Search results for: parallel data mining

Authors: Devendra Gupta, Sushilk K. Agarwal, Amit Kesari, P. K. Singh

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Objectives: Pediatric patients often may experience persistent respiratory failure that requires tracheostomy placement in Pediatric ICU. We have designed a technique of tracheostomy in pediatric patients with S-shaped incision on the tracheal wall with higher success rate and lower complication rate. Technique: Following general anesthesia and positioning of the patient, the trachea was exposed in midline by a vertical skin incision. In order to make S-shaped tracheostoma, second tracheal ring was identified. The conventional vertical incision was made in second tracheal ring and then extended at both its ends laterally in the inter-cartilaginous space parallel to the tracheal cartilage in the opposite direction to make the incision S-shaped. The trachea was dilated with tracheal dilator and appropriate size of tracheostomy tube was then placed into the trachea. Results: S-shaped tracheostomy was performed in 20 children with mean age of 6.25 years (age range is 2-7) requiring tracheostomy placement. The tracheostomy tubes were successfully placed in all the patients in single attempt. There was no incidence of significant intra-operative bleeding, subcutaneous emphysema, vocal cord palsy or pneumothorax. Two patients developed pneumonia and expired within a year. However, there was no incidence of tracheo-esophageal fistula, suprastomal collapse or difficulty in decannulation on one year of follow up related to our technique. One patient developed late trachietis managed conservatively. Conclusion: S-shaped tracheoplasty was associated with high success rate, reduced risk of the early and late complications in pediatric patients requiring tracheostomy.

Keywords: peatrics, tracheostomy, ICU, tracheostoma

Procedia PDF Downloads 256

Authors: Islam Elsayed Hussein

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The aim of this paper is to discover the impact of students’ attitude towards social media and the skills required to adopt social media as a university e-learning (2.0) platform. In addition, it measures the effect of social media adoption on interactive learning effectiveness. The population of this study was students at Faculty of tourism and Hotels, Fayoum University. A questionnaire was used as a research instrument to collect data from respondents, which had been selected randomly. Data had been analyzed using quantitative data analysis method. Findings showed that the students have a positive attitude towards adopting social networking in the learning process and they have also good skills for effective use of social networking tools. In addition, adopting social media is effectively affecting the interactive learning environment.

Keywords: attitude, skills, e-learning 2.0, interactive learning, Egypt

Procedia PDF Downloads 499

Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

Procedia PDF Downloads 290

Authors: Sathapath Kilaso

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Nowadays, Today, wireless sensor networks are an important technology that works with Internet of Things. It is receiving various data from many sensor. Then sent to processing or storing. By wireless network or through the Internet. The devices around us are intelligent, can receiving/transmitting and processing data and communicating through the system. There are many applications of wireless sensor networks, such as smart city, smart farm, environmental management, weather. This article will explore the use of wireless sensor networks in Thailand and collect data from Thai Thesis database in 2012-2017. How to Implementing Wireless Sensor Network Technology. Advantage from this study To know the usage wireless technology in many fields. This will be beneficial for future research. In this study was found the most widely used wireless sensor network in agriculture field. Especially for smart farms. And the second is the adoption of the environment. Such as weather stations and water inspection.

Keywords: wireless sensor network, smart city, survey, Adhoc Network

Procedia PDF Downloads 192

Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

Procedia PDF Downloads 173

Authors: Neha Singh, Anuj Ranjan, Tanu Jindal

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Over the last decade, the exponential growth of mobile communication has been accompanied by a parallel increase in density of electromagnetic fields (EMF). The continued expansion of mobile phone usage raises important questions as EMF, especially radio frequency (RF), have long been suspected of having biological effects. In the present experiments, we studied the effects of RF-EMF on cell death (apoptosis) and DNA damage of a well- tested biological model, Drosophila melanogaster exposed to 2400 MHz frequency for different time duration i.e. 2 hrs, 4 hrs, 6 hrs,8 hrs, 10 hrs, and 12 hrs each day for five continuous days in ambient temperature and humidity conditions inside an exposure chamber. The flies were grouped into control, sham-exposed, and exposed with 100 flies in each group. In this study, well-known techniques like Comet Assay and TUNEL (Terminal deoxynucleotide transferase dUTP Nick End Labeling) Assay were used to detect DNA damage and for apoptosis studies, respectively. Experiments results showed DNA damage in the brain cells of Drosophila which increases as the duration of exposure increases when observed under the observed when we compared results of control, sham-exposed, and exposed group which indicates that EMF radiation-induced stress in the organism that leads to DNA damage and cell death. The process of apoptosis and mutation follows similar pathway for all eukaryotic cells; therefore, studying apoptosis and genotoxicity in Drosophila makes similar relevance for human beings as well.

