Search results for: vector density
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4437

Search results for: vector density

3327 Smartphone-Based Human Activity Recognition by Machine Learning Methods

Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

Procedia PDF Downloads 136
3326 Experimental Study of Vibration Isolators Made of Expanded Cork Agglomerate

Authors: S. Dias, A. Tadeu, J. Antonio, F. Pedro, C. Serra

Abstract:

The goal of the present work is to experimentally evaluate the feasibility of using vibration isolators made of expanded cork agglomerate. Even though this material, also known as insulation cork board (ICB), has mainly been studied for thermal and acoustic insulation purposes, it has strong potential for use in vibration isolation. However, the adequate design of expanded cork blocks vibration isolators will depend on several factors, such as excitation frequency, static load conditions and intrinsic dynamic behavior of the material. In this study, transmissibility tests for different static and dynamic loading conditions were performed in order to characterize the material. Since the material’s physical properties can influence the vibro-isolation performance of the blocks (in terms of density and thickness), this study covered four mass density ranges and four block thicknesses. A total of 72 expanded cork agglomerate specimens were tested. The test apparatus comprises a vibration exciter connected to an excitation mass that holds the test specimen. The test specimens under characterization were loaded successively with steel plates in order to obtain results for different masses. An accelerometer was placed at the top of these masses and at the base of the excitation mass. The test was performed for a defined frequency range, and the amplitude registered by the accelerometers was recorded in time domain. For each of the signals (signal 1- vibration of the excitation mass, signal 2- vibration of the loading mass) a fast Fourier transform (FFT) was applied in order to obtain the frequency domain response. For each of the frequency domain signals, the maximum amplitude reached was registered. The ratio between the amplitude (acceleration) of signal 2 and the amplitude of signal 1, allows the calculation of the transmissibility for each frequency. Repeating this procedure allowed us to plot a transmissibility curve for a certain frequency range. A number of transmissibility experiments were performed to assess the influence of changing the mass density and thickness of the expanded cork blocks and the experimental conditions (static load and frequency of excitation). The experimental transmissibility tests performed in this study showed that expanded cork agglomerate blocks are a good option for mitigating vibrations. It was concluded that specimens with lower mass density and larger thickness lead to better performance, with higher vibration isolation and a larger range of isolated frequencies. In conclusion, the study of the performance of expanded cork agglomerate blocks presented herein will allow for a more efficient application of expanded cork vibration isolators. This is particularly relevant since this material is a more sustainable alternative to other commonly used non-environmentally friendly products, such as rubber.

Keywords: expanded cork agglomerate, insulation cork board, transmissibility tests, sustainable materials, vibration isolators

Procedia PDF Downloads 327
3325 Roadway Infrastructure and Bus Safety

Authors: Richard J. Hanowski, Rebecca L. Hammond

Abstract:

Very few studies have been conducted to investigate safety issues associated with motorcoach/bus operations. The current study investigates the impact that roadway infrastructure, including locality, roadway grade, traffic flow and traffic density, have on bus safety. A naturalistic driving study was conducted in the U.S.A that involved 43 motorcoaches. Two fleets participated in the study and over 600,000 miles of naturalistic driving data were collected. Sixty-five bus drivers participated in this study; 48 male and 17 female. The average age of the drivers was 49 years. A sophisticated data acquisition system (DAS) was installed on each of the 43 motorcoaches and a variety of kinematic and video data were continuously recorded. The data were analyzed by identifying safety critical events (SCEs), which included crashes, near-crashes, crash-relevant conflicts, and unintentional lane deviations. Additionally, baseline (normative driving) segments were also identified and analyzed for comparison to the SCEs. This presentation highlights the need for bus safety research and the methods used in this data collection effort. With respect to elements of roadway infrastructure, this study highlights the methods used to assess locality, roadway grade, traffic flow, and traffic density. Locality was determined by manual review of the recorded video for each event and baseline and was characterized in terms of open country, residential, business/industrial, church, playground, school, urban, airport, interstate, and other. Roadway grade was similarly determined through video review and characterized in terms of level, grade up, grade down, hillcrest, and dip. The video was also used to make a determination of the traffic flow and traffic density at the time of the event or baseline segment. For traffic flow, video was used to assess which of the following best characterized the event or baseline: not divided (2-way traffic), not divided (center 2-way left turn lane), divided (median or barrier), one-way traffic, or no lanes. In terms of traffic density, level-of-service categories were used: A1, A2, B, C, D, E, and F. Highlighted in this abstract are only a few of the many roadway elements that were coded in this study. Other elements included lighting levels, weather conditions, roadway surface conditions, relation to junction, and roadway alignment. Note that a key component of this study was to assess the impact that driver distraction and fatigue have on bus operations. In this regard, once the roadway elements had been coded, the primary research questions that were addressed were (i) “What environmental condition are associated with driver choice of engagement in tasks?”, and (ii) “what are the odds of being in a SCE while engaging in tasks while encountering these conditions?”. The study may be of interest to researchers and traffic engineers that are interested in the relationship between roadway infrastructure elements and safety events in motorcoach bus operations.

