No abstract

No abstract

The open communication medium of the Internet of Things (IoT) is more vulnerable to security attacks. As the IoT environment consists of distributed power limited units, the routing protocol used for distributed routing should be light-weighted compared to other centralized networks. In this situation, complex security algorithms and routing mechanisms affect the generic data communications in IoT platforms. To handle this problem, this proposed system develops a cooperative and feedback-based trustable energy-efficient routing protocol (CFTEERP). This protocol calculates local trust value (LTV) and global trust value (GTV) of each node using node attributes and K-means-based feedback evaluation procedures. The K-means clustering algorithm leaves out the distorted node routing metrics and misbehaving node metrics for all channels. This proposed CFTEERP uses the nearest secure node costs to increase the network lifetime without selecting the nearest nodes for routing the data. In this work, secure routing is initiated using multipath routing strategy that analyses LTV, GTV, next trustable node, average throughput, energy consumption, average packet delivery ratio (PDR) and traffic various metrics of entire IoT communication. The technical aspects of proposed system are implemented to solve different existing techniques' limitations.In the comparative experiment, the proposed method provides 90% of PDR and a minimal energy consumption rate of 25% lesser than the existing systems against different malicious attacks.

Background: Depression is found to be common among patients with diabetes and it is associated with poor outcomes in disease control. Mani objective of the study was to study the prevalence and occurrence of depression and anxiety in patients of type 2 diabetes mellitus (T2DM). Materials:115 adults with T2DM without prior diagnosis of depression and 115 matched controls were evaluated. Sociodemographic and relevant clinical variables were collected. They were evaluated for depression and anxiety using Hamilton Depression Rating Scale and Hamilton Anxiety Rating Scale respectively. Results: Significantly larger proportion of diabetic patients had depression [32 (27.8%) vs. 11 (9.57%), P = 0.005), anxiety (38 (33%) vs. 16 (13.9%, P = 0.005) and comorbid depression and anxiety (28 (24.3%) vs. 10 (8.7%), P = 0.005) as compared to healthy controls. The prevalence rate of depression was higher in age between 41 and 60 years (18.8% vs. 7.6%, respectively) in diabetic and healthy control group. Diabetic women had higher depression (21.2% vs. 8.7%) and anxiety (18.8% vs. 9.7%) than men. Depression was found significantly associated with retinopathy 28.6% (p=0.005), nephropathy 16.3% (p=0.005) and ischemic heart disease (IHD) 17.2% (p=0.005) in the present study. Comorbid depression and anxiety was significantly associated with age (40-60 years), obesity (BMI ≥ 25 kg/m2), poor glycemic control (≥7.5%), insulin therapy, nephropathy, neuropathy, and IHD but no significant association was found with education level. Conclusion: This study found a high proportion of depression and anxiety among patients with T2DM. Public health measures are required to create more awareness for managing depression in diabetes. Disclosure N. Kumar: None. A. K. Chandra: None. S. Ahsan: None. A. Kumar: None.

No abstract