Forensic Process as a Service (FPaaS) for Cloud Computing

Cloud computing is the technology that enables individuals and businesses to utilize computing services (e.g. online file storage, social networking sites, webmail)and a shared pool of resources (e.g. data storage space, networks, user applications) from anywhere over the Internet. Cloud computing has become popular as a cost-effective and convenient computing paradigm. However, cloud computing architecture is at its infancy stage and lacks support for security and forensic investigations. Due to the distributed and virtual nature of cloud, malicious activities can be carried out very easily and are very difficult to subsequently investigate. Cloud forensic investigators currently face challenges as they lack forensic tools and techniques in context of cloud. This highlights the need to develop the new research area of digital forensics in the cloud computing model. This paper presents a cloud forensic process that consists of (i) Identification, (ii) Collection/Acquisition and preservation, (iii) Examination/Processing and analysis, and (iv) Results dissemination phases. In addition, this paper develops the proposed forensic process as a service (FPaaS) using cloud-based Business Process Execution Language (BPEL) that combines the four phases/services into a new composite service called FPaaS

Adopting Continuing Personal and Professional Development to Improve Quality of Teaching (Personal Experience)

Quality of teaching is an essential issue in developing a significant academic quality. Continuing personal and professional development is a procedure of improving teaching quality. It helps the teacher to spot weaknesses and overcome them by adopting and developing individual learning plan. This paper introduces the different teaching theories to follow in the teaching process and how these theories affect positively personal teaching experience. The paper also recommends the adoption of the process of continuing professional and developing program to create a new culture of personal development through accepting observations from line manager or colleagues to raise strengths and weaknesses of teaching and consequently improving the quality of teaching and then improve the academic qualit

Coaching, Tutoring and Mentoring in the Higher Education as a solution ‎to retain students in their major and help them achieve success.

This paper introduces new concepts of mentoring and tutoring which can be applied in the higher education institutions to improve the quality of teaching and learning in the Palestinian Universities especially the IT faculties where the students retention rates and performance are low as they face lots of problems and could not find solutions but to change their major and try another faculty or stay more than four years before graduation or withdrew from the faculty and leave education because of failure. These concepts are quite important for both students and teachers and consequently for the university. Teachers should utilize from these concepts and be close to the students, listen to their problems and concerns and propose actions to improve the overall performance

Optimization Water Leakage Detection using Wireless Sensor Networks (OWLD)

This paper presents a technical method to monitor the water distribution pipelines against leakage and to control the pump when the water level decreases in the tank. Water leakage is the most popular cause of water wasted in the domestic water distribution systems. Nowadays most people have their smartphone nearby them; therefore, adding an interface on the smartphone to control an automated system is a big plus. Energy saving is a benefit of the Optimization Water Leakage Detection (OWLD) system. It enables us to save energy, time and cost by having smart leakage detection in pipelines, measuring the water level in the tank and controlling the pump when the water level is low. This paper focuses mainly on two parts: The first part is an alarm based on Global System for Mobile technology (GSM) to send a Short Message Service (SMS) to the owner. This is made up of the following components: sensors, GSM Module, Arduino and relays to control the device. The second is the controlling part; it uses android application mobile to control the pump. The proposed system can effectively improve the efficiency of operation, reduce delay time and cost of maintenance pipelines after leakage detection

A System Dynamics Model to Predict Municipal Waste Generation and Management Costs in Developing Areas

This paper utilized system dynamics modeling as a new analytical approach to predict both the municipal waste generated and the associated disposal costs in developing areas. This approach facilitates the decomposition of general waste into its main components to enable municipalities to manage recyclables and find out the feasibility of performing recycling better rather than disposal by performing comparative disposal cost analysis. This study is different from previous work as it only considers population as a factor to predict the total waste generated and recycled, together with the associated expenditure and disposal cost savings. The approach is verified by applying it to a case study in Nablus and demonstrates the evaluation of the quantity and composition of generated waste by considering population as the main influencing factor. The quantity and composition of municipal solid waste was evaluated to identify opportunities for waste recycling in the Nablus municipality. Municipal solid waste was collected and classified into eight main physical categories. The system dynamics model enable the quantity of each generated component such as plastic and metals to be anticipated together with the cost of recycling or disposal

Developing a Knowledge-Based System for Diagnosis and Treatment Recommendation of Neonatal Diseases Using CLIPS

A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from a clinical dataset. The PART algorithm achieved the highest performance result with 98.06% accuracy under 10-fold cross-validation, and the generated rules were used to develop the knowledge-based system. The system achieved 90.9% accuracy in system performance testing and 89.2% in user acceptance testing, and is intended to serve as an assistant tool for healthcare experts

AI-Driven Innovations in Agriculture: Transforming Farming Practices and Outcomes

Abstract: Artificial Intelligence (AI) is transforming the agricultural sector, enhancing both productivity and sustainability. This paper delves into the impact of AI technologies on agriculture, emphasizing their application in precision farming, predictive analytics, and automation. AI-driven tools facilitate more efficient crop and resource management, leading to higher yields and a reduced environmental footprint. The paper explores key AI technologies, such as machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, it discusses challenges like data privacy, barriers to technology adoption, and the ethical implications of AI in farming. Integrating AI into agricultural practices holds the promise of greater efficiency and sustainability, paving the way for future innovations

Image feature extraction using compressive sensing

In this paper a new approach for image feature extraction is presented. We used the Compressive Sensing (CS) concept to generate the measurement matrix. The new measurement matrix is different from the measurement matrices in literature as it was constructed using both zero mean and nonzero mean rows. The image is simply projected into a new space using the measurement matrix to obtain the feature vector. Another proposed measurement matrix is a random matrix constructed from binary entries. Face recognition problem was used as an example for testing the feature extraction capability of the proposed matrices. Experiments were carried out using two well-known face databases, namely, ORL and FERET databases. System performance is very promising and comparable with the classical baseline feature extraction algorithms. © Springer International Publishing Switzerland 2014