Search results for: concurrent computing

Authors: Panagiotis Tsarchopoulos, Nicos Komninos, Christina Kakderi

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Smart cities are high on the political agenda around the globe. However, planning smart cities and deploying applications dealing with the complex problems of the urban environment is a very challenging task that is difficult to be undertaken solely by the cities. We argue that the uptake of smart city strategies is facilitated, first, through the development of smart city application repositories allowing re-use of already developed and tested software, and, second, through cloud computing which disengages city authorities from any resource constraints, technical or financial, and has a higher impact and greater effect at the city level The combination of these two solutions allows city governments and municipalities to select and deploy a large number of applications dedicated to different city functions, which collectively could create a multiplier effect with a greater impact on the urban environment.

Keywords: smart cities, applications, cloud computing, migration to the cloud, application repositories

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Authors: Aleksey Fedorov

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Building a scalable platform for quantum computing remains one of the most challenging tasks in quantum science and technologies. However, the implementation of most important quantum operations with qubits (quantum analogues of classical bits), such as multiqubit Toffoli gate, requires either a polynomial number of operation or a linear number of operations with the use of ancilla qubits. Therefore, the reduction of the number of operations in the presence of scalability is a crucial goal in quantum information processing. One of the most elegant ideas in this direction is to use qudits (multilevel systems) instead of qubits and rely on additional levels of qudits instead of ancillas. Although some of the already obtained results demonstrate a reduction of the number of operation, they suffer from high complexity and/or of the absence of scalability. We show a strong reduction of the number of operations for the realization of the Toffoli gate by using qudits for a scalable multi-qudit processor. This is done on the basis of a general relation between the dimensionality of qudits and their topology of connections, that we derived.

Keywords: quantum computing, qudits, Toffoli gates, gate decomposition

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

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In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

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Authors: Amir Rashid

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Cloud Computing frameworks empower organizations to cut expenses by outsourcing computation resources on-request. As of now, customers of Cloud service providers have no methods for confirming the privacy and ownership of their information and data. To address this issue we propose the platform of a trusted cloud computing program (TCCP). TCCP empowers Infrastructure as a Service (IaaS) suppliers, for example, Amazon EC2 to give a shout box execution condition that ensures secret execution of visitor virtual machines. Also, it permits clients to bear witness to the IaaS supplier and decide if the administration is secure before they dispatch their virtual machines. This paper proposes a Trusted Cloud Computing Platform (TCCP) for guaranteeing the privacy and trustworthiness of computed data that are outsourced to IaaS service providers. The TCCP gives the deliberation of a shut box execution condition for a client's VM, ensuring that no cloud supplier's authorized manager can examine or mess up with its data. Furthermore, before launching the VM, the TCCP permits a client to dependably and remotely acknowledge that the provider at backend is running a confided in TCCP. This capacity extends the verification of whole administration, and hence permits a client to confirm the data operation in secure mode.

Keywords: cloud security, IaaS, cloud data privacy and integrity, hybrid cloud

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Authors: Telesphore Tiendrebeogo, Oumarou Sié

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Cloud computing technologies have attracted considerable interest in recent years. Thus, these latters have become more important for many existing database applications. It provides a new mode of use and of offer of IT resources in general. Such resources can be used “on demand” by anybody who has access to the internet. Particularly, the Cloud platform provides an ease to use interface between providers and users, allow providers to develop and provide software and databases for users over locations. Currently, there are many Cloud platform providers support large scale database services. However, most of these only support simple keyword-based queries and can’t response complex query efficiently due to lack of efficient in multi-attribute index techniques. Existing Cloud platform providers seek to improve performance of indexing techniques for complex queries. In this paper, we define a new cloud computing architecture based on a Distributed Hash Table (DHT) and design a prototype system. Next, we perform and evaluate our cloud computing indexing structure based on a hyperbolic tree using virtual coordinates taken in the hyperbolic plane. We show through our experimental results that we compare with others clouds systems to show our solution ensures consistence and scalability for Cloud platform.

