of the project were focused towards the provision of information about market prices, transportation options, agricultural decision support and modern agriculture practices of the farmer communities to improve their livelihood with the effective use of technologies. The project used Web and Mobile (SMS) enabled systems. The Green Lanka project was sponsored by the Information Communication Technology Agency (ICTA) of Sri Lanka under the Institutional Capacity Building Programme (ICBP) grant scheme which was sponsored by the World Bank. Six hundred families in Wilgamuwa village participated in the project activities. The project was designed, executed and studied through an Action Research approach. The lessons learned through the project activities provide an important understanding of the complex interaction between different stakeholders in the process of implementation of ICT enabled solutions within digitally divided societies. The paper analyses the processes used to reduce the resistance to change and improved involvement of farmer communities in ICT enabled projects. It also analyses the interaction between stakeholders involved in design and implementation of the project activities to improve the chances of project success
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