Multi-view human action recognition system employing 2DPCA
A novel algorithm for view-invariant human action recognition is presented. This approach is based on Two-Dimensional Principal Component Analysis (2DPCA) applied directly on the Motion Energy Image (MEI) or the Motion History Image (MHI) in both the spatial domain and the transform domain. This method reduces the computational complexity by a factor of at least 66, achieving the highest recognition accuracy per camera, while maintaining minimum storage requirements, compared with the most recent reports in the field. Experimental results performed on the Weizmann action and the INIRIA IXMAS
Multiplicity per rapidity in Carruthers and hadron resonance gas approaches
The multiplicity per rapidity of the well-identified particles π-, π+, k-, k+, p¯ , p, and p- p¯ measured in different high-energy experiments, at energies ranging from 6.3 to 5500 GeV, is successfully compared with the Cosmic Ray Monte Carlo event generator. For these rapidity distributions, we introduce a theoretical approach based on fluctuations and correlations (Carruthers approach) and another one based on statistical thermal assumptions (hadron resonance gas approach). Both approaches are fitted to both sets of results deduced from experiments and simulations. We found that the
In silico identification of potential key regulatory factors in smoking-induced lung cancer
Background: Lung cancer is a leading cause of cancer-related death worldwide and is the most commonly diagnosed cancer. Like other cancers, it is a complex and highly heterogeneous disease involving multiple signaling pathways. Identifying potential therapeutic targets is critical for the development of effective treatment strategies. Methods: We used a systems biology approach to identify potential key regulatory factors in smoking-induced lung cancer. We first identified genes that were differentially expressed between smokers with normal lungs and those with cancerous lungs, then integrated
Labour productivity in building construction: A field study
This paper describes a field study conducted over a period of 11-months on labour productivity observed during the construction of a new university campus in Cairo, Egypt. The campus is being built on 127 acres and the field study was conducted during the construction of two main buildings; each of 20,000 m 2 built up area. The study utilized work sampling (WS), craftsman questionnaire (CQ), and foreman delay survey (FDS) methods to analyze labour productivity of three indicative and labour-intensive trades, namely formwork, masonry work, and HVAC duct installation. The results were also
Artificial intelligence for retail industry in Egypt: Challenges and opportunities
In the era of digital transformation, a mass disruption in the global industries have been detected. Big data, the Internet of Things (IoT) and Artificial Intelligence (AI) are just examples of technologies that are holding such digital disruptive power. On the other hand, retailing is a high-intensity competition and disruptive industry driving the global economy and the second largest globally in employment after the agriculture. AI has large potential to contribute to global economic activity and the biggest sector gains would be in retail. AI is the engine that is poised to drive the
Entrepreneurial ecosystems: Global practices and reflection on the egyptian context
Following the Egyptian revolution that had taken place in 2011, many social and economic norms changed. The Egyptian economy witnessed a severe deterioration. In 2016, the Egyptian pound lost almost 60% of its value overnight. Egyptian government and foreign development agencies rallied to find a remedy to the economic downturn. With no jobs, young Egyptians started experimenting with the possibility of entrepreneurship. This acted as a pretext to the massive transformations taking place in the Egyptian ecosystem. The objective of this paper is to identify how Egypt should shape its
A dynamic system development method for startups migrate to c loud
Cloud computing has become the most convenient environment for startups to run, build and deploy their products. Most startups work on availing platforms as a solution for problems related to education, health, traffic and others. Many of these platforms are mobile applications. With platforms as a service (PaaS), startups can provision their applications and gain access to a suite of IT infrastructure as their business needs. But, startups face many business and technical challenges to adapt rapidly to cloud computing. This paper helps startups to build a migration strategy. It discusses
Supporting bioinformatics applications with hybrid multi-cloud services
Cloud computing provides a promising solution to the big data problem associated with next generation sequencing applications. The increasing number of cloud service providers, who compete in terms of performance and price, is a clear indication of a growing market with high demand. However, current cloud computing based applications in bioinformatics do not profit from this progress, because they are still limited to just one cloud service provider. In this paper, we present different use case scenarios using hybrid services and resources from multiple cloud providers for bioinformatics
Trans-Compiler based Mobile Applications code converter: Swift to java
Numerous commercial tools like Xamarin, React Native and PhoneGap utilize the concept of cross-platform mobile applications development that builds applications once and runs it everywhere opposed to native mobile app development that writes in a specific programming language for every platform. These commercial tools are not very efficient for native developers as mobile applications must be written in specific language and they need the usage of specific frameworks. In this paper, a suggested approach in TCAIOSC tool to convert mobile applications from Android to iOS is used to develop the
Studying Genes Related to the Survival Rate of Pediatric Septic Shock
Pediatric septic shock is generally considered as a devastating clinical syndrome that can lead to tissue damage and organ failure due to the over exaggerated immune response to an infection. Therefore, in this paper, we attempted to early identify the clinical course of such disease with the aid of peripheral blood T-cells of 181 pediatric patients who admitted to Intensive Care Unit (ICU), Accordingly, 34 differential expressed genes have been identified as biological genetic biomarkers. Minimum redundancy and maximum relevance feature selection strategy has been proposed for the discovery
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