The market for Electric Vehicles (EVs) has expanded tremendously as seen in the recent Conference of the Parties 27 (COP27) held at Sharm El Sheikh, Egypt in November 2022. This needs the creation of an ecosystem that is user-friendly and secure. Internet-connected Electric Vehicle Charging Stations (EVCSs) provide a rich user experience and add-on services. Eventually, the EVCSs are connected to a management system, which is the Electric Vehicle Charging Station Management System (EVCSMS). Attacking the EVCS ecosystem remotely via cyberattacks is rising at the same rate as physical attacks

Abdominal Aortic Aneurysm (AAA) is a serious medical condition characterized by the abnormal enlargement of the abdominal aorta. If left untreated, AAA can have life-threatening consequences. Accurate segmentation of the aorta in Computed Tomography Angiography (CTA) images plays a vital role in treatment planning for AAA. However, manual and semi-automatic segmentation methods suffer from limitations in terms of time and accuracy. This study presents a deep learning pipeline that aims to fully automate the precise and efficient segmentation of the aorta and its branches within CTA images. A

Automotive steering wheel switches technologies are evolving to give easy access to the several interior or exterior functions. This is worth a deep analysis for the current trends in order not to become unintuitive for the driver due to the increasing number of buttons. Through different technologies particularly the capacitive ones, range of innovative solutions have been developed like reconfigurable buttons on the steering wheel to offer commanding several functions twice or triple the number of allocated push buttons. In this paper, we address the problem in a different freely way to

Nowadays events stream processing is one of the top demanding field(s) because of the business urgent need for ongoing real time analytics & decisions. Most business domains avail huge amount of data aiming to make use of each data point efficiently. Corporate(s) have a cloud of events vary from internal business transactions, social media feeds, IoT devices logs,.. etc. In this paper we would discuss state of the art event stream processing technologies using cloud of events by summarizing event stream processing definition, data flow architectures, common use cases, frameworks and

The exploration of sentiment analysis in multilingual contexts, particularly through the integration of deep learning techniques and knowledge graphs, represents a significant advance in language processing research. This study specifically concentrates on the Arabic language, addressing the challenges presented by its morphological complexity. While the primary focus is Arabic, the research also includes a comprehensive review of related work in other languages such as Bangla and Chinese. This contextualizes the challenges and solutions found in Arabic sentiment analysis within a broader

Ransomwares are amongst the most dangerous malwares that face and affect any business by restricting data access or leaking sensitive information over the internet. Ransomwares binary analysis can provide a way to define the relationships between distinct features employed by ransomware families. Malware classification and clustering systems offer an effective malware indexing with search functionalities, similarity checking, samples classification and clustering. Most studies focus on the static and dynamic features extraction, machine and deep learning or visualization techniques used to

Despite software startups often not handlingsensitive data, the implementation of robust security measures is crucial to mitigate significant financial and reputational risks. This study investigates the cost-benefit analysis of implementing best practices in penetration testing (Pentest) versus notimplementing them, using Roboost as a case study. It emphasizes that proactive security investments not only protect current assets but also prepare organizations for future growthThe research employs a mixed-methods approach, combining quantitative analysis of financial data with qualitative

The market needs a deeper and more comprehensive grasp of its insight, where the analytics world and methodologies such as 'Sentiment Analysis' come in. These methods can assist people especially 'business owners' in gaining live insights into their businesses and determining wheatear customers are satisfied or not. This paper plans to provide indicators by gathering real world Amazon reviews from Egyptian customers. By applying both Bidirectional Encoder Representations from Transformers 'Bert' and 'Text Blob' sentiment analysis methods. The processes shall determine the overall satisfaction

The automotive industry currently is seeking to increase remote connectivity to a vehicle, which creates a high demand to implement a secure way of connecting vehicles, as well as verifying and storing their data in a trusted way. Furthermore, much information must be leaked in order to correctly diagnose the vehicle and determine when or how to remotely update it. In this context, we propose a Blockchain-based, fully automated remote vehicle diagnosis system. The proposed system provides a secure and trusted way of storing and verifying vehicle data and analyzing their performance in

The growth of mobile application development industry made it crucial for researchers to study the industry practices of choosing mobile applications programming languages, systems, and tools. With the increased attention of cross-platform mobile applications development from both researchers and industry, this paper aims at answering the question of whether most of the industries are using cross-platform development or native development. The paper collects feedback about industry’s most used mobile development systems. In addition, it provides a map of the different technologies used by