Grabisch and Labreuche have recently proposed a generalization of capacities, called the bi-capacities. Recently, a new approach for studying bi-capacities through introducing a notion of ternary-element sets proposed by the author. In this paper, we propose many results such as bipolar Mobius transform, importance index, and interaction index of bi-capacities based on our approach.

Background: Monocyte chemotactic protein-1 (MCP-1) is a chemokine expressed by inflammatory and endothelial cells. It has a crucial role in initiating, regulating, and mobilizing monocytes to active sites of periodontal inflammation. Its expression is also elevated in response to pro-inflammatory stimuli and tissue injury, both of which are linked to atherosclerotic lesions. Aim of the study: To determine the serum level of MCP-1 in patients with periodontitis and atherosclerotic cardiovascular disease in comparison to healthy control and evaluate the biomarker's correlations with periodontal parameters. methods: This study enrolled 88 subjects, both males and females, ranging in age from 36-66 years old, and divided into four groups: 1<

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

     The central nervous system (CNS) disease known as multiple sclerosis (MS) is essentially an inflammatory demyelinating condition with a variety of clinical manifestations and variable histological findings. A number of immunological and biochemical markers may alter MS, which is also characterized as an autoimmune illness. MS patients (n = 100) were divided into two groups: newly diagnosed (n = 42) and patients with ongoing treatments (n = 58). These groups were compared to healthy subjects (n = 55); the mean age ±SD was (30±8.46 years), (37±8.06 years), and (31±8.73 years) for MS newly diagnosed patients, patients with ongoing treatments, and healthy subjects, respectively. Studies for serum levels of eotaxin-1, myelin basi

Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

The current work was designed to investigate serum angiopoietin like protein-8 and hyaluronic acid among Iraqi hemodialysis patients with and without type 2 diabetes mellitus, and to find relationship between them, as well as if these patients are at risk of kidney fibrosis. Subjects & Methods: in this study, serum samples were obtained from (60) Iraqis patients with end stage renal diseases (ESRD)on hemodialysis (HD) (30 patients with T2DM (G2) and 30 patients withoutT2DM (G3)) in addition to (30) healthy individuals as a control group (G1), their ages ranged from (35-65) years. The patients attended the Al-Yarmouk Teaching Hospital, Baghdad. Results: the results in this study showed a highly a significant elevation inserum angiopoietin li