Search results for: distributed computing

Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 160

Authors: Shinoy Vengaramkode Bhaskaran, Kaushik Sathupadi, Sandesh Achar

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Human locomotion recognition is important in a variety of sectors, such as robotics, security, healthcare, fitness tracking and cloud computing. With the increasing pervasiveness of peripheral devices, particularly Inertial Measurement Units (IMUs) sensors, researchers have attempted to exploit these advancements in order to precisely and efficiently identify and categorize human activities. This research paper introduces a state-of-the-art methodology for the recognition of human locomotion patterns in a cloud environment. The methodology is based on a publicly available benchmark dataset. The investigation implements a denoising and windowing strategy to deal with the unprocessed data. Next, feature extraction is adopted to abstract the main cues from the data. The SelectKBest strategy is used to abstract optimal features from the data. Furthermore, state-of-the-art ML classifiers are used to evaluate the performance of the system, including logistic regression, random forest, gradient boosting and SVM have been investigated to accomplish precise locomotion classification. Finally, a detailed comparative analysis of results is presented to reveal the performance of recognition models.

Keywords: artificial intelligence, cloud computing, IoT, human locomotion, gradient boosting, random forest, neural networks, body-worn sensors

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Authors: Jaleh Shoshtarian Malak, Niloofar Mohamadzadeh

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Managing pre-hospital emergency patients requires real-time practices and efficient resource utilization. Since we are facing a distributed Network of healthcare providers, services and applications choosing the right resources and treatment protocol considering patient situation is a critical task. Delivering care to emergency patients at right time and with the suitable treatment settings can save ones live and prevent further complication. In recent years Multi Agent Systems (MAS) introduced great solutions to deal with real-time, distributed and complicated problems. In this paper we propose a multi agent based pre-hospital emergency management architecture in order to manage coordination, collaboration, treatment protocol and healthcare provider selection between different parties in pre-hospital emergency in a self-organizing manner. We used AnyLogic Agent Based Modeling (ABM) tool in order to simulate our proposed architecture. We have analyzed and described the functionality of EMS center, Ambulance, Consultation Center, EHR Repository and Quality of Care Monitoring as main collaborating agents. Future work includes implementation of the proposed architecture and evaluation of its impact on patient quality of care improvement.

Keywords: multi agent systems, pre-hospital emergency, simulation, software architecture

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Authors: Mohamed I. Mahrous, Mohamed G. Ashmawy

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Hybrid genetic algorithm (HGA) is proposed in this paper to determine the economic scheduling of electric power generation over a fixed time period under various system and operational constraints. The proposed technique can outperform conventional genetic algorithms (CGAs) in the sense that HGA make it possible to improve both the quality of the solution and reduce the computing expenses. In contrast, any carefully designed GA is only able to balance the exploration and the exploitation of the search effort, which means that an increase in the accuracy of a solution can only occure at the sacrifice of convergent speed, and vice visa. It is unlikely that both of them can be improved simultaneously. The proposed hybrid scheme is developed in such a way that a simple GA is acting as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method (pattern search technique) is next employed to do the fine tuning. The aim of the strategy is to achieve the cost reduction within a reasonable computing time. The effectiveness of the proposed hybrid technique is verified on two real public electricity supply systems with 13 and 40 generator units respectively. The simulation results obtained with the HGA for the two real systems are very encouraging with regard to the computational expenses and the cost reduction of power generation.

Keywords: genetic algorithms, economic dispatch, pattern search

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Authors: Asim Majeed, Rehan Bhana, Mak Sharma, Rebecca Goode, Nizam Bolia, Mike Lloyd-Williams

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This study aims to investigate and explore the underlying causes of security concerns of customers emerged when WHSmith transformed its physical system to virtualized business model through NetSuite. NetSuite is essentially fully integrated software which helps transforming the physical system to virtualized business model. Modern organisations are moving away from traditional business models to cloud based models and consequently it is expected to have a better, secure and innovative environment for customers. The vital issue of the modern age race is the security when transforming virtualized through cloud based models and designers of interactive systems often misunderstand privacy and even often ignore it, thus causing concerns for users. The content analysis approach is being used to collect the qualitative data from 120 online bloggers including TRUSTPILOT. The results and finding provide useful new insights into the nature and form of security concerns of online users after they have used the WHSmith services offered online through their website. Findings have theoretical as well as practical implications for the successful adoption of cloud computing Business-to-Business model and similar systems.

