A Rule Based Segmentation Approaches to Extract Retinal Blood Vessels in Fundus Image

The physiological structures of the retinal blood vessel are one of the key features that visible in the retinal images and contain the information associate with the anatomical abnormalities. It is accepted all over the world to judge the cardiovascular and retinal disease. To avoid the risk of visual impairment, appropriate vessel segmentation is mandatory. Here has proposed a segmentation algorithm that efficiently extracts the blood vessels from the retinal fundus image. The proposed segmentation algorithm is performed Lab and Principle Component (PC) based gray level conversion, Contrast Limited Adaptive Histogram Equalization (CLAHE), morphological operations, Local Property-Based Pixel Correction (LPBPC). For appropriate detection proposed vessels correction algorithm LPBPC that check the feature of the vessels and remove the wrong vessel detection. To measure the appropriateness of the proposed algorithm, the experimental results are compared with the corresponding ground truth images. The experimental results have shown that the proposed blood vessel algorithm is more accurate than the existing algorithms

A High-Throughput Size Exclusion Chromatography Method to Determine the Molecular Size Distribution of Meningococcal Polysaccharide Vaccine

Molecular size distribution of meningococcal polysaccharide vaccine is a readily identifiable parameter that directly correlates with the immunogenicity. In this paper, we report a size exclusion chromatography method to determine the molecular size distribution and distribution coefficient value of meningococcal polysaccharide serogroups A, C, W, and Y in meningococcal polysaccharide (ACWY) vaccines. The analyses were performed on a XK16/70 column packed with sepharose CL-4B with six different batches of Ingovax® ACWY, a meningococcal polysaccharide vaccine produced by Incepta Vaccine Ltd., Bangladesh. A quantitative rocket immunoelectrophoresis assay was employed to determine the polysaccharide contents of each serogroup. The calculated distribution coefficient values of serogroups A, C, W, and Y were found to be 0.26±0.16, 0.21±0.11, 0.21±0.11, and 0.14±0.12, respectively, and met the requirements of British Pharmacopeia. The method was proved to be robust for determining the distribution coefficient values which is an obligatory requirement for vaccine lot release

Automated measurement of penile curvature using deep learning-based novel quantification method

ObjectiveDevelop a reliable, automated deep learning-based method for accurate measurement of penile curvature (PC) using 2-dimensional images.Materials and methodsA set of nine 3D-printed models was used to generate a batch of 913 images of penile curvature (PC) with varying configurations (curvature range 18° to 86°). The penile region was initially localized and cropped using a YOLOv5 model, after which the shaft area was extracted using a UNet-based segmentation model. The penile shaft was then divided into three distinct predefined regions: the distal zone, curvature zone, and proximal zone. To measure PC, we identified four distinct locations on the shaft that reflected the mid-axes of proximal and distal segments, then trained an HRNet model to predict these landmarks and calculate curvature angle in both the 3D-printed models and masked segmented images derived from these. Finally, the optimized HRNet model was applied to quantify PC in medical images of real human patients and the accuracy of this novel method was determined.ResultsWe obtained a mean absolute error (MAE) of angle measurement <5° for both penile model images and their derivative masks. For real patient images, AI prediction varied between 1.7° (for cases of ∼30° PC) and approximately 6° (for cases of 70° PC) compared with assessment by a clinical expert.DiscussionThis study demonstrates a novel approach to the automated, accurate measurement of PC that could significantly improve patient assessment by surgeons and hypospadiology researchers. This method may overcome current limitations encountered when applying conventional methods of measuring arc-type PC

Edge-Based and Prediction-Based Transformations for Lossless Image Compression

Pixelated images are used to transmit data between computing devices that have cameras and screens. Significant compression of pixelated images has been achieved by an “edge-based transformation and entropy coding” (ETEC) algorithm recently proposed by the authors of this paper. The study of ETEC is extended in this paper with a comprehensive performance evaluation. Furthermore, a novel algorithm termed “prediction-based transformation and entropy coding” (PTEC) is proposed in this paper for pixelated images. In the first stage of the PTEC method, the image is divided hierarchically to predict the current pixel using neighboring pixels. In the second stage, the prediction errors are used to form two matrices, where one matrix contains the absolute error value and the other contains the polarity of the prediction error. Finally, entropy coding is applied to the generated matrices. This paper also compares the novel ETEC and PTEC schemes with the existing lossless compression techniques: “joint photographic experts group lossless” (JPEG-LS), “set partitioning in hierarchical trees” (SPIHT) and “differential pulse code modulation” (DPCM). Our results show that, for pixelated images, the new ETEC and PTEC algorithms provide better compression than other schemes. Results also show that PTEC has a lower compression ratio but better computation time than ETEC. Furthermore, when both compression ratio and computation time are taken into consideration, PTEC is more suitable than ETEC for compressing pixelated as well as non-pixelated images

Performance Analysis of Mesh Based Enterprise Network Using RIP, EIGRP and OSPF Routing Protocols

