Eman M. G. Younis

Minia University · Department of Information Systems

Semantic Web resources such as DBpedia provide a rich source of structured knowledge about geographical features such as towns, rivers and historical buildings. Retrieval from these resources of all content that is relevant to a particular spatial query of, for example, containment or proximity is not always straightforward because there is conside...

Recently, Social media has arisen not only as a personal communication media, but also, as a media to communicate opinions about products and services or even political and general events among its users. Due to its widespread and popularity, there is a massive amount of user reviews or opinions produced and shared daily. Twitter is one of the most...

Abstract Over the past few years, there has been a noticeable advancement in environmental models and information fusion systems taking advantage of the recent developments in sensor and mobile technologies. However, little attention has been paid so far to quantifying the relationship between environment changes and their impact on our bodies in r...

Urban spaces have a great impact on how people’s emotion and behaviour. There are number of factors that impact our brain responses to a space. This paper presents a novel urban place recommendation approach, that is based on modelling in-situ EEG data. The research investigations leverages on newly affordable Electroencephalogram (EEG) headsets, w...

The detection and monitoring of emotions are important in various applications, e.g. to enable naturalistic and personalised human-robot interaction. Emotion detection often require modelling of various data inputs from multiple modalities, including physiological signals (e.g.EEG and GSR), environmental data (e.g. audio and weather), videos (e.g....

Emotion recognition, a burgeoning field with applications in healthcare, human-computer interaction, and affective computing, has seen significant advances by integrating physiological signals and environmental factors. With the increasing development of Artificial Intelligence (AI), the precision and efficiency of machine learning (ML) algorithms...

Cancer ranks second among the causes of mortality worldwide,following cardiovascular diseases.Brain cancer, in particular, has lowest survival rate of any kind of cancer. Brain tumours vary in their morphology, texture, and location, which determine their classification. Accurate diagnosis of the tumour category enables physicians to select optimal...

In March 2020, the whole world suffered from the coronavirus pandemic. This virus is a sort of virus that comes in many forms, some of which may kill. It mainly affects the human respiratory system. The development and search for COVID-19 vaccines became the global goal to stop the spread of the deadly disease. By the end of 2020, the first set of...

This paper proposes a modified version of the weighted mean of vectors algorithm (mINFO), which combines the strengths of the INFO algorithm with the Enhanced Solution Quality Operator (ESQ). The ESQ boosts the quality of the solutions by avoiding optimal local values, verifying that each solution moves towards a better position, and increasing the...

Misinformation can profoundly impact the reputation of an entity, and eliminating its spread has become a critical concern across various applications. Social media, often a primary source of information, can significantly influence individuals’ perspectives through content from less credible sources. The utilization of machine-learning (ML) algori...

Emotion is an interdisciplinary research field investigated by many research areas such as psychology, philosophy, computing, and others. Emotions influence how we make decisions, plan, reason, and deal with various aspects. Automated human emotion recognition (AHER) is a critical research topic in Computer Science. It can be applied in many applic...

Exploration and exploitation are fundamental concepts within the domain of Nature-Inspired Algorithms (NIAs) when optimizing solutions. Exploration aims to traverse a substantial portion of the solution space, whereas exploitation is directed at refining the current solution toward either local or global optima. For example, mutation represents an...

Optimizing data instances play a crucial role in dealing with ranking problems. In scenarios such as ranking instances in medical diagnosis, search engine optimization, and information retrieval, there is a need for models that can rank data instances based on the significance of their features within the datasets. This paper provides a hybrid-box...

This concise paper introduces the inaugural Explainable and Interactive Learning to Rank (LTR) Package within the field of Information Retrieval (IR). The framework presented here is built upon the fusion of the Simulated Annealing Strategy with the (1+1)-Evolutionary Strategy, known as SAS-Rank, a ranking algorithm previously established in prior...

Grey wolf optimizer with adaptive upper and lower arrays bounds-based fitness performances

Grey wolf Strategy: Combining Grey Wolf with Evolutionary Strategy to adapt Lower and Upper bounds for better for Learning to Rank

Probability Distributed Grey wolf optimizer Hybrid-Box tool for Ranking Preferences

Grey Wolf for Learning to Rank Problem is developed and customized by Osman Ali Sadek Ibrahim for Ranking Problem. Grey Wolf Algorithm is Proposed as a novel algorithm in Seyedali Mirjalili, Seyed Mohammad Mirjalili , Andrew Lewis, Grey Wolf Optimizer, Advances in Engineering Software 69 (2014). The code was developed and customized by me after che...

In recent years, medical data analysis has become paramount in delivering accurate diagnoses for various diseases. The plethora of medical data sources, encompassing disease types, disease-related proteins, ligands for proteins, and molecular drug components, necessitates adopting effective disease analysis and diagnosis methods. Soft computing tec...

In the Era of Mega Low Earth Orbit (LEO) satellite constellation, the efficient networking through Inter-Satellite Links (ISLs) plays a vital role in its mission success. The deployed networking resources must be justified regarding the feasibility, reliability, and Quality of Service (QoS). The main challenge of such networks is the ISLs intermitt...

Cancer is the major cause of death after cardiovascular infections. In comparison to other sorts of cancer, brain cancer has the lowest survival rate. Brain tumors have many types depending on their shape and location. Diagnosis of the tumor class empowers the specialist to decide the optimal treatment and can help save lives. Over the past years,...

