HYBRID BINARIZTION TECHNIQUE FOR HISTORICAL MANUSCRIPTS

This paper presents a new hybrid approach for the binarization and enhancement of Historical Manuscript. This paper deals with degradations which occur due to shadows, non-uniform illumination, low contrast and strain. We follow two distinct method of Binarization with a pre-processing procedure using a adaptive Wiener filter, a rough estimation of foreground regions and a background surface calculation by interpolating neighboring background intensities. Further logical anding of the calculated background surface with compliment of second method result, performing final thresholding and post-processing in order to improve the quality of text regions. After extensive experiments, our method demonstrated superior performance against some wellknown techniques on numerous degraded document images as well as on Historical Manuscript in both manners qualitatively and quantitatively

Quantum computing challenges in the software industry. A fuzzy AHP-based approach

publishedVersio

Behavioral reasoning theory (BRT) perspectives on E-waste recycling and management

Each year, millions of tons of electronic waste (or e-waste) are generated worldwide, thus, fueling concerns among scholars, practitioners, policymakers, and governments about e-waste recycling and management. The past few years have witnessed a growing interest among scholars to examine the behavioral issues concerning e-waste recycling. However, most of the existing studies have focused on adopting e-waste recycling and related innovations. It is already known that ‘reasons for’ and ‘reasons against’ the adoption of any innovation are quantitatively different. The current study bridges this gap by utilizing a novel consumer behavior framework called behavioral reasoning theory (BRT) to study e-waste recycling attitudes and intentions. The study examined the relative influence of ‘reasons for’ and ‘reasons against’ in predicting attitude and intentions within the context of e-waste recycling by using a single framework. The developed model was tested using structural equation modeling with 774 Japanese consumers. The study also examined the moderating role of environmental assessment and environmental concerns in influencing the studied associations. The results suggest that ‘reasons for’ was positively associated with attitude and intentions. The consumer values shared negative associations only with ‘reasons against.’ The study findings offer interesting insights for service providers, policymakers, and governments.publishedVersio

Comparison of hysteroscopic and laparoscopic myomectomy in large type 2 submucous leiomyomas

Background: Uterine leiomyomas are the most common benign tumors, affecting 30% of women of reproductive age. Submucous myomas are seen in 5.5-10% of all myomas. This study aimed to compare clinical, peri, and post-op outcomes of hysteroscopic and laparoscopic myomectomy in large type 2 submucous myomas. Methods: A prospective study was performed on 50 patients with large submucous type 2 leiomyomas measuring 3-5cm from October 2020 to August 2022. Patients were randomized into two groups of 25 each. Group A underwent hysteroscopic myomectomy and group B underwent laparoscopic myomectomy. Results: There was no significant difference in the demographic data of both groups except parity. Perioperative outcomes including bleeding, pain, and hospital stay were significantly higher in the laparoscopy group. None of our patients had air embolism. One patient had blindness in the postoperative period. 2 patients had uterine perforation in the hysteroscopy group. Postoperative pain was higher in the laparoscopy group. Recurrence at 3 months was seen in 2 patients of group A. Asherman syndrome was seen in group A. Single-stage success rate was seen higher in the laparoscopy group. Conclusions: Laparoscopy and hysteroscopy both are feasible techniques of myomectomy for submucous leiomyomas but for removal of large submucous leiomyomas laparoscopy myomectomy is considered better. For successful removal of large myomas in single-stage hysteroscopy, use of hysteroscopic morcellation should be considered

Design of Swap Space in Virtual Memory Management System

Abstrac

A Hybrid Convolutional Network and Long Short-Term Memory (HBCNLS) model for Sentiment Analysis on Movie Reviews

This paper proposes a hybrid model (HBCNLS) for sentiment analysis that combines the strengths of multiple machine learning approaches. The model consists of a convolutional neural network (CNN) for feature extraction, a long short-term memory (LSTM) network for capturing sequential dependencies, and a fully connected layer for classification on movie review dataset. We evaluate the performance of the HBCNLS on the IMDb movie review dataset and compare it to other state-of-the-art models, including BERT. Our results show that the hybrid model outperforms the other models in terms of accuracy, precision, and recall, demonstrating the effectiveness of the hybrid approach. The research work also compares the performance of BERT, a pre-trained transformer model, with long short-term memory (LSTM) networks and convolutional neural networks (CNNs) for the task of sentiment analysis on a movie review dataset.

