A smart home’s safety is a very urgent question due to several causes. This chapter analyzes current directions of smart house system safety technologies in use nowadays. Current studies are dedicated to the integration of Internet of Things (IoT) into smart home systems; critical situations that may arise; and specifications of sensors in the smart home system. The huge number of connected devices and the capacity embedded within these devices to direct demand resources make deliberate attacks on them and/or inadvertent downfall events such as abrupt bad interactions between connected devices, mechanical failure of devices, and unsuccessful communication may lead to IoT-based systems entering unreliable and threatening physical states. We review current trends in security-enabled safety monitoring frameworks for IoT-based smart homes. We demonstrate the use of various techniques in utilizing system analysis during design to develop a monitoring model that can be executed, providing run-time safety assurance for a system. This is achieved through collecting and analysis of operational data and evidence to assess the safety status of the system. Subsequently, appropriate actions are taken, and the safety status is communicated securely to system users, along with recommended actions to reduce the risk of the system entering an unsafe state.
Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope
... Show More<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T
... Show MoreMultilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d
This study evaluated the effect of two different types of amino group-containing pharmacological inhibitors on titanium corrosion under acidic conditions. The first inhibitor examined was the antibiotic trimethoprim. The second inhibitor studied was the nonsteroidal anti-inflammatory drug voltaren. The results showed that titanium had a high corrosion current in the absence of a corrosion inhibitor, however, trimethoprim notably enhanced corrosion resistance and protection percentages of titanium (%IE) at higher concentrations by adhering to the metal surface, as evidenced by improved protection percentages. Furthermore, the results showed that as Voltaren concentration was increased, both corrosion resistance and inhibition efficie
... Show MoreEach school of Islamic jurisprudence has principles and rules upon which the diligent work in these schools is based. This is due to the view of sanctification of these rulings, as they are divine rulings. Therefore, the goal is to reach a ruling that represents the intent of the legislator as much as possible.
Hence, these schools of thought established rules for issuing fatwas with the intention of restricting the performance of a fatwa to the hands of those who are qualified for it and have met its conditions, so they gave priority to the most knowledgeable person over others to perform the fatwa. In the Hanafi school of thought, for example, the saying of Imam Abu Hanifa (may God have mercy on him) is given precedence over others,
Background: Animal bite is one of the public health problems all over the world, especially in poor countries. Animal bites have an impact on human health due to rabies disease, which is a viral transmitted disease from animal to human with a high mortality rate.
Objective: To determine the epidemiological characteristics of animal bite cases by person, time, and place.
Method: Descriptive cross sectional study was done by reviewing cases caused by animal bites., Data including the demographic characteristics of age, gender, occupation, site of bite, and attending health institutions searching treatment were all included.
Results: There were 11600 animal bite cases. Most of bites caused by stray dogs 11577(99.8%), and the males
Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac
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