Search results for: open data

Authors: Imtiaz Ali, Imam Mansoor

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Investigations as a part of the academic study were undertaken to identify and evaluate the significant risks associated with the construction of K-span buildings in the region of UAE. Primary field data was collected through questionnaires obtaining specific open and close-ended questions from carefully selected construction firms, civil engineers and, construction manager regarding risks associated to K-span building construction. Historical data available for other regions of the same construction technique was available which was compared for identifying various non-critical and critical risk parameters by comparative evaluation techniques to come up with important risks and potential sources for their control and minimization in K-Span buildings that is increasing in the region. The associated risks have been determined with their Relative Importance Index (RII) values of which Risk involved in Change of Design required by Owners carries the highest value (RII=0.79) whereas, Delayed Payment by Owner to Contractor is one of the least (RII=0.42) value. The overall findings suggest that most relative risks as quantified originate or associated with the contractors. It may be concluded that project proponents undertaking K-span projects in planning and budgeting the cost and delays should take into account of risks on high account if changes in design are also required any delays in the material by the supplier would then be a major risk in K-span project delay. Since projects are, less costly, so owners have limited budgets, then they hire small contractors, which are not highly competent contractors. So study suggests that owner should be aware of these types of risks associated with the construction of K-span buildings in order to make it cost effective.

Keywords: k-span buildings, k-span construction, risk management, relative improvement index (RII)

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Authors: Tejinder Singh

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Information system is the flow of data from different levels to different directions for decision making and data operations in information system (IS). Data can be violated by different manner like manual or technical errors, data tampering or loss of integrity. Security system called firewall of IS is effected by such type of violations. The flow of data among various levels of Information System is done by networking system. The flow of data on network is in form of packets or frames. To protect these packets from unauthorized access, virus attacks, and to maintain the integrity level, network security is an important factor. To protect the data to get pirated, various security techniques are used. This paper represents the various security techniques and signifies different harmful attacks with the help of detailed data analysis. This paper will be beneficial for the organizations to make the system more secure, effective, and beneficial for future decisions making.

Keywords: information systems, data integrity, TCP/IP network, vulnerability, decision, data

Procedia PDF Downloads 307

Authors: Tamas Jancso, Andrea Podor, Eva Nagyne Hajnal, Peter Udvardy, Gabor Nagy, Attila Varga, Meng Qingyan

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The paper deals with the conditions and circumstances of integration of remotely sensed data for rural environmental monitoring purposes. The main task is to make decisions during the integration process when we have data sources with different resolution, location, spectral channels, and dimension. In order to have exact knowledge about the integration and data fusion possibilities, it is necessary to know the properties (metadata) that characterize the data. The paper explains the joining of these data sources using their attribute data through a sample project. The resulted product will be used for rural environmental analysis.

Keywords: remote sensing, GIS, metadata, integration, environmental analysis

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Authors: Deepak Suresh Mohale, Anil V. Chandewar

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Anxiety is defined as an exaggerated feeling of apprehension, uncertainty and fear. Nerium indicum is a well-known ornamental and medicinal plant belonging to the family Apocynaceae. A wide spectrum of biological activities has been reported with various constituents isolated from different parts of the plant. This study was conducted to investigate antianxiety activity of flower extract. Flowers were collected and dried in shade and coarsely powdered. Powdered mixture was extracted with ethyl acetate by maceration process. Extract of flowers obtained was subsequently dried in oven at 40-50 °C. This extract is then tested for antianxiety activity at low and high dose using elevated plus maze and light & dark model. Rats shown increased open arm entries and time spent in open arm in elevated Plus maze with treatment low and high dose of extract of Nerium indicum flower as compared to their respective control groups. In Light & dark Model, light box entries and time spent in light box increased with treatment low and high dose of extract of Nerium indicum flower as compared to their respective control groups. From result it is concluded that ethyl acetate extract of flower of Nerium indicum possess antianxiety activity at low and high dose.