Computer network communication is quickly growing in this pandemic situation. Phone conferencing, video streaming and sharing file/printing are all made easier with communications technologies. Data transmitted in time with little interruption become a significant achievement of wireless sensor networks (WSNs). A massive network is interconnection computer networks in the globe connected by the Internet, and the Internet plays a critical role in WSNs. Data access is a key element of any enterprise network, and the routing protocol is used to transmit data or access data. Due to the growing use of WSNs, it is essential to know about the network structure, the routing protocol. The routing protocols must be used to route all data sent over the Internet between the source and the destination. Which chooses the optimum routes between any two nodes in an enterprise network. This research focused on how the routing table will determine the optimum path/route of data packets to be transmitted from source to destination. The performance of three routing protocols, Routing Information Protocol (RIP), Enhanced Interior Gateway Routing Protocol (EIGRP) and Open Shortest Path First (OSPF), is investigated in this research for the massive mesh based enterprise wireless sensor network. We also investigated the behaviors of end-to-end packet latency, convergence time on flapping connections and average point-to-point throughput (bits/sec) between network links. Finally, the simulation results are compared to the efficacy and performance of these protocols implemented in the wireless LAN and internet-based wireless sensor network

Changing institutional landscape and transportation development in Dhaka, Bangladesh

Cities in the global south, constrained by limited resources, face challenges in delivering efficient transportation infrastructure and services to support their rapidly growing urban populations. Dhaka, serves as an example, as it grapples with the increasing demand driven by population growth, exacerbated by factors like land and resource scarcity, as well as intricate geopolitical dynamics. Despite the construction of a metro rail and other similar mass transit options, Dhaka continues to face difficulties in meeting the increasing transportation demand, posing a persistent challenge. Multiple institutions, including a coordination authority, are working to provide improved transportation services by implementing diverse strategic approaches focusing on infrastructure development, and formulating policies aimed at facilitating better mobility and accessibility. Over the past fifty years, the institutional arrangement and roles within the transportation system have changed. This study examines the institutional arrangements and how they have evolved, along with reviewing transportation development policies during this period. The findings indicate the involvement of multiple organizations in the city's transportation system performing distinct activities–– administrative, coordinating, legislative, regulatory, construction and management, and law enforcement. These authorities often encounter challenges fulfilling their responsibilities stemming from differences in vision, organizational structure, jurisdiction and most notably, lack of coordinatoon, resulting in ineffective infrastructure development and duplicated activities. To improve the transportation system, this study recommends better equipping the existing coordinating authority and expanding its jurisdiction to include other institutions. This approach aims to enhance coordination and address the challenges faced by Dhaka's transportation system, ultimately facilitating improved mobility and accessibility for the city's growing population

Bottleneck analysis of maternal and newborn health services in hard-to-reach areas of Bangladesh using 'TANAHASHI' framework': An explanatory mixed-method study.

Maternal and Newborn Health (MNH) is of paramount importance in the realm of attaining sustainable development goals that also focuses on universal health coverage (UHC). The study aimed at identifying and exploring the bottlenecks in MNH services in Hard-to-reach (HtR) areas of Bangladesh using the Tanahashi framework exploring the possible remedial approaches. The study was conducted in four different types of HtR areas (hilly, coastal, lowlands, and river islands) by utilizing a sequential explanatory mixed-method design. Overall, we collected information from 20 health facilities and 2,989 households by interviewing 2,768 recently delivered women (RDW) with a structured questionnaire and qualitative interviews (n = 55) of facility managers, local stakeholders, RDWs, and health care providers (HCP). The quantitative data were analyzed principally for descriptive statistics and the qualitative data was analyzed by utilizing the thematic approach. Antenatal care, under-5 care, and family planning services were available in almost all the facilities. However, Normal vaginal deliveries were performed in 55.6% of the union-level facilities. Only 40% of sub-district level facilities had provision for C-sections. Blood transfusion services were available in only 20.1% of facilities, whereas laboratory services were obtainable in 51.7% of facilities. Overall, the bottlenecks were identified in cases of availability of drugs, human resources, transportation, lack of knowledge regarding different essential services and health components, out of pocket expenditure etc. There have been several remedial approaches suggested from both the demand and supply side that included incentives for care providers for staying in these areas, a coordinated transport/referral system, and health education campaigns. More research works are warranted in HtR areas, especially to test the proposed interventions. Meanwhile, the government should take the necessary steps to overcome the bottlenecks identified

Table1_Automated measurement of penile curvature using deep learning-based novel quantification method.docx

ObjectiveDevelop a reliable, automated deep learning-based method for accurate measurement of penile curvature (PC) using 2-dimensional images.Materials and methodsA set of nine 3D-printed models was used to generate a batch of 913 images of penile curvature (PC) with varying configurations (curvature range 18° to 86°). The penile region was initially localized and cropped using a YOLOv5 model, after which the shaft area was extracted using a UNet-based segmentation model. The penile shaft was then divided into three distinct predefined regions: the distal zone, curvature zone, and proximal zone. To measure PC, we identified four distinct locations on the shaft that reflected the mid-axes of proximal and distal segments, then trained an HRNet model to predict these landmarks and calculate curvature angle in both the 3D-printed models and masked segmented images derived from these. Finally, the optimized HRNet model was applied to quantify PC in medical images of real human patients and the accuracy of this novel method was determined.ResultsWe obtained a mean absolute error (MAE) of angle measurement DiscussionThis study demonstrates a novel approach to the automated, accurate measurement of PC that could significantly improve patient assessment by surgeons and hypospadiology researchers. This method may overcome current limitations encountered when applying conventional methods of measuring arc-type PC.</p