Keywords: bus safety, motorcoach, naturalistic driving, roadway infrastructure

Procedia PDF Downloads 174
3324 Discriminating Between Energy Drinks and Sports Drinks Based on Their Chemical Properties Using Chemometric Methods

Authors: Robert Cazar, Nathaly Maza

Abstract:

Energy drinks and sports drinks are quite popular among young adults and teenagers worldwide. Some concerns regarding their health effects – particularly those of the energy drinks - have been raised based on scientific findings. Differentiating between these two types of drinks by means of their chemical properties seems to be an instructive task. Chemometrics provides the most appropriate strategy to do so. In this study, a discrimination analysis of the energy and sports drinks has been carried out applying chemometric methods. A set of eleven samples of available commercial brands of drinks – seven energy drinks and four sports drinks – were collected. Each sample was characterized by eight chemical variables (carbohydrates, energy, sugar, sodium, pH, degrees Brix, density, and citric acid). The data set was standardized and examined by exploratory chemometric techniques such as clustering and principal component analysis. As a preliminary step, a variable selection was carried out by inspecting the variable correlation matrix. It was detected that some variables are redundant, so they can be safely removed, leaving only five variables that are sufficient for this analysis. They are sugar, sodium, pH, density, and citric acid. Then, a hierarchical clustering `employing the average – linkage criterion and using the Euclidian distance metrics was performed. It perfectly separates the two types of drinks since the resultant dendogram, cut at the 25% similarity level, assorts the samples in two well defined groups, one of them containing the energy drinks and the other one the sports drinks. Further assurance of the complete discrimination is provided by the principal component analysis. The projection of the data set on the first two principal components – which retain the 71% of the data information – permits to visualize the distribution of the samples in the two groups identified in the clustering stage. Since the first principal component is the discriminating one, the inspection of its loadings consents to characterize such groups. The energy drinks group possesses medium to high values of density, citric acid, and sugar. The sports drinks group, on the other hand, exhibits low values of those variables. In conclusion, the application of chemometric methods on a data set that features some chemical properties of a number of energy and sports drinks provides an accurate, dependable way to discriminate between these two types of beverages.

Keywords: chemometrics, clustering, energy drinks, principal component analysis, sports drinks

Procedia PDF Downloads 95
3323 Improving Carbon Fiber Structural Battery Performance with Polymer Interface

Authors: Kathleen Moyer, Nora Ait Boucherbil, Murtaza Zohair, Janna Eaves-Rathert, Cary Pint

Abstract:

This study demonstrates the significance of interface engineering in the field of structural energy by being the first case where the performance of the system with the structural battery is greater than the performance of the same system with a battery separate from the system. The benefits of improving the interface in the structural battery were tested by creating carbon fiber composite batteries (and independent graphite electrodes and lithium iron phosphate electrodes) with and without an improved interface. Mechanical data on the structural batteries were collected using tensile tests and electrochemical data was collected using scanning electron microscopy equipment. The full-cell lithium-ion structural batteries had capacity retention of over 80% exceeding 100 cycles with an average energy density of 52 W h kg−1 and a maximum energy density of 58 W h kg−1. Most scientific developments in the field of structural energy have been done with supercapacitors. Most scientific developments with structural batteries have been done where batteries are simply incorporated into the structural element. That method has limited advantages and can create mechanical disadvantages. This study aims to show that a large improvement in structure energy research can be made by improving the interface between the structural device and the battery.

Keywords: composite materials, electrochemical performance, mechanical properties, polymer interface, structural batteries

Procedia PDF Downloads 92
3322 Microwave-Assisted Torrefaction of Teakwood Biomass Residues: The Effect of Power Level and Fluid Flows

Authors: Lukas Kano Mangalla, Raden Rinova Sisworo, Luther Pagiling

Abstract:

Torrefaction is an emerging thermo-chemical treatment process that aims to improve the quality of biomass fuels. This study focused on upgrading the waste teakwood through microwave torrefaction processes and investigating the key operating parameters to improve energy density for the quality of biochar production. The experiments were carried out in a 250 mL reactor placed in a microwave cavity on two different media, inert and non-inert. The microwave was operated at a frequency of 2.45GHz with power level variations of 540W, 720W, and 900W, respectively. During torrefaction processes, the nitrogen gas flows into the reactor at a rate of 0.125 mL/min, and the air flows naturally. The temperature inside the reactor was observed every 0.5 minutes for 20 minutes using a K-Type thermocouple. Changes in the mass and the properties of the torrefied products were analyzed to predict the correlation between calorific value, mass yield, and level power of the microwave. The results showed that with the increase in the operating power of microwave torrefaction, the calorific value and energy density of the product increased significantly, while mass and energy yield tended to decrease. Air can be a great potential media for substituting the expensive nitrogen to perform the microwave torrefaction for teakwood biomass.

Keywords: torrefaction, microwave heating, energy enhancement, mass and energy yield

Procedia PDF Downloads 79
3321 The Biosphere as a Supercomputer Directing and Controlling Evolutionary Processes

Authors: Igor A. Krichtafovitch

Abstract:

The evolutionary processes are not linear. Long periods of quiet and slow development turn to rather rapid emergences of new species and even phyla. During Cambrian explosion, 22 new phyla were added to the previously existed 3 phyla. Contrary to the common credence the natural selection or a survival of the fittest cannot be accounted for the dominant evolution vector which is steady and accelerated advent of more complex and more intelligent living organisms. Neither Darwinism nor alternative concepts including panspermia and intelligent design propose a satisfactory solution for these phenomena. The proposed hypothesis offers a logical and plausible explanation of the evolutionary processes in general. It is based on two postulates: a) the Biosphere is a single living organism, all parts of which are interconnected, and b) the Biosphere acts as a giant biological supercomputer, storing and processing the information in digital and analog forms. Such supercomputer surpasses all human-made computers by many orders of magnitude. Living organisms are the product of intelligent creative action of the biosphere supercomputer. The biological evolution is driven by growing amount of information stored in the living organisms and increasing complexity of the biosphere as a single organism. Main evolutionary vector is not a survival of the fittest but an accelerated growth of the computational complexity of the living organisms. The following postulates may summarize the proposed hypothesis: biological evolution as a natural life origin and development is a reality. Evolution is a coordinated and controlled process. One of evolution’s main development vectors is a growing computational complexity of the living organisms and the biosphere’s intelligence. The intelligent matter which conducts and controls global evolution is a gigantic bio-computer combining all living organisms on Earth. The information is acting like a software stored in and controlled by the biosphere. Random mutations trigger this software, as is stipulated by Darwinian Evolution Theories, and it is further stimulated by the growing demand for the Biosphere’s global memory storage and computational complexity. Greater memory volume requires a greater number and more intellectually advanced organisms for storing and handling it. More intricate organisms require the greater computational complexity of biosphere in order to keep control over the living world. This is an endless recursive endeavor with accelerated evolutionary dynamic. New species emerge when two conditions are met: a) crucial environmental changes occur and/or global memory storage volume comes to its limit and b) biosphere computational complexity reaches critical mass capable of producing more advanced creatures. The hypothesis presented here is a naturalistic concept of life creation and evolution. The hypothesis logically resolves many puzzling problems with the current state evolution theory such as speciation, as a result of GM purposeful design, evolution development vector, as a need for growing global intelligence, punctuated equilibrium, happening when two above conditions a) and b) are met, the Cambrian explosion, mass extinctions, happening when more intelligent species should replace outdated creatures.

Keywords: supercomputer, biological evolution, Darwinism, speciation

Procedia PDF Downloads 153
3320 Effect of Halloysite on Heavy Metals Fate during Solid Waste Pyrolysis: A Combinatorial Experimental/Computational Study

Authors: Tengfei He, Mengjie Zhang, Baosheng Jin

Abstract:

In this study, the low-cost halloysite (Hal) was utilized for the first time to enhance the solid-phase enrichment and stability of heavy metals (HMs) during solid waste pyrolysis through experimental and theoretical methods, and compared with kaolinite (Kao). Experimental results demonstrated that Hal was superior to Kao in improving the solid-phase enrichment of HMs. Adding Hal reduced the proportion of HMs in the unstable fraction (F1+F2), consequently lowering the environmental risk of biochar and the extractable state of HMs. Through Grand canonical Monte Carlo and Density Functional Theory (DFT) simulations, the adsorption amounts and adsorption mechanisms of Cd/Pb compound on Hal/Kao surfaces were analyzed. The adsorption amounts of HMs by Hal were significantly higher than Kao and decreased with increasing temperature, and the difference in adsorption performance caused by structural bending was negligible. The DFT results indicated that Cd/Pb monomers were stabilized by establishing covalent bonds with OH or reactive O atoms on the Al-(0 0 1) surface, whereas the covalent bonds with ionic bonding properties formed between Cl atoms and unsaturated Al atoms played a crucial role in stabilizing HM chlorides. This study highlights the potential of Hal in stabilizing HMs during pyrolysis without requiring any modifications.

Keywords: heavy metals, halloysite, density functional theory, grand canonical Monte Carlo

Procedia PDF Downloads 62
3319 Hydrogen Embrittlement Properties of the Hot Stamped Carbon Steels

Authors: Mitsuhiro Okayasu, Lele Yang, Koji Shimotsu

Abstract:

The effects of microstructural characteristics on the mechanical and hydrogen embrittlement properties of 1,800MPa grade hot stamping carbon steel were investigated experimentally. The tensile strength increased with increasing the hot stamping temperature until around 921°C, but that decreased with increasing the temperature in more than 921°C due to the increment of the size of lath martensite and prior austenite. With the hot stamping process, internal strain was slightly created in the sample, which led to the slight increment of the hardness value although no clear change of the microstructural formation was detected. Severity of hydrogen embrittlement was investigated using the hot stamped carbon steels after the immersion in a hydrogen gas, and that was directly attributed to the infiltration of the hydrogen into their grain boundaries. The high strength carbon steel with tiny lath martensite microstructure could make severe hydrogen brittleness as the hydrogen was strongly penetrated in the grain boundaries in the hydrogen gas for a month. Because of weak embrittlement for the as-received carbon (ferrite and pearlite), hydrogen embrittlement is caused by the high internal strain and high dislocation density. The hydrogen embrittlement for carbon steel is attributed to amount of the hydrogen immersed in-between grain boundaries, which is caused by the dislocation density and internal strain.

Keywords: hydrogen embrittlement, hot stamping process, carbon steel, mechanical property

Procedia PDF Downloads 190
3318 PolyScan: Comprehending Human Polymicrobial Infections for Vector-Borne Disease Diagnostic Purposes

Authors: Kunal Garg, Louise Theusen Hermansan, Kanoktip Puttaraska, Oliver Hendricks, Heidi Pirttinen, Leona Gilbert

Abstract:

The Germ Theory (one infectious determinant is equal to one disease) has unarguably evolved our capability to diagnose and treat infectious diseases over the years. Nevertheless, the advent of technology, climate change, and volatile human behavior has brought about drastic changes in our environment, leading us to question the relevance of the Germ Theory in our day, i.e. will vector-borne disease (VBD) sufferers produce multiple immune responses when tested for multiple microbes? Vector diseased patients producing multiple immune responses to different microbes would evidently suggest human polymicrobial infections (HPI). Ongoing diagnostic tools are exceedingly unequipped with the current research findings that would aid in diagnosing patients for polymicrobial infections. This shortcoming has caused misdiagnosis at very high rates, consequently diminishing the patient’s quality of life due to inadequate treatment. Equipped with the state-of-art scientific knowledge, PolyScan intends to address the pitfalls in current VBD diagnostics. PolyScan is a multiplex and multifunctional enzyme linked Immunosorbent assay (ELISA) platform that can test for numerous VBD microbes and allow simultaneous screening for multiple types of antibodies. To validate PolyScan, Lyme Borreliosis (LB) and spondyloarthritis (SpA) patient groups (n = 54 each) were tested for Borrelia burgdorferi, Borrelia burgdorferi Round Body (RB), Borrelia afzelii, Borrelia garinii, and Ehrlichia chaffeensis against IgM and IgG antibodies. LB serum samples were obtained from Germany and SpA serum samples were obtained from Denmark under relevant ethical approvals. The SpA group represented chronic LB stage because reactive arthritis (SpA subtype) in the form of Lyme arthritis links to LB. It was hypothesized that patients from both the groups will produce multiple immune responses that as a consequence would evidently suggest HPI. It was also hypothesized that the multiple immune response proportion in SpA patient group would be significantly larger when compared to the LB patient group across both antibodies. It was observed that 26% LB patients and 57% SpA patients produced multiple immune responses in contrast to 33% LB patients and 30% SpA patients that produced solitary immune responses when tested against IgM. Similarly, 52% LB patients and an astounding 73% SpA patients produced multiple immune responses in contrast to 30% LB patients and 8% SpA patients that produced solitary immune responses when tested against IgG. Interestingly, IgM immune dysfunction in both the patient groups was also recorded. Atypically, 6% of the unresponsive 18% LB with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Similarly, 12% of the unresponsive 19% SpA with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Thus, results not only supported hypothesis but also suggested that IgM may atypically prevail longer than IgG. The PolyScan concept will aid clinicians to detect patients for early, persistent, late, polymicrobial, & immune dysfunction conditions linked to different VBD. PolyScan provides a paradigm shift for the VBD diagnostic industry to follow that will drastically shorten patient’s time to receive adequate treatment.

Keywords: diagnostics, immune dysfunction, polymicrobial, TICK-TAG

Procedia PDF Downloads 316
3317 A Numerical Study on Electrophoresis of a Soft Particle with Charged Core Coated with Polyelectrolyte Layer

Authors: Partha Sarathi Majee, S. Bhattacharyya

Abstract:

Migration of a core-shell soft particle under the influence of an external electric field in an electrolyte solution is studied numerically. The soft particle is coated with a positively charged polyelectrolyte layer (PEL) and the rigid core is having a uniform surface charge density. The Darcy-Brinkman extended Navier-Stokes equations are solved for the motion of the ionized fluid, the non-linear Nernst-Planck equations for the ion transport and the Poisson equation for the electric potential. A pressure correction based iterative algorithm is adopted for numerical computations. The effects of convection on double layer polarization (DLP) and diffusion dominated counter ions penetration are investigated for a wide range of Debye layer thickness, PEL fixed surface charge density, and permeability of the PEL. Our results show that when the Debye layer is in order of the particle size, the DLP effect is significant and produces a reduction in electrophoretic mobility. However, the double layer polarization effect is negligible for a thin Debye layer or low permeable cases. The point of zero mobility and the existence of mobility reversal depending on the electrolyte concentration are also presented.

Keywords: debye length, double layer polarization, electrophoresis, mobility reversal, soft particle

Procedia PDF Downloads 337
3316 Adaptive Process Monitoring for Time-Varying Situations Using Statistical Learning Algorithms

Authors: Seulki Lee, Seoung Bum Kim

Abstract:

Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

Procedia PDF Downloads 290
3315 An Investigation on Fresh and Hardened Properties of Concrete While Using Polyethylene Terephthalate (PET) as Aggregate

Authors: Md. Jahidul Islam, A. K. M. Rakinul Islam, M. Salamah Meherier

Abstract:

This study investigates the suitability of using plastic, such as polyethylene terephthalate (PET), as a partial replacement of natural coarse and fine aggregates (for example, brick chips and natural sand) to produce lightweight concrete for load bearing structural members. The plastic coarse aggregate (PCA) and plastic fine aggregate (PFA) were produced from melted polyethylene terephthalate (PET) bottles. Tests were conducted using three different water–cement (w/c) ratios, such as 0.42, 0.48, and 0.57, where PCA and PFA were used as 50% replacement of coarse and fine aggregate respectively. Fresh and hardened properties of concrete have been compared for natural aggregate concrete (NAC), PCA concrete (PCC) and PFA concrete (PFC). The compressive strength of concrete at 28 days varied with the water–cement ratio for both the PCC and PFC. Between PCC and PFC, PFA concrete showed the highest compressive strength (23.7 MPa) at 0.42 w/c ratio and also the lowest compressive strength (13.7 MPa) at 0.57 w/c ratio. Significant reduction in concrete density was mostly observed for PCC samples, ranging between 1977–1924 kg/m³. With the increase in water–cement ratio PCC achieved higher workability compare to both NAC and PFC. It was found that both the PCA and PFA contained concrete achieved the required compressive strength to be used for structural purpose as partial replacement of the natural aggregate; but to obtain the desired lower density as lightweight concrete the PCA is most suited.

Keywords: polyethylene terephthalate, plastic aggregate, concrete, fresh and hardened properties

Procedia PDF Downloads 427
3314 Communicative Strategies in Colombian Political Speech: On the Example of the Speeches of Francia Marquez

Authors: Danila Arbuzov

Abstract:

In this article the author examines the communicative strategies used in the Colombian political discourse, following the example of the speeches of the Vice President of Colombia Francia Marquez, who took office in 2022 and marked a new development vector for the Colombian nation. The lexical and syntactic means are analyzed to achieve the communicative objectives. The material presented may be useful for those who are interested in investigating various aspects of discursive linguistics, particularly political discourse, as well as the implementation of communicative strategies in certain types of discourse.

Keywords: political discourse, communication strategies, Colombian political discourse, Colombia, manipulation

Procedia PDF Downloads 97
3313 Comparison of Different Activators Impact on the Alkali-Activated Aluminium-Silicate Composites

Authors: Laura Dembovska, Ina Pundiene, Diana Bajare

Abstract:

Alkali-activated aluminium-silicate composites (AASC) can be used in the production of innovative materials with a wide range of properties and applications. AASC are associated with low CO₂ emissions; in the production process, it is possible to use industrial by-products and waste, thereby minimizing the use of a non-renewable natural resource. This study deals with the preparation of heat-resistant porous AASC based on chamotte for high-temperature applications up to 1200°C. Different fillers, aluminium scrap recycling waste as pores forming agent and alkali activation with 6M sodium hydroxide (NaOH) and potassium hydroxide (KOH) solution were used. Sodium hydroxide (NaOH) is widely used for the synthesis of AASC compared to potassium hydroxide (KOH), but comparison of using different activator for geopolymer synthesis is not well established. Changes in chemical composition of AASC during heating were identified and quantitatively analyzed by using DTA, dimension changes during the heating process were determined by using HTOM, pore microstructure was examined by SEM, and mineralogical composition of AASC was determined by XRD. Lightweight porous AASC activated with NaOH have been obtained with density in range from 600 to 880 kg/m³ and compressive strength from 0.8 to 2.7 MPa, but for AAM activated with KOH density was in range from 750 to 850 kg/m³ and compressive strength from 0.7 to 2.1 MPa.

Keywords: alkali activation, alkali activated materials, elevated temperature application, heat resistance

Procedia PDF Downloads 167
3312 Improved Computational Efficiency of Machine Learning Algorithm Based on Evaluation Metrics to Control the Spread of Coronavirus in the UK

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

Procedia PDF Downloads 113
3311 Comparing SVM and Naïve Bayes Classifier for Automatic Microaneurysm Detections

Authors: A. Sopharak, B. Uyyanonvara, S. Barman

Abstract:

Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists’ hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.

Keywords: diabetic retinopathy, microaneurysm, naive Bayes classifier, SVM classifier

Procedia PDF Downloads 317
3310 The Effects of Exercise Training on LDL Mediated Blood Flow in Coronary Artery Disease: A Systematic Review

Authors: Aziza Barnawi

Abstract:

Background: Regular exercise reduces risk factors associated with cardiovascular diseases. Over the past decade, exercise interventions have been introduced to reduce the risk of and prevent coronary artery disease (CAD). Elevated low-density lipoproteins (LDL) contribute to the formation of atherosclerosis, its manifestations on the endothelial narrow the coronary artery and affect the endothelial function. Therefore, flow-mediated dilation (FMD) technique is used to assess the function. The results of previous studies have been inconsistent and difficult to interpret across different types of exercise programs. The relationship between exercise therapy and lipid levels has been extensively studied, and it is known to improve the lipid profile and endothelial function. However, the effectiveness of exercise in altering LDL levels and improving blood flow is controversial. Objective: This review aims to explore the evidence and quantify the impact of exercise training on LDL levels and vascular function by FMD. Methods: Electronic databases were searched PubMed, Google Scholar, Web of Science, the Cochrane Library, and EBSCO using the keywords: “low and/or moderate aerobic training”, “blood flow”, “atherosclerosis”, “LDL mediated blood flow”, “Cardiac Rehabilitation”, “low-density lipoproteins”, “flow-mediated dilation”, “endothelial function”, “brachial artery flow-mediated dilation”, “oxidized low-density lipoproteins” and “coronary artery disease”. The studies were conducted for 6 weeks or more and influenced LDL levels and/or FMD. Studies with different intensity training and endurance training in healthy or CAD individuals were included. Results: Twenty-one randomized controlled trials (RCTs) (14 FMD and 7 LDL studies) with 776 participants (605 exercise participants and 171 control participants) met eligibility criteria and were included in the systematic review. Endurance training resulted in a greater reduction in LDL levels and their subfractions and a better FMD response. Overall, the training groups showed improved physical fitness status compared with the control groups. Participants whose exercise duration was ≥150 minutes /week had significant improvement in FMD and LDL levels compared with those with <150 minutes/week.Conclusion: In conclusion, although the relationship between physical training, LDL levels, and blood flow in CAD is complex and multifaceted, there are promising results for controlling primary and secondary prevention of CAD by exercise. Exercise training, including resistance, aerobic, and interval training, is positively correlated with improved FMD. However, the small body of evidence for LDL studies (resistance and interval training) did not prove to be significantly associated with improved blood flow. Increasing evidence suggests that exercise training is a promising adjunctive therapy to improve cardiovascular health, potentially improving blood flow and contributing to the overall management of CAD.

Keywords: exercise training, low density lipoprotein, flow mediated dilation, coronary artery disease

Procedia PDF Downloads 63
3309 Modeling and Optimization of a Microfluidic Electrochemical Cell for the Electro-Reduction of CO₂ to CH₃OH

Authors: Barzin Rajabloo, Martin Desilets

Abstract:

First, an electrochemical model for the reduction of CO₂ into CH₃OH is developed in which mass and charge transfer, reactions at the surface of the electrodes and fluid flow of the electrolyte are considered. This mathematical model is developed in COMSOL Multiphysics® where both secondary and tertiary current distribution interfaces are coupled to consider concentrations and potentials inside different parts of the cell. Constant reaction rates are assumed as the fitted parameters to minimize the error between experimental data and modeling results. The model is validated through a comparison with experimental data in terms of faradaic efficiency for production of CH₃OH, the current density in different applied cathode potentials as well as current density in different electrolyte flow rates. The comparison between model outputs and experimental measurements shows a good agreement. The model indicates the higher hydrogen evolution in comparison with CH₃OH production as well as mass transfer limitation caused by CO₂ concentration, which are consistent with findings in the literature. After validating the model, in the second part of the study, some design parameters of the cell, such as cathode geometry and catholyte/anolyte channel widths, are modified to reach better performance and higher faradaic efficiency of methanol production.

Keywords: carbon dioxide, electrochemical reduction, methanol, modeling

Procedia PDF Downloads 96
3308 The Effects of Electron Trapping by Electron-Ecoustic Waves Excited with Electron Beam

Authors: Abid Ali Abid

Abstract:

One-dimensional (1-D) particle-in-cell (PIC) electrostatic simulations are carried out to investigate the electrostatic waves, whose constituents are hot, cold and beam electrons in the background of motionless positive ions. In fact, the electrostatic modes excited are electron acoustic waves, beam driven waves as well as Langmuir waves. It is assessed that the relevant plasma parameters, for example, hot electron temperature, beam electron drift speed, and the electron beam density significantly modify the electrostatics wave's profiles. In the nonlinear stage, the wave-particle interaction becomes more evident and the waves have obtained its saturation level. Consequently, electrons become trapped in the waves and trapping vortices are clearly formed. Because of this trapping vortices and mixing of the electrons in phase space, finally, lead to electrons thermalization. It is observed that for the high-density value of the beam-electron, the solitary waves having a bipolar form of the electric field. These solitons are the nonlinear Brenstein-Greene and Kruskal wave mode that attributes the trapping of electrons potential well of phase-space hole. These examinations revealed that electrostatic waves have been exited in beam-plasma model and producing waves having broad-frequency ranges, which may clarify the broadband electrostatic noise (BEN) spectrum studied in the auroral zone.

Keywords: electron acoustic waves, trapping of cold electron, Langmuir waves, particle-in cell simulation

Procedia PDF Downloads 193
3307 Thermodynamic Performance Tests for 3D Printed Steel Slag Powder Concrete Walls

Authors: Li Guoyou, Zhang Tao, Ji Wenzhan, Huo Liang, Lin Xiqiang, Zhang Nan

Abstract:

The three dimensional (3D) printing technology has undergone rapid development in the last few years and it is possible to print engineering structures. 3D printing buildings use wastes from constructions, industries and mine tailings as “ink”, and mix it with property improved materials, such as cement, fiber etc. This paper presents a study of the Thermodynamic performance of 3D printed walls using cement and steel slag powder. Analyses the thermal simulation regarding 3D printed walls and solid brick wall by the way of the hot-box methods and the infrared technology, and the results were contrasted with theoretical calculation. The results show that the excellent thermodynamic performance of 3D printed concrete wall made it suitable as the partial materials for self-thermal insulation walls in residential buildings. The thermodynamic performance of 3D printed concrete walls depended on the density of materials, distribution of holes, and the filling materials. Decreasing the density of materials, increasing the number of holes or replacing the filling materials with foamed concrete could improve its thermodynamic performance significantly. The average of heat transfer coefficient and thermal inertia index of 3D printed steel slag powder concrete wall all better than the traditional solid brick wall with a thickness of 240mm.

Keywords: concrete, 3D printed walls, thermodynamic performance, steel slag powder

Procedia PDF Downloads 175
3306 Evolution of Nettlespurge Oil Mud for Drilling Mud System: A Comparative Study of Diesel Oil and Nettlespurge Oil as Oil-Based Drilling Mud

Authors: Harsh Agarwal, Pratikkumar Patel, Maharshi Pathak

Abstract:

Recently the low prices of Crude oil and increase in strict environmental regulations limit limits the use of diesel based muds as these muds are relatively costlier and toxic, as a result disposal of cuttings into the eco-system is a major issue faced by the drilling industries. To overcome these issues faced by the Oil Industry, an attempt has been made to develop oil-in-water emulsion mud system using nettlespurge oil. Nettlespurge oil could be easily available and its cost is around ₹30/litre which is about half the price of diesel in India. Oil-based mud (OBM) was formulated with Nettlespurge oil extracted from Nettlespurge seeds using the Soxhlet extraction method. The formulated nettlespurge oil mud properties were analysed with diesel oil mud properties. The compared properties were rheological properties, yield point and gel strength, and mud density and filtration loss properties, fluid loss and filter cake. The mud density measurement showed that nettlespurge OBM was slightly higher than diesel OBM with mud density values of 9.175 lb/gal and 8.5 lb/gal, respectively, at barite content of 70 g. Thus it has a higher lubricating property. Additionally, the filtration loss test results showed that nettlespurge mud fluid loss volumes, oil was 11 ml, compared to diesel oil mud volume of 15 ml. The filtration loss test indicated that the nettlespurge oil mud with filter cake thickness of 2.2 mm had a cake characteristic of thin and squashy while the diesel oil mud resulted in filter cake thickness of 2.7 mm with cake characteristic of tenacious, rubbery and resilient. The filtration loss test results showed that nettlespurge oil mud fluid loss volumes was much less than the diesel based oil mud. The filtration loss test indicated that the nettlespurge oil mud filter cake thickness less than the diesel oil mud filter cake thickness. So Low formation damage and the emulsion stability effect was analysed with this experiment. The nettlespurge oil-in-water mud system had lower coefficient of friction than the diesel oil based mud system. All the rheological properties have shown better results relative to the diesel based oil mud. Therefore, with all the above mentioned factors and with the data of the conducted experiment we could conclude that the Nettlespurge oil based mud is economically and well as eco-logically much more feasible than the worn out and shabby diesel-based oil mud in the Drilling Industry.

Keywords: economical feasible, ecological feasible, emulsion stability, nettle spurge oil, rheological properties, soxhlet extraction method

Procedia PDF Downloads 193
3305 The Impact of Geopolitical Risks and the Oil Price Fluctuations on the Kuwaiti Financial Market

Authors: Layal Mansour

Abstract:

The aim of this paper is to identify whether oil price volatility or geopolitical risks can predict future financial stress periods or economic recessions in Kuwait. We construct the first Financial Stress Index for Kuwait (FSIK) that includes informative vulnerable indicators of the main financial sectors: the banking sector, the equities market, and the foreign exchange market. The study covers the period from 2000 to 2020, so it includes the two recent most devastating world economic crises with oil price fluctuation: the Covid-19 pandemic crisis and Ukraine-Russia War. All data are taken by the central bank of Kuwait, the World Bank, IMF, DataStream, and from Federal Reserve System St Louis. The variables are computed as the percentage growth rate, then standardized and aggregated into one index using the variance equal weights method, the most frequently used in the literature. The graphical FSIK analysis provides detailed information (by dates) to policymakers on how internal financial stability depends on internal policy and events such as government elections or resignation. It also shows how monetary authorities or internal policymakers’ decisions to relieve personal loans or increase/decrease the public budget trigger internal financial instability. The empirical analysis under vector autoregression (VAR) models shows the dynamic causal relationship between the oil price fluctuation and the Kuwaiti economy, which relies heavily on the oil price. Similarly, using vector autoregression (VAR) models to assess the impact of the global geopolitical risks on Kuwaiti financial stability, results reveal whether Kuwait is confronted with or sheltered from geopolitical risks. The Financial Stress Index serves as a guide for macroprudential regulators in order to understand the weakness of the overall Kuwaiti financial market and economy regardless of the Kuwaiti dinar strength and exchange rate stability. It helps policymakers predict future stress periods and, thus, address alternative cushions to confront future possible financial threats.

Keywords: Kuwait, financial stress index, causality test, VAR, oil price, geopolitical risks

Procedia PDF Downloads 73
3304 Breast Cancer Risk Factors: A Big Data Analysis of Black and White Women in the USA

Authors: Tejasvi Parupudi, Mochen Li, Lakshya Mittal, Ignacio G. Camarillo, Raji Sundararajan

Abstract:

With breast cancer becoming a global pandemic, it is very important to assess a woman’s risk profile accurately in a timely manner. Providing an estimate of the risk of developing breast cancer to a woman gives her an opportunity to consider options to decrease this risk. Women at low risk may be suggested yearly screenings whereas women with a high risk of developing breast cancer would be candidates for aggressive surveillance. Fortunately, there is a set of risk factors that are used to predict the probability of a woman being diagnosed with breast cancer in the future. Studying risk factors and understanding how they correlate to cancer is important for early diagnosis, prevention and reducing mortality rates. The effect of crucial risk factors among black and white women was compared in this study. The various risk factors analyzed include breast density, age, cancer in a first-degree relative, menopausal status, body mass index (BMI) and prior breast cancer diagnosis, etc. Breast density, age at first full-term birth and BMI were utilized in this study as important risk factors for the comparison of incidence rates between women of black and white races in the USA. Understanding the differences could lead to the development of solutions to reduce disparity in mortality rates among black women by improving overall access to care.

Keywords: big data, breast cancer, risk factors, incidence rates, mortality, race

Procedia PDF Downloads 268
3303 Monitoring Systemic Risk in the Hedge Fund Sector

Authors: Frank Hespeler, Giuseppe Loiacono

Abstract:

We propose measures for systemic risk generated through intra-sectorial interdependencies in the hedge fund sector. These measures are based on variations in the average cross-effects of funds showing significant interdependency between their individual returns and the moments of the sector’s return distribution. The proposed measures display a high ability to identify periods of financial distress, are robust to modifications in the underlying econometric model and are consistent with intuitive interpretation of the results.

Keywords: hedge funds, systemic risk, vector autoregressive model, risk monitoring

Procedia PDF Downloads 311
3302 Molecular Characterisation and Expression of Glutathione S-Transferase of Fasciola Gigantica

Authors: J. Adeppa, S. Samanta, O. K. Raina

Abstract:

Fasciolosis is a widespread economically important parasitic infection throughout the world caused by Fasciola hepatica and F. gigantica. In order to identify novel immunogen conferring significant protection against fasciolosis, currently, research has been focused on the defined antigens viz. glutathione S-transferase, fatty acid binding protein, cathepsin-L, fluke hemoglobin, paramyosin, myosin and F. hepatica- Kunitz Type Molecule. Among various antigens, GST which plays a crucial role in detoxification processes, i.e. phase II defense mechanism of this parasite, has a unique position as a novel vaccine candidate and a drug target in the control of this disease. For producing the antigens in large quantities and their purification to complete homogeneity, the recombinant DNA technology has become an important tool to achieve this milestone. RT- PCR was carried out using F. gigantica total RNA as template, and an amplicon of 657 bp GST gene was obtained. TA cloning vector was used for cloning of this gene, and the presence of insert was confirmed by blue-white selection for recombinant colonies. Sequence analysis of the present isolate showed 99.1% sequence homology with the published sequence of the F. gigantica GST gene of cattle origin (accession no. AF112657), with six nucleotide changes at 72, 74, 423, 513, 549 and 627th bp found in the present isolate, causing an overall change of 4 amino acids. The 657 bp GST gene was cloned at BamH1 and HindIII restriction sites of the prokaryotic expression vector pPROEXHTb in frame with six histidine residues and expressed in E. coli DH5α. Recombinant protein was purified from the bacterial lysate under non-denaturing conditions by the process of sonication after lysozyme treatment and subjecting the soluble fraction of the bacterial lysate to Ni-NTA affinity chromatography. Western blotting with rabbit hyper-immune serum showed immuno-reactivity with 25 kDa recombinant GST. Recombinant protein detected F. gigantica experimental as well as field infection in buffaloes by dot-ELISA. However, cross-reactivity studies on Fasciola gigantica GST antigen are needed to evaluate the utility of this protein in the serodiagnosis of fasciolosis.

Keywords: fasciola gigantic, fasciola hepatica, GST, RT- PCR

Procedia PDF Downloads 174
3301 Soil Properties and Yam Performance as Influenced by Poultry Manure and Tillage on an Alfisol in Southwestern Nigeria

Authors: E. O. Adeleye

Abstract:

Field experiments were conducted to investigate the effect of soil tillage techniques and poultry manure application on the soil properties and yam (Dioscorea rotundata) performance in Ondo, southwestern Nigeria for two farming seasons. Five soil tillage techniques, namely ploughing (P), ploughing plus harrowing (PH), manual ridging (MR), manual heaping (MH) and zero-tillage (ZT) each combined with and without poultry manure at the rate of 10 tha-1 were investigated. Data were obtained on soil properties, nutrient uptake, growth and yield of yam. Soil moisture content, bulk density, total porosity and post harvest soil chemical characteristics were significantly (p>0.05) influenced by soil tillage-manure treatments. Addition of poultry manure to the tillage techniques in the study increased soil total porosity, soil moisture content and reduced soil bulk density. Poultry manure improved soil organic matter, total nitrogen, available phosphorous, exchangeable Ca, k, leaf nutrients content of yam, yam growth and tuber yield relative to tillage techniques plots without poultry manure application. It is concluded that the possible deleterious effect of tillage on soil properties, growth and yield of yam on an alfisol in southwestern Nigeria can be reduced by combining tillage with poultry manure.

Keywords: poultry manure, tillage, soil chemical properties, yield

Procedia PDF Downloads 435
3300 Risk of Cardiovascular Diseases: Evaluation of Serum Lipid Profiles in Urban and Rural Population of Sindh

Authors: Mohsin Ali Baloch, Saira Baloch

Abstract:

Objective: The aim of this study was to evaluate the levels of serum lipid profiles in Urban and Rural Population of Sindh, to indicate the existing risk of cardiovascular diseases. Material and Methods: Study was conducted at Liaquat University of Medical & Health Sciences, in the cities of Jamshoro and Hyderabad of Sindh. Blood samples from 300 healthy individuals were collected in fasting condition, out them 100 were from rural population, 100 were urban while 100 were used as control group. The biochemistry of these samples was obtained by the analysis of total Cholesterol, high density lipoprotein Cholesterol (HDL), low-density lipoprotein Cholesterol (LDL) and Triglycerides using kit method on Analyzer Clinical Chemistry. Results and Conclusion: Serum levels of total cholesterol, Triglycerides, and LDL cholesterol were significantly raised in the rural and urban males, whereas HDL cholesterol was decreased as compared to the Healthy controls that indicated significant risk of CVD. Urban population was with more risk of CVD and male gender in both groups was at more risk. The worst lipid profile in gender wise distribution was observed in male gender of urban population with highest Total Cholesterol/HDL Ratio while female gender also shown moderate risk of CVD with highest LDL/HDL Ratio.

Keywords: cardiovascular diseases, lipid profiles, urban and rural population, LDL/HDL Ratio

Procedia PDF Downloads 397
3299 The Reproducibility and Repeatability of Modified Likelihood Ratio for Forensics Handwriting Examination

Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

Abstract:

The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: confidence interval, handwriting, kernel density estimator, KDE, logistic regression LoR, repeatability, reproducibility

Procedia PDF Downloads 110
3298 Development and Validation of a Coronary Heart Disease Risk Score in Indian Type 2 Diabetes Mellitus Patients

Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

Abstract:

Diabetes in India is growing at an alarming rate and the complications caused by it need to be controlled. Coronary heart disease (CHD) is one of the complications that will be discussed for prediction in this study. India has the second most number of diabetes patients in the world. To the best of our knowledge, there is no CHD risk score for Indian type 2 diabetes patients. Any form of CHD has been taken as the event of interest. A sample of 750 was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of CHD. Predictive risk scores of CHD events are designed by cox proportional hazard regression. Model calibration and discrimination is assessed from Hosmer Lemeshow and area under receiver operating characteristic (ROC) curve. Overfitting and underfitting of the model is checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Youden’s index is used to choose the optimal cut off point from the scores. Five year probability of CHD is predicted by both survival function and Markov chain two state model and the better technique is concluded. The risk scores for CHD developed can be calculated by doctors and patients for self-control of diabetes. Furthermore, the five-year probabilities can be implemented as well to forecast and maintain the condition of patients.

Keywords: coronary heart disease, cox proportional hazard regression, ROC curve, type 2 diabetes Mellitus

Procedia PDF Downloads 211