Keywords: cell death, apoptosis, Comet Assay, DNA damage, Drosophila, electromagnetic fields, EMF, radio frequency, RF, TUNEL assay

Procedia PDF Downloads 145

Authors: A. Bayaga

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This research provides a technical account of estimating Transition Probability using Time-homogeneous Markov Jump Process applying by South African HIV/AIDS data from the Statistics South Africa. It employs Maximum Likelihood Estimator (MLE) model to explore the possible influence of Transition Probability of mortality cases in which case the data was based on actual Statistics South Africa. This was conducted via an integrated demographic and epidemiological model of South African HIV/AIDS epidemic. The model was fitted to age-specific HIV prevalence data and recorded death data using MLE model. Though the previous model results suggest HIV in South Africa has declined and AIDS mortality rates have declined since 2002 – 2013, in contrast, our results differ evidently with the generally accepted HIV models (Spectrum/EPP and ASSA2008) in South Africa. However, there is the need for supplementary research to be conducted to enhance the demographic parameters in the model and as well apply it to each of the nine (9) provinces of South Africa.

Keywords: AIDS mortality rates, epidemiological model, time-homogeneous markov jump process, transition probability, statistics South Africa

Procedia PDF Downloads 476

Authors: Xiaofang Wei

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Harmful Algal Blooms are a recurrent disturbing occurrence in Lake Erie that has caused significant negative impacts on water quality and aquatic ecosystem around Great Lakes areas in the United States. Targeting the recent HAB events in western Lake Erie, this paper utilizes satellite imagery and hydrological modeling to monitor HAB cyanobacteria blooms and analyze the impacts of agricultural activities from Maumee watershed, the biggest watershed of Lake Erie and agriculture dominant.SWAT (Soil & Water Assessment Tool) Model for Maumee watershed was established with DEM, land use data, crop data layer, soil data, and weather data, and calibrated with Maumee River gauge stations data for streamflow and nutrients. Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) was applied to remove atmospheric attenuation and cyanobacteria Indices were calculated from Landsat OLI imagery to study the intensity of HAB events in the years 2015, 2017, and 2019. The agricultural practice and nutrients management within the Maumee watershed was studied and correlated with HAB cyanobacteria indices to study the relationship between HAB intensity and nutrient loadings. This study demonstrates that hydrological models and satellite imagery are effective tools in HAB monitoring and modeling in rivers and lakes.

Keywords: harmful algal bloom, landsat OLI imagery, SWAT, HAB cyanobacteria

Procedia PDF Downloads 162

Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

Procedia PDF Downloads 63

Authors: Chante J. De Klerk

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The potential of music to facilitate superior performance during high to elite level gymnastics conditioning instigated this research. A team of seven gymnasts completed a fixed conditioning programme eight times, alternating the two variable conditions. Four sessions of each condition were conducted: without music (session 1), with music (session 2), without music (3), with music (4), without music (5), and so forth. Quantitative data were collected in both conditions through physiological monitoring of the gymnasts, and administration of the Situational Motivation Scale (SIMS). Statistical analysis of the physiological data made it possible to quantify the presence as well as the magnitude of the musical intervention’s impact on various aspects of the gymnasts' physiological functioning during conditioning. The SIMS questionnaire results were used to evaluate if their motivation towards conditioning was altered by the intervention. Thematic analysis of qualitative data collected through semi-structured interviews revealed themes reflecting the gymnasts’ sentiments towards the data collection process. Gymnast-specific descriptions and experiences of the team as a whole were integrated with the quantitative data to facilitate greater dimension in establishing the impact of the intervention. The results showed positive physiological, motivational, and emotional effects. In the presence of music, superior sympathetic nervous activation, and energy efficiency, with more economic breathing, dominated the physiological data. Fatigue and arousal levels (emotional and physiological) were also conducive to improved conditioning outcomes compared to conventional conditioning (without music). Greater levels of positive affect and motivation emerged in analysis of both the SIMS and interview data sets. Overall, the intervention was found to promote psychophysiological coherence during the physical activity. In conclusion, a strategically constructed musical intervention, designed to accompany a gymnastics conditioning session for high to elite level gymnasts, has ergogenic potential.