Keywords: virtual coordinates, cloud, hyperbolic plane, storage, scalability, consistency

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Authors: Arpit K. Shrivastava, Nirmal K. Mohakud, Subrat Kumar, Priyadarshi S. Sahu

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Acute diarrhea is one of the major causes of morbidity and mortality among children less than five years of age. Multiple etiologies have been implicated for infectious gastroenteritis causing acute diarrhea. In our study fecal samples (n=165) were collected from children (<5 years) presenting with symptoms of acute diarrhea. Samples were screened for viral, bacterial, and parasitic etiologies such as Rotavirus, Adenovirus, Diarrhoeagenic Escherichia coli (EPEC, EHEC, STEC, O157, O111), Shigella spp., Salmonella spp., Vibrio cholera, Cryptosporidium spp., and Giardia spp. The overall results from our study showed that 57% of children below 5 years of age with acute diarrhea were positive for at least one infectious etiology. Diarrhoeagenic Escherichia coli was detected to be the major etiological agent (29.09%) followed by Rotavirus (24.24%), Shigella (21.21%), Adenovirus (5.45%), Cryptosporidium (2.42%), and Giardia (0.60%). Among the different DEC strains, EPEC was detected significantly higher in <2 years children in comparison to >2 years age group (p =0.001). Concurrent infections with two or more pathogens were observed in 47 of 160 (28.48%) cases with a predominant incidence particularly in <2-year-old children (66.66%) compared to children of 2 to 5 years age group. Co-infection of Rotavirus with Shigella was the most frequent combination, which was detected in 17.94% cases, followed by Rotavirus with EPEC (15.38%) and Shigella with STEC (12.82%). Detection of multiple infectious etiologies and diagnosis of the right causative agent(s) can immensely help in better management of acute childhood diarrhea. In future more studies focusing on the detection of cases with concurrent infections must be carried out, as we believe that the etiological agents might be complementing each other’s strategies of pathogenesis resulting in severe diarrhea.

Keywords: children, co-infection, infectious diarrhea, Odisha

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Seyong Oh, Jin-Hong Park

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Recently, neuromorphic computing based on brain-inspired artificial neural networks (ANNs) has attracted huge amount of research interests due to the technological abilities to facilitate massively parallel, low-energy consuming, and event-driven computing. In particular, research on artificial synapse that imitate biological synapses responsible for human information processing and memory is in the spotlight. Here, we demonstrate a photosynaptic device, wherein a synaptic weight is governed by a mixed spike consisting of voltage and light spikes. Compared to the device operated only by the voltage spike, ∆G in the proposed photosynaptic device significantly increased from -2.32nS to 5.95nS with no degradation of nonlinearity (NL) (potentiation/depression values were changed from 4.24/8 to 5/8). Furthermore, the Modified National Institute of Standards and Technology (MNIST) digit pattern recognition rates improved from 36% and 49% to 50% and 62% in ANNs consisting of the synaptic devices with 20 and 100 weight states, respectively. We expect that the photosynaptic device technology processed by optoelectronic spike will play an important role in implementing the neuromorphic computing systems in the future.

Keywords: optoelectronic synapse, IGZO (Indium-Gallium-Zinc Oxide) photosynaptic device, optoelectronic spiking process, neuromorphic computing

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Authors: Aymen Gammoudi, Hamza Labbaci, Nizar Messai, Yacine Sam

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Web Service Composition (Mash-up) has been considered as a new approach used to offer the user a set of Web Services responding to his request. These approaches can return a set of similar Mash-ups in a given context that makes users unable to select the perfect one. Recent approaches focus on computing the skyline over a set of Quality of Service (QoS) attributes. However, these approaches are not sufficient in a dynamic web service environment where the delivered QoS by a Web service is inherently uncertain. In this paper, we treat the problem of computing the skyline over a set of similar Mash-ups under certain dimension values. We generate dimensions for each Mash-up using aggregation operations applied to the QoS attributes. We then tackle the problem of computing the skyline under uncertain dimensions. We present each dimension value of mash-up using a frame of discernment and introduce the d-dominance using the Evidence Theory. Finally, we propose our experimental results that show both the effectiveness of the introduced skyline extensions and the efficiency of the proposed approaches.