Keywords: antianxiety, anxiety, kaner, nerium indicum, social isolation

Procedia PDF Downloads 392

Authors: L. Hoade, O. O. Onafowokan, K. Anderson, G. E. Bartlett, E. D. Fern, M. R. Norton, R. G. Middleton

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Aims: Femoroacetabular impingement (FAI) was first recognised as a potential driver for hip pain at the turn of the last millennium. While there is an increasing trend towards surgical management of FAI by arthroscopic means, open surgical hip dislocation and debridement (SHD) remains the Gold Standard of care in terms of reported outcome measures. (1) Long-term functional and survivorship outcomes of SHD as a treatment for FAI are yet to be sufficiently reported in the literature. This study sets out to help address this imbalance. Methods: We undertook a retrospective review of our institutional database for all patients who underwent SHD for FAI between January 2003 and December 2008. A total of 223 patients (241 hips) were identified and underwent a ten year review with a standardised radiograph and patient-reported outcome measures questionnaire. The primary outcome measure of interest was survivorship, defined as progression to total hip arthroplasty (THA). Negative predictive factors were analysed. Secondary outcome measures of interest were survivorship to further (non-arthroplasty) surgery, functional outcomes as reflected by patient reported outcome measure scores (PROMS) scores, and whether a learning curve could be identified. Results: The final cohort consisted of 131 females and 110 males, with a mean age of 34 years. There was an overall native hip joint survival rate of 85.4% at ten years. Those who underwent a THA were significantly older at initial surgery, had radiographic evidence of preoperative osteoarthritis and pre- and post-operative acetabular undercoverage. In those whom had not progressed to THA, the average Non-arthritic Hip Score and Oxford Hip Score at ten year follow-up were 72.3% and 36/48, respectively, and 84% still deemed their surgery worthwhile. A learning curve was found to exist that was predicated on case selection rather than surgical technique. Conclusion: This is only the second study to evaluate the long-term outcomes (beyond ten years) of SHD for FAI and the first outside the originating centre. Our results suggest that, with correct patient selection, this remains an operation with worthwhile outcomes at ten years. How the results of open surgery compared to those of arthroscopy remains to be answered. While these results precede the advent of collison software modelling tools, this data helps set a benchmark for future comparison of other techniques effectiveness at the ten year mark.

Keywords: femoroacetabular impingement, hip pain, surgical hip dislocation, hip debridement

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Authors: Rit M., Girard R., Villot J., Thorel M.

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In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: Mohammad A. Alia

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With the rapid evolution of the internet applications, cloud computing becomes one of today’s hottest research areas due to its ability to reduce costs associated with computing. Cloud is, therefore, increasing flexibility and scalability for computing services in the internet. Cloud computing is Internet based computing due to shared resources and information which are dynamically delivered to consumers. As cloud computing share resources via the open network, hence cloud outsourcing is vulnerable to attack. Therefore, this paper will explore data security of cloud computing by implementing chaotic cryptography. The proposal scenario develops a problem transformation technique that enables customers to secretly transform their information. This work proposes the chaotic cryptographic algorithms have been applied to enhance the security of the cloud computing accessibility. However, the proposed scenario is secure, easy and straightforward process. The chaotic encryption and digital signature systems ensure the security of the proposed scenario. Though, the choice of the key size becomes crucial to prevent a brute force attack.

