Comparison of Supervised Machine Learning Algorithms for Malware Detection

Due to the prevalence of security issues and cyberattacks, cybersecurity is crucial in today's environment. Malware has also evolved significantly over the past few years. With the advancement of malware analysis, Machine Learning (ML) is increasingly being used to detect malware. This study's major objective is to compare the best-supervised ML algorithms for malware detection based on detection accuracy. This study includes the scripting and development of supervised ML techniques such as Decision Tree (DT), K-Nearest Neighbors (KNN), Naive Bayes, Random Forest, and Neural Networks. This study was solely concerned with the Windows malware dataset. The malware classification was determined by testing and training the supervised ML algorithms using the extracted features from the malware dataset. Then, the percentage of detection accuracy was used to compare the detection performance of all five algorithms. The detection accuracy is calculated using the confusion matrix, which includes the False Positive Rate (FPR), the True Positive Rate (TPR), and the False Negative Rate (FNR). The results indicated that the Decision Tree and Random Forest algorithms provided the best detection accuracy at 96%, followed by the K-NN algorithm at 95%. To improve the detection accuracy for future research, it is suggested that the malware dataset be enhanced using several architectures, such as Linux and Android, and use additional supervised and unsupervised machine learning algorithms

Inadvertent puncture of right vertebral artery during central venous line catheter insertion

The use of ultrasound has been proposed to reduce the number of complications and to increase the safety and quality of central venous catheter (CVC) placement. In this report, we recommend the structures approach for US-guided to insert venous access for clinical practice. To achieve the best skill for CVC placement, The knowledge from anatomic landmark techniques and knowledge from US-guided CVC placement need to be combined and integrated. 59 years old lady, planned for total abdominal hysterectomy for pelvic tumour excision. Anticipate massive bleeding with major fluids shift during intraoperative, invasive monitoring with CVC was inserted preoperative at right internal jugular vein. The procedure of insertion was done using US-guided with out-of-plane method. While connected to CVP monitoring noted to have arterial wave. Decided to keep the central venous line in-situ and referral to radiologist for imaging was arranged. CT angiogram's findings of a catheter were seen to transverse the right internal jugular vein through-and-through and seen to lie within the right vertebral artery coursing into the right subclavian artery. No evidence of carotid artery injury. Referred to intervention radiology and vascular surgery team for the best method of removal the central line catheter. Removal of CVC for inadvertent injury to right verterbral artery under guided contrast study by intervention radiologist. The case illustrates the importance of ultrasound-guided CVL insertion

Towards Designing A Hierarchical Fuzzy System for Early Diagnosis of Heart Disease

Heart disease may represent a range of conditions that affect our heart. Disease under heart diseases umbrella include coronary heart disease, heart attack, congestive heart failure, and congenital heart disease, is the leading cause of death. Mor eover, heart disease not only attacks the elderly. In the present day, lots of younger people might be getting affected by the number of heart diseases. In order to decrease the mortality rate caused by heart disease, it is necessary for the disease, to be diagnosed at an early stage. In this paper, we have proposed the use of hierarchical fuzzy systems (HFSs) for early diagnosis of heart disease. However, to design the HFSs is challenging, especially for the complex system. Therefore, in this paper, we foc us on designing a hierarchical fuzzy system to handle the complex medical application. The designed HFS consists of six key main steps implemented on heart disease. The input variables of heart disease includes shortness of breath, discomfort, pressure, he aviness, or pain in the chest, arm, or below the breastbone, fatigue, nausea, difficulties in climbing stairs, swelling in ankles, difficulty to sleep at night, irregular heartbeats, fullness, sweating, take frequent break during the day, dizzy and depress ed. Additionally, the output of heart disease is to classify whether the patient is healthy or suspecting with heart disease. The study contributes to providing insight into a way of designing the HFSs, particularly for the complex medical application

Self-medication practice for dental problems: a cross-sectional study among adults in Kuantan, Pahang in Peninsular Malaysia

Aim: To investigate the prevalence, attitude, and pattern of self-medication practice for dental problems among adults in Kuantan, the state capital of Pahang, Malaysia. Materials and Methods: This cross-sectional study was conducted among adults over 18 years of age who live in Kuantan via self-administered online- and paper-based bilingual questionnaires. Descriptive statistics and chi-square analysis were run using IBM SPSS® Version 26 software. Results: From 275 respondents, one-fifth of respondents (21.8%) practised self-medication for dental problems and most of them obtained a mean attitude score of 21.7 ± 2.5% out of 25. Most self-medicating respondents were from the age group of 18–27 years (78.3%), females (55%), singles (78.3%), resides urban area (75.0%), and students (71.7%), with a household income of <MYR 3860 (46.7%), have no dental insurance (66.7 %), and did not have any family relationship with dental personnel (90.0%). Only gender has significant association with self-medication practice, X2 (1, N = 275) = 4.916, P < 0.05. Most of self-medicating respondents gained information related to self-medication from internet (62.0%) and obtained medication from pharmacy (78.0%). The major dental problem that triggered them to self-medicate was toothache (76.0%), and the majority used paracetamol for pain relief (62.0%). Their main reason for self-medication was the perceived mildness of the dental problems (60.0%). Conclusion: Adult populations in Kuantan, Pahang have moderate prevalence (21.8%) in self-medicating practice for dental problems which was mainly caused by toothache and was primarily treated with over-the-counter pain-relief medication. They also have good attitude toward appropriate self-medication