Apple Leave Disease Detection Using Collaborative ML/DL and Artificial Intelligence Methods: Scientometric Analysis.

Infection in apple leaves is typically brought on by unanticipated weather conditions such as rain, hailstorms, draughts, and fog. As a direct consequence of this, the farmers suffer a significant loss of productivity. It is essential to be able to identify apple leaf diseases in advance in order to prevent the occurrence of this disease and minimise losses to productivity caused by it. The research offers a bibliometric analysis of the effectiveness of artificial intelligence in diagnosing diseases affecting apple leaves. The study provides a bibliometric evaluation of apple leaf disease detection using artificial intelligence. Through an analysis of broad current developments, publication and citation structures, ownership and cooperation patterns, bibliographic coupling, productivity patterns, and other characteristics, this scientometric study seeks to discover apple diseases. Nevertheless, numerous exploratory, conceptual, and empirical studies have concentrated on the identification of apple illnesses. However, given that disease detection is not confined to a single field of study, there have been very few attempts to create an extensive science map of transdisciplinary studies. In bibliometric assessments, it is important to take into account the growing amount of research on this subject. The study synthesises knowledge structures to determine the trend in the research topic. A scientometric analysis was performed on a sample of 214 documents in the subject of identifying apple leaf disease using a scientific search technique on the Scopus database for the years 2011-2022. In order to conduct the study, the Bibliometrix suite's VOSviewer and the web-based Biblioshiny software were also utilised. Important journals, authors, nations, articles, and subjects were chosen using the automated workflow of the software. Furthermore, citation and co-citation checks were performed along with social network analysis. In addition to the intellectual and social organisation of the meadow, this investigation reveals the conceptual structure of the area. It contributes to the body of literature by giving academics and practitioners a strong conceptual framework on which to base their search for solutions and by making perceptive recommendations for potential future research areas.

Internet of Medical Things-Based Secure and Energy-Efficient Framework for Health Care.

The Internet of Medical Things (IoMT) is a collection of medical equipment and software that can help patients get better care. The purpose of this study is to improve the security of data collected through remote health monitoring of patients utilizing Constrained Application Protocol (CoAP). Asymmetric cryptography techniques may be used to assure the security of such sensor networks. For communication between different IoMT devices and a remote server, the safe CoAP is compatible with the Datagram Transport Layer Security (DTLS) protocol for creating a secure session using existing algorithms such as Lightweight Establishment of Secure Session. The DTLS layer of CoAP, in contrast, has shortcomings in key control, session establishment, and multicast message exchange. As a consequence, for IoMT communication, the creation of an efficient protocol for safe CoAP session establishment is needed. Thus, to solve the existing problems related to key management and multicast security in CoAP, we have proposed an efficient and secure communication technique to establish a secure session key between IoMT devices and distant servers using lightweight Energy-Efficient and Secure CoAP Elliptic Curve Cryptography (E2SCEC2). The advantage of using E2SCEC2 over other identification methods such as Rivest-Shamir-Adleman (RSA) is its compact key size, which allows it to use a smaller key size. This article also compares these algorithms on parameters such as time spent generating keys, signature generation, and verification of E2SCEC2 and RSA algorithms, as well as energy consumption and radio duty cycle, to see if they are compatible in constrained environments.

Malroatation of gut with superior mesenteric artery syndrome and multiple jejunal diverticula presenting as acute intestinal obstruction in 6th decade: A rare case report.

INTRODUCTION: Intestinal malrotation is a disease of neonates and young children presenting as acute intestinal obstruction. Presentation of malrotation in elderly patients with intestinal obstruction is quite rare with only a few cases reported in literature. We report a case of intestinal malrotation presenting as acute obstruction in sixth decade. PRESENTATION OF CASE: A 55 years old male presented to the emergency with features of acute intestinal obstruction. Imaging studies revealed intestinal malrotation. Exploratory laparotomy revealed malrotation with compression of 3rd part of duodenum and terminal ileum by superior mesenteric artery with multiple jejunal diverticula. Bypass procedures (duodenojejunostomy and ileo-colic anastomosis) with appendicectomy were done. DISCUSSION: Malrotation of gut is an anomaly usually presenting in neonatal period with complications such as midgut volvulus. Presentation in adult age is rare with most cases being asymptomatic. Ladd's procedure is the operation of choice with division of the Ladd's bands and appendicectomy being performed. CONCLUSION: Surgeons should keep a flexible approach in management of malrotation of gut presenting in late stages of life as more and more clinical variants to the presentations described in literature are being encountered.