Keywords: chaos, cloud computing, security, cryptography

Procedia PDF Downloads 345

Authors: Amira Rjiba, Mohamed Ghanmi, Tahar Aifa, Achref Boulares

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This study, involving the interpretation of geological outcrops data (structures, and lithostratigraphiec colones) and subsurface structures (seismic and gravimetric data) help us to identify and precise (i) the lithology of the sedimentary formations between the Aptian and the recent formations, (ii) to differentiate the sedimentary formations it from the salt-bearing Triassic (iii) and to specify the major structures though the tectonics effects having affected the region during its geological evolution. By placing our study area placed in the context of Tunisia, located on the southern margin of the Tethys show us through tectonic traces and structural analysis conducted, that this area was submitted during the Triassic perio at an active rifting triggered extensional tectonic events and extensive respectively in the Cretaceous and Paleogene. Lithostratigraphic correlations between outcrops and seismic data sets on those of six oil wells conducted in the region have allowed us to better understand the structural complexity and the role of different tectonic faults having contributed to the current configuration, and marked by the current rifts. Indeed, three directions of NW-SE faults, NNW-SSE to NS and NE-SW to EW had a major role in the genesis of folds and open ditches collapse of NW-SE direction. These results were complemented by seismic reflection data to clarify the geometry of the southern and western areas of Kalaa Khasba ditch. The eight selected seismic lines for this study allowed to characterize the main structures, with isochronous maps, contour and isovitesse of Serdj horizon that presents the main reservoir in the region. The line L2, keyed by the well 6, helped highlight the NW-SE compression that has resulted in persistent discrepancies widely identifiable in its lithostratigraphic column. The gravity survey has confirmed the extension of most of the accidents deep subsurface whose activity seems to go far. Gravimetry also reinforced seismic interpretation confirming, at the L2 well, that both SW and NE flank of the moat are two opposite faults and trace the boundaries of NNW-SSE direction graben whose sedimentation of Mio-Pliocene age and Quaternary.

Keywords: graben, graben collapse, gravity, Kalat Es Senan, seismic, tectogenesis

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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

Procedia PDF Downloads 299

Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

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Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: big data, machine learning, ontology model, urban data model

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

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Authors: Wahhaj Ahmed Farooqi, Bilal Ahmad, Sandra Maritza Zambrano Bernal

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In view of structural engineering, monitoring of structural responses over time is of great importance with respect to recent developments of construction technologies. Recently, developments of advanced computing tools have enabled researcher’s better execution of structural health monitoring (SHM) and control systems. In the last decade, building information modeling (BIM) has substantially enhanced the workflow of planning and operating engineering structures. Typically, building information can be stored and exchanged via model files that are based on the Industry Foundation Classes (IFC) standard. In this study a modeling approach for semantic modeling of SHM and control systems is integrated into the BIM methodology using the IFC standard. For validation of the modeling approach, a laboratory test structure, a four-story shear frame structure, is modeled using a conventional BIM software tool. An IFC schema extension is applied to describe information related to monitoring and control of a prototype SHM and control system installed on the laboratory test structure. The SHM and control system is described by a semantic model applying Unified Modeling Language (UML). Subsequently, the semantic model is mapped into the IFC schema. The test structure is composed of four aluminum slabs and plate-to-column connections are fully fixed. In the center of the top story, semi-active tuned liquid column damper (TLCD) is installed. The TLCD is used to reduce effects of structural responses in context of dynamic vibration and displacement. The wireless prototype SHM and control system is composed of wireless sensor nodes. For testing the SHM and control system, acceleration response is automatically recorded by the sensor nodes equipped with accelerometers and analyzed using embedded computing. As a result, SHM and control systems can be described within open BIM, dynamic responses and information of damages can be stored, documented, and exchanged on the formal basis of the IFC standard.

Keywords: structural health monitoring, open building information modeling, industry foundation classes, unified modeling language, semi-active tuned liquid column damper, nondestructive testing

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Authors: Thilivhali E. Rasimphi, David Tinarwo

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Access to energy is crucial in poverty alleviation, economic growth, education, and agricultural improvement. The best renewable energy source is one which is locally available, affordable, and can easily be used and managed by local communities. The usage of renewable energy technology has the potential to alleviate many of the current problems facing rural areas. To address energy poverty, biogas technology has become an important part of resolving such. This study, therefore, examines the performance of digesters in Gawula village; it also identifies the contributing factors to the adoption and use of the technology. Data was collected using an open-ended questionnaire from biogas users. To evaluate the performance of the digesters, a data envelopment analysis (DEA) non-parametric technique was used, and to identify key factors affecting adoption, a logit model was applied. The reviewed critical barriers to biogas development in the area seem to be a poor institutional framework, poor infrastructure, a lack of technical support, user training on maintenance and operation, and as such, the implemented plants have failed to make the desired impact. Thus most digesters were abandoned. To create awareness amongst rural communities, government involvement is key, and there is a need for national programs. Biogas technology does what few other renewable energy technologies do, which is to integrate waste management and energy. This creates a substantial opportunity for biogas generation and penetration. That is, a promising pathway towards achieving sustainable development through biogas technology.