Keywords: innovation, virtualization, cloud computing, organizational flexibility

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Authors: Junze Li, M. Li

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Laser diodes fabricated from the III-nitride material system are emerging solutions for the next generation telecommunication systems and optical clocks based on Ca at 397nm, Rb at 420.2nm and Yb at 398.9nm combined 556 nm. Most of the applications require single longitudinal optical mode lasers, with very narrow linewidth and compact size, such as communication systems and laser cooling. In this case, the GaN based distributed feedback (DFB) laser diode is one of the most effective candidates with gratings are known to operate with narrow spectra as well as high power and efficiency. Given the wavelength range, the period of the first-order diffraction grating is under 100 nm, and the realization of such gratings is technically difficult due to the narrow line width and the high quality nitride overgrowth based on the Bragg grating. Some groups have reported GaN DFB lasers with high order distributed feedback surface gratings, which avoids the overgrowth. However, generally the strength of coupling is lower than that with Bragg grating embedded into the waveguide within the GaN laser structure by two-step-epitaxy. Therefore, the overgrowth on the grating technology need to be studied and optimized. Here we propose to fabricate the fine step shape structure of first-order grating by the nanoimprint combined inductively coupled plasma (ICP) dry etching, then carry out overgrowth high quality AlGaN film by metalorganic chemical vapor deposition (MOCVD). Then a series of gratings with different period, depths and duty ratios are designed and fabricated to study the influence of grating structure to the nano-heteroepitaxy. Moreover, we observe the nucleation and growth process by step-by-step growth to study the growth mode for nitride overgrowth on grating, under the condition that the grating period is larger than the mental migration length on the surface. The AFM images demonstrate that a smooth surface of AlGaN film is achieved with an average roughness of 0.20 nm over 3 × 3 μm2. The full width at half maximums (FWHMs) of the (002) reflections in the XRD rocking curves are 278 arcsec for the AlGaN film, and the component of the Al within the film is 8% according to the XRD mapping measurement, which is in accordance with design values. By observing the samples with growth time changing from 200s, 400s to 600s, the growth model is summarized as the follow steps: initially, the nucleation is evenly distributed on the grating structure, as the migration length of Al atoms is low; then, AlGaN growth alone with the grating top surface; finally, the AlGaN film formed by lateral growth. This work contributed to carrying out GaN DFB laser by fabricating grating and overgrowth on the nano-grating patterned substrate by wafer scale, moreover, growth dynamics had been analyzed as well.

Keywords: DFB laser, MOCVD, nanoepitaxy, III-niitride

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Authors: Loong Qing Zhe, Foo Jing Heng

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A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

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Authors: Hossein Soltani, Zahra Hojati, Seyed Reza Attarzadeh Hossini

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Anxiety levels before and during competition are not clear due to conflicting findings; various athletes have reported different levels of anxiety from much too low. With respect to the fact that every sport field has its own special nature, and the lack of a comprehensive theory in this field made the author to compare competitive state anxiety among team sport and individual sport athletes in Iran. The sample included 120 male athletes, 60 athletes in individual sports (taekwondo, karate, and wrestling) and 60 athletes in team sports (volleyball, basketball, futsal). All participants in this study were regularly competing at the super leagues and regional level. The research instrument employed was the Persian version of the Competitive State Anxiety Inventory-2. This inventory was distributed among the subjects about 30 minutes before the first competition. Finally, using one-way ANOVA data was analyzed. The results indicated that the mean score of cognitive and somatic anxiety among individual sport athletes was higher than that of team sport athletes (P<0.05). Self-confidence levels of individual sports athletes was higher than that of team sports athletes but the difference was not significant (P >0.05). It seems the being part of a team alleviates some of the pressure experienced by those who compete alone. Conclusion: Individual sport athletes may be more exposed to evaluation and more engaged in their own skills and abilities than team sport athletes given that responsibility for performance is not distributed across several performers.

