Search results for: low data rate

Authors: Siyamak Sarafraz, Reza Esmaeil Pour, Saeed Jamshidi, Asghar Molaei Dehkordi

Abstract:

Cutting transport is one of the major problems in directional and extended reach oil and gas wells. Lack of sufficient attention to this issue may bring some troubles such as casing running, stuck pipe, excessive torque and drag, hole pack off, bit wear, decreased the rate of penetration (ROP), increased equivalent circulation density (ECD) and logging. Since it is practically impossible to directly observe the behavior of deep wells, a test setup was designed to investigate cutting transport phenomena. This experimental work carried out to scrutiny behavior of the effective variables in cutting transport. The test setup contained a test section with 17 feet long that made of a 3.28 feet long transparent glass pipe with 3 inch diameter, a storage tank with 100 liters capacity, drill pipe rotation which made of stainless steel with 1.25 inches diameter, pump to circulate drilling fluid, valve to adjust flow rate, bit and a camera to record all events which then converted to RGB images via the Image Processing Toolbox. After preparation of test process, each test performed separately, and weights of the output particles were measured and compared with each other. Observation charts were plotted to assess the behavior of viscosity, flow rate and RPM in inclinations of 0°, 30°, 60° and 90°. RPM was explored with other variables such as flow rate and viscosity in different angles. Also, effect of different flow rate was investigated in directional conditions. To access the precise results, captured image were analyzed to find out bed thickening and particles behave in the annulus. The results of this experimental study demonstrate that drill string rotation helps particles to be suspension and reduce the particle deposition cutting movement increased significantly. By raising fluid velocity, laminar flow converted to turbulence flow in the annulus. Increases in flow rate in horizontal section by considering a lower range of viscosity is more effective and improved cuttings transport performance.

Keywords: cutting transport, directional drilling, flow rate, hole cleaning, pipe rotation

Procedia PDF Downloads 274

Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

Abstract:

This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

Procedia PDF Downloads 453

Authors: Jafar Akbari, Masoud Rismanchian, Samira Ramezani

Abstract:

Purpose: The photocatalytic degradation of pollutants is a novel technology with various advantages such as high efficiency and energy saving. In this research, the effects of operational variables on the photocatalytic efficiency of TiO₂ coated on nickel foam in the removal of toluene from the simulated indoor air have been investigated. Methods: TiO₂ film were prepared via the sol-gel method and coated on nickel foam. The characteristics and morphology were found using XRD, SEM, and BET technique. Then, the effects of relative humidity, UV-A intensity, the initial toluene concentration, TiO₂ loading, and the air circulation velocity on the photocatalytic degradation rate have been evaluated. Results: The optimal degradation of toluene has been achieved with loading 4.35 g TiO2 on the foam, 30% RH, 5.4 µW.cm−2 UV-A intensity, and 20 ppm initial concentration in the air circulation velocity of 0.15 fpm. Conclusion: The changes of toluene photocatalytic degradation rate have been studied at various times. Also, the kinetic behavior of toluene photocatalytic degradation has been investigated using Langmuir-Hinshelwood (L-H) model.

Keywords: photocatalytic degradation, operational variables, tio₂, nickel foam, gaseous toluene, nanotechnology

Procedia PDF Downloads 71

Authors: Javad Sarvestan, Zdenek Svoboda

Abstract:

Force-time (F-T) curvature characteristics are globally referenced as the main indicators of athletic jump performance. Nevertheless, to the best of authors’ knowledge, no investigation tried to deeply study the relationship between F-T curve variables and real-game jump performance among elite volleyball players. To this end, this study was designated to investigate the association between F-T curve variables, including movement timings, force, velocity, power, rate of force development (RFD), modified reactive strength index (RSImod), and net impulse with spike jump height during real-game circumstances. Twelve young elite volleyball players performed 3 countermovement jump (CMJ) and 3 spike jump in real-game circumstances with 1-minute rest intervals to prevent fatigue. Shapiro-Wilk statistical test illustrated the normality of data distribution, and Pearson’s product correlation test portrayed a significant correlation between CMJ height and peak RFD (0.85), average RFD (r=0.81), RSImod (r=0.88) and concentric net impulse (r=0.98), and also significant correlation between spike jump height and peak RFD (0.73), average RFD (r=0.80), RSImod (r=0.62) and concentric net impulse (r=0.71). Multiple regression analysis also reported that these factors have a strong contribution in predicting of CMJ (98%) and spike jump (77%) heights. Outcomes of this study confirm that the RFD, concentric net impulse, and RSImod values could precisely monitor and track the volleyball attackers’ explosive strength, muscular stretch-shortening cycle function efficiency, and ultimate spike jump height. To this effect, volleyball coaches and trainers are advised to have an in-depth focus on their athletes’ progression or the impacts of strength trainings by observing and chasing the F-T curve variables such as RFD, net impulse, and RSImod.