Keywords: domestic biogas technology, economic, sustainable, social, rural development

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Authors: Abubakar Uba Ibrahim, Ibrahim Haruna Shanono

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Smart metering and demand response are gaining ground in industrial and residential applications. Smart Appliances have been given concern towards achieving Smart home. The success of Smart grid development relies on the successful implementation of Information and Communication Technology (ICT) in power sector. Smart Appliances have been the technology under development and many new contributions to its realization have been reported in the last few years. The role of ICT here is to capture data in real time, thereby allowing bi-directional flow of information/data between producing and utilization point; that lead a way for the attainment of Smart appliances where home appliances can communicate between themselves and provide a self-control (switch on and off) using the signal (information) obtained from the grid. This paper depicts the background on ICT for smart appliances paying a particular attention to the current technology and identifying the future ICT trends for load monitoring through which smart appliances can be achieved to facilitate an efficient smart home system which promote demand response program. This paper grouped and reviewed the recent contributions, in order to establish the current state of the art and trends of the technology, so that the reader can be provided with a comprehensive and insightful review of where ICT for smart appliances stands and is heading to. The paper also presents a brief overview of communication types, and then narrowed the discussion to the load monitoring (Non-intrusive Appliances Load Monitoring ‘NALM’). Finally, some future trends and challenges in the further development of the ICT framework are discussed to motivate future contributions that address open problems and explore new possibilities.

Keywords: communication technology between appliances, demand response, load monitoring, smart appliances, smart grid

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Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

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Authors: Jay Patel

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This Research is about investigating the ‘image’ of the city, and asks whether this ‘image’ holds any significance that can be changed. Kevin Lynch in the book ‘The image of the city’ develops a framework that breaks down the city’s image into five physical elements. These elements (Paths, Edge, Nodes, Districts, and Landmarks), according to Lynch assess the legibility of the urbanscapes, that emerged from his perception-based study in 3 different cities (New Jersey, Los Angeles, and Boston) in the USA. The aim of this research is to investigate whether Lynch’s framework can be applied within an Indian context or not. If so, what are the possibilities and whether the imageability of Indian cities can be depicted through the Lynch’s physical elements or it demands an extension to the framework by either adding or subtracting a physical attribute. For this research project, the walled city of Jaipur was selected, as it is considered one of the futuristic designed cities of all time in India. The other significant reason for choosing Jaipur was that it is a historically planned city with solid historical, touristic and local importance; allowing an opportunity to understand the application of Lynch's elements to the city's image. In other words, it provides an opportunity to examine how the disadvantages of a city's implicit programme (its relics of bygone eras) can be converted into assets by improving the imageability of the city. To obtain data, a structured semi-open ended interview method was chosen. The reason for selecting this method explicitly was to gain qualitative data from the users rather than collecting quantitative data from closed-ended questions. This allowed in-depth understanding and applicability of Kevin Lynch’s framework while assessing what needs to be added. The interviews were conducted in Jaipur that yielded varied inferences that were different from the expected learning outcomes, highlighting the need for extension on Lynch’s physical elements to achieve city’s image. Whilst analyzing the data, there were few attributes found that defined the image of Jaipur. These were categorized into two: a Physical aspect (streets and arcade entities, natural features, temples and temporary/ informal activities) and Associational aspects (History, Culture and Tradition, Medium of help in wayfinding, and intangible aspects).

Keywords: imageability, Kevin Lynch, people’s perception, assessment, associational aspects, physical aspects

Procedia PDF Downloads 198

Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Xiaohan Bookman, Xiaoyan Zhu

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The outputs of non-linear feed-forward neural network are positive, which could be treated as probability when they are normalized to one. If we take Entropy-Based Principle into consideration, the outputs for each sample could be represented as the distribution of this sample for different clusters. Entropy-Based Principle is the principle with which we could estimate the unknown distribution under some limited conditions. As this paper defines two processes in Feed-Forward Neural Network, our limited condition is the abstracted features of samples which are worked out in the abstraction process. And the final outputs are the probability distribution for different clusters in the clustering process. As Entropy-Based Principle is considered into the feed-forward neural network, a clustering method is born. We have conducted some experiments on six open UCI data sets, comparing with a few baselines and applied purity as the measurement. The results illustrate that our method outperforms all the other baselines that are most popular clustering methods.