Keywords: competitive state anxiety, cognitive anxiety, somatic anxiety, team sports, individual sports

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Authors: G. Mazor, I. Ladizhensky, A. Shapiro, D. Nemirovsky

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A lot of researches was dedicated to the evaluation of the efficiency of the uniform constant and temporary coatings enhancing a heat transfer rate. Our goal is an investigation of the sand coatings distributed by both uniform and non-uniform forms. The sand of different sizes (0.2-0.4-0.6 mm) was attached to a copper ball (30 mm diameter) surface by means of PVA adhesive as a uniform layer. At the next stage, sand spots were distributed over the ball surface with an areal density that ranges between one spot per 1.18 cm² (for low-density spots) and one spot per 0.51 cm² (for high-density spots). The spot's diameter value varied from 3 to 6.5 mm and height from 0.5 to 1.5 mm. All coatings serve as a heat transfer enhancer during the quenching in liquid nitrogen. Highest heat flux densities, achieved during quenching, lie in the range 10.8-20.2 W/cm², depending on the sand layer structure. Application of the enhancing coating increases an amount of heat, evacuated by highly effective nucleate and transition boiling, by a factor of 4.5 as compared to the bare sample. The non-uniform sand coatings were increasing the heat transfer rate value under all pool boiling conditions: nucleate boiling, transfer boiling and the most severe film boiling. A combination of uniform sand coating together with high-density sand spots increased the average heat transfer rate by a factor of 3.

Keywords: heat transfer enhancement, nucleate boiling, film boiling, transfer boiling

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Authors: Roseline Oghogho Osaseri, Osaseri E. I.

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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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Authors: Nader Chavoshi Boroujeni, Naser Chavoshi Boroujeni

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Considering the importance of managerial competencies on organizational performance as well as the role of social capital and entrepreneurship as mediator parameters affecting organizational performance, this study attempts to examine the impact carefully. In this regard, Isfahan Science and Technology Town (ISTT) as an effective and knowledge generator company that has a great effect on improving organizational performances of many other companies such as Knowledge-Based Companies (KBCs) activing in the ISTT's site was selected as statistical population. According to coordination with the Department of Development and Technology of ISTT, all employees of ISTT and active KBCs were selected as sample. Then, to analyze the variables a standard and self-made questionnaire containing 98 questions was designed and distributed. Of the 350 questionnaires distributed, 319 questionnaires were collected that 313 cases were confirmed and analyzed. To confirm the reliability of questionnaire, the Leader professor and two other professors approved it. Cronbach's alpha coefficient was used to validate the questionnaire that all coefficient was between 0/7 and 0/95. So, the validity was confirmed. After descriptive study population, the normality of distribution was investigated with Kolmogorov-Smirnov test. Finally, the results obtained from the questionnaires were analyzed by Amos software that all hypotheses were confirmed.

Keywords: managerial competencies, personnel organizational performance, entrepreneurship, social capital

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Authors: Jawid Ahmad Baktash, Tadashi Shiroma, Tomokazu Nagata, Yuji Taniguchi, Morikazu Nakamura

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The goal of this paper is to explore the use of formal methods for Dynamic Routing, The purpose of network communication with dynamic routing is sending a massage from one node to others by using pacific protocols. In dynamic routing connections are possible based on protocols of Distance vector (Routing Information Protocol, Border Gateway protocol), Link State (Open Shortest Path First, Intermediate system Intermediate System), Hybrid (Enhanced Interior Gateway Routing Protocol). The responsibility for proper verification becomes crucial with Dynamic Routing. Formal methods can play an essential role in the Routing, development of Networks and testing of distributed systems. Event-B is a formal technique consists of describing rigorously the problem; introduce solutions or details in the refinement steps to obtain more concrete specification, and verifying that proposed solutions are correct. The system is modeled in terms of an abstract state space using variables with set theoretic types and the events that modify state variables. Event-B is a variant of B, was designed for developing distributed systems. In Event-B, the events consist of guarded actions occurring spontaneously rather than being invoked. The invariant state properties must be satisfied by the variables and maintained by the activation of the events.