Keywords: arousal, fatigue, gymnastics conditioning, motivation, musical intervention, psychophysiological coherence

Procedia PDF Downloads 78

Authors: Musa D. Aliyu, Ouahid Harireche, Colin D. Hills

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The incapability of supercritical C02 to transport and dissolve mineral species from the geothermal reservoir to the fracture apertures and other important parameters in heat mining makes it an attractive substance for Heat extraction from hot dry rock. In other words, the thermodynamic efficiency of hot dry rock (HDR) reservoirs also increases if supercritical C02 is circulated at excess temperatures of 3740C without the drawbacks connected with silica dissolution. Studies have shown that circulation of supercritical C02 in homogenous geothermal reservoirs is quite encouraging; in comparison to that of the water. This paper aims at investigating the aforementioned processes in the case of the heterogeneous geothermal reservoir located at the Soultz site (France). The MultiPhysics finite element package COMSOL with an interface of coupling different processes encountered in the geothermal reservoir stimulation is used. A fully coupled numerical model is developed to study the thermal and hydraulic processes in order to predict the long-term operation of the basic reservoir parameters that give optimum energy production. The results reveal that the temperature of the SCC02 at the production outlet is higher than that of water in long-term stimulation; as the temperature is an essential ingredient in rating the energy production. It is also observed that the mass flow rate of the SCC02 is far more favourable compared to that of water.

Keywords: FEM, HDR, heterogeneous reservoir, stimulation, supercritical C02

Procedia PDF Downloads 372

Authors: Terentes Printzios Dimitrios, Loanna Gourgouli, Vlachopoulos Charalambos

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Aims: Atrial fibrillation (AF) remains one of the major causes of stroke, heart failure, sudden death and cardiovascular morbidity. Ablation techniques are becoming more appealing after the latest results of randomized trials showing the overall clinical benefit. On the other hand, imaging techniques and the frontier application of 3D printing are emerging as a valuable ally for cardiac procedures. However, no randomized trial has directly assessed the impact of preprocedural imaging and especially 3D printing guidance for AF ablation. The present study is designed to investigate for the first time the effect of 3D printing of the heart on the safety and effectiveness of the ablation procedure. Methods and design: The 3D-GALA trial is a randomized, open-label, controlled, multicentre clinical trial of 2 parallel groups designed to enroll a total of 100 patients undergoing ablation using cryo-balloon for paroxysmal and persistent AF. Patients will be randomized with a patient allocation ratio of 1: 1 to preprocedural MRI scan of the heart and 3D printing of left atrium and pulmonary veins and cryoablation versus standard cryoablation without imaging. Patients will be followed up to 6 months after the index procedure. The primary outcome measure is the reduction of radiation dose and contrast amount during pulmonary veins isolation. Secondary endpoints will include the percentage of atrial fibrillation relapse at 24h-Holter electrocardiogram monitoring at 6 months after initial treatment. Discussion: To our knowledge, the 3D-GALA trial will be the first study to provide evidence about the clinical impact of preprocedural imaging and 3D printing before cryoablation.

Keywords: atrial fibrillation, cardiac MRI, cryoablation, 3-d printing

Procedia PDF Downloads 160

Authors: Shinji Kawakura, Ryosuke Shibasaki

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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis

Procedia PDF Downloads 379

Authors: E. A. Krasikov

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Dependence of the materials properties on neutron irradiation intensity (flux) is a key problem while usage data of the accelerated materials irradiation in test reactors for forecasting of their capacity for work in realistic (practical) circumstances of operation. Investigations of the reactor pressure vessel steel radiation degradation dependence on fast neutron fluence (embrittlement kinetics) at low flux reveal the instability in the form of the scatter of the experimental data and wave-like sections of embrittlement kinetics appearance. Disclosure of the steel degradation oscillating is a sign of the steel structure cyclic self-recovery transformation as it take place in self-organization processes. This assumption has received support through the discovery of the similar ‘anomalous’ data in scientific publications and by means of own additional experiments. Data obtained stimulate looking-for ways to management of the structural steel radiation stability (for example, by means of nano - structure modification for radiation defects annihilation intensification) for creation of the intelligent self-recovering material. Expected results: - radiation degradation theory and mechanisms development, - more adequate models of the radiation embrittlement elaboration, - surveillance specimen programs improvement, - methods and facility development for usage data of the accelerated materials irradiation for forecasting of their capacity for work in realistic (practical) circumstances of operation, - search of the ways for creating of the radiation stable self-recovery intelligent materials.