Machine learning algorithms need feature selection (FS) as a significant step toward filtering unnecessary data. This paper proposes a wrapper FS approach that combines the rat swarm optimization (RSO) algorithm with genetic operators to avoid local optimal. In the proposed approach the transfer functions (TFs) are added to balance local and global...

Metaheuristic applications for information retrieval research are limited in spite of the importance of this problem domain. Ranking the retrieved documents based on their importance is a vital issue for the scientific and industrial communities. This paper proposes a novel variable neighborhood search (VNS) algorithm with adaptation based on an ob...

In this article, the authors investigate the development of sensor data fusion-based emotion detection models. They use direct and continuous sensor data to construct emotion prediction models. They use sensor data fusion involving the environmental and physiological signals. This article integrates on-body physiological markers, surrounding sensor...

Feature selection (FS) is one of the basic data preprocessing steps in data mining and machine learning. It is used to reduce feature size and increase model generalization. In addition to minimizing feature dimensionality, it also enhances classification accuracy and reduces model complexity, which are essential in several applications. Traditiona...

Stroke is one of death causes and one the primary causes of severe long-term weakness in the world. In this paper, we compare different distributed machine learning algorithms for stroke prediction on the Healthcare Dataset Stroke. This work is implemented by a big data platform that is Apache Spark. Apache Spark is one of the most popular big data...

Learning to rank (LTR) is the process of constructing a model for ranking documents or objects. It is useful for many applications such as Information retrieval (IR) and recommendation systems. This paper introduces a comparison between Offline and Online (LTR) for IR. It also proposes a novel Offline (1+1)-Simulated Annealing Strategy (SAS-Rank) a...

Automatic recognition of human emotions is not a trivial process. There are many factors affecting emotions internally and externally. Expressing emotions could also be performed in many ways such as text, speech, body gestures or even physiologically by physiological body responses. Emotion detection enables many applications such as adaptive user...

Recently, renewable energy sources have great significance and contracted to be more and more interesting for the numerous reasons. Among these reasons, they are considered environment friendly, green, safe and sustainable power sources. The use of solar radiation is increasing as a clean source of energy. The Photovoltaic (PV) panels that contain...

Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment,...

The use of solar photovoltaic systems (PVs) is increasing as a clean and affordable source of electric energy. The PV cell is the main component of the PV system. To improve the performance, control, and evaluation of the PV system, it is necessary to provide accurate design and to define the intrinsic parameters of the solar cells. There are many...

The parameter estimation of solar cell models is considered an important problem in the computational simulation and design of photovoltaic (PV) systems. In this paper, the PV parameters of single, double, and triple-diode models are extracted and tested under different environmental conditions. The parameter estimation of the three models is prese...

High systolic blood pressure causes many problems, including stroke, brain attack, and others. Therefore, examining blood pressure and discovering issues related to it at the right time can help prevent the occurrence of health problems. Nowadays, health-based data brings a new dimension to healthcare by exploiting the real-time patients’ data to e...

Twitter is a virtual social network where people share their posts and opinions about the current situation, such as the coronavirus pandemic. It is considered the most significant streaming data source for machine learning research in terms of analysis, prediction, knowledge extraction, and opinions. Sentiment analysis is a text analysis method th...

Nearly all of the Egyptian hospitals are currently suffering from shortage in rare blood types (e.g., -AB, -B, +AB) which are urgent to perform vital surgeries. This leads them (hospitals or doctors) to ask patients’ relatives to donate the amount of the required blood. The alternative is that they are forced to pay for the blood if the required ty...

Nearly all of the Egyptian hospitals are currently suffering from shortage in rare blood types (e.g., -AB, -B, +AB), which are needed to perform vital surgeries. This leads them (hospitals or doctors) to ask patients' relatives to donate the amount of the required blood. The alternative is that they are forced to pay for the blood if the required t...

Heart diseases are one of the first causes of death worldwide. This paper presents a real-time system for predicting heart disease from medical data streams that describe a patient’s current health status. The main goal of the proposed system is to find the optimal machine learning algorithm that achieves high accuracy for heart disease prediction....

In recent years, mobile phone technology has taken tremendous leaps and bounds to enable all types of sensing applications and interaction methods, including mobile journaling and self-reporting to add metadata and to label sensor data streams. Mobile self-report techniques are used to record user ratings of their experiences during structured stud...

Stroke is one of death causes and one the primary causes of severe long-term weakness in the world. In this paper, we compare different distributed machine learning algorithms for stroke prediction on the Healthcare Dataset Stroke. This work is implemented by a big data platform that is Apache Spark. Apache Spark is one of the most popular big data...

During the past decade, there were rapid developments in the Internet, computing technologies, wide-spread and use of location-aware technologies such as GPS and mobile phones. These developments influenced how people communicate and share their opinions, views, knowledge, maps, and many others throughout software platforms. These technologies have...

Semantic Web data sources such as DBpedia are a rich resource of structured representations of knowledge about geographical features and provide potential data for computing the results of Question Answering System queries that require geo-spatial computations. Retrieval from these resources of all content that is relevant to a particular spatial q...

The web is growing very fast; it has a very large amount of information from different types. This necessitates the need to ways to arrange and organize this vast amount of data. One of these ways is automatic Web page classification; that is used in many other applications. In this paper, the comparison between various page structural elements, w...

Web page classification is a very important topic today; this is due to the increasing volume of data available on the World Wide Web and the heterogeneity in the formats of the data. For that, there exist a need to ways to manage and extract important knowledge from the web and to facilitate indexing and searching. This paper proposes a method for...