Keywords: net impulse, reactive strength index, rate of force development, stretch-shortening cycle

Procedia PDF Downloads 129

Authors: Amaraja Taur, Pankaj Doshi, Hak Koon Yeoh

Abstract:

The dripping modes for a Newtonian liquid of viscosity µ emanating from an inclined nozzle at flow rate Q is investigated experimentally. As the liquid flow rate Q increases, starting with period-1 with satellite drops, the system transitions to period-1 dripping without satellite, then to limit cycle before showing chaotic responses. Phase diagrams shows the changes in the transitions between the different dripping modes for different nozzle inclination angle θ is constructed in the dimensionless (Q, µ) space.

Keywords: dripping, inclined nozzle, phase diagram, satellite

Procedia PDF Downloads 280

Authors: D. M. Samartsev, A. G. Copping

Abstract:

As with all industries, architects are using increasing amounts of automation within practice, with approaches such as generative design and use of AI becoming more commonplace. However, the discourse on the rate at which the architectural design process is being automated is often personal and lacking in objective figures and measurements. This results in confusion between people and barriers to effective discourse on the subject, in turn limiting the ability of architects, policy makers, and members of the public in making informed decisions in the area of design automation. This paper proposes the use of a framework to quantify the progress of automation within the design process. The use of a reductionist analysis of the design process allows it to be quantified in a manner that enables direct comparison across different times, as well as locations and projects. The methodology is informed by the design of this framework – taking on the aspects of a systematic review but compressed in time to allow for an initial set of data to verify the validity of the framework. The use of such a framework of quantification enables various practical uses such as predicting the future of the architectural industry with regards to which tasks will be automated, as well as making more informed decisions on the subject of automation on multiple levels ranging from individual decisions to policy making from governing bodies such as the RIBA. This is achieved by analyzing the design process as a generic task that needs to be performed, then using principles of work breakdown systems to split the task of designing an entire building into smaller tasks, which can then be recursively split further as required. Each task is then assigned a series of milestones that allow for the objective analysis of its automation progress. By combining these two approaches it is possible to create a data structure that describes how much various parts of the architectural design process are automated. The data gathered in the paper serves the dual purposes of providing the framework with validation, as well as giving insights into the current situation of automation within the architectural design process. The framework can be interrogated in many ways and preliminary analysis shows that almost 40% of the architectural design process has been automated in some practical fashion at the time of writing, with the rate at which progress is made slowly increasing over the years, with the majority of tasks in the design process reaching a new milestone in automation in less than 6 years. Additionally, a further 15% of the design process is currently being automated in some way, with various products in development but not yet released to the industry. Lastly, various limitations of the framework are examined in this paper as well as further areas of study.

Keywords: analysis, architecture, automation, design process, technology

Procedia PDF Downloads 90

Authors: Yael Wolff Sagy, Yiska Loewenberg Weisband, Vered Kaufman Shriqui, Michal Krieger, Arie Ben Yehuda, Ronit Calderon Margalit

Abstract:

