Named entity recognition (NER) is a subfield of information extraction, which aims to detect and classify predefined named entities (e.g., people, locations, organizations, etc.) in a body of text. In the literature, many researchers have studied the application of different machine learning models and features to NER. However, few research efforts have been devoted to studying annotation schemes used

The explosive growth of cloud usage encourages several challenges, especially high energy consumption of Cloud Data Centers (CDCs), new security risks to Virtual Machines (VMs) resulting from co-residency with other risky VMs on the same Physical Machine (PM), and the Quality of Service (QoS) degradation due to sharing resources. Many recent studies have proposed Dynamic VM Consolidation (DVMC) to

Personality Traits Detection is one of the important problems as a text analytics task in Natural Language Processing (NLP). Text analytics is the process of finding out insight knowledge over written text. Although most deep learning models give high performance, they often lack interpretability. Computer Vision (CV) has been affected significantly with inductive transfer learning, however training

It has been predicted that more devices will be connected to the internet network along with the development of IoT, and that will increase the complexity in the security system. The most important thing in security systems is the process of encryption and authentication. Various encryption techniques are developed to overcome security problems of the data. One of the methods used for authentication

Recommending sustainable products to the target users in a timely manner is the key drive for consumer purchases in online stores and served as the most effective means of user engagement in online services. In recent times, recommender systems are incorporated with different mechanisms, such as sliding windows or fading factors to make them adaptive to dynamic change of user preferences. Those techniques

In the virtual world, the authentication process is used to prove the identity for both of the server and the clients. Therefore, the authentication is an urgent issue for sharing data between users in the data warehouse systems. This paper presents the enhancement of Data Warehouse Signature (DWS) framework through proposing a novel authentication and group-key distribution model, based on the modular

Due to increasing complexity of mobile applications, and limited computation resources of smart mobile devices, the quality of service requirements of mobile application can be enhanced by offloading the computation tasks of the mobile applications to edge servers, such as cloudlets, which exist at the edge of wireless networks. However, improper placement of mobile tasks on the edge servers may increase

Multi-label classification assigns multiple labels to each document concurrently. Many real-world classification problems tend to employ high-dimensional label spaces, which can be naturally structured in a hierarchy. In this type of problem, each instance may belong to multiple labels and labels are organized in a hierarchical structure. It presents a more complex problem than flat classification

The concept of picture fuzzy sets (PFS) is a generalization of ordinary fuzzy sets and intuitionistic fuzzy sets, which is characterized by positive membership, neutral membership, and negative membership functions. Keeping in mind the importance of similarity measures and applications in data mining, medical diagnosis, decision making, and pattern recognition, several studies have been proposed in

A novel evolutionary algorithm called learner performance based behavior algorithm (LPB) is proposed in this article. The basic inspiration of LPB originates from the process of accepting graduated learners from high school in different departments at university. In addition, the changes those learners should do in their studying behaviors to improve their study level at university. The most important

Each organization faces threats and risks in daily operations. One of the main risks is how to assess the security level to protect from the increasing risks associated with technology evolution. So, organizations can specify the required approaches and skills. In this paper, we propose a security maturity model that classifies the organizations into five levels. Each level determines the technologies

Machine-based classification usually involves some computer programs, known as algorithms, developed using several mathematical formulations to accelerate the automated classification process. Along with the exponential increase in the size and computational complexity of the data today, such optimized, robust, agile and reliable computational algorithms are required which can efficiently carry out

Nowadays, human emotion recognition is a mandatory task for many human machine interaction fields. This paper proposes a novel multi-modal human emotion recognition framework. The proposed scheme utilizes first the 3D-Convolutional Neural Network (3D-CNN) deep learning architecture for extracting the spatio-temporal features from the electroencephalogram (EEG) signals, and the video data of human faces

Electronic Medical Records (EMRs) can provide many benefits to physicians, patients and healthcare services if they are adopted by healthcare organizations. But concerns about privacy and security that relate to patient information can cause there to be relatively low EMR adoption by a number of health institutions. Safeguarding a huge quantity of health data that is sensitive at separate locations

This paper presents a generalization of chaotic systems using two-dimensional affine transformations with six introduced parameters to achieve scaling, reflection, rotation, translation and/or shearing. Hence, the location of the strange attractor in space can be controlled without changing its chaotic dynamics. In addition, the embedded parameters enhance the randomness and sensitivity of the system