Keywords: dynamic rout RIP, formal method, event-B, pro-B

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Authors: Namrata D. Hiremath, Mahalaxmi Bhille, P. G. Sunitha Hiremath

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Computer systems play an integral role in all facets of the engineering profession. This calls for an understanding of the processor-level components of computer systems, their design and operation, and their impact on the overall performance of the systems. Systems users are always in need of faster, more powerful, yet cheaper computer systems. The focus of Computer Science engineering graduates is inclined towards software oriented base. To be an efficient programmer there is a need to understand the role of hardware architecture towards the same. It is essential for the students of Computer Science and Engineering to know the basic building blocks of any computing device and how the digital principles can be used to build them. Hence two courses Digital Electronics of 3 credits, which is associated with lab of 1.5 credits and Computer Organization of 5 credits, were introduced at the sophomore level. Activity was introduced with the objective to teach the hardware concepts to the students of Computer science engineering through structured lab. The students were asked to design and implement a component of a computing device using MultiSim simulation tool and build the same using hardware components. The experience of the activity helped the students to understand the real time applications of the SSI and MSI components. The impact of the activity was evaluated and the performance was measured. The paper explains the achievement of the ABET outcomes a, c and k.

Keywords: digital, computer organization, ABET, structured enquiry, course activity

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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Authors: Thilina Ranaweera, Enes Makalic, John L. Hopper, Adrian Bickerstaffe

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Data are the primary asset of biomedical researchers, and the engine for both discovery and research translation. As the volume and complexity of research datasets increase, especially with new technologies such as large single nucleotide polymorphism (SNP) chips, so too does the requirement for software to manage, process and analyze the data. Researchers often need to execute complicated queries and conduct complex analyzes of large-scale datasets. Existing tools to analyze such data, and other types of high-dimensional data, unfortunately suffer from one or more major problems. They typically require a high level of computing expertise, are too simplistic (i.e., do not fit realistic models that allow for complex interactions), are limited by computing power, do not exploit the computing power of large-scale parallel architectures (e.g. supercomputers, GPU clusters etc.), or are limited in the types of analysis available, compounded by the fact that integrating new analysis methods is not straightforward. Solutions to these problems, such as those developed and implemented on parallel architectures, are currently available to only a relatively small portion of medical researchers with access and know-how. The past decade has seen a rapid expansion of data management systems for the medical domain. Much attention has been given to systems that manage phenotype datasets generated by medical studies. The introduction of heterogeneous genomic data for research subjects that reside in these systems has highlighted the need for substantial improvements in software architecture. To address this problem, we have developed SPARK, an enabling and translational system for medical research, leveraging existing high performance computing resources, and analysis techniques currently available or being developed. It builds these into The Ark, an open-source web-based system designed to manage medical data. SPARK provides a next-generation biomedical data management solution that is based upon a novel Micro-Service architecture and Big Data technologies. The system serves to demonstrate the applicability of Micro-Service architectures for the development of high performance computing applications. When applied to high-dimensional medical datasets such as genomic data, relational data management approaches with normalized data structures suffer from unfeasibly high execution times for basic operations such as insert (i.e. importing a GWAS dataset) and the queries that are typical of the genomics research domain. SPARK resolves these problems by incorporating non-relational NoSQL databases that have been driven by the emergence of Big Data. SPARK provides researchers across the world with user-friendly access to state-of-the-art data management and analysis tools while eliminating the need for high-level informatics and programming skills. The system will benefit health and medical research by eliminating the burden of large-scale data management, querying, cleaning, and analysis. SPARK represents a major advancement in genome research technologies, vastly reducing the burden of working with genomic datasets, and enabling cutting edge analysis approaches that have previously been out of reach for many medical researchers.