Keywords: feed-forward neural network, clustering, max-entropy principle, probabilistic models

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Authors: H. Solomon, A. Abdul-Latif, R. Baleh, I. Deiab, K. Khanafer

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Aluminum foams were developed and tested due to their high energy absorption abilities for multifunctional applications. The aim of this research work was to investigate experimentally the effect of quasi-static biaxial loading complexity (combined compression-torsion) on the energy absorption capacity of highly uniform architecture open-cell aluminum foam manufactured by kelvin cell model. The two generated aluminum foams have 80% and 85% porosities, spherical-shaped pores having 11mm in diameter. These foams were tested by means of several square-section specimens. A patented rig called ACTP (Absorption par Compression-Torsion Plastique), was used to investigate the foam response under quasi-static complex loading paths having different torsional components (i.e., 0°, 37° and 53°). The main mechanical responses of the aluminum foams were studied under simple, intermediate and severe loading conditions. In fact, the key responses to be examined were stress plateau and energy absorption capacity of the two foams with respect to loading complexity. It was concluded that the higher the loading complexity and the higher the relative density, the greater the energy absorption capacity of the foam. The highest energy absorption was thus recorded under the most complicated loading path (i.e., biaxial-53°) for the denser foam (i.e., 80% porosity).

Keywords: open-cell aluminum foams, biaxial loading complexity, foams porosity, energy absorption capacity, characterization

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Authors: Fatma Ahmed, Heba Mostafa, Bassem Ramdan, Azza El-Soussi

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Background: World Health Organization stated that by 2020 cardiac disease will be the number one cause of death worldwide and estimates that 25 million people per year will suffer from heart disease. Cardiac surgery is considered an effective treatment for severe forms of cardiovascular diseases that cannot be treated by medical treatment or cardiac interventions. In spite of the benefits of cardiac surgery, it is considered a major stressful experience for patients who are candidate for surgery. Prehabilitation can decrease incidences of postoperative complications as it prepares patients for surgical stress through enhancing their defenses to meet the demands of surgery. When patients anticipate the postoperative sequence of events, they will prepare themselves to act certain behaviors, identify their roles and actively participate in their own recovery, therefore, anxiety levels are decreased and functional capacity is enhanced. Prehabilitation programs can comprise interventions that include physical exercise, psychological prehabilitation, nutritional optimization and risk factor modification. Physical exercises are associated with improvements in the functioning of the various physiological systems, reflected in increased functional capacity, improved cardiac and respiratory functions and make patients fit for surgical intervention. Prehabilitation programs should also prepare patients psychologically in order to cope with stress, anxiety and depression associated with postoperative pain, fatigue, limited ability to perform the usual activities of daily living through acting in a healthy manner. Notwithstanding the benefits of psychological preparations, there are limited studies which investigated the effect of psychological prehabilitation to confirm its effect on psychological, quality of life and physiological outcomes of patients who had undergone cardiac surgery. Aim of the study: The study aims to determine the effect of prehabilitation interventions on outcomes of patients undergoing cardiac surgeries. Methods: Quasi experimental study design was used to conduct this study. Sixty eligible and consenting patients were recruited and divided into two groups: control and intervention group (30 participants in each). One tool namely emotional, physiological, clinical, cognitive and functional capacity outcomes of prehabilitation intervention assessment tool was utilized to collect the data of this study. Results: Data analysis showed significant improvement in patients' emotional state, physiological and clinical outcomes (P < 0.000) with the use of prehabilitation interventions. Conclusions: Cardiac prehabilitation in the form of providing information about surgery, circulation exercise, deep breathing exercise, incentive spirometer training and nutritional education implemented daily by patients scheduled for elective open heart surgery one week before surgery have been shown to improve patients' emotional state, physiological and clinical outcomes.