Background: Obesity is both a risk factor and common comorbidity of diabetes. Obesity impedes the achievement of glycemic control, and enhances damage caused by hyperglycemia to blood vessels; thus it increases diabetes-related complications. This study assessed the prevalence of obesity and morbid obesity among Israeli adults with diabetes, and estimated disparities associated with sex and socioeconomic position (SEP). Methods: A cross-sectional study was conducted in the setting of the Israeli National Program for Quality Indicators in Community Healthcare. Data on all the Israeli population is retrieved from electronic medical records of the four health maintenance organizations (HMOs). The study population included all Israeli patients with diabetes aged 20-64 with documented body mass index (BMI) in 2016 (N=180,451). Diabetes was defined as the existence of one or more of the following criteria: (a) Plasma glucose level >200 mg% in at least two tests conducted at least one month apart in the previous year; (b) HbA1c>6.5% at least once in the previous year (c) at least three prescriptions of diabetes medications were dispensed during the previous year. Two measures were included: the prevalence of obesity (defined as last BMI≥ 30 kg/m2 and <35 kg/m2) and the prevalence of morbid obesity (defined as last BMI≥ 35 kg/m2) in individuals aged 20-64 with diabetes. The cut-off value for morbid obesity was set in accordance with the eligibility criteria for bariatric surgery in diabetics. Data were collected by the HMOs and aggregated by age, sex and SEP. SEP was based on statistical areas ranking by the Israeli Central Bureau of Statistics and divided into 4 categories, ranking from 1 (lowest) to 4 (highest). Results: BMI documentation among adults with diabetes was 84.9% in 2016. The prevalence of obesity in the study population was 30.5%. Although the overall rate was similar in both sexes (30.8% in females, 30.3% in males), SEP disparities were stronger in females (32.7% in SEP level 1 vs. 27.7% in SEP level 4; 18.1% relative difference) compared to males (30.6% in SEP level 1 vs. 29.3% in SEP level 4; 4.4% relative difference). The overall prevalence of morbid obesity in this population was 20.8% in 2016. The rate among females was almost double compared to the rate in males (28.1% and 14.6%, respectively). In both sexes, the prevalence of morbid obesity was strongly associated with lower SEP. However, in females, disparities between SEP levels were much stronger (34.3% in SEP level 1 vs. 18.7% in SEP level 4; 83.4% relative difference) compared to SEP-disparities in males (15.7% in SEP level 1 vs. 12.3% in SEP level 4; 27.6% relative difference). Conclusions: The overall prevalence of BMI≥ 30 kg/m2 among adults with diabetes in Israel exceeds 50%; and the prevalence of morbid obesity suggests that 20% meet the BMI-criteria for bariatric surgery. Prevalence rates show major SEP- and sex-disparities; especially strong SEP disparities in morbid obesity among females. These findings highlight the need for greater consideration of different population groups when implementing interventions.

Keywords: diabetes, health disparities, health policy, obesity, socio-economic position

Procedia PDF Downloads 197

Authors: Piotr Muzyk, Beata Morawiec, Mariusz Opara, Andrzej Tomasik, Brygida Przywara-Chowaniec, Wojciech Jachec, Ewa Nowalany-Kozielska, Damian Kawecki

Abstract:

Background: Coronary bifurcation is one of the most complex lesion in patients with coronary ar-tery disease. Provisional T-stenting is currently one of the recommended techniques. The aim was to assess optimal methods of treatment in the era of drug-eluting stents (DES). Methods: The regis-try consisted of data from 1916 patients treated with coronary percutaneous interventions (PCI) using either first- or second-generation DES. Patients with bifurcation lesion entered the analysis. Major adverse cardiac and cardiovascular events (MACCE) were assessed at one year of follow-up and comprised of death, acute myocardial infarction (AMI), repeated PCI (re-PCI) of target ves-sel and stroke. Results: Of 1916 registry patients, 204 patients (11%) were diagnosed with bifurcation lesion >50% and entered the analysis. The most commonly used technique was provi-sional T-stenting (141 patients, 69%). Optimization with kissing-balloons technique was performed in 45 patients (22%). In 59 patients (29%) second-generation DES was implanted, while in 112 pa-tients (55%), first-generation DES was used. In 33 patients (16%) both types of DES were used. The procedure success rate (TIMI 3 flow) was achieved in 98% of patients. In one-year follow-up, there were 39 MACCE (19%) (9 deaths, 17 AMI, 16 re-PCI and 5 strokes). Provisional T-stenting resulted in similar rate of MACCE to other techniques (16% vs. 5%, p=0.27) and similar occurrence of re-PCI (6% vs. 2%, p=0.78). The results of post-PCI kissing-balloon technique gave equal out-comes with 3% vs. 16% of MACCE in patients in whom no optimization technique was used (p=0.39). The type of implanted DES (second- vs. first-generation) had no influence on MACCE (4% vs 14%, respectively, p=0.12) and re-PCI (1.7% vs. 51% patients, respectively, p=0.28). Con-clusions: The treatment of bifurcation lesions with PCI represent high-risk procedures with high rate of MACCE. Stenting technique, optimization of PCI and the generation of implanted stent should be personalized for each case to balance risk of the procedure. In this setting, the operator experience might be the factor of better outcome, which should be further investigated.

