Enhancing Smart Home Security: Anomaly Detection and Face Recognition in Smart Home IoT Devices Using Logit-Boosted CNN Models.

Internet of Things (IoT) devices for the home have made a lot of people's lives better, but their popularity has also raised privacy and safety concerns. This study explores the application of deep learning models for anomaly detection and face recognition in IoT devices within the context of smart homes. Six models, namely, LR-XGB-CNN, LR-GBC-CNN, LR-CBC-CNN, LR-HGBC-CNN, LR-ABC-CNN, and LR-LGBM-CNN, were proposed and evaluated for their performance. The models were trained and tested on labeled datasets of sensor readings and face images, using a range of performance metrics to assess their effectiveness. Performance evaluations were conducted for each of the proposed models, revealing their strengths and areas for improvement. Comparative analysis of the models showed that the LR-HGBC-CNN model consistently outperformed the others in both anomaly detection and face recognition tasks, achieving high accuracy, precision, recall, F1 score, and AUC-ROC values. For anomaly detection, the LR-HGBC-CNN model achieved an accuracy of 94%, a precision of 91%, a recall of 96%, an F1 score of 93%, and an AUC-ROC of 0.96. In face recognition, the LR-HGBC-CNN model demonstrated an accuracy of 88%, precision of 86%, recall of 90%, F1 score of 88%, and an AUC-ROC of 0.92. The models exhibited promising capabilities in detecting anomalies, recognizing faces, and integrating these functionalities within smart home IoT devices. The study's findings underscore the potential of deep learning approaches for enhancing security and privacy in smart homes. However, further research is warranted to evaluate the models' generalizability, explore advanced techniques such as transfer learning and hybrid methods, investigate privacy-preserving mechanisms, and address deployment challenges.

Global geographical discrepancy in numerical distribution of cardiovascular surgeries and human resource development in South Asia.

Objective: The region South Asia is in the south-central part of the Asian continent. The 8 countries of the area, Afghanistan, Bangladesh, Bhutan, India, Nepal, The Maldives, Pakistan, and Sri Lanka collectively possess 1.8 billion people living in 5.1 million square miles. Covering 2.96% of World's surface, this area is inhabited by 23.9% of the world population. The objective of this study was to observe the number of cardiac operations in South Asia and the human resource development facilities of cardiac surgery in the region. Methods: Information was collected from the surgeons and anesthetists through personal visits, phone calls, and emails. The websites of various organizations were also checked. Results: The estimated number of cardiac operations collectively performed in the South Asian countries was between 250,000 and 300,000 as of 2019. With more than 6 times the US population, these nations combined performed less than half of the annual number of cardiac operations performed in the United States. The number of operations per million population ranged from 62 to 271 in different countries. This indicates that there should be more capacity-building of surgeons to meet the growing demand of operations. India, Pakistan, Bangladesh, Sri Lanka, and Nepal have their own education and training systems for cardiovascular surgeons. A substantial portion of the seats available for cardiovascular surgery courses remained vacant in South Asia these days. Conclusions: Five countries have their various surgical education and training programs. There should be coordinated efforts to increase the production of new cardiac surgeons in the region.

Surveillance and Assessment of Risk Factors for Newcastle Disease Virus from Live Bird Retail Stalls in Lahore District of Pakistan.

Live bird markets (LBMs) in Asian countries are considered hubs for the spread of several poultry viruses. In Pakistan, there is a lack of uniformity in practices used in LBMs, which leads to the spread of poultry diseases. A cross-sectional survey was conducted in June-October 2017 to determine the circulation of Newcastle disease virus (NDV) in chickens being sold in live bird retail stalls (LBRSs) and to identify potential risk factors associated with estimated prevalence. A total of 189 stalls (n = 1134 birds) distributed in eight administrative towns of Lahore were visited. A pool of six oropharyngeal swabs was collected from each stall and tested by real-time reverse transcriptase PCR for the presence of NDV. Forty-two out of 189 swabs were found positive with an overall prevalence of 22.22% (95% confidence interval [Cl]: 16.88%-28.67%). Data for 11 potential risk factors acquired through questionnaires were analyzed by survey-weighted logistic regression and prevalence odds ratios (ORs) for associated risk factors were calculated. A final multivariable model identified three risk factors for NDV prevalence in LBRSs, including trading other poultry breeds alongside broilers (OR = 2.41; 95% confidence interval [CI] = 1.5-6.1), purchasing birds from mixed sources (OR = 3.12; 95% CI = 1.4-11.9), and number of birds sold per day (OR = 6.32; 95% CI = 1.9-23.5). Additionally, 24 selected samples were sequenced and phylogenetic analysis of the complete fusion gene (1662 bp) revealed that all isolates belonged to Subgenotype VII.2. This study provides important information on the epidemiology of NDV in Pakistan and highlights the importance of implementing surveillance and biosecurity practices in LBRSs.

Vigilancia y evaluación de factores de riesgo para el virus de la enfermedad de Newcastle en puestos de venta al menudeo de aves vivas en el distrito de Lahore en Pakistán. Los mercados de aves vivas (LBM, por sus siglas en inglés) en los países asiáticos se consideran centros de propagación de varios virus aviares. En Pakistán, existe una falta de uniformidad en las prácticas utilizadas en los mercados de aves vivas, lo que conduce a la propagación de enfermedades avícolas. Se realizó una encuesta transversal de junio a octubre del 2017 para determinar la circulación del virus de la enfermedad de Newcastle (NDV) en pollos que se venden en puestos minoristas de aves vivas y para identificar posibles factores de riesgo asociados con la prevalencia estimada. Se visitó un total de 189 puestos (n = 1134 aves) distribuidos en ocho ciudades administrativas de Lahore. Se recolectó un grupo de seis hisopos orofaríngeos de cada puesto y se analizó mediante transcripción reversa y PCR en tiempo real para detectar la presencia del virus de Newcastle. Cuarenta y dos de los 189 hisopos resultaron positivos con una prevalencia general del 22.22 % (intervalo de confianza [IC] del 95 % = 16.88­28.67). Los datos para 11 factores de riesgo potenciales adquiridos a través de cuestionarios se analizaron mediante regresión logística ponderada por encuesta y se calcularon las razones de probabilidad (OR) de prevalencia para los factores de riesgo asociados. Un modelo multivariable final identificó tres factores de riesgo para la prevalencia del virus de Newcastle en puestos minoristas de aves vivas, incluido el comercio de otras razas de aves de corral junto con pollos de engorde (OR = 2.41; IC del 95 % = 1.5­6.1), la compra de aves de fuentes mixtas (OR = 3.12; IC del 95 % = 1.4 ­11.9), y número de aves vendidas por día (OR = 6.32; IC 95% = 1.9­23.5). Además, se secuenciaron 24 muestras seleccionadas y el análisis filogenético del gene de fusión completo (1662 pb) reveló que todos los aislamientos pertenecían al subgenotipo VII.2. Este estudio brinda información importante sobre la epidemiología del virus de Newcastle en Pakistán y destaca la importancia de implementar prácticas de vigilancia y bioseguridad en los en puestos minoristas de aves vivas.