Keywords: degradation, radiation, steel, wave-like kinetics

Procedia PDF Downloads 292

Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

Procedia PDF Downloads 200

Authors: Ramanen Sugunesegran, Michael L. Williams

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Over the past two decades surgical approaches for mitral valve (MV) disease have evolved with the advent of minimally invasive techniques. Robotic mitral valve repair (RMVr) safety and efficacy has been well documented, however, mid- to long-term data are limited. The aim of this review was to provide a comprehensive analysis of the available mid- to long-term term data for RMVr. Electronic searches of five databases were performed to identify all relevant studies reporting minimum 5-year data on RMVr. Pre-defined primary outcomes of interest were overall survival, freedom from MV reoperation and freedom from moderate or worse mitral regurgitation (MR) at 5-years or more post-RMVr. A meta-analysis of proportions or means was performed, utilizing a random effects model, to present the data. Kaplan-Meier curves were aggregated using reconstructed individual patient data. Nine studies totaling 3,300 patients undergoing RMVr were identified. Rates of overall survival at 1-, 5- and 10-years were 99.2%, 97.4% and 92.3%, respectively. Freedom from MV reoperation at 8-years post RMVr was 95.0%. Freedom from moderate or worse MR at 7-years was 86.0%. Rates of early post-operative complications were low with only 0.2% all-cause mortality and 1.0% cerebrovascular accident. Reoperation for bleeding was low at 2.2% and successful RMVr was 99.8%. Mean intensive care unit and hospital stay were 22.4 hours and 5.2 days, respectively. RMVr is a safe procedure with low rates of early mortality and other complications. It can be performed with low complication rates in high volume, experienced centers. Evaluation of available mid-term data post-RMVr suggests favorable rates of overall survival, freedom from MV reoperation and freedom from moderate or worse MR recurrence.

Keywords: mitral valve disease, mitral valve repair, robotic cardiac surgery, robotic mitral valve repair

Procedia PDF Downloads 71

Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Wilawan Senaratana, Jaras Singkaew

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Geographical information system (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, 'smart' devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive health care services. The objective of this study is to apply GPS location services that are available on the common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms. The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG, and XLS. The data were collected in the database beginning in March 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients’ household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province. The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home health care service and also to create health promotion activities according to medical needs of the people in the community.

Keywords: health, public health, GIS, geographic information system

Procedia PDF Downloads 315

Authors: Nabaouia.Maktouf, Ali Ben Moussa, Saïd Turki

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This paper discusses the effect of an attached flexible membrane on the control of fluid around a circular cylinder. A parametric study has been investigated for different positions, sizes, modes as well as frequencies of oscillation of the flexible membrane. The numerical investigation was conducted for a Reynolds number equal to 150 using the commercial code Fluent 16.0 and parallel calculation into 4 processors. The motion of the flexible membrane was managed by the dynamic mesh and compiled into Fluent as a user-defined function. The first part of this paper discusses the effect of changing the position of a flexible membrane sized 8° as an angle of aperture on the aerodynamic coefficients. Results show that the flexible membrane placed at 110° from the stagnation point presents more non-linearity on the behavior of the drag coefficient compared to the drag behavior when placed at 180°, relative to the stagnation point. The effect of the size of the flexible surface was studied for the corresponding angles of aperture: 32° and 42°, respectively. The effect of modes (modes 1, 2, and 3) of vibrations has been investigated at a constant frequency of vibration f=2Hz for angles 32° and 42°. All the calculations have been done with a constant amplitude A =0.001m. A non-linearity of the drag coefficient was clearly observed for all the sizes, modes as well as frequencies of excitation. The Fast Fourier transformation shows the appearance of the natural shedding frequency and the multiples of the frequency of excitation. An increase in the modes of oscillation leads to a more linear behavior of the drag coefficient.

