A Security Framework for IOT Based Smart Home Automation System

The Internet of Things (IOT) is a new platform for our technology. Though of IOT, we can control our daily life work such as home application, control and communication systems, easy communication systems, improve our digital services etc. The Internet of Things (IOT) is joining our daily contents information wisely to the internet to make communication between objects and people and among themselves. In this paper, we show an improved home automation by the help of IOT. For calculating response time of IOT, we need fog computing platform. Fog computing also known as fogging or edge computing which is built by Cisco and it is extended the version of cloud computing through a network. In our proposed system, we use motion sensor, SBC-PT which is a network access component and daily life component in home. We can monitor and control that equipment by the approach of IOT based system. The home automation system uses the portable devices as a user interface. They can connect with home automation network through an internet approach. The user will move straightly with the system via control interface whereas home apparatus are remotely controlled through sensor and server. The home automation system has an additional property that enhances the facet of defense from unauthorized accidents. The communication with the server consents the user to pick out the receivable device. This design proposed an efficient control of home automation system

A Comparison of Semi-Parametric and Nonparametric Methods for Estimating Mean Time to Event for Randomly Left Censored Data

The aim of this study was to make a comparison among existing estimation methods (Kaplan-Meier, Nelson-Aalen and Regression on Ordered Statistics (ROS)) for randomly left censored time to event data under selected distributions and for different level of censoring and sample sizes in order to determine the strength of these methods based on simulated data. Comparisons among the methods are made on the basis of unbiasedness and Monte Carlo Standard Error of the summary statistics (mean time to event) obtained by those methods under different conditions

Prevalence of cervical intraepithelial neoplasia and cervical carcinoma in a tertiary care hospital at Rajshahi

Background: Cervical intraepithelial neoplasia (CIN) is a precancerous cervical condition with the potential to develop into cervical carcinoma if untreated. While research on CIN and cervical carcinoma exists in various regions, the Rajshahi area lacks such investigations. Examining the prevalence of CIN and cervical carcinoma in this region is essential. This study aimed to assess the prevalence of CIN and cervical carcinoma in a tertiary care hospital at Rajshahi in Bangladesh. Methods: This cross-sectional descriptive study was conducted at the department of pathology, Rajshahi medical college, and the department of gynaecology and obstetrics, Rajshahi medical college hospital, Rajshahi, Bangladesh from July 2019 to June 2022. A total of 1000 VIA test-positive cases of cervical lesions were enrolled as study subjects purposively. Data were processed and analyzed by the MS office tools. Results: Cervical carcinoma was identified through cytological analysis in 4.6% of cases, with 7.6% exhibiting high-grade squamous intraepithelial lesions (HSIL) and 13.1% showing low-grade squamous intraepithelial lesions (LSIL). Through histopathological analysis, cervical carcinoma found in 5.3% of cases, CIN-grade III (CIN-III) in 7.1%, and CIN-II and CIN-I in 2.2%, 16.4% of cases, respectively. Human papillomavirus (HPV) vaccination rate was 0.70%. Conclusions: The prevalence of CIN and cervical carcinoma in the Rajshahi region of Bangladesh is alarmingly high. These findings underscore the pressing need for the immediate implementation of a comprehensive vaccination and awareness development program for cervical carcinoma

An Analytic Real-Time Framework for IoT based Home Automation System

The Internet of Things or IoT means the ability to connect billions of physical devices around the world that are now linking to the internet for collecting and sharing data. Internet of Things (IoT) technologies is used to sense the real-time primordial manufacture data and included the energy alliance data and the provision circumstance data. The Internet of Things (IoT) will approve any contents to be sensed or monitored remotely wherever there any remaining network infrastructure, making amenities for the integration of the actual world into computer-based systems. Real-time narrates the path of flowing media is processing. In the real-time procedure, anyone can entrance information barring to narrate for it and save our time. In our proposed system, we build a system where we calculate real-time. To compute real-time, we need an IoT based automated system. And here we use an IoT based home automation system. We are passing data through the system for collecting data with the help of Cisco Packet Tracer simulator. For calculating real-time performance, we use six performance metrics to evaluate the event detection system performance. They are sensitivity, specificity, precision, accuracy, F1-score, and G-mean

The role of the initial modality in the investigation of thyroid lesions

Background: Partial or complete thyroidectomies are frequently encountered via the working towards pathologist and the opportunity of neoplastic disease is of principal problem in patients with thyroid nodules. Pathological comparison of these specimens ranged from non-neoplastic lesion to exceedingly aggressive malignancy. The aim of this study is to assess the role of the initial modality in the investigation of thyroid lesions. Methods: This is an observational study. The study used to be carried out in the admitted patient’s department of histopathology, National institute of ear, nose and throat, Dhaka. Bangladesh. In Bangladesh for the duration of the period from June 2021 to May 2022. Results: This study shows that according to 301 patients where, most of the patients in initial modality in the investigation of thyroid lesions 95 (31.56%) were 40 to 49 years and the minimum sex distribution of study 105 (34.88%) belongs to males. Non-neoplastic of goiter were 194 (64.45%), benign cyst was 43 (14.29%), DeQuervains (Subacute) thyroiditis 11 (3.65%), Lymphocytic thyroiditis were 8 (2.65%) and hashimoto thyroiditis were 3 (1.0%). And acfemalesg to neoplastic of papillary carcinoma were 30 (9.97%), Follicular neoplasm were 9 (2.99%) and Anaplastic carcinoma were 3 (1.0%). Conclusions: Thyroid lesions are more common in female. The majority of the thyroid nodules are either non-neoplastic or benign neoplasm. Thyroid lesions present a dependable analysis and is an incredible first line technique for investigating the nature of lesion