This study presents a new approach for calculations within the Common Vulnerability Scoring System that scoring the effects of vulnerabilities in software on the security status. These calculations is the method that is most commonly used in scoring software vulnerabilities. The present model demonstrates how software security vulnerabilities can be calculated using linguistic terms. Therefore, the

Hyperspectral data are a curse with huge dimensionality, high redundancy of spectral information, and are noisy in nature. Hundreds of narrow adjacent bands are present in HS (Hyperspectral) data with high spectral information and it always leads to a computational complexity in space and time. The information theoretic methods are used for hyperspectral band selection to avoid computational complexity

Local outlier detection is a hot area and great challenge in data mining, especially for large-scale datasets. On the one hand, traditional algorithms often achieve low-quality detection results and are sensitive to neighborhood size. On the other hand, they are infeasible for large-scale datasets due to at least O(N2) time and space complexity. In light of these, we propose a new local outlier detection

This paper presents a new method for generating all prime numbers up to a particular number m∈N,m⩾9, by using the set theory. The proposed method is explicit and works oriented in finding the prime numbers in order. Also, we give an efficiently computable explicit formula which exactly determines the number of primes up to a particular number m∈N,m⩾9. For the best of our knowledge, this is the first

The extensive growth of the Internet of Things (IoT) devices leads to the evolution of the broad range of smart applications in numerous fields such as smart home, wearable, education, agriculture, health care, transportation and many more. But security for IoT devices is still a challenging issue as many attacks are possible in the environment. Therefore strong security requirements are an important

Non-negative matrix factorization (NMF) is an effective model in converting data into non-negative coefficient representation whose discriminative ability is usually enhanced to be used for diverse pattern recognition tasks. In NMF-based clustering, we often need to perform K-means on the learned coefficient as postprocessing step to get the final cluster assignments. This breaks the connection between

Internet of things architecture is the integration of real-world objects and places with the internet. This booming in technology is bringing ease in our lifestyle and making formerly impossible things possible. Internet of things playing a vital role in bridging this gap easily and rapidly. IoT is changing our lifestyle and the way of working the technologies, by bringing them together at the one

Although the number of Arabic language writers in social media is increasing, the research work targeting Author Profiling (AP) is at the initial development phase. This paper investigates Gender Identification (GI) (male or female) of authors posting Egyptian dialect tweets using Neural Networks (NN) models. Various architectures of NN are explored with extensive parameters’ selection such as simple

Searching relevant articles from medical resources is an important search task in clinical decision support system. The technical contents and long length of biomedical articles make this search task more complicated than many other search tasks. Previous research on biomedical information retrieval (IR) is typically based on keyword search. In this paper we propose a new approach. Using our approach

Background/introduction The dawn of the internet opened the doors to the easy and widespread sharing of information on subject matters such as products, services, events and political opinions. While the volume of studies conducted on sentiment analysis is rapidly expanding, these studies mostly address English language concerns. The primary goal of this study is to present state-of-art survey for

Modern medical diagnosis heavily rely on bio-medical and clinical data. Machine learning algorithms have proven effectiveness in mining this data to provide an aid to the physicians in supporting their decisions. In response, machine learning based approaches were developed to address this problem. These approaches vary in terms of effectiveness and computational cost. Attention has been paid towards

Software defined networks are an emerging category of networks in which the data plane and control plane are separated. This separation of planes opens the door for designing sophisticated routing algorithms that would overwhelm the computing power of traditional networking nodes. In this paper, we consider the possibility of introducing node trust into the routing problem. There are many ways for

This paper describes how a simple novel Galois Power-of-Two (GPOW2) real-time embedding scheme is used to improve the performance and accuracy of downstream NLP tasks. GPOW2 computes embeddings live on the fly (real time) in the context of target NLP tasks without the need for tabulated pre-embeddings. One excellent feature of the method is the ability to capture multilevel embeddings in the same pass

The analysis of human emotions plays a significant role in providing sufficient information about patients in monitoring their feelings for better management of their diseases. Audio-based emotions recognition has become a fascinating research interest for such domains during the last decade. Mostly, audio-based emotions systems depend on the recognition stage. The existing model has a common issue

Pain is defined as “a distressing experience associated with actual or potential tissue damage with sensory, emotional, cognitive and social components”, knowing the exact level of pain experienced to have a critical impact for caregivers to make diagnosis and make he suitable treatment plan, but the available methods depend entirely on the patient self-report, which increase the difficulties of knowing