Keywords: fluid flow control, numerical simulation, dynamic mesh, aerodynamic forces, flexible membrane

Procedia PDF Downloads 59

Authors: Mattias Bergstrom

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Significance of the Study: This research will provide new insights into the risks with digital embedded infrastructure. Through this research, we will analyze each risk and its potential negation strategies, especially for AI and autonomous automation. Moreover, the analysis that is presented in this paper will convey valuable information for future research that can create more stable, secure, and efficient autonomous systems. To learn and understand the risks, a large IoT system was envisioned, and risks with hardware, tampering, and cyberattacks were collected, researched, and evaluated to create a comprehensive understanding of the potential risks. Potential solutions have then been evaluated on an open source IoT hardware setup. This list shows the identified passive and active risks evaluated in the research. Passive Risks: (1) Hardware failures- Critical Systems relying on high rate data and data quality are growing; SCADA systems for infrastructure are good examples of such systems. (2) Hardware delivers erroneous data- Sensors break, and when they do so, they don’t always go silent; they can keep going, just that the data they deliver is garbage, and if that data is not filtered out, it becomes disruptive noise in the system. (3) Bad Hardware injection- Erroneous generated sensor data can be pumped into a system by malicious actors with the intent to create disruptive noise in critical systems. (4) Data gravity- The weight of the data collected will affect Data-Mobility. (5) Cost inhibitors- Running services that need huge centralized computing is cost inhibiting. Large complex AI can be extremely expensive to run. Active Risks: Denial of Service- It is one of the most simple attacks, where an attacker just overloads the system with bogus requests so that valid requests disappear in the noise. Malware- Malware can be anything from simple viruses to complex botnets created with specific goals, where the creator is stealing computer power and bandwidth from you to attack someone else. Ransomware- It is a kind of malware, but it is so different in its implementation that it is worth its own mention. The goal with these pieces of software is to encrypt your system so that it can only be unlocked with a key that is held for ransom. DNS spoofing- By spoofing DNS calls, valid requests and data dumps can be sent to bad destinations, where the data can be extracted for extortion or to corrupt and re-inject into a running system creating a data echo noise loop. After testing multiple potential solutions. We found that the most prominent solution to these risks was to use a Peer 2 Peer consensus algorithm over a blockchain to validate the data and behavior of the devices (sensors, storage, and computing) in the system. By the devices autonomously policing themselves for deviant behavior, all risks listed above can be negated. In conclusion, an Internet middleware that provides these features would be an easy and secure solution to any future autonomous IoT deployments. As it provides separation from the open Internet, at the same time, it is accessible over the blockchain keys.

Keywords: IoT, security, infrastructure, SCADA, blockchain, AI

Procedia PDF Downloads 92

Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

Procedia PDF Downloads 155

Authors: Awdhesh Narayan Sharma

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The use of herbal medicines for the cure of various ailments among the tribal population is as old as human origin itself. Most of the tribal populations of Madhya Pradesh inhabit in remote and inaccessible ecological setup. From long back, tribals and forests are interrelated to each other. They use an enormous range of wild plants for their basic needs and medicines. The tribal developed a unique understanding with wild plants, herbs, etc., and earned specialized knowledge of disease pattern and curative therapy-through hard experiences, common sense, trial, and error methods. They have passed this knowledge through traditions, taboos, totems, folklore by words of mouth from generation to generation. Here, an attempt has been made to study the possible aspects of herbal medicine for the cure of Jaundice among the tribal populations of Madhya Pradesh, India, through primary data as well as available secondary data. The data have been collected from the 305 Bharias of Patalkot, Madhya Pradesh, India, and included available secondary source of data by various investigators. It may be concluded that a sizable herbal medicinal plants' wealth exists in Madhya Pradesh, India, which still awaits for scientific exploration. The existing herbal medicines used for the cure of jaundice need an extensive investigation from the pharmaceutical point of view.