Keywords: biomedical research, genomics, information systems, software

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Authors: Seyedeh Banafsheh Bagheri Marzouni, Sona Rostampour Yasouri

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Salmonella is one of the most important common pathogens between humans and animals worldwide. Globally, the prevalence of the disease in humans is due to the consumption of food contaminated with animal-derived Salmonella. These foods include eggs, red meat, chicken, and milk. Contamination of chicken and its products with Salmonella may occur at any stage of the chicken processing chain. Salmonella infection is usually not fatal. However, its occurrence is considered dangerous in some individuals, such as infants, children, the elderly, pregnant women, or individuals with weakened immune systems. If Salmonella infection enters the bloodstream, the possibility of contamination of tissues throughout the body will arise. Therefore, determining the potential risk of Salmonella at various stages is essential from the perspective of consumers and public health. The aim of this study is to isolate and identify Salmonella from chicken samples distributed in the Tehran market using the Gold standard culture method and PCR techniques based on specific genes, invA and ent. During the years 2022-2023, sampling was performed using swabs from the liver and intestinal contents of distributed chickens in the Tehran province, with a total of 120 samples taken under aseptic conditions. The samples were initially enriched in buffered peptone water (BPW) for pre-enrichment overnight. Then, the samples were incubated in selective enrichment media, including TT broth and RVS medium, at temperatures of 37°C and 42°C, respectively, for 18 to 24 hours. Organisms that grew in the liquid medium and produced turbidity were transferred to selective media (XLD and BGA) and incubated overnight at 37°C for isolation. Suspicious Salmonella colonies were selected for DNA extraction, and PCR technique was performed using specific primers that targeted the invA and ent genes in Salmonella. The results indicated that 94 samples were Salmonella using the PCR technique. Of these, 71 samples were positive based on the invA gene, and 23 samples were positive based on the ent gene. Although the culture technique is the Gold standard, PCR is a faster and more accurate method. Rapid detection through PCR can enable the identification of Salmonella contamination in food items and the implementation of necessary measures for disease control and prevention.

Keywords: culture, PCR, salmonella spp, salmonella enteritidis

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Authors: Markus Meyer, Bastian Maucher, Rolf Witzmann

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The ever increasing amount of distributed generation in low voltage distribution grids (mainly PV and micro-CHP) can lead to reverse load flows from low to medium/high voltage levels at times of high feed-in. Reverse load flow leads to rising voltages that may even exceed the limits specified in the grid codes. Furthermore, the share of electrical loads connected to low voltage distribution grids via switched power supplies continuously increases. In combination with inverter-based feed-in, this results in high harmonic levels reducing overall power quality. Especially high levels of third-order harmonic currents can lead to neutral conductor overload, which is even more critical if lines with reduced neutral conductor section areas are used. This paper illustrates a possible concept for smart grids in order to increase the feed-in capacity, improve power quality and to ensure safe operation of low voltage distribution grids at all times. The key feature of the concept is a hierarchically structured control strategy that is run on a superordinated controller, which is connected to several distributed grid analyzers and inverters via broad band powerline (BPL). The strategy is devised to ensure both quick response time as well as the technically and economically reasonable use of the available inverters in the grid (PV-inverters, batteries, stepless line voltage regulators). These inverters are provided with standard features for voltage control, e.g. voltage dependent reactive power control. In addition they can receive reactive power set points transmitted by the superordinated controller. To further improve power quality, the inverters are capable of active harmonic filtering, as well as voltage balancing, whereas the latter is primarily done by the stepless line voltage regulators. By additionally connecting the superordinated controller to the control center of the grid operator, supervisory control and data acquisition capabilities for the low voltage distribution grid are enabled, which allows easy monitoring and manual input. Such a low voltage distribution grid can also be used as a virtual power plant.

Keywords: distributed generation, distribution grid, power quality, smart grid, virtual power plant, voltage control