Keywords: web services, uncertain QoS, mash-ups, uncertain dimensions, skyline, evidence theory, d-dominance

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Authors: Folajinmi Oluwasina, Towolawi Adetayo, Kate Ssamula, Penninah Iutung, Daniel Reijer

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Objective: Routine HIV screening has been promoted as an essential component of efforts to reduce incidence, morbidity, and mortality. The objectives of this study were to identify the optimal annual volume needed to realize the public health goals of HIV screening in the AIDS Healthcare Foundation supported hospitals and establish an implementation process to realize that optimal annual volume. Methods: Starting in 2011 a program was established to routinize HIV screening within communities and government hospitals. In 2016 Five-years of HIV screening data were reviewed to identify the optimal annual proportions of age-eligible patients screened to realize the public health goals of reducing new diagnoses and ending late-stage diagnosis (tracked as concurrent HIV/AIDS diagnosis). Analysis demonstrated that rates of new diagnoses level off when 42% of age-eligible patients were screened, providing a baseline for routine screening efforts; and concurrent HIV/AIDS diagnoses reached statistical zero at screening rates of 70%. Annual facility based targets were re-structured to meet these new target volumes. Restructuring efforts focused on right-sizing HIV screening programs to align and transition programs to integrated HIV screening within standard medical care and treatment. Results: Over one million patients were screened for HIV during the five years; 16, 033 new HIV diagnoses and access to care and treatment made successfully for 82 % (13,206), and concurrent diagnosis rates went from 32.26% to 25.27%. While screening rates increased by 104.7% over the 5-years, volume analysis demonstrated that rates need to further increase by 62.52% to reach desired 20% baseline and more than double to reach optimal annual screening volume. In 2011 facility targets for HIV screening were increased to reflect volume analysis, and in that third year, 12 of the 19 facilities reached or exceeded new baseline targets. Conclusions and Recommendation: Quantifying targets against routine HIV screening goals identified optimal annual screening volume and allowed facilities to scale their program size and allocate resources accordingly. The program transitioned from utilizing non-evidence based annual volume increases to establishing annual targets based on optimal volume analysis. This has allowed efforts to be evaluated on the ability to realize quantified goals related to the public health value of HIV screening. Optimal volume analysis helps to determine the size of an HIV screening program. It is a public health tool, not a tool to determine if an individual patient should receive screening.

Keywords: HIV screening, optimal volume, HIV diagnosis, routine

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Authors: Arfan Ali Nagra, Tariq Shahzad, Meshal Alharbi, Khalid Masood Khan, Muhammad Mugees Asif, Taher M. Ghazal, Khmaies Ouahada

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Gene selection is an essential step for the classification of microarray cancer data. Gene expression cancer data (DNA microarray) facilitates computing the robust and concurrent expression of various genes. Particle swarm optimization (PSO) requires simple operators and less number of parameters for tuning the model in gene selection. The selection of a prognostic gene with small redundancy is a great challenge for the researcher as there are a few complications in PSO based selection method. In this research, a new variant of PSO (Self-inertia weight adaptive PSO) has been proposed. In the proposed algorithm, SIW-APSO-ELM is explored to achieve gene selection prediction accuracies. This new algorithm balances the exploration capabilities of the improved inertia weight adaptive particle swarm optimization and the exploitation. The self-inertia weight adaptive particle swarm optimization (SIW-APSO) is used to search the solution. The SIW-APSO is updated with an evolutionary process in such a way that each particle iteratively improves its velocities and positions. The extreme learning machine (ELM) has been designed for the selection procedure. The proposed method has been to identify a number of genes in the cancer dataset. The classification algorithm contains ELM, K- centroid nearest neighbor (KCNN), and support vector machine (SVM) to attain high forecast accuracy as compared to the start-of-the-art methods on microarray cancer datasets that show the effectiveness of the proposed method.