Keywords: coronary bifurcation, drug eluting stents, long-term follow-up, percutaneous coronary interventions

Procedia PDF Downloads 193

Authors: Mahmoud Tarek, Alaa Obeida, Mai Magdy, Khalid Hussein, Aly Shalaby

Abstract:

Background: More doctors are complaining of burnout than before, Burnout is a state of physical and mental exhaustion caused by the doctor’s lifestyle, unfortunately, Medical errors are also more likely in those suffering from burnout and these may result in malpractice suits. Methodology: It is a retrospective audit of burnout response on all neonatologists over a 9 months period. We gathered data using burnout questionnaire, it was obtained from 23 physicians, the physicians divided into 5 categories according to the final score of the 28 questions in the questionnaire. Category 1 with score from 28-38 with almost no work stress, category 2 with score (38-50) who express a low amount of job related stress, category 3 with score (51-70) with moderate amount of stress, category 4 with score (71-90) those express a high amount of job stress and begun to burnout, category 5 with score (91 and above) who are under a dangerous amount of stress and advanced stage of burnout. Results: 33 neonatologists have received the questionnaire, 23 responses were sent back with a response rate of 69.6%. The results showed that 61% of physicians fall in category 4, 31% of the physician in category 5, while 8% of physicians equally distributed between category 2 and 3 (4% each of them). On the other hand, there is no physician present in category 1. Conclusion: Burnout is prevalent in SNICUs, So interventions to minimize burnout prevalence may be of greater importance as this may be reflected indirectly on medical conditions of the patients and physicians, efforts should be done to decrease this high rate of burnout.

Keywords: Cairo, work overload, exhaustion, surgery, neonatal ICU

Procedia PDF Downloads 197

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 72

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 82

Authors: Neetu Tyagi, Sumit Sharma

Abstract:

The study illustrates the results of an integrated study done on Tangni landslide located on NH-58 at Chamoli, Uttarakhand. Geological, geo-morphological and geotechnical investigations were carried out to understand the mechanism of landslide and to plan further investigation and monitoring. At any rate, the movements were favored by continuous rainfall water infiltration from the zones where the phyllites/slates and Dolomites outcrop. The site investigations were carried out including the monitoring of landslide movements and of the water level fluctuations due to rainfall give us a better understanding of landslide dynamics that have been causing in time soil instability at Tangni landslide site. The Early Warning System (EWS) installed different types of sensors and all sensors were directly connected to data logger and raw data transfer to the Defence Terrain Research Laboratory (DTRL) server room with the help of File Transfer Protocol (FTP). The slip surfaces were found at depths ranging from 8 to 10 m from Geophysical survey and hence sensors were installed to the depth of 15m at various locations of landslide. Rainfall is the main triggering factor of landslide. In this study, the developed model of unsaturated soil slope stability is carried out. The analysis of sensors data available for one year, indicated the sliding surface of landslide at depth between 6 to 12m with total displacement up to 6cm per year recorded at the body of landslide. The aim of this study is to set the threshold and generate early warning. Local peoples already alert towards landslide, if they have any types of warning system.