Keywords: Bharias, herbal medicine, tribal, Madhya Pradesh

Procedia PDF Downloads 159

Authors: Vedansh More, Lalatendu Bal, Ronak Panchal, Atharva Kulkarni

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The project aims at developing a cost-effective test bench capable of testing and validating the complete powertrain package of an electric vehicle. Emrax 228 high voltage synchronous motor was selected as the prime mover for study. A tandem type dynamometer comprising of two loading methods; inertial, using standard inertia rollers and absorptive, using a separately excited DC generator with resistive coils was developed. The absorptive loading of the prime mover was achieved by implementing a converter circuit through which duty of the input field voltage level was controlled. This control was efficacious in changing the magnetic flux and hence the generated voltage which was ultimately dropped across resistive coils assembled in a load bank with all parallel configuration. The prime mover and loading elements were connected via a chain drive with a 2:1 reduction ratio which allows flexibility in placement of components and a relaxed rating of the DC generator. The development will aid in determination of essential characteristics like torque-RPM, power-RPM, torque factor, RPM factor, heat loads of devices and battery pack state of charge efficiency but also provides a significant financial advantage over existing versions of dynamometers with its cost-effective solution.

Keywords: absorptive load, chain drive, chordal action, DC generator, dynamometer, electric vehicle, inertia rollers, load bank, powertrain, pulse width modulation, reduction ratio, road load, testbench

Procedia PDF Downloads 208

Authors: Yamba Dabone, Tounwendyam Frédéric Ouedraogo, Pengwendé Justin Kouraogo, Oumarou Sie

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Reliable data transport over the Internet is one of the goals of researchers in the field of computer science. Data such as videos and audio files are becoming increasingly large. As a result, transporting them over the Internet is becoming difficult. Therefore, it has been important to establish a method to locally interconnect autonomous systems (AS) with each other to facilitate traffic exchange. It is in this context that Internet Exchange Points (IXPs) are set up to facilitate local and even regional traffic. They are now the lifeblood of the Internet. Therefore, it is important to think about the factors that can characterize IXPs. However, other more quantifiable characteristics can help determine the quality of an IXP. In addition, these characteristics may allow ISPs to have a clearer view of the exchange node and may also convince other networks to connect to an IXP. To that end, we define five new IXP characteristics: the attraction rate (τₐₜₜᵣ); and the peering rate (τₚₑₑᵣ); the target rate of an IXP (Objₐₜₜ); the number of IXP links (Nₗᵢₙₖ); the resistance rate τₑ𝒻𝒻 and the attraction failure rate (τ𝒻).

Keywords: characteristic, autonomous system, internet service provider, internet exchange point, rate

Procedia PDF Downloads 78

Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

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This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

Procedia PDF Downloads 209

Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

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With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

Procedia PDF Downloads 434

Authors: Y. Atilgan Şengül

Abstract:

Health information technologies promise higher quality, safer care and much more for both patients and professionals. Despite their promise, they are costly to develop and difficult to implement. On the other hand, user acceptance and usage determine the success of implemented information technology in healthcare. This study provides a model to understand health professionals’ perception and expectation of health information technology. Extensive literature review has been conducted to determine the main factors to be measured. A questionnaire has been designed as a measurement model and submitted to the personnel of an in vitro fertilization clinic. The respondents’ degree of agreement according to five-point Likert scale was 72% for convenient access to data and 69.4% for the importance of data security. There was a significant difference in acceptance of electronic data storage for female respondents. Also, other significant differences between professions were obtained.

Keywords: healthcare, health informatics, medical record system, questionnaire

Procedia PDF Downloads 158

Authors: Fatemeh Yazdanmehr, Iulian Nistor

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The scope of the current study is the evaluation of the electric field effect on electrostatic desalting mathematical modeling with laboratory data. This research study was focused on developing a model for an existing operation desalting unit of one of the Iranian heavy oil field with a 75 MBPD production capacity. The high temperature of inlet oil to dehydration unit reduces the oil recovery, so the mathematical modeling of desalter operation parameters is very significant. The existing production unit operating data has been used for the accuracy of the mathematical desalting plant model. The inlet oil temperature to desalter was decreased from 110 to 80°C, and the desalted electrical field was increased from 0.75 to 2.5 Kv/cm. The model result shows that the desalter parameter changes meet the water-oil specification and also the oil production and consequently annual income is increased. In addition to that, changing desalter operation conditions reduces environmental footprint because of flare gas reduction. Following to specify the accuracy of selected electrostatic desalter electrical field, laboratory data has been used. Experimental data are used to ensure the effect of electrical field change on desalter. Therefore, the lab test is done on a crude oil sample. The results include the dehydration efficiency in the presence of a demulsifier and under electrical field (0.75 Kv) conditions at various temperatures. Comparing lab experimental and electrostatic desalter mathematical model results shows 1-3 percent acceptable error which confirms the validity of desalter specification and operation conditions changes.