Keywords: microarray cancer, improved PSO, ELM, SVM, evolutionary algorithms

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Authors: Tonderai Muchenje, Xolani Mkhwanazi

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Precision agriculture uses a number of technologies, devices, protocols, and computing paradigms to optimize agricultural processes. Big data, artificial intelligence, cloud computing, and edge computing are all used to handle the huge amounts of data generated by precision agriculture. However, precision agriculture is still emerging and has a low level of security features. Furthermore, future solutions will demand data availability and accuracy as key points to help farmers, and security is important to build robust and efficient systems. Since precision agriculture comprises a wide variety and quantity of resources, security addresses issues such as compatibility, constrained resources, and massive data. Moreover, conventional protection schemes used in the traditional internet may not be useful for agricultural systems, creating extra demands and opportunities. Therefore, this paper aims at reviewing state of the art of precision agriculture security, particularly in open field agriculture, discussing its architecture, describing security issues, and presenting the major challenges and future directions.

Keywords: precision agriculture, security, IoT, EIDE

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Authors: Inayat Ur Rehman, Georgia Sakellari

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Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: cloud computing, cloud monitoring, performance optimization, high availability

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Authors: Shuen-Tai Wang, Hsi-Ya Chang

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Cloud virtualization technologies are becoming more and more prevalent, cloud users usually encounter the problem of how to access to the virtualized remote desktops easily over the web without requiring the installation of special clients. To resolve this issue, we took advantage of the HTML5 technology and developed web-based remote desktop. It permits users to access the terminal which running in our cloud platform from anywhere. We implemented a sketch of web interface following the cloud computing concept that seeks to enable collaboration and communication among users for high performance computing. Given the development of remote desktop virtualization, it allows to shift the user’s desktop from the traditional PC environment to the cloud platform, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. This is also made possible by the low administrative costs as well as relatively inexpensive end-user terminals and reduced energy expenses.

Keywords: virtualization, remote desktop, HTML5, cloud computing

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Authors: Jawid Ahmad Baktash, Mursal Dawodi, Tomokazu Nagata

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With the rapid growth of Cloud Computing, Formal Methods became a good choice for the refinement of message specification and verification for Dynamic Routing in Cloud Computing. Cloud-based Dynamic Routing is becoming increasingly popular. We propose feedback in Formal Methods for Dynamic Routing and Cloud Computing; the model and topologies show how to send messages from index zero to all others formally. The responsibility of proper verification becomes crucial with Dynamic Routing in the cloud. Formal Methods can play an essential role in the routing and development of Networks, and the testing of distributed systems. Event-B is a formal technique that consists of describing the problem rigorously and introduces solutions or details in the refinement steps. Event-B is a variant of B, designed for developing distributed systems and message passing of the dynamic routing. In Event-B and formal methods, the events consist of guarded actions occurring spontaneously rather than being invoked.

