Accurate estimation of software development effort is essential for effective management and control projects. Many methods have been proposed in the literature including computational intelligence models. However, none existing models proved to be suitable under all circumstances; that is, their performance varies from one dataset another. The goal an ensemble model manage each its individual models’ strengths weaknesses automatically, leading best possible decision being taken overall. In...

People depend on popular search engines, like Google and Yahoo, to retrieve the desired information from Web. Searching for right food, eat, is an example of frequent queries Web where people do not find relevant easily. One reason this un-satisfaction fact that many have personal preferences each one likes dislikes certain food. Also, some specific health conditions restrict their food choices encourage them take other In addition, cultures, live in, influence varieties. Therefore, it will...

Inter-Planetary File System (IPFS) is a peer-to-peer distributed file system that has gained wide interest recently. The IPFS network public and its content can be accessed by any user in the Internet. also used as sharing an isolated private network. However, it notable writing reading performance drawbacks. aim of this study to evaluate operations networks understand what factors affect it. In our evaluation approach, Transfer Protocol (FTP) selected baseline measurement, virtual three...

Ontology, the backbone of Semantic Web, is defined as formal specification conceptual hierarchy with relationships between concepts. Ontology Learning (OL) a process to create an ontology from text automatically or semi-automatically. OL important topic in Web field last two decades but it still not mature Arabic like Latin languages. Currently, there limited support for using knowledge literature semantically-enabled systems. Deep (DL), artificial neural networks learning based application,...

Fog computing has emerged as a promising paradigm to extend cloud services toward the edge of network, enabling low-latency processing and real-time responsiveness for Internet Things (IoT) applications. However, distributed, heterogeneous, resource-constrained nature fog environments introduces significant challenges in balancing workloads efficiently. This study presents systematic literature review (SLR) 113 peer-reviewed articles published between 2020 2024, aiming provide comprehensive...

The hybridization of two or more Computational Intelligence (CI) techniques to build a single model has increased in popularity over the recent years. Such models that combine best properties different Artificial (AI) package are very much required process reservoir characterization petroleum engineering, where high degree prediction accuracy is essential for efficient exploration, and management oil gas resources. In this paper, we have successfully predicted, with higher accuracy, porosity...

As we aim to retrieve personalized information user's queries related food, health and nutrition domains such as "Is apple good for people with heart diseases?", "How much honey can be taken by a diabetic patient?", "What are the benefits of eating pineapple?" fruits that contain daily need quantity calcium?" The retrieval system needs integrate ontologies from different nutrition, (diseases, body parts, functions) recipe in order answer kind queries. In addition, support multilingual...

This paper presents recently introduced learning algorithm called extreme machine (ELM) for single-hidden layer feed-forward neural-networks (SLFNs) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs. The ELM avoids problems like local minima, improper rate over fitting commonly faced by iterative methods completes training very fast. We have evaluated multicategory classification performance on five different data sets related to bioinformatics...

The implementation of CPU-Scheduling algorithms such as Shortest-Job-First (SJF) and Shortest Remaining Time First (SRTF) is relying on knowing the length CPU-bursts for processes in ready queue. There are several methods to predict CPU-bursts, exponential averaging method, however these may not give an accurate or reliable predicted values. In this paper, we will propose a Machine Learning (ML) based approach estimate processes. proposed aims select most significant attributes process using...

Fog computing offers low-latency and real-time big-data processing capabilities closer to the network edge. This particular benefit addresses main bottleneck in a centralized cloud framework, which is, it cannot process latency-sensitive large video frames generated from Internet of Things-based surveillance cameras real-time. Besides, recent advancements computer vision field offer many state-of-the-art image that can be utilized for data processing. Deploying those powers at several fog...

This paper proposes functional networks as an unconstrained classifier scheme for multivariate data to diagnose the breast cancer tumor. The performance of this new technique is measured using two well known databases under minimum description length criterion, results are compared with most common existing classifiers in both computer science and statistics literatures. shown reliable efficient better correct classification rate, much less computational time.

Load balancing is essential for efficient utilization of resources and enhancing the responsiveness a computational grid, especially that hosts services most frequently used, i.e. food, health nutrition. Various techniques have been developed applied; each has its own limitations due to dynamic nature grid. Efficient load can be achieved by an effective measure node’s/cluster’s utilization. In this paper, as part NSTIP project # 10-INF1381-04 in order assess FAQIH framework ability support...

To have a successful semantic Web, it is critically required to sufficient amount of relevant and high-quality Web content. One way produce such content through the annotation sources. Semantic process adding machine-readable natural language textual Annotating in Arabic has received less attention compared Latin Languages especially for related specific domains as food, nutrition health. Considering huge emerging content, their contents by hand neither practicable nor scalable. In this...

The vision of semantic Web is to have a data instead documents in form that can be processed by machines. This could achieved the existing using annotation. Due exponential growth and huge size sources, there need fast automatic annotation documents. Arabic language has received less attention research compared Latin languages especially field In this paper, we present an tool supports takes URL document corresponding ontology then produces external Resource Description Framework (RDF)...

Abstract In the last decade, Hardware Performance Counters (HPCs) events are increasingly used by Machine Learning (ML) algorithms for malware detection. Modern processors provide a variety of HPCs to measure and monitor processes’ such as memory accesses, instructions, etc. during their execution. this paper, an analysis study categorize machine learning based on that have been detection is introduced. Besides, most efficient effective features exploited recognize abnormal activities...

Ontology Learning (OL) from a text is process that consists of processing, knowledge extraction, and ontology construction. For Arabic language, extraction tasks are not mature as for Latin languages. They have been integrated into the full OL pipeline. Currently, there very little automated support using literature in semantically-enabled systems. This paper demonstrates feasibility some existing methods elicits proposals further work toward building open domain systems Arabic. done by an...

Semantic Web vision is to have machines interpret and understand the content of documents. There a need convert existing documents into an understandable format, which could be done by automatic semantic annotation. Annotation performed using set tools provided with general domain-specific ontologies. The aim this paper present generic annotation framework Arabic text deep learning models. produces annotations different output formats for given With prototype framework, initial evaluation...

In order to realize the vision of Semantic Web, which is a Web things instead documents, there need convert existing documents into content that could be processed by machines. annotation tool used perform this task through using common and public ontologies. Due exponential growth huge size sources, have fast automatic documents. The aim paper investigate use word embeddings from deep learning algorithms semantically annotate Arabic To enhance performance annotation, we utilized complex...