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Authors: Bubaker F. Shareia

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The aim of this paper is to determine a general frame of the auditor's legal responsibilities in Libya which were implied in professional codes and rules, these codes and rules were concerned with the auditor's rights and duties in conducting his professional duties. This will provide a background for the Libyan accounting profession, and the challenges in tailoring Auditors to meet third party's needs. Being informed of the kinds of legal responsibilities which the external auditors could face during conducting their duties. The study is based on a literature review and archival research, reinforced by a qualitative case study comprised of interviews, questionnaire and a study of internal documents. To reach such an understanding, the researcher designed two questionnaires for collecting the data. One questionnaire was distributed among the certified public accountant firms in Libya and the second was distributed among a group of randomly selected lawyers and judges in the same country. Most auditors agreed upon the determination of their responsibilities toward the state and they emphasized that their responsibilities toward their clients were limited to the accepted standards of auditing. Moreover, all auditors who were surveyed emphasized that there has never been any juridical claims against them, and as a consequence they have never paid any legal fines. This study focuses on one country, which does limit its generalisability. However, it also suggests fruitful research areas in considering the impact and challenge of the historic factors in the accounting profession in emerging economies.

Keywords: accounting, external auditor, legal responsibilities, libyan accounting profession

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Authors: Aydin M. Torkabadi, Ehsan Pourjavad

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A decade after the introduction of Lean in Saskatchewan’s public healthcare system, its effectiveness remains a controversial subject among health researchers, workers, managers, and politicians. Therefore, developing a framework to quantitatively assess the Lean achievements is significant. This study investigates the success of initiatives across Saskatchewan health regions by recognizing the Lean healthcare criteria, measuring the success levels, comparing the regions, and identifying the areas for improvements. This study proposes an integrated intelligent computing approach by applying Fuzzy Inference System (FIS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FIS is used as an efficient approach to assess the Lean healthcare criteria, and TOPSIS is applied for ranking the values in regards to the level of leanness. Due to the innate uncertainty in decision maker judgments on criteria, principals of the fuzzy theory are applied. Finally, FIS-TOPSIS was established as an efficient technique in determining the lean merit in healthcare systems.

Keywords: lean healthcare, intelligent computing, fuzzy inference system, healthcare evaluation, technique for order of preference by similarity to ideal solution, multi-criteria decision making, MCDM

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Authors: Fatma Abdel Moneim Al Tawil

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Low back pain (LBP) among nurses has been the subject of research studies worldwide. However, evidence of the influence of patients lifting behaviors and LBP among nurses in Saudi Arabia remains scarce. The purpose of this study was to investigate the relationship between LBP and nurses lifting behaviors. LBP questionnaire was distributed to 100 nurses working in Alsadairy Hospital distributed as Emergency unit(9),Coronary Care unit (9), Intensive Care Unit (7), Dialysis unit (30), Burn unit (5), surgical unit (11), Medical (14) and, X-ray unit (15). The questionnaire included demographic data, attitude scale, Team work scale, Back pain history and Knowledge scale. Regarding to emergency unit, there is appositive significant relation between teamwork scale and Knowledge as r = (0.807) and P =0.05. Regarding to ICU unit, there is a positive significant relation between teamwork scale and attitude scale as r= (0.781) and P =0.05. Regarding to Dialysis unit, there is a positive significant relation between attitude scale and teamwork scale as r=(0.443) and P =0.05. The findings suggest enhanced awareness of occupational safety with safe patient handling practices among nursing students must be emphasized and integrated into their educational curriculum. Moreover, back pain prevention program should incorporate the promotion of an active lifestyle and fitness training the implementation of institutional patient handling policies.

Keywords: low back pain, lifting behaviors, nurses, team work

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Authors: João Madureira, Ricardo Lagido, Inês Sousa, Fraunhofer Portugal

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Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.

Keywords: inertial measurement unit (IMU), global positioning system (GPS), smartphone, surfing performance

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Authors: Harshdeep Singh, Kuljeet Singh Anand

Abstract:

