The problem of finding the shortest path between two nodes is a common that requires solution in many applications like games, robotics, and real-life problems. Since its deals with large number possibilities. Therefore, parallel algorithms are suitable to solve this optimization has attracted lot researchers from both industry academia find optimal terms runtime, speedup, efficiency, cost compared sequential algorithms. In mountain climbing, start node under reach destination fundamental...

<div class="WordSection1"><p>In the last few years, deep learning has exhibited its efficacy and capacity in field of computer vision owing to exceptional precision widespread acceptance. The primary objective this study is investigate an improved approach for segmentation context various fruit categories. Despite utilization learning, current techniques items exhibit subpar performance. proposed enhanced multiple algorithm following main steps: 1) modifying size filter, 2)...

Abstract According to Moore’s law, computer processing hardware technology performance is doubled every year. To make effective use of this technological development, the algorithmic solutions have be developed at same speed. Consequently, it necessary design parallel algorithms implemented on machines. This helps exploit multi-core environment by executing multiple instructions simultaneously processors. Traveling Salesman (TSP) a challenging non-deterministic-hard optimization problem that...

Software requirements prioritization plays a crucial role in software development. It can be viewed as the process of ordering by determining which must done first and later. Powerful techniques are paramount importance to finish implementation on time budget. Many factors affect requirement such stakeholder expectations, complexity, dependency, scalability, risk cost. Therefore, finding proper order is challenging process. Hence, different types have been developed support this task. In...

Abstract To identify risk factors for smoking among pregnant women, and adverse perinatal outcomes women. A case–control study of singleton full-term women who gave birth at a university hospital in Jordan June 2020. Pregnant were divided into three groups according to their status, active, passive, non-smokers. They interviewed using semi-structured questionnaire that included demographic data, current pregnancy history, neonatal outcomes. Low-level maternal education, unemployment,...

Recently, the proliferation of smartphones, tablets, and smartwatches has raised security concerns from researchers. Android-based mobile devices are considered a dominant operating system. The open-source nature this platform makes it good target for malware attacks that result in both data exfiltration property loss. To handle issues attacks, researchers proposed novel algorithms detection approaches. However, there is no standard dataset used by to make fair evaluation. Most research...

Dental caries is arguably the most persistent dental condition that affects people over their lives. Carious lesions are commonly diagnosed by dentists using clinical and visual examination along with oral radiographs. In many circumstances, challenging to detect photography might be mistaken as shadows for various reasons, including poor photo quality. However, introduction of Artificial Intelligence robotic systems in dentistry, photographs can a helpful tool epidemiological research...

Abstract It is of paramount importance to enhance medical practices, given how important it protect human life. Medical therapy can be accelerated by automating patient prediction using machine learning techniques. To double the efficiency classifiers, several preprocessing strategies must adopted for their crucial duty in this field. Feature Selection (FS) one tool that has been used frequently modify data and classification outcomes lowering dimensionality datasets. Excluded features are...

Abstract A critical task and a competitive research area is to secure networks against attacks. One of the most popular security solutions Intrusion Detection Systems (IDS). Machine learning has been recently used by researchers develop high performance IDS. main challenges in developing intelligent IDS Feature Selection (FS). In this manuscript, hybrid FS for network proposed based on an ensemble filter, improved Intelligent Water Drop (IWD) wrapper. The Improved version from IWD algorithm...

Technological advancements affect everyday life; they benefited our daily routines, habits, and activities. Underwater diving is one of the most interesting attractive activities for tourists worldwide but could be risky challenging. When paths are not clear, might take additional time effort leading to some health problems. Thus, providing divers with proper direction information surf underwater can useful helpful. Also, monitoring diverse statuses alerting them in case any undesirable...

Abstract The Internet of Things (IoT) is widespread in our lives these days (e.g., Smart homes, smart cities, etc.). Despite its significant role providing automatic real-time services to users, devices are highly vulnerable due their design simplicity and limitations regarding power, CPU, memory. Tracing network traffic investigating behavior helps building a digital forensics framework secure IoT networks. This paper proposes new Network Digital Forensics approach called (NDF IoT)....

Software requirements prioritization plays a crucial role in software development. It can be viewed as the process of ordering by determining which must done first and later. Powerful techniques are paramount importance to finish implementation on time within budget. Many factors affect requirement such stakeholder expectations, complexity, dependency, scalability, risk, cost. Therefore, finding proper order is challenging process. Hence, different types have been developed support this...

Classifying text is a method for categorizing documents into pre-established groups. Text must be prepared and represented in way that appropriate the algorithms used data mining prior to classification. As result, number of term weighting strategies have been created literature enhance categorization algorithms' functionality. This study compares effects Binary Term frequency feature methodologies on text's classification when stop words are eliminated once they not. In recognition...

It is of paramount importance to enhance medical practices, given how important it protect human life. Medical therapy can be accelerated by automating patient prediction using machine learning techniques. To double the efficiency classifiers, several preprocessing strategies must adopted for their crucial duty in this field. Feature selection (FS) one tool that has been used frequently modify data and classification outcomes lowering dimensionality datasets. Excluded features are those have...

Ayat Mahmoud Al-Hinawi 1*, Radwan A. Alelaimat , Esraa Alhenawi 2, Mohammad I. AlBiajawi 3, 1Department of Allied Engineering Sciences, Hashemite University, Zarqa 2 Faculty Information Technology, Zarqa, Jordan 3 Civil Universiti Malaysia Pahang AL-Sultan Abdullah, Persiaran Tun Khalil Yaakob, 26300 Gambang, Pahang,

The proliferation of internet things (IoT) technologies has expanded the user base internet, but it also exposed users to increased cyber threats. Intrusion detection systems (IDSs) play a vital role in safeguarding against cybercrimes by enabling early threat response. This research uniquely centers on critical dimensionality aspects wireless datasets. study focuses intricate interplay between feature and intrusion systems. We rely renowned IEEE 802.11 security-oriented AWID3 dataset...

Phishing email assaults have been a prevalent cybercriminal tactic for many decades. Various detectors suggested over time that rely on textual information. However, to address the growing prevalence of phishing emails, more sophisticated techniques are required use all aspects emails improve detection capabilities machine learning classifiers. This paper presents novel approach detecting emails. The proposed methodology combines ensemble with various variables, such as word frequency,...

The current study aimed to construct a measure based on dramatization of the sociological and psychological skills students with autism spectrum disorders, in light variables gender group (experimental control), verify its psychometric characteristics. sample consisted (50) male female disorders who were selected simple random manner. was distributed into two groups. experimental amounted (25), control (25). results showed that there statistically significant differences at significance...