Identifying Lung Cancer Using CT Scan Images Based On Artificial Intelligence

Lung cancer appears to be the common reason behind the death of human beings at some stage on the planet. Early detection of lung cancers can growth the possibility of survival amongst human beings. The preferred 5-years survival rate for lung most cancers sufferers will increase from 16% to 50% if the disease is detected in time. Although computerized tomography (CT) is frequently more efficient than X-ray. However, the problem regarded to merge way to time constraints in detecting this lung cancer concerning the numerous diagnosing strategies used. Hence, a lung cancer detection system that usage of image processing is hired to categorize lung cancer in CT images. In image processing procedures, procedures like image pre-processing, segmentation, and have extraction are mentioned intimately. This paper is pointing to set off the extra precise comes approximately through making use of distinctive improve and department procedures. In this proposal paper, the proposed method is built in some filter and segmentation that pre-process the data and classify the trained data. After the classification and trained WONN-MLB method is used to reduce the time complexity of finding result. Therefore, our research goal is to get the maximum result of lung cancer detection

Home environment factors associated with early childhood development in rural areas of Bangladesh: evidence from a national survey

BackgroundKnowing the relationship between the factors related to home environment and early childhood development (ECD) in Bangladeshi children aged 3 to 4  years would help to find out appropriate interventions for the children with lower ECD outcomes. Therefore, we aimed to understand the relationship between the home environment factors and ECD in rural Bangladeshi children aged 3 to 4  years.MethodsWe used data from the Multiple Indicator Cluster Survey (MICS) 2019, and included 7,326 rural children aged 3 to 4  years. The ECD index (ECDI) included four domains: literacy-numeracy, learning, physical and socio-emotional development. If a child met at least three of these four domains, the child was indicated as developmentally “on track”.ResultsThe findings show that 27.4% of rural children missed to reach developmentally on-track while 72.2% of children did not attain the literacy-numeracy domain of ECD. The home environment factors including parental participation in children’s activities, was found to be associated with ECD. For instance, reading books to child had 26% (aOR = 1.26, 95% CI = 1.08–1.48), and telling stories to child had 29% (aOR = 1.29, 95% CI = 1.09–1.53) more developmentally on-track in overall ECDI. Similar associations between home environment factors and specific ECD domains were also obtained. We also identified that children aged 4  years, girls, and children of mothers with higher socio-economic status (SES) were higher developmentally on-track than their counterparts.ConclusionHome environment factors like reading books and telling stories to children were found to be significantly associated with ECD in rural areas of Bangladesh. Our study’s findings would assist in implementing the essential public health intervention to enhance the ECD program especially in the rural Bangladeshi context

Letrozole versus dienogest in endometrioma recurrent after surgery: a randomized controlled trial

Background: Letrozole is a third-generation aromatase inhibitor. As there is aberrant aromatase production by endometriotic stromal cells and the growth and regression of endometriosis is estrogen-dependent, the use of letrozole to reduce the size and symptoms of endometrioma especially in recurrent cases is a promising medical intervention. Dienogest is a fourth-generation progestin which is being used for the treatment of endometriosis due to its antiproliferative and antiangiogenic properties on endometrial tissue. The present study was conducted to compare the effects of letrozole and dienogest on endometrioma recurrent after surgery.Methods: This randomized controlled study was conducted on 38 women having recurrence of endometrioma after surgery. They were randomly assigned to receive either letrozole (2.5 mg daily) or dienogest (2 mg once daily) for 6 months. Size of the endometrioma was measured by transvaginal ultrasound and the pain (dysmenorrhoea) was measured on a visual analog scale (VAS) of 0-10, prior to treatment and after 3 and 6 months of treatment.Results: The mean size of endometrioma was reduced from a baseline of 6.06±2.40 cm to 5.23±1.37 cm and to 4.59±1.25 cm after 3 and 6 months of treatment with letrozole. While with dienogest the reduction was from a baseline of 6.67±1.31 cm to 4.83±1.50 cm and to 3.80±1.34 cm after 3 and 6 months of treatment. The difference between the two groups was not statistically significant but dienogest yielded better result in terms of effect size. Decrease in pain (dysmenorrhoea) was highly significant with both the drugs.Conclusions: In terms of reduction of the size of endometrioma, dienogest yields better results than letrozole. Both the drugs are highly effective in alleviating pain (dysmenorrhoea)