Preparation and Evaluation of Sodium Alginate Microparticles using Pepsin

Aim: The main aim of this article is to prepare and evaluate sodium alginate microparticles and evaluate on the basis of their characterization. The drug is dissolved, encapsulated or attached to a microparticles matrix. Depending upon method of preparation microparticles were obtained. Microparticles were developed as a carrier for vaccines and other disease like rheumatoid arthritis, cancer etc. Microparticles were developed to increase the efficacy of active pharmaceutical ingredient to a specific targeted site. Material and Method: Microparticles of Sodium Alginate, Pepsin and Calcium Chloride were prepared in six batches (A-F) with different ratio of sodium alginate and calcium chloride respectively i.e. (0.25:2.5), (0.25:5), (0.25:7.5), (0.5:2.5), (0.5:5), (0.5:7.5) by using a homogenizing method. Microparticles were evaluated for particle size distribution, zeta potential and morphology. Result and Discussion:  The normal particle size of each of the six batches were analyzed by Zeta Sizer (Delsa C Particle Analyzer) and it was found that the Batch B (0.25:5) delivered the best microparticles with size distribution of 1.2731 (µm). All batches were seen under Motic magnifying microscope by using the Sulforhodamine B (M.W. 479.02) color as staining dye. Microparticles was found to be semi spherical in shape. Conclusion: Results of all the six batches was contrasted based on particle size investigation, zeta potential and morphology. Batch B (0.25:5) was considered as the best formulation. Key words:  Micro Particle, Pepsin, Sodium Alginate and Calcium Chloride, Sulforhodamine B, Zeta Sizer

Quantum computing challenges in the software industry. A fuzzy AHP-based approach

ContextThe current technology revolution has posed unexpected challenges for the software industry. In recent years, the field of quantum computing (QC) technologies has continued to grow in influence and maturity, and it is now poised to revolutionise software engineering. However, the evaluation and prioritisation of QC challenges in the software industry remain unexplored, relatively under-identified and fragmented.ObjectiveThe purpose of this study is to identify, examine and prioritise the most critical challenges in the software industry by implementing a fuzzy analytic hierarchy process (F-AHP).MethodFirst, to identify the key challenges, we conducted a systematic literature review by drawing data from the four relevant digital libraries and supplementing these efforts with a forward and backward snowballing search. Second, we followed the F-AHP approach to evaluate and rank the identified challenges, or barriers.ResultsThe results show that the key barriers to QC adoption are the lack of technical expertise, information accuracy and organisational interest in adopting the new process. Another critical barrier is the lack of standards of secure communication techniques for implementing QC.ConclusionBy applying F-AHP, we identified institutional barriers as the highest and organisational barriers as the second highest global weight ranked categories among the main QC challenges facing the software industry. We observed that the highest-ranked local barriers facing the software technology industry are the lack of resources for design and initiative while the lack of organisational interest in adopting the new process is the most significant organisational barrier. Our findings, which entail implications for both academicians and practitioners, reveal the emergent nature of QC research and the increasing need for interdisciplinary research to address the identified challenges.</p

Successful Percutaneous Management of LVAD Outflow Graft Stenosis: Role of Invasive Hemodynamics in Decision Making

Left ventricular assist device (LVAD) outflow graft stenosis (OGS) is a rare but lethal complication. We present a case of a 79-year-old male with pertinent past medical history of an LVAD implanted as destination therapy, stage III chronic kidney disease, and hypertension. He was admitted for low-flow alarms, and the echocardiogram showed stable right ventricle function and no pericardial effusion. Invasive hemodynamic assessments demonstrated a peak-to-peak gradient of 90 mm Hg in the outflow graft between the mid and distal ends of the graft on pullback. Contrast angiography confirmed OGS. The OGS was successfully treated with a VBX-covered stent (Gore). OGS should be considered when low flow alarms are found in patients with LVADs