Background: Cerebrovascular Accidents (CVA) cause abnormal or asymmetrical tendon reflexes contributing to motor impairments. Since the tendon reflexes are mediated by the spinal cord, their effects on cognitive performances are overlooked. This study aims to find the contributions of tendon reflexes on the performance of the Flanker task. Methods: A total population of 46 mixed subjects with movement disorders were recruited for the study. Deep tendon reflexes (DTR) of the biceps, triceps and brachioradialis were assessed for both upper extremities. Later, the Flanker task was performed on all the subjects, and the mean Reaction Time (RT) along with both the congruent and incongruent stimuli were evaluated. For the final analysis, the Kruskal Wallis test was performed to see the difference between the DTR and the performance of the Flanker Task. Results: The Kruskal Wallis test results showed a significant difference between the DTR scores, X²(2) = 11.328, p= 0.023 with the mean RT of the flanker task and X²(2) = 9.531, p= 0.049 with mean RT of the Incongruent Stimuli. Whereas the result found a non-significant difference in the mean RT of the Congruent Stimuli. Conclusion: Each DTR score is distributed differently with the mean RT of the flanker task and for the incongruent stimuli as well. Therefore, the tendon reflexes in PD may be contributing to the performance of the Flanker Task and may be an indicator of abnormal cognitive performance. Further research is needed to evaluate how the RTs are distributed with each DTR score.

Keywords: cerebrovascular accidents, deep tendon reflexes, flanker task, reaction time, congruent stimuli, incongruent stimuli

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Authors: Gisele Mah, Paul Saah

Abstract:

The rising rates of inflation are hindering economic growth in developing nations. Hence, this study investigated the effects of inflation rates on the economic growth of South Africa using the secondary time series data from 1987 to 2022. The main objectives of this study were to investigate the long run relationship between inflation and economic growth, and also to determine the causality direction between these two variables. The study utilized the Autoregressive Distributed Lag (ARDL) bounds test of co-integration to investigate whether there is a long-run relationship between inflation and economic growth. The Pairwise Granger causality approach was employed to determine the second objective, which is the direction of causality. The study discovered only one co-integration relationship between our variables and it was between inflation and economic growth. The results showed that there is a negative and significant relationship between inflation and economic growth. There appeared to be a positive and significant relationship between economic growth and exchange rate. The interest rates have shown to be negative and insignificant in explaining economic growth. The study also established that inflation does Granger cause economic growth which is given as GDP. Similarly, the study discovered that inflation Granger causes exchange rates. Therefore, the study recommends that inflation should be decreased in South Africa, in order for economic growth to increase. Contrary, this study recommends that South Africa should increase its exchange rates, in order for economic growth to also increase.

Keywords: inflation rate, economic growth, South Africa, autoregressive distributed lag model

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Authors: Tan Zhang, Zhongjian Wang, Jack Xin, Zhiwen Zhang

Abstract:

We aim to efficiently compute the spreading speeds of reaction-diffusion-advection (RDA) fronts in divergence-free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) nonlinearity. We study a stochastic interacting particle method (IPM) for the reduced principal eigenvalue (Lyapunov exponent) problem of an associated linear advection-diffusion operator with spatially random coefficients. The Fourier representation of the random advection field and the Feynman-Kac (FK) formula of the principal eigenvalue (Lyapunov exponent) form the foundation of our method implemented as a genetic evolution algorithm. The particles undergo advection-diffusion and mutation/selection through a fitness function originated in the FK semigroup. We analyze the convergence of the algorithm based on operator splitting and present numerical results on representative flows such as 2D cellular flow and 3D Arnold-Beltrami-Childress (ABC) flow under random perturbations. The 2D examples serve as a consistency check with semi-Lagrangian computation. The 3D results demonstrate that IPM, being mesh-free and self-adaptive, is simple to implement and efficient for computing front spreading speeds in the advection-dominated regime for high-dimensional random flows on unbounded domains where no truncation is needed.

Keywords: KPP front speeds, random flows, Feynman-Kac semigroups, interacting particle method, convergence analysis

Procedia PDF Downloads 47

Authors: Freitas Vania Moreira, Rodrigues B. B., Araujo M.B., Silva D. R., Sousa A. C., Araujo K. P., Pimentel R. R., Cares J. E., Junqueira N. T. V.