Keywords: cloud, dynamic routing, formal method, Pro-B, event-B

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Authors: Jerome Joshi

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The paper presents the modelling of financial markets using the Stochastic Pi Calculus model. The Stochastic Pi Calculus model is mainly used for biological applications; however, the feature of this model promotes its use in financial markets, more prominently in high frequency trading. The trading system can be broadly classified into exchange, market makers or intermediary traders and fundamental traders. The exchange is where the action of the trade is executed, and the two types of traders act as market participants in the exchange. High frequency trading, with its complex networks and numerous market participants (intermediary and fundamental traders) poses a difficulty while modelling. It involves the participants to seek the advantage of complex trading algorithms and high execution speeds to carry out large volumes of trades. To earn profits from each trade, the trader must be at the top of the order book quite frequently by executing or processing multiple trades simultaneously. This would require highly automated systems as well as the right sentiment to outperform other traders. However, always being at the top of the book is also not best for the trader, since it was the reason for the outbreak of the ‘Hot – Potato Effect,’ which in turn demands for a better and more efficient model. The characteristics of the model should be such that it should be flexible and have diverse applications. Therefore, a model which has its application in a similar field characterized by such difficulty should be chosen. It should also be flexible in its simulation so that it can be further extended and adapted for future research as well as be equipped with certain tools so that it can be perfectly used in the field of finance. In this case, the Stochastic Pi Calculus model seems to be an ideal fit for financial applications, owing to its expertise in the field of biology. It is an extension of the original Pi Calculus model and acts as a solution and an alternative to the previously flawed algorithm, provided the application of this model is further extended. This model would focus on solving the problem which led to the ‘Flash Crash’ which is the ‘Hot –Potato Effect.’ The model consists of small sub-systems, which can be integrated to form a large system. It is designed in way such that the behavior of ‘noise traders’ is considered as a random process or noise in the system. While modelling, to get a better understanding of the problem, a broader picture is taken into consideration with the trader, the system, and the market participants. The paper goes on to explain trading in exchanges, types of traders, high frequency trading, ‘Flash Crash,’ ‘Hot-Potato Effect,’ evaluation of orders and time delay in further detail. For the future, there is a need to focus on the calibration of the module so that they would interact perfectly with other modules. This model, with its application extended, would provide a basis for researchers for further research in the field of finance and computing.

Keywords: concurrent computing, high frequency trading, financial markets, stochastic pi calculus

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Authors: Emmanuel Ogala

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Cloud computing has been envisioned as the next-generation architecture of Information Technology (IT) enterprise. In contrast to traditional solutions where IT services are under physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centres, where the management of the data and services may not be fully trustworthy. This is due to the fact that the systems are opened to the whole world and as people tries to have access into the system, many people also are there trying day-in day-out on having unauthorized access into the system. This research contributes to the improvement of cloud computing security for better operation. The work is motivated by two problems: first, the observed easy access to cloud computing resources and complexity of attacks to vital cloud computing data system NIC requires that dynamic security mechanism evolves to stay capable of preventing illegitimate access. Second; lack of good methodology for performance test and evaluation of biometric security algorithms for securing records in cloud computing environment. The aim of this research was to evaluate the performance of an integrated security system (ISS) for securing exams records in cloud computing environment. In this research, we designed and implemented an ISS consisting of three security mechanisms of biometric (fingerprint), auto-PIN and password into one stream of access control and used for securing examination records in Kogi State University, Anyigba. Conclusively, the system we built has been able to overcome guessing abilities of hackers who guesses people password or pin. We are certain about this because the added security system (fingerprint) needs the presence of the user of the software before a login access can be granted. This is based on the placement of his finger on the fingerprint biometrics scanner for capturing and verification purpose for user’s authenticity confirmation. The study adopted the conceptual of quantitative design. Object oriented and design methodology was adopted. In the analysis and design, PHP, HTML5, CSS, Visual Studio Java Script, and web 2.0 technologies were used to implement the model of ISS for cloud computing environment. Note; PHP, HTML5, CSS were used in conjunction with visual Studio front end engine design tools and MySQL + Access 7.0 were used for the backend engine and Java Script was used for object arrangement and also validation of user input for security check. Finally, the performance of the developed framework was evaluated by comparing with two other existing security systems (Auto-PIN and password) within the school and the results showed that the developed approach (fingerprint) allows overcoming the two main weaknesses of the existing systems and will work perfectly well if fully implemented.

Keywords: performance evaluation, fingerprint, auto-pin, password-based, security systems, cloud computing environment

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Authors: Tim Nedyalkov

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A business decision to move to the cloud brings fundamental changes in how an organization develops and delivers its Information Technology solutions. The accelerated pace of digital transformation across businesses and government agencies increases the reliance on cloud-based services. They are collecting, managing, and retaining large amounts of data in cloud environments makes information security and data privacy protection essential. It becomes even more important to understand what key factors drive successful cloud adoption following the commencement of the Privacy Amendment Notifiable Data Breaches (NDB) Act 2017 in Australia as the regulatory changes impact many organizations and industries. This quantitative correlational research investigated the governance, risk management, and compliance factors contributing to cloud security success. The factors influence the adoption of cloud computing within an organizational context after the commencement of the NDB scheme. The results and findings demonstrated that corporate information security policies, data storage location, management understanding of data governance responsibilities, and regular compliance assessments are the factors influencing cloud computing adoption. The research has implications for organizations, future researchers, practitioners, policymakers, and cloud computing providers to meet the rapidly changing regulatory and compliance requirements.