Keywords: desalter, electrical field, demulsification, mathematical modeling, water-oil separation

Procedia PDF Downloads 120

Authors: Eliane Abdo, Olivier Colot

Abstract:

SMEs are always considered as a national priority due to their contribution to job creation, innovation and growth. Once the start-up phase is crossed with encouraging results, the company enters the phase of growth. In order to improve its competitiveness, maintain and increase its market share, the company is in the necessity even the obligation to develop its tangible and intangible investments. SMEs are generally closed companies with special and critical financial situation, limited resources and difficulty to access the capital markets; their shareholders are always living in a conflict between their independence and their need to increase capital that leads to the entry of new shareholder. The capital structure was always considered the core of research in corporate finance; moreover, the financial crisis and its repercussions on the credit’s availability, especially for SMEs make SME financing a hot topic. On the other hand, financial theories do not provide answers to capital structure’s questions; they offer tools and mode of financing that are more accessible to larger companies. Yet, SME’s capital structure can’t be independent of their governance structure. The classic financial theory supposes independence between the investment decision and the financing decision. Thus, investment determines the volume of funding, but not the split between internal or external funds. In this context, we find interesting to study the hypothesis that SMEs respond positively to the financial theories applied to large firms and to check if they are constrained by conventional solutions used by large companies. In this context, this research focuses on the analysis of the resource’s structure of SME in parallel with their investments’ structure, in order to highlight a link between their assets and liabilities structure. We founded our conceptual model based on two main theoretical frameworks: the Pecking order theory, and the Trade Off theory taking into consideration the SME’s characteristics. Our data were generated from DIANE database. Five hypotheses were tested via a panel regression to understand the type of dependence between the financing methods of 3,244 French SMEs and the development of their investment over a period of 10 years (2007-2016). The results show dependence between equity and internal financing in case of intangible investments development. Moreover, this type of business is constraint to financial debts since the guarantees provided are not sufficient to meet the banks' requirements. However, for tangible investments development, SMEs count sequentially on internal financing, bank borrowing, and new shares issuance or hybrid financing. This is compliant to the Pecking Order Theory. We, therefore, conclude that unlisted SMEs incur more financial debts to finance their tangible investments more than their intangible. However, they always prefer internal financing as a first choice. This seems to be confirmed by the assumption that the profitability of the company is negatively related to the increase of the financial debt. Thus, the Pecking Order Theory predictions seem to be the most plausible. Consequently, SMEs primarily rely on self-financing and then go, into debt as a priority to finance their financial deficit.

Keywords: capital structure, investments, life cycle, pecking order theory, trade off theory

Procedia PDF Downloads 97

Authors: Anant Sharma, Ashwin Rajan

Abstract:

Customer experience is measured today based on defining a set of metrics and KPIs, setting up thresholds and defining triggers across those thresholds. While this is an effective way of measuring against a Key Performance Indicator ( referred to as KPI in the rest of the paper ), this approach cannot capture the various nuances that make up the overall customer experience. Customers consume a product or service at various levels, which is not reflected in metrics like Customer Satisfaction or Net Promoter Score, but also across other measurements like recurring revenue, frequency of service usage, e-learning and depth of usage. Here we explore an alternative method of measuring customer experience by flipping the traditional views. Rather than rolling customers up to a metric, we roll up metrics to hierarchies and then measure customer experience. This method allows any team to quantify customer experience across multiple touchpoints in a customer’s journey. We make use of various data sources which contain information for metrics like CXSAT, NPS, Renewals, and depths of service usage collected across a customer lifecycle. This data can be mined systematically to get linkages between different data points like geographies, business groups, products and time. Additional views can be generated by blending synthetic contexts into the data to show trends and top/bottom types of reports. We have created a framework that allows us to measure customer experience using the above logic.

Keywords: analytics, customers experience, BI, business operations, KPIs, metrics

Procedia PDF Downloads 58

Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

Procedia PDF Downloads 316