Keywords: emotional recovery, clinical recovery, coronary artery bypass grafting patients, prehabilitation

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Authors: Papakonstantinou Apostolos, Argyrios Moustakas, Panagiotis Zervos, Dimitrios Stefanakis, Manolis Tsapakis, Nektarios Spyridakis, Mary Paspaliari, Christos Kontos, Antonis Legakis, Sarantis Houzouris, Konstantinos Topouzelis

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For years unmanned and remotely operated robots have been used as tools in industry research and education. The rapid development and miniaturization of sensors that can be attached to remotely operated vehicles in recent years allowed industry leaders and researchers to utilize them as an affordable means for data acquisition in air, land, and sea. Despite the recent developments in the ground and unmanned airborne vehicles, a small number of Unmanned Surface Vehicle (USV) platforms are targeted for mapping and monitoring environmental parameters for research and industry purposes. The ARGO project is developed an open-design USV equipped with multi-level control hardware architecture and state-of-the-art sensors and payloads for the autonomous monitoring of environmental parameters in large sea areas. The proposed USV is a catamaran-type USV controlled over a wireless radio link (5G) for long-range mapping capabilities and control for a ground-based control station. The ARGO USV has a propulsion control using 2x fully redundant electric trolling motors with active vector thrust for omnidirectional movement, navigation with opensource autopilot system with high accuracy GNSS device, and communication with the 2.4Ghz digital link able to provide 20km of Line of Sight (Los) range distance. The 3-meter dual hull design and composite structure offer well above 80kg of usable payload capacity. Furthermore, sun and friction energy harvesting methods provide clean energy to the propulsion system. The design is highly modular, where each component or payload can be replaced or modified according to the desired task (industrial or research). The system can be equipped with Multiparameter Sonde, measuring up to 20 water parameters simultaneously, such as conductivity, salinity, turbidity, dissolved oxygen, etc. Furthermore, a high-end multibeam echo sounder can be installed in a specific boat datum for shallow water high-resolution seabed mapping. The system is designed to operate in the Aegean Sea. The developed USV is planned to be utilized as a system for autonomous data acquisition, mapping, and monitoring bathymetry and various environmental parameters. ARGO USV can operate in small or large ports with high maneuverability and endurance to map large geographical extends at sea. The system presents state of the art solutions in the following areas i) the on-board/real-time data processing/analysis capabilities, ii) the energy-independent and environmentally friendly platform entirely made using the latest aeronautical and marine materials, iii) the integration of advanced technology sensors, all in one system (photogrammetric and radiometric footprint, as well as its connection with various environmental and inertial sensors) and iv) the information management application. The ARGO web-based application enables the system to depict the results of the data acquisition process in near real-time. All the recorded environmental variables and indices are presented, allowing users to remotely access all the raw and processed information using the implemented web-based GIS application.

Keywords: monitor marine environment, unmanned surface vehicle, mapping bythometry, sea environmental monitoring

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Authors: Luvisa Kusuma, Panji Yudha Prakasa

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Cloud storage, as a subservice of infrastructure as a service (IaaS) in Cloud Computing, is the model of nerworked storage where data can be stored in server. In this paper, we propose a secure cloud storage system consisting of two main components; client as a user who uses the cloud storage service and server who provides the cloud storage service. In this system, we propose the protocol schemes to guarantee against security attacks in the data transmission. The protocols are login protocol, upload data protocol, download protocol, and push data protocol, which implement hybrid cryptographic mechanism based on data encryption before it is sent to the cloud, so cloud storage provider does not know the user's data and cannot analysis user’s data, because there is no correspondence between data and user.