Keywords: cloud compliance, cloud security, data governance, privacy protection

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Malika Yaici, Assia Arab, Betitra Yakouben, Samia Zermani

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Ubiquitous computing is nowadays a reality through the networking of a growing number of computing devices. It allows providing users with context aware information and services in a heterogeneous environment, anywhere and anytime. Selection of the best context-aware service, between many available services and providers, is a tedious problem. In this paper, a service selection method based on Constraint Satisfaction Problem (CSP) formalism is proposed. The services are considered as variables and domains; and the user context, preferences and providers characteristics are considered as constraints. The Backtrack algorithm is used to solve the problem to find the best service and provider which matches the user requirements. Even though this algorithm has an exponential complexity, but its use guarantees that the service, that best matches the user requirements, will be found. A comparison of the proposed method with the existing solutions finishes the paper.

Keywords: ubiquitous computing, services selection, constraint satisfaction problem, backtrack algorithm

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Authors: Gabrielle Veloso, Melanie Porter, Kelsie Boulton, Adam Guastella

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The aim of the current systematic review was to examine child and parent factors and their associations with parent sensitivity towards children with Autism Spectrum Disorder (ASD). Eight bibliographic databases were used to identify peer-reviewed journal articles examining these associations via quantitative analyses, with parent sensitivity measured via validated and reliable observation coding systems. Thirty-one studies were finalized as having met full criteria for inclusion. The review found agreement across studies that parent sensitivity was positively associated with the child’s initiations and responsiveness toward their parent, with more frequent parent-directed behaviors providing greater opportunity for parents to act and react in sensitive manner. There was also substantial evidence that parent sensitivity predicted later growth in child language ability and child social skills. Other factors such as child attachment, parent insightfulness toward their child, and parent resolution of the diagnosis were also identified across a number of studies as being positively associated with parent sensitivity, however, interpretations of these findings were limited by the absence of covariates identified in the literature as explaining much of the variance in parent sensitivity. With respect to non-significant associations, the literature reliably found that parents showed sensitivity toward their child with ASD, regardless of child age, ASD symptomology, concurrent child social skills, and concurrent child cognitive abilities. The robust associations found in this review and their potential explanations can serve as a jump off point in identifying an understanding protective and risk factors for families of children with ASD. With regard to future directions in research, assessment of the studies’ methodological quality identified points for improvement with respect to the measurement of parent sensitivity, as well as the consideration of several important methodological confounds that may be controlled for in statistical analyses.

Keywords: ASD, autism, parenting, parent sensitivity

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Authors: Indu Saini, Ashu Khanna, S. K. Peddoju

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Cloud computing is the new buzz word today attracting high interest among various domains like business enterprises, Particularly in Small and Medium Enterprises. As it is a pay-per-use model, SMEs have high expectations that adapting this model will not only make them flexible, hassle-free but also economic. In view of such expectations, this paper analyses the possibility of adapting cloud computing technologies in SMEs in light of economic concerns. In this paper, two hypotheses are developed to compare the average annual per-user costs of using Enterprise Resource Planning systems in two ways, The traditional approach and the cloud approach. A web based survey is conducted apart from the Interviews with the peers to collect the data across the selected SMEs and t-test is performed to compare both the technologies on the proposed hypothesis. Results achieved are produced and discussed.