This work is inspired by Kaggle competition which was part of the Fine-Grained Visual Categorization workshop at CVPR 2019 (Conference on Computer Vision and Pattern Recognition) we participated in. It aimed at detecting cassava diseases using 5 fine-grained cassava leaf disease categories with 10,000, labeled images collected during a regular survey in Uganda. Traditionally, this detection is done

The data capturing and access process is an important stage in the big data applications. Most of these applications are exploited the wireless sensor networks (WSNs) to accomplish this process through the sensor nodes that are deployed in unsecure and unattended environments. Therefore, these applications are suffered from numerous security weaknesses, an adversary may exploit such weaknesses to break

Many IoT applications have been developed recently, this leads to increasing the network load. To avoid the lack of spectrum, IoT can use cognitive radio network concept. This paper presents most of the researches addressing channel allocation and packets scheduling, when merging the cognitive radio networks with the IoT technology. Surveying the researches done in this area shows the work done is

Arabic Information Retrieval has gained significant attention due to an increasing usage of Arabic text on the web and social media networks. This paper discusses a new approach for Arabic stem, called Arabic Morphology Information Retrieval (AMIR), to generate/extract stems by applying a set of rules regarding the relationship among Arabic letters to find the root/stem of the respective words used

This paper presents an indoor navigation support system based on the Building Information Models (BIM) paradigm. Although BIM is initially defined for the Architecture, Engineering and Construction/Facility Management (AEC/FM) industry, the authors believe that it can provide added value in this context. To this end, the authors will focus on the Industry Foundation Classes (IFC) standard for the formal

The human cognitive map formation is still an open question. Based on biological facts, the cognitive map origin goes back to the age of the fetus human. In this paper, our aim is to provide a possible answer to that question. Accordingly, we present a theoretical model of the development of the cognitive map of a fetus human using its sensorimotor data. We define positions of the cognitive map as

In the present era, cloud computing has earned much popularity, mainly because of its utilities and relevance with the current technological trends. It is an arrangement which is highly customizable and encapsulated for providing better computational services to its clients worldwide. In cloud computing, scheduling plays a pivotal role in the optimal utilization of resources. Prevalent priority based

Software is evolving rapidly. Many software systems release new versions in short iterations. Code changes within such versions may be enhancements, bug fixes, or new features. While preserving some of those changes, the functionality of software may accidentally degrade its performance within a new version when compared to a previous version thus introducing performance regressions. Developers suffer

The future of Internet of Things (IoT) foresees a world of interconnected people with every physical object in a seamless manner. The security related aspects for the IoT world are still an open field of discussion and research. The Message Queue Telemetry Transport (MQTT) application layer protocol is widely used in IoT networks. Since, MQTT standard has no mandatory requirements regarding the security

The rapid increase in the era of the technological revolution and the Internet, especially the social media, have created a new reality in the daily life of the societies in general and of the university students in particular, so this new reality without any doubt imposes on us the general effects of this increasing use of social media has affected all areas and societies The effects are positive

We propose a novel methodology for extractive, generic summarization of text documents. The Maximum Independent Set, which has not been used previously in any summarization study, has been utilized within the context of this study. In addition, a text processing tool, which we named KUSH, is suggested in order to preserve the semantic cohesion between sentences in the representation stage of introductory

Internet of Things (IoT) is a fundamental concept of a new technology that will be promising and significant in various fields. IoT is a vision that allows things or objects equipped with sensors, actuators, and processors to talk and communicate with each other over the internet to achieve a meaningful goal. Unfortunately, one of the major challenges that affect IoT is data quality and uncertainty

Event-based data transfer through Wireless Body Sensor Networks (WBSN) for monitoring the health of the elderly has so far not been successfully implemented due to limitations arising forms unreliable data, end-to-end delay during data transmission and the high energy consumption by sensors. This paper aims to improve reliability and latency and to reduce energy consumption by sensors during data transmission

Background: Current Augmented Reality systems in liver and bowel surgeries, are not accurate enough to classify the hidden parts such as gallbladder and uterus which are behind the liver and bowel. Therefore, we aimed to improve the visualization accuracy of bowel and liver augmented videos to avoid the unexpected cuttings on the hidden parts. Methodology: The proposed system consists of an Enhanced

This paper proposed an approach for Arabic text summarization. Text summarization is one of the natural language processing's applications which is used for reducing the original text amount and retrieving only the important information from the original text. The Arabic language has a complex morphological structure which makes it very difficult to extract nouns to be used as a feature for summarization

