Heath data are sensitive and valuable for individuals. The patients need to integrate and manage their medical data continuously. Personal Health Record (PHR) is introduced as a solution for managing their health information. It gives patients ownership over their medical data and provides physicians with realignment data. However, it does not achieve reliability, traceability, trust, nor security of patient control. Centralization of any data is vulnerable to the problem of hacking and single failure in addition to control from one organization. So, the centralization of data is the common

This chapter explores the integration of omics and bioinformatics for Parkinson's disease (PD) diagnosis and potential cure discovery. It begins with an overview of PD and its prevalence, followed by an examination of key mutations in genes linked to the disease. These mutations lead to dysfunctional proteins, triggering PD progression. The chapter delves into techniques like whole-exome sequencing (WES), genome-wide association sequencing (GWAS), and whole-genome sequencing (WGS). These methods enable the exploration of omics levels such as lipidomics, metabolomics, genomics, and proteomics

Topic modeling automatically infers the hidden themes in a collection of documents. There are several developed techniques for topic modeling, which are broadly categorized into Algebraic, Probabilistic and Neural. In this paper, we use an Arabic dataset to experiment and compare six models (LDA, NMF, CTM, ETM, and two Bertopic variants). The comparison used evaluation metrics of topic coherence, diversity, and computational cost. The results show that among all the presented models, the neural BERTopic model with Roberta-based sentence transformer achieved the highest coherence score (0.1147)

Following cybersecurity st and ards nowadays is becoming one of the highest priorities to the digital specialists. Due to the global direction to apply digital transformation, data security is a concern. It becomes crucial to ensure data confidentiality, integrity, and availability whether while transmitting, at rest or even while processing it. The difficulty being faced by organizations, is the challenge of applying the needed security measures. Also, implementing, and maintaining the cryptographic algorithms that ensure the wellness of the data encryption. Having a crypto library or a

Today, automatic food/non-food classification became extremely important for many real-time applications, specifically since the pandemic of the COVID-19 virus. Such that the 'no food policy' now became applied more than ever to help decrease the spread of the COVID-19 virus. Consequently, many studies used deep neural networks for the food/non-food classification task, yet these deep neural networks were computationally expensive. As a result, in this paper, a lightweight Convolution Neural Network (CNN) is proposed and put into use for classifying foods and non-foods. Compared to prior

Cross-platform mobile application development is emerging widely in the mobile applications industry. Cross-platform Frameworks (CPFs) like React Native, Flutter, and Xamarin are used by many developing companies. The technology these frameworks use faces performance and resource use efficiency limitations compared to native applications. The native applications are written in the native languages of the platforms. Trans-complier-based conversion between native languages of different platforms of mobile applications has been addressed in recent research. However, the problem statement needed

Gold is one of the valuable materials that is used for funding trading purchases. Nowadays, more investors are interested in gold investments due to the sudden increase in gold prices. However, transactions involving gold are risky, the price of gold fluctuates wildly due to the unpredictability of the gold market. Hence, there is a need for the development of gold price prediction scheme to assist and support investors, marketers, and financial institutions in making effective economic and monetary decisions. This paper analyzes the correlation between gold price movements and sentiments of

Multiple Sclerosis (MS) is a long-term autoimmune disorder affecting the central nervous system, marked by inflammation, demyelination, and neurodegeneration. While the exact cause of MS remains unknown, recent research indicates that environmental factors, particularly diet, may influence the disease's risk and progression. As a result, the potential neuroprotective effects of coffee, one of the most popular beverages worldwide, have garnered significant attention due to its rich content of bioactive compounds. This chapter explores the impact of coffee consumption on patients with Multiple

With the extensive usage of mobile applications in daily life, it has become crucial for the companies of software to develop applications for the most popular platforms such as Android and iOS in the shortest possible time and at the lowest possible cost. However, ensuring consistent UIs and functionalities among cross-platform versions can be challenging and costly since different platforms have their own UI controls and programming languages. Also, when cross-platform tools are used, it is always time consuming to learn a new language. Many solutions were proposed to achieve the native

Electric vehicles (EVs) can only provide lower carbon emissions than conventional, internal combustion-powered vehicles if they are charged using green energy. They also have the drawback of long charging times to 'refuel' them. To combat these two problems, a solar-powered battery charging and swapping station was developed using centered-human design and systems engineering. The design focuses on electric two-wheeled vehicles (e-scooters) due to the easier handling of their light and low-capacity batteries compared to electric cars. These stations are easy to maintain and manage and can be