Keywords: cloud computing, small and medium enterprises, enterprise resource solutions, interviews

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Authors: Yasser F. Hassan

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In this paper, a proposed model of cellular automata is studied by means of fractional integral function. A cellular automaton is a decentralized computing model providing an excellent platform for performing complex computation with the help of only local information. The paper discusses how using fractional integral function for representing cellular automata memory or state. The architecture of computing and learning model will be given and the results of calibrating of approach are also given.

Keywords: fractional integral, cellular automata, memory, learning

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Authors: Nivedha Rajaram

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Hybrid Quantum solvers have been given prime focus in recent days by computation problem-solving domain industrial applications. D’Wave Quantum Computers are one such paragon of systems built using quantum annealing mechanism. Discrete Quadratic Models is a hybrid quantum computing model class supplied by D’Wave Ocean SDK - a real-time software platform for hybrid quantum solvers. These hybrid quantum computing modellers can be employed to solve classic problems. One such problem that we consider in this paper is finding a network connectivity knowledge hub in a huge network of systems. Using this quantum solver, we try to find out the prime system hub, which acts as a supreme connection point for the set of connected computers in a large network. This paper establishes an innovative problem approach to generate a connectivity system hub plot for a set of systems using DWave ocean SDK hybrid quantum solvers.

Keywords: quantum computing, hybrid quantum solver, DWave annealing, network knowledge graph

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Authors: Abeer Alkhwaldi, Mumtaz Kamala

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On the inception of the third millennium, there is much evidence that cloud technologies have become the strategic trend for many governments not only developed countries (e.g., UK, Japan, and USA), but also developing countries (e.g. Malaysia and the Middle East region), who have launched cloud computing movements for enhanced standardization of IT resources, cost reduction, and more efficient public services. Therefore, cloud-based e-government services considered as one of the high priorities for government agencies in Jordan. Although of their phenomenal evolution, government cloud-services still suffering from the adoption challenges of e-government initiatives (e.g. technological, human-aspects, social, and financial) which need to be considered carefully by governments contemplating its implementation. This paper presents a pilot study to investigate the citizens' perception of the extent in which these challenges affect the acceptance and use of cloud computing in Jordanian public sector. Based on the data analysis collected using online survey some important challenges were identified. The results can help to guide successful acceptance of cloud-based e-government services in Jordan.

Keywords: challenges, cloud computing, e-government, acceptance, Jordan

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Authors: Amir Rashid

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Today is the world of innovation and Cloud Computing is becoming a day to day technology with every passing day offering remarkable services and features on the go with rapid elasticity. This platform took business computing into an innovative dimension where clients interact and operate through service provider web portals. Initially, the trust relationship between client and service provider remained a big question but with the invention of several cryptographic paradigms, it is becoming common in everyday business. This research work proposes a solution for building a cloud storage service with respect to Data Security addressing public cloud infrastructure where the trust relationship matters a lot between client and service provider. For the great satisfaction of client regarding high-end Data Security, this research paper propose a layer of cryptographic primitives combining several architectures in order to achieve the goal. A survey has been conducted to determine the benefits for such an architecture would provide to both clients/service providers and recent developments in cryptography specifically by cloud storage.

Keywords: data security in cloud computing, cloud storage architecture, cryptographic developments, token key

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Authors: Eduardo Álvarez, Gerardo Quiroga, Jorge Orozco, Gabriel Chavira

Abstract:

AmI proposes a new way of thinking about computers, which follows the ideas of the Ubiquitous Computing vision of Mark Weiser. In these, there is what is known as a Disappearing Computer Initiative, with users immersed in intelligent environments. Hence, technologies need to be adapted so that they are capable of replacing the traditional inputs to the system by embedding these in every-day artifacts. In this work, we present an approach, which uses Radiofrequency Identification (RFID) and Near Field Communication (NFC) technologies. In the latter, a new form of interaction appears by contact. We compare both technologies by analyzing their requirements and advantages. In addition, we propose using a combination of RFID and NFC.