Previous research showed that conditioning a PSO agent’s movement based on its personal fitness improvement enhances the standard PSO method. In this article, Languid Particle Dynamics (LPD) technique is used on five adequate and widely used PSO variants. Five unmodified PSO variants were tested against their LPD-enabled counterparts on three search space dimensionalities (10, 20, and 50 dimensions)

One of the significant issues in information security areas is a hidden exchange of data. There are several techniques for this purpose such as cryptography, steganography, etc. Generally, in cryptography, the secret message content is scrambled. In another hand in steganography, the secret message is embedded inside the cover medium. In this paper, a new crypto technique-based ciphertext shifting

Magnetic Resonance Imaging (MRI) is a medical imaging modality that is commonly employed for the analysis of different diseases. However, these images come with several problems such as noise and other imaging artifacts added during acquisition process. The researchers have actual challenges for segmentation under the consideration of these effects. In medical images, a well-known clustering approach

Laws’ mask method has achieved wide acceptance in texture analysis, however it is not robust to noise. Fuzzy filters are well known for denoising applications. This work proposes a noise-robust Laws’ mask descriptor by integrating the exiting fuzzy filters with the traditional Laws’ mask for the improvement of texture classification of noisy texture images. Images are corrupted by adding Gaussian noise

To achieve a highly efficient brain-computer interface (BCI) system regarding emotion recognition from electroencephalogram (EEG) signal, the most crucial issues are feature extractions and classifier selection. This work proposes an innovative method that hybridizes the principal component analysis (PCA) and t-statistics for feature extraction. This work contributes to successfully implement spatial

Non-Orthogonal multiple access (NOMA) and Cognitive radio (Cr) are seen as one of the most promising techniques, which improves the utilization of the spectrum in 5G. The expanding number of wireless applications like new gadgets, IOT brought about developing a block in the ISM groups. The FCC requested to permit unlicensed clients to work in the void area without obstruction to an authorized guest

Genetic diseases are one of the most critical diseases facing human societies, their risk lies in the transmission of genetic characteristics from one generation to another, where the imbalance of these characteristics leads to an unhealthy offspring, which negatively affects the effort of this offspring and its services to society. Genetic disease is caused by a mutation in the Deoxyribonucleic Acid

Arabic language processing works on multiple levels; less often, these complementary levels synergize well with each other. Arabic Language Sentiment Analysis (ALSA) levels consist of phonetics, morphology, syntax, lexicology, semantics, and figurative nature. The analysis of opinions and feelings is of interest in English and Indo-European languages, with little emphasis in the Arabic language, which

Text clustering is a challenging task in natural language processing due to the very high dimensional space produced by this process (i.e. curse of dimensionality problem). Since these texts contain considerable amounts of ambiguities and redundancies, they produce different noise effects. For an efficient and accurate clustering algorithm, we need to extract the main concepts of the text by eliminating

A target tracking in wireless sensor networks consists of two main functions: The detection and the tracking of the target along its trajectory by means of sensors deployed in an area of interest. Generally, these sensors are not maintainable after deployments. Dynamic clustering algorithms seem to be an effective mechanism for increasing the network’s lifetime. Indeed, this type of algorithms only

Algorithm Visualisation (AV) tool is commonly used to learn data structures. However, since that tool does not address technical details, some students may not know how to implement the data structures. This paper integrates the AV tool with Program Visualisation (PV) tool to help the students understanding the data structures’ implementation. The integration (which is implemented as a tool named DS-PITON)

Microarray technology has increased exponentially in the past few years. Such technology encompasses various applications related to drug design, tumor detection, clinical diagnosis and treatment, and environmental health research. However, the segmentation of the spots in microarray image is still a problem due to variations of spots qualities such as spots shapes and sizes for example. Hence, we

A huge amount of data is generated since the evolution in technology and the tremendous growth of social networks. In spite of the availability of data, there is a lack of tools and resources for analysis. Though Arabic is a popular language, there are too few dialectal Arabic analysis tools. This is because of the many challenges in Arabic due to its morphological complexity and dynamic nature. Sentiment

Handling multi-label student complaints is one of interesting research topics. One of techniques used for handling multi-label student complaints is Bag of Word (BoW) method. In this research bigram word rule and preprocess are proposed to increase the accuracy of multi-label classification results. To show the effectiveness of the proposed method, data from Telkom University student data and additional

The purpose of this paper was to measure the quality of concordance of one- and two-level structural equation models by testing the two following statistical hypotheses: first, the structure of the two-level model is more efficient than that of the one-level model; second, economic and social determinants and intermediate variables have a significant effect on current and future fertility in Giza Governorate