Keywords: cloud storage, security, cryptographic protocol, artificial intelligence

Procedia PDF Downloads 357

Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

Abstract:

Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

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Authors: Faraj M. Elkhatri, Hana Ali Allafi

Abstract:

The spatial and temporal distribution of diagenetic alterations related impact on the reservoir quality of the Sarir Formation. (present day burial depth of about 9000 feet) Depositional facies and diagenetic alterations are the main controls on reservoir quality of Sarir Formation Sirt Ba-sin Libya; these based on lithology and grain size as well as authigenic clay mineral types and their distributions. However, petrology investigation obtained on study area with five sandstone wells concentrated on main rock components and the parameters that may have impacts on reservoirs. the main authigenic clay minerals are kaolinite and dickite, these investigations have confirmed by X.R.D analysis and clay fraction. mainly Kaolinite and Dickite were extensively presented on all of wells with high amounts. As well as trace of detrital smectite and less amounts of illitized mud-matrix are possibly find by SEM image. Thin layers of clay presented as clay-grain coatings in local depth interpreted as remains of dissolved clay matrix is partly transformed into kaolinite adjacent and towards pore throat. This also may have impacts on most of the pore throats of this sandstone which are open and relatively clean with some of fine martial have been formed on occluded pores. This material is identified by EDS analysis to be collections of not only kaolinite booklets, but also small, disaggregated kaolinite platelets derived from the dis-aggregation of larger kaolinite booklets. These patches of kaolinite not only fill this pore, but also coat some of the sur-rounding framework grains. Quartz grains often enlarged by authigenic quartz overgrowths partially occlude and re-duce porosity. Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM) was conducted on the post-test samples to examine any mud filtrate particles that may be in the pore throats. Semi-qualitative elemental data on select-ed minerals observed during the SEM study were obtained using an Energy Dispersive Spectroscopy (EDS) unit. The samples showed mostly clean open pore throats, with limited occlusion by kaolinite.

Keywords: por throat, formation damage, porosity lose, solids plugging

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Authors: Mina Sarabi, Dariush Sattarzadeh, Mitra Asadollahi Oula

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In the old days, gardens reflect the identity and culture of each country. Persian garden in urban planning and architecture has a high position and it is a kind of paradise in Iranian opinion. But nowadays, the gardens were replaced with parks and urban open spaces. On the other hand, due to the industrial development of cities and increasing air pollution in urban environments, living in this spaces make problem for people. And improving ecological conditions will be felt more than ever. The purposes of this study are identification and reproduction of Persian garden pattern and adaptation of it with sustainability features in green spaces in contemporary cities and developing meaningful green spaces instead of designing aimless spaces in urban environment. The research method in this article is analytical and descriptive. Studying and collecting information about Iranian garden pattern is referring to library documents, articles and analysis case studies. The result reveals that Persian garden was the main factor the bond between man and nature. But in the last century, this relationship is in trouble. It has a significant impact in reducing the adverse effects of urban air pollution, noise and etc as well. Nowadays, recreated pattern of Iranian gardens in urban green spaces not only keep Iranian identity for future generations but also, using the principles of sustainability can play an important role in sustainable development and quality space of a city.

Keywords: green open spaces, nature, Persian garden, urban sustainability

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Authors: William Middleton, Nodumo Zulu, Sue Harrison

Abstract:

Open raceway ponds are currently the most used system for the commercial cultivation of algal biomass, as it is a cost-effective means of production. However, raceway ponds suffer from lower algal productivity when compared to closed photobioreactors. This is due to poor gas exchange between the fluid and the atmosphere. Carbon dioxide (CO₂) mass transfer is a large concern in the production of algae in raceway pond systems. The utilization of atmospheric CO₂ does not support maximal growth; however, CO₂ supplementation in the form of flue gas or concentrated CO₂ is not cost-effective. The introduction of slopes into the raceway system presents a possible improvement to the mass transfer from the air, as seen in previous work conducted at CeBER. Slopes improve turbulence (decreasing the concentration gradient of dissolved CO₂) and can cause air entrainment (allowing for greater surface area and contact time between the air and water). This project tests the findings of previous studies conducted in an indoor lab-scale raceway on a larger scale under outdoor conditions. The addition of slopes resulted in slightly increased CO₂ mass transfer as well as algal growth rate and productivity. However, there were reductions in energy consumption and average fluid velocity in the system. These results indicate a potential to improve the economic feasibility of algal biomass production, but further economic assessment would need to be carried out.