Keywords: early warning system, file transfer protocol, geo-morphological, geotechnical, landslide

Procedia PDF Downloads 145

Authors: Martin Van, Mohammed Javed, Sarah Hemington-Gorse

Abstract:

Aim: Our aim was to determine the effect of size and tumor depth of basal cell carcinomas (BCCs) on surgical margin clearance. Methods: A retrospective study was conducted at the Welsh Centre for Burns and Plastic Surgery (WCBPS), Morriston Hospital between 1 Jan 2016 – 31 July 2016. Only patients with confirmed BCC on histopathological analysis were included. Patient data including anatomical region treated, lesion size, histopathological clearance margins and histological sub-types were recorded. An independent T-test was performed determine statistical significance. Results: A total of 228 BCCs were excised in 160 patients. Eleven lesions (4.8%) were incompletely excised. The nose area had the highest rate of incomplete excision. The mean diameter of incompletely excised lesions was 11.4mm vs 11.5mm in completely excised lesions (p=0.959) and the mean histological depth of incompletely excised lesions was 4.1mm vs. 2.5mm for completely excised BCCs (p < 0.05). Conclusions: BCC tumor depth of > 4.1 mm was associated with high rate of incomplete margin clearance. Hence, in prospective patients, a BCC tumor depth (>4 mm) on tissue biopsy should alert the surgeon of potentially higher risk of incomplete excision of lesion.

Keywords: basal cell carcinoma, excision margins, plastic surgery, treatment

Procedia PDF Downloads 230

Authors: Glebert C. Dadol, Camila Flor Y. Lobarbio, Noel Peter B. Tan

Abstract:

Water scarcity is a global problem. One of the promising solutions to this challenge is the use of membrane-based desalination technologies. In this study, a passive solar-driven membrane (PSDM) distillation was employed to test its desalination performance. The PSDM was fabricated using a TiNOX sheet solar absorber, cellulose-based hydrophilic top and bottom layers, and a middle layer. The effects of the middle layer material and thickness on the desalination performance in terms of distillate flow rate, productivity, and salinity were investigated. An air-gap screen mesh (2 mm, 4 mm, 6 mm thickness) and a hydrophobic PTFE membrane (0.3 mm thickness) were used as middle-layer materials. Saltwater input (35 g/L NaCl) was used for the PSDM distiller on a rooftop setting at the University of San Carlos, Cebu City, Philippines. The highest distillate flow rate and productivity of 1.08 L/m²-h and 1.47 L/kWh, respectively, were achieved using a 2 mm air-gap middle layer, but it also resulted in a high salinity of 25.20 g/L. Increasing the air gap lowered the salinity but also decreased the flow rate and productivity. The lowest salinity of 1.07 g/L was achieved using 6 mm air gap, but the flow rate and productivity were reduced to 0.08 L/m²-h and 0.17 L/kWh, respectively. The use of a hydrophobic PTFE membrane, on the other hand, did not offer a significant improvement in its performance. A PDSM distiller with a thick air gap as the middle layer can deliver a distillate with low salinity and is preferred over a thin hydrophobic PTFE membrane. Various modifications and optimizations to the distiller can be done to improve its performance further.

Keywords: desalination, membrane distillation, passive solar-driven membrane distiller, solar distillation

Procedia PDF Downloads 114

Authors: Ji Eun Shin, Dong Hoon Lim

Abstract:

Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

Procedia PDF Downloads 419

Authors: Iva Hereitova, Miroslav Svatek, Vit Novacek

Abstract:

Background and Aim: Autonomic imbalance is one of the complications for immobilized patients in the acute stage after a stroke. The predominance of sympathetic activity significantly increases cardiac activity. The technique of glenohumeral joint approximation may contribute in a non-pharmacological way to the regulation of blood pressure and heart rate in patients in this risk group. The aim of the study was to evaluate the effect of glenohumeral joint approximation on the change in heart rate and blood pressure in immobilized patients in the acute phase after a stroke. Methods: The experimental study bilaterally evaluated heart rate, systolic and diastolic pressure values before and after glenohumeral joint approximation in 40 immobilized participants (72.6 ± 10.2 years) in the acute phase after stroke. The experimental group was compared with 40 healthy participants in the control group (68.6 ± 14.2 years). An SpO2 vital signs monitor and a validated Microlife WatchBP Office blood pressure monitor were used for evaluation. Statistical processing and evaluation were performed in MATLAB R2019 (The Math Works®, Inc., Natick, MA, USA). Results: Approximation of the glenohumeral joint resulted in a statistically significant decrease in systolic and diastolic pressure. An average decrease in systolic pressure for individual groups ranged from 8.2 to 11.3 mmHg (p <0.001). For diastolic pressure, the average decrease ranged from 5.0 - 14.2 mmHg (p <0.001). There was a statistically significant reduction in heart rate (p <0.01) only in patients after ischemic stroke in the inferior cerebral artery. There was the average decrease in heart rate of 3.9 beats per minute (median 4 beats per minute). Conclusion: Approximation of the glenohumeral joint leads to a statistically significant decrease in systolic and diastolic pressure in immobilized patients in the acute phase after stroke.