Keywords: touching interaction, ambient intelligence, ubiquitous computing, interaction, NFC and RFID

Procedia PDF Downloads 481

Authors: Linda Smail, Zineb Azouz

Abstract:

Given a Bayesian network relative to a set I of discrete random variables, we are interested in computing the probability distribution P(S) where S is a subset of I. The general idea is to write the expression of P(S) in the form of a product of factors where each factor is easy to compute. More importantly, it will be very useful to give an interpretation of each of the factors in terms of conditional probabilities. This paper considers a semantic interpretation of the factors involved in computing marginal probabilities in Bayesian networks. Establishing such a semantic interpretations is indeed interesting and relevant in the case of large Bayesian networks.

Keywords: Bayesian networks, D-Separation, level two Bayesian networks, factorization of computation

Procedia PDF Downloads 503

Authors: Jeana Cadby, Kae Miyazawa

Abstract:

With rapidly expanding worldwide adoption of mobile technologies, Information and Communication Technology (ITC) is a major energy user and a contributor to global carbon emissions, due to infrastructure and operational energy consumption. The agricultural sector is also significantly responsible for contributing to global carbon emissions. However, ICT cloud computing using mobile technology can directly reduce environmental impacts in the agricultural sector through applications and mobile connectivity, such as precision fertilizer and pesticide applications, or access to weather data, for example. While direct impacts are easily calculated, indirect environmental impacts from ICT cloud computing usage have not been thoroughly investigated. For example, while women may be more poorly equipped for adaptation to environmentally sustainable agricultural practices due to resource constraints, this research concludes that indirect environmental benefits can be achieved by improving rural access to mobile technology for women. Women in advanced roles and secure land tenure are more likely to invest in long-term agricultural conservation strategies, which protect against environmental degradation. This study examines how ICT using mobile technology advances the role of women in rural agricultural systems and indirectly reduces environmental impacts from agricultural production, through literature examination from secondary sources. Increasing access for women to ICT mobile technology provides indirect environmental and social benefits in the rural agricultural sector.

Keywords: cloud computing, environmental benefits, mobile technology, women

Procedia PDF Downloads 146

Authors: Siddhant Yadav, Ann Vincent, Sanjeev Nanda, Karen M. Fischer, Jessica A. Wright

Abstract:

Statement of the Problem: Despite the growing popularity of cannabis in the general population, there are several unknowns regarding its use, specific reasons for use, patient’s choice of products, health benefits, and adverse effects. The aim of our study was to evaluate patient-reported information related to cannabis use that was recorded in the electronic medical records. Methodology & Theoretical Orientation: We manually reviewed the electronic medical records of cannabis users who were part of a large pharmacogenomic study. Data abstracted included demographics, level of education, concurrent alcohol and tobacco use, type of cannabis utilized, formulation, indication, symptomatic improvement, or adverse effects reported. Following this, we did a descriptive statistical analysis. Findings: Our sample of 164 cannabis users were predominantly female (73.2%); 66% of users reported using cannabis for medical indications. Of the 109 patients who recorded information pertaining to alcohol/tobacco use, two-thirds of cannabis users reported concurrent use of alcohol, and about half of them were former or current tobacco users. The mean age of cannabis use was 66 years. Regarding the type of cannabis, 34.1% reported using marijuana, 32.3% reported CBD use, 1.8% reported using THC, and 1.2% reported using Marinol. Oral formulations (capsules, oils, suspensions, brownies, cakes, and tea) were the most common route (44 %). Indications for use included chronic pain (n=76), anxiety (n=9), counteracting side effects of chemotherapy (n=4), and palliative reasons (n=2). Fifty-eight of the 76 users endorsed improvement in chronic pain (80%), 5 users reported improvement in anxiety, and 2 reported improvement in side effects of chemotherapy. Conclusion & Significance: The majority of our cannabis users were Caucasian females, and there was a high likelihood of coinciding use of alcohol/tobacco in patients using cannabis. Most of our patients used the oral formulation for chronic pain. Importantly, a considerable number of patients reported improvements in chronic pain, anxiety, and side effects of chemotherapy.

Keywords: cannabis use, adverse effects, medical practice, indications

Procedia PDF Downloads 77