Keywords: algae, raceway ponds, mass transfer, algal culture, biotechnology, reactor design

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Authors: Christina Zourna, Ioanna Papavassiliou-Alexiou

Abstract:

The purpose of this multi-phased action research PhD study in Greece was to investigate if and how Drama in Education (DiE) – used as an innovative group counselling method – may have positive effects on secondary education students’career self-efficacy and career decision-making skills development. Using both quantitative and qualitative research tools, high quality data were gathered at various stages of the research and were analysed through multivariate methods and open-source computer aided data analysis software such as R Studio, QualCoder, and SPSS packages. After a five-month-long educational intervention based on DiE method, it was found that 9th, 10th, and 11th gradersameliorated their self-efficacy and learned the process of making an informed career decision – through targeted information gathering about themselves and possible study paths – thus, developing career problem-solving and career management skills. Gender differences were non statistically important, while differences in grades showed a minor influence on some of the measured factorssuch as general career indecisiveness and self-evaluation. Students in the 11th grade scored significantly higher than younger students in the career self-efficacy scale and have stronger faith in their abilities e.g., choosing general over vocational school and major study orientation. The study has shown that DiE can be effective in group career guidance, especially concerning the pillars of self-awareness, self-efficacy, and career decision-making processes.

Keywords: career decision-making skills, career self-efficacy, CDDQ scale, CDMSE-SF scale, drama in education method

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Authors: Cristina Costa-Lobo, Ana Martins, Maria Das Dores Formosinho, Ana Campina, Filomena Ponte

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This paper is a report on the findings of a study conducted at an international leading food group. Documentary analysis and discourse analysis techniques were used to examine how corporate social responsibility and career education are valued by this international group. The Survey on Corporate Social Responsibility and Career Education was used, with 18 open-ended questions, the first six related to Corporate Social Responsibility and the last 12 related to Education for the Career. The Survey on the Social Emergency Fund was made up of 16 open-ended questions. The Social Welfare Survey was used to investigate the contribution of social workers in this area, as well as to understand their status. The sample of this investigation is composed by the Director of the development area, by the Coordinator and two Social Assistants of the Social Emergency Fund. Their collaboration was the provision of information in the form of an interview where the two main axes of this study were explored: Corporate Social Responsibility and Career Education. With regard to the analysis of data obtained from interviews, it was accomplished through the content analysis according to the Bardin's method (2004), through the pre-analytical, exploratory and qualitative treatment and interpretation of responses. Critical review of documents was also used. The success and effectiveness of this international group are marked by ambition, ability to resist difficulties, sharing of values, spirit of unity and team sense that is shared in its different companies, its leadership position is also due to the concern to see reinforced and developed values of work, discipline, rigor and competence, its management is geared towards responding to immediate challenges from a Corporate Social Responsibility perspective that is characteristic of it, incorporating concerns about impacts both in the medium and long term. In addition to internal training, it directs investments for external training by promoting actions such as participation in seminars and congresses worldwide and the creation of partnerships in various areas of management with prestigious teaching entities. Findings indicate the creation of a training school, with initiatives for internal and external training, in partnerships with prestigious teaching entities. Of particular note is the Management Trainees Program, developed for more than 25 years, characterized by building a career by obtaining knowledge and skills acquired in the combination of on-the-job experience and a training program.

Keywords: career education, corporate social responsibility, training school, management trainees program

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

Abstract:

Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Benbya Hind, Belbaly Nassim

Abstract:

Markets and communities are often cast as alternative forms of knowledge sharing, but an open question is how and why people dynamically transition between them. To study these transitions, we design a technology that allows geographically distributed participants to either buy knowledge (using virtual points) or request it for free. We use a data-driven, inductive approach, studying 550 members in over 5000 interactions, during nine months. Because the technology offered participants choices between market or community forms, we can document both individual and collective transitions that emerge as people cycle between these forms. Our inductive analysis revealed that uncertainties endemic to knowledge sharing were the impetus for these transitions. Communities evoke uncertainties about knowledge sharing’s costs and benefits, which markets resolve by quantifying explicit prices. However, if people manipulate markets, they create uncertainties about the validity of those prices, allowing communities to reemerge to establish certainty via identity-based validation.

Keywords: knowledge sharing, communities, information technology design, transitions, markets

Procedia PDF Downloads 180