Abstract:

The Pitahayas are cactus native from America and abundant in arid regions. The cultivation is based mainly on the following species: Hylocereus undatus, H. polyrhizus, H. setaceus and H. megalanthus, being H. undatus the most cultivated in Brazil. The pitahaya cultivation is recent in Brazil and is concentrated in São Paulo. Meloidogyne enterolobii is of unknown origin being distributed in several countries. This nematode has recently been detected in Brazil causing damage in several crops. Similarly, M. incognita is a widely distributed pathogen in Brazil. The objective of this study is to evaluate the following accesses of pitahaya to M. enterolobii: CPAC- Py H. hundatus 01, 02, 03, 04, 05, 06, 07 and 08; CPAC - Py H. costaricense 8A; CPAC - Py Selenicereus setaceus 17 and CPAC - Py S. megalantus 22. And the following accesses to M. incognita: CPAC- Py H. hundatus 05; CPAC - Py H. costaricense 8A; CPAC - Py S. setaceus 17 and CPAC - Py S. megalantus 22. According to the results, CPAC – Py H. hundatus 01, 02, 03, 04 and 07 were considered resistant. While CPAC - Py 05 and 08 was susceptible. CPAC-Py 06 also was considered susceptible, because there was the reaction of susceptibility in one of the trials. Given this wide diversity in H. hundatus and being this species the most cultivated in Brazil it is suggested to work more with this material in Embrapa Cerrados. CPAC - Py H. costaricense 8A behaved as susceptible in one of the trials. CPAC - Py S. setaceus 17 and CPAC – Py S. megalantus 22 were considered highly susceptible. The susceptibility of S. megalantus is widely described in the literature. In relation to M. incognita, there were differences between the results in both experiments, but all behaved as susceptible in at least one of the tests.

Keywords: pitaya, meloidogyne, fruit, resistance

Procedia PDF Downloads 184

Authors: T. Sattarpour, D. Nazarpour

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This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

Procedia PDF Downloads 303

Authors: Vladimir Kulyukin, Tanwir Zaman, Sarat Kiran Andhavarapu

Abstract:

Research on nutrition label use identifies four factors that impede comprehension and retention of nutrition information by consumers: label’s location on the package, presentation of information within the label, label’s surface size, and surrounding visual clutter. In this paper, a system is presented that makes nutrition label use more effective for nutrition information comprehension and retention. The system’s front end is a smartphone application. The system’s back end is a four node Linux cluster for image recognition and data storage. Image frames captured on the smartphone are sent to the back end for skewed or aligned barcode recognition. When barcodes are recognized, corresponding nutrition labels are retrieved from a cloud database and presented to the user on the smartphone’s touchscreen. Each displayed nutrition label is positioned centrally on the touchscreen with no surrounding visual clutter. Wikipedia links to important nutrition terms are embedded to improve comprehension and retention of nutrition information. Standard touch gestures (e.g., zoom in/out) available on mainstream smartphones are used to manipulate the label’s surface size. The nutrition label database currently includes 200,000 nutrition labels compiled from public web sites by a custom crawler. Stress test experiments with the node cluster are presented. Implications for proactive nutrition management and food policy are discussed.

Keywords: mobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

Procedia PDF Downloads 375

Authors: Abdul Mannan Akhtar

Abstract:

In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

Procedia PDF Downloads 464

Authors: Syarif Hidayat

Abstract:

As millions of people with different backgrounds perform hajj every year in Saudi Arabia, it brings out several problems. Missing people is among many crucial problems need to be encountered. Some people might have had insufficient knowledge of using tracking system equipment. Other might become a victim of an accident, lose consciousness, or even died, prohibiting them to perform certain activity. For those reasons, people could not send proper SOS message. The major contribution of this paper is the application of the diverse alert method in pilgrims tracking system. It offers a simple yet robust solution to send SOS message by pilgrims during Hajj. Knowledge of context aware computing is assumed herein. This study presents four methods that could be utilized by pilgrims to send SOS. The first method is simple mobile application contains only a button. The second method is based on behavior analysis based off GPS location movement anomaly. The third method is by introducing pressing pattern to smartwatch physical button as a panic button. The fourth method is by identifying certain accelerometer pattern recognition as a sign of emergency situations. Presented method in this paper would be an important part of pilgrims tracking system. The discussion provided here includes easy to use design whilst maintaining tracking accuracy, privacy, and security of its users.

Keywords: context aware computing, emergency alert system, GPS, hajj pilgrim tracking, location-based services

Procedia PDF Downloads 217