Keywords: Aproximation technique, Cardiovaskular system, Glenohumeral joint, Stroke

Procedia PDF Downloads 195

Authors: Anwar Hasan Abdullah Othman, Ahamed Kameel, Hasanuddeen Abdul Aziz

Abstract:

In this study, an attempt has been made to investigate the relationship specifically the causal relation between fund unit prices of Islamic equity unit trust fund which measure by fund NAV and the selected macro-economic variables of Malaysian economy by using VECM causality test and Granger causality test. Monthly data has been used from Jan, 2006 to Dec, 2012 for all the variables. The findings of the study showed that industrial production index, political election and financial crisis are the only variables having unidirectional causal relationship with fund unit price. However, the global oil prices is having bidirectional causality with fund NAV. Thus, it is concluded that the equity unit trust fund industry in Malaysia is an inefficient market with respect to the industrial production index, global oil prices, political election and financial crisis. However, the market is approaching towards informational efficiency at least with respect to four macroeconomic variables, treasury bill rate, money supply, foreign exchange rate and corruption index.

Keywords: fund unit price, unit trust industry, Malaysia, macroeconomic variables, causality

Procedia PDF Downloads 461

Authors: Silumpa Suboonsan, Suwat Pattaramalai

Abstract:

In this paper, the performance of internet usage by using Vertical Handover (VHO) between cellular network and wireless local area network (WLAN) on Silom line Bangkok Mass Transit System (BTS) is evaluated. In the evaluation model, there is the WLAN on every BTS station and there are cellular base stations along the BTS path. The maximum data rates for cellular network are 7.2, 14.4, 42, and 100Mbps and for WLAN are 54, 150, and 300Mbps. The simulation are based on users using internet, watching VDOs and browsing web pages, on the BTS train from first station to the last station (full time usage) and on the BTS train for traveling some number of stations (random time). The results shows that VHO system has throughput a lot more than using only cellular network when the data rate of WLAN is more than one of cellular network. Lastly, the number of watching HD VDO and Full HD VDO is higher on VHO system on both regular time and rush hour of BTS travelling.

Keywords: vertical handover, WLAN, cellular, silom line BTS

Procedia PDF Downloads 468

Authors: Nikita Valluri, Vatcharaporn Esichaikul

Abstract:

With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

Procedia PDF Downloads 145

Authors: Joel Y. Y. Loh, Geoffrey A. Ozin, Charles A. Mims, Nazir P. Kherani

Abstract:

A major goal in the emerging field of solar fuels is to realize an ‘artificial leaf’ – a material that converts light energy in the form of solar photons into chemical energy – using CO2 as a feedstock to generate useful chemical species. Enabling this technology will allow the greenhouse gas, CO2, emitted from energy and manufacturing production exhaust streams to be converted into valuable solar fuels or chemical products. Indium Oxide (In2O3) with surface hydroxyl (OH) groups have been shown to reduce CO2 in the presence of H2 to CO with a reaction rate of 15 μmol gcat−1 h−1. The likely mechanism is via a Frustrated Lewis Pair sites heterolytically splitting H2 to be absorbed and form protonic and hydric sites that can dissociate CO2. In this study, we investigate the dependence of oxygen composition of In2O3 on the CO2 reduction rate. In2O3-x films on quartz fiber paper were DC sputtered with an Indium target and varying O2/Ar plasma mixture. OH surface groups were then introduced by immersing the In2O3-x samples in KOH. We show that hydroxylated In2O3-x reduces more CO2 than non-hydroxylated groups and that a hydroxylated and higher O2/Ar ratio sputtered In2O3-x has a higher reaction rate of 45 μmol gcat-1 h-1. We show by electrical resistivity-temperature curves that H2 is adsorbed onto the surface of In2O3 whereas CO2 itself does not affect the indium oxide surface. We also present activation and ionization energy levels of the hydroxylated In2O3-x under vacuum, CO2 and H2 atmosphere conditions.

Keywords: solar fuels, photocatalysis, indium oxide nanoparticles, carbon dioxide

Procedia PDF Downloads 228

Authors: Moti Zwilling, Srečko Natek

Abstract:

This paper aims to present an innovative predictive analytics analysis in order to find the best combination between two consumers who strive to find their partner or in internet sites. The methodology shown in this paper is based on analysis of consumer preferences and involves data mining and machine learning search techniques. The study is composed of two parts: The first part examines by means of descriptive statistics the correlations between a set of parameters that are taken between man and women where they intent to meet each other through the social media, usually the internet. In this part several hypotheses were examined and statistical analysis were taken place. Results show that there is a strong correlation between the affiliated attributes of man and woman as long as concerned to how they present themselves in a social media such as "Facebook". One interesting issue is the strong desire to develop a serious relationship between most of the respondents. In the second part, the authors used common data mining algorithms to search and classify the most important and effective attributes that affect the response rate of the other side. Results exhibit that personal presentation and education background are found as most affective to achieve a positive attitude to one's profile from the other mate.

Keywords: dating sites, social networks, machine learning, decision trees, data mining

Procedia PDF Downloads 285

Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

Abstract:

In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

Procedia PDF Downloads 294

Authors: Sami Kabir, Sadek Hossain Khoka

Abstract:

Open Government Data (OGD) refers to all data produced by government which are accessible in reusable way by common people with access to Internet and at free of cost. In line with “Digital Bangladesh” vision of Bangladesh government, the concept of open data has been gaining momentum in the country. Opening all government data in digital and customizable format from single platform can enhance e-governance which will make government more transparent to the people. This paper presents a well-in-progress case study on OGD portal by Bangladesh Government in order to link decentralized data. The initiative is intended to facilitate e-service towards citizens through this one-stop web portal. The paper further discusses ways of collecting data in digital format from relevant agencies with a view to making it publicly available through this single point of access. Further, possible layout of this web portal is presented.

Keywords: e-governance, one-stop web portal, open government data, reusable data, web of data

Procedia PDF Downloads 339

Authors: Diana Larisa Vladoiu, Vasile Ostafe, Adriana Isvoran

Abstract:

Molecular docking calculations reveal that pesticides provide favorable interactions with the bacterial chitinases. Pesticides interact with both hydrophilic and aromatic residues involved in the active site of the enzymes, their positions partially overlapping the substrate and the inhibitors locations. Molecular docking outcomes, in correlation with experimental literature data, suggest that the pesticides may be degraded or having an inhibitor effect on the activity of these enzymes, depending of the application dose and rate.

Keywords: chitinases, inhibition, molecular docking, pesticides

Procedia PDF Downloads 537

Authors: Zengmin Tian, Bin Lv, Rui Hui, Yupeng Liu, Chuan Wang, Qing Liu, Hongyu Li, Yan Qi, Li Song

Abstract:

Objective Robot was used for replacement of the frame in recent years. The paper is to investigate the safety and effectiveness of frameless stereotactic surgery in the treatment of children with cerebral palsy. Methods Clinical data of 425 children with spastic cerebral palsy were retrospectively analyzed. The patients were treated with robot-assistant frameless stereotactic surgery of nuclear mass destruction. The motor function was evaluated by gross motor function measure-88 (GMFM-88) before the operation, 1 week and 3 months after the operation respectively. The statistical analysis was performed. Results The postoperative CT showed that the destruction area covered the predetermined target in all the patients. Minimal bleeding of puncture channel occurred in 2 patient, and mild fever in 3 cases. Otherwise, there was no severe surgical complication occurred. The GMFM-88 scores were 49.1±22.5 before the operation, 52.8±24.2 and 64.2±21.4 at the time of 1 week and 3 months after the operation, respectively. There was statistical difference between before and after the operation (P<0.01). After 3 months, the total effective rate was 98.1%, and the average improvement rate of motor function was 24.3% . Conclusion Replaced the traditional frame, the robot-assistant frameless stereotactic surgery is safe and reliable for children with spastic cerebral palsy, which has positive significance in improving patients’ motor function.

Keywords: cerebral palsy, robotics, stereotactic techniques, frameless operation

Procedia PDF Downloads 77

Authors: Janne Engblom, Elias Oikarinen

Abstract:

The understanding of housing price dynamics is of importance to a great number of agents: to portfolio investors, banks, real estate brokers and construction companies as well as to policy makers and households. A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models is dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Common Correlated Effects estimator (CCE) of dynamic panel data which also accounts for cross-sectional dependence which is caused by common structures of the economy. In presence of cross-sectional dependence standard OLS gives biased estimates. In this study, U.S housing price dynamics were examined empirically using the dynamic CCE estimator with first-difference of housing price as the dependent and first-differences of per capita income, interest rate, housing stock and lagged price together with deviation of housing prices from their long-run equilibrium level as independents. These deviations were also estimated from the data. The aim of the analysis was to provide estimates with comparisons of estimates between 1980-1999 and 2000-2012. Based on data of 50 U.S cities over 1980-2012 differences of short-run housing price dynamics estimates were mostly significant when two time periods were compared. Significance tests of differences were provided by the model containing interaction terms of independents and time dummy variable. Residual analysis showed very low cross-sectional correlation of the model residuals compared with the standard OLS approach. This means a good fit of CCE estimator model. Estimates of the dynamic panel data model were in line with the theory of housing price dynamics. Results also suggest that dynamics of a housing market is evolving over time.

Keywords: dynamic model, panel data, cross-sectional dependence, interaction model

Procedia PDF Downloads 242

Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

Abstract:

Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

Procedia PDF Downloads 240

Authors: Pawel Flaszynski, Piotr Doerffer, Jan Holnicki-Szulc, Grzegorz Mikulowski

Abstract:

Results of numerical simulations for transonic flow in a piezoelectric valve are presented. The valve is the main part of an adaptive pneumatic shock absorber. Flow structure in the valve domain and the influence of the flow non-uniformity in the valve on a mass flow rate is investigated. Numerical simulation results are compared with experimental data.

Keywords: pneumatic valve, transonic flow, numerical simulations, piezoelectric valve

Procedia PDF Downloads 495

Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem

Abstract:

The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.

Keywords: IoT, traffic security, deep learning, classification

Procedia PDF Downloads 139

Authors: Yingjeng James Li, Chih Chi Hsu, Chiao-Chih Hu

Abstract:

Membrane electrode assemblies MEAs for proton exchange membrane PEM water electrolyzers were prepared by employing 175um perfluorosulfonic acid PFSA membranes as the PEM, onto which iridium oxide catalyst was coated on one side as the anode and platinum catalyst was coated on the other side as the cathode. The cathode catalyst ink was prepared so that the weight ratio of the catalyst powder to ionomer was 75:25, 70:30, 65:35, 60:40, and 55:45, respectively. Whereas, the ratio of catalyst powder to ionomer of the anode catalyst ink keeps constant at 50:50. All the MEAs have a catalyst coated area of 5cm*5cm. The test cell employs a platinum plated titanium grid as anode gas diffusion media; whereas, carbon paper was employed as the cathode gas diffusion media. The measurements of the MEA gases production rate were carried out by holding the cell voltage ranging from 1.6 to 2.8 volts at room temperature. It was found that the MEA with cathode catalyst to ionomer ratio of 65:35 gives the largest hydrogen production rate which is 2.8mL/cm2*min.

Keywords: electrolyzer, membrane electrode assembly, proton exchange membrane, ionomer, hydrogen

Procedia PDF Downloads 243