Search results for: camera type weft straightener

Authors: Boma Nellie S, Nambiar Ritu, K. Kanchanmala, T. Rashida, Israell Imelda, Moul Khusnud, Michael Marina

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Gestational diabetes (GDM) imparts an increased life long risk of developing Type 2 Diabetes Mellitus (T2DM) and cardiovascular disease in women. Once diagnosed with GDM women have up to 74% increased cumulative risk developing T2DM in 10-15 years. Identifying women at increased risk of developing T2DM and offering them pharmacological and lifestyle management interventions will delay or eliminate the development of diabetes in this population. While ADA recommends that all gestational diabetics be offered postnatal screening, worldwide the screening rates from 35-75% and Al Rahba Hospital with a robust universal antenatal screening program for GDM was at a dismal 9% in 2011. A multidisciplinary team was put together involving OB/Gyn Physicians, Midwives, Nurses (ward and OPD) Diabetic Educators, Dietitians, Medical Records, Laboratory & IT with the implementation of multiple strategies to increase the uptake of postpartum screening of the gestational diabetic.

Keywords: GDM, postnatal screening, preventing type 2 diabetes, lifestyle management

Procedia PDF Downloads 521

Authors: Dianis Wulan Sari, Takeo Minematsu, Mikako Yoshida, Hiromi Sanada

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Introduction: Pruritus is diagnosed as itching without macroscopic abnormalities on skin. It is the most skin complaint of elderly people. In the present study, we conducted a dermatological study to examine the risk factors of pruritic skin and predicted how to prevent pruritus especially in the elderly population. Pruritus is caused several types of inflammation, including epidermal innate immunity based on keratinocyte responses and acquired immunity regulated by type 1 or 2 helper T (Th) cells. The triggers of pruritus differ among inflammation types, therefore we did separately assess the pruritus-associated factors of each inflammation type in an effort to contribute to the identification of intervention targets for preventing pruritus. Therefore, this study aimed to investigate the factors related with actual condition of pruritic skin by examine the skin properties. Method: This study was conducted in elderly population of Indonesian nursing home. Basic characteristics and behaviors were obtained by interview. The properties of pruritic skin were collected by examination of skin biomarker using skin blotting as novel method of non-invasive skin assessment method and examination of skin barrier function using stratum corneum hydration and skin pH. Result: The average age of participants was 74 years with independent status was 66.8%. Age (β = -0.130, p = 0.044), cumulative lifetime sun exposure (β = 0.145, p = 0.026), bathing duration (β = 0.151, p = 0.022), clothing change frequency (β = 0.135, p = 0.029), and clothing type (β = -0.139, p = 0.021) were risk factors of pruritic skin in multivariate analysis. Conclusion: Risk factors of pruritic skin in elderly population were caused by internal factors such as skin senescence and external factors such as sun exposure, hygiene care and skin care behavior.

Keywords: aging, hygiene care, pruritus, skin care, sun exposure

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Authors: L. Musak, J. Valachova, T. Vasicko, O. Osina

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Introduction: Stainless steel is resistant to electrochemical corrosion by passivation. Welders are greatly exposed to welding fumes of toxic metals, which added to this steel. The content of chromium (Cr) in steel was above 11.5%, Ni and Mo from 2 to 6.5%. The aim of the study was the evaluation of occupational exposure to Cr, chromosome analysis and valuation of individual susceptibility polymorphism of gene CCND1 c.870 G>A. Materials and Methods: The exposed group was consisted from 117 welders of stainless steels. The average age was 38.43 years and average exposure time 7.14 years. Smokers represented 40.17%. The control group consisted of 123 non-exposed workers with an average age of 39.74 years and time employment 16.67 years. Smokers accounted for 22.76%. Analysis of Cr in blood and urine was performed by atomic absorption spectrophotometry (AAS Varian SpectraAA 30P) with electrothermal decomposition of the sample in the graphite furnace. For the evaluation of chromosomal aberrations (CA) was used cytogenetic analysis of peripheral blood lymphocytes, gene polymorphism was determined by PCR-RFLP reaction using appropriate primers and restriction enzymes. For statistical analysis was used the Mann-Whitney U-test. Results: The mean Cr level in exposed group was 0.095 mmol/l (0.019 min-max 0.504). No value does exceed the average normal value. The average value Cr in urine was 7.9 mmol/mol creatinine (min 0.026 to max 19.26). The total number of CA was 1.86% in compared to 1.70% controls. (CTA-type 0.90% vs 0.80% and CSA-type 0.96% vs 0.90%). In the number of total CA was observed statistical difference between smokers and non-smokers of exposed group (S-1.57% vs. NS-2.04%, P<0.05). In CCND1 gene polymorphisms was observed the increasing of the total CA with wild-type allele (WT) via heterozygous to the VAR genotype (1.44%<1.82%<2.13%). There was observed a statistically higher incidence of CTA-type aberrations in variant genotypes between exposed and control groups (1.22% vs. 0.59%, P<0.05). Discussion and conclusions: The work place is usually higher source of exposure to harmful factors. Workers need consistently and checked frequently health control. In assessing the risk of adverse effects of metals is important to consider their persistence, behavior and bioavailability. Prolonged exposure to carcinogens may not manifest symptoms of poisoning, but delayed effects may occur, which resulted in a higher incidence of malignant tumors.

Keywords: genotoxicity, chromium, stainless steels, welders

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Authors: H. Barati, M. Wu, A. Kharicha, A. Ludwig

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A transient model for nozzle clogging has been developed and successfully validated against a laboratory experiment. Key steps of clogging are considered: transport of particles by turbulent flow towards the nozzle wall; interactions between fluid flow and nozzle wall, and the adhesion of the particle on the wall; the growth of the clog layer and its interaction with the flow. The current paper is to investigate the mesh (size and type) sensitivity of the model in both two and three dimensions. It is found that the algorithm for clog growth alone excluding the flow effect is insensitive to the mesh type and size, but the calculation including flow becomes sensitive to the mesh quality. The use of 2D meshes leads to overestimation of the clog growth because the 3D nature of flow in the boundary layer cannot be properly solved by 2D calculation. 3D simulation with tetrahedron mesh can also lead to an error estimation of the clog growth. A mesh-independent result can be achieved with hexahedral mesh, or at least with triangular prism (inflation layer) for near-wall regions.

Keywords: clogging, continuous casting, inclusion, simulation, submerged entry nozzle

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Authors: Taru Singh, Shukla Das, V. G. Ramachandran

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Objectives: To develop SYBR green based real-time PCR assay to detect carbapenemases (NDM, IMP) genes in E. coli. Methods: A total of 40 E. coli from stool samples were tested. Six were previously characterized as resistant to carbapenems and documented by PCR. The remaining 34 isolates previously tested susceptible to carbapenems and were negative for these genes. Bacterial RNA was extracted using manual method. The real-time PCR was performed using the Light Cycler III 480 instrument (Roche) and specific primers for each carbapenemase target were used. Results: Each one of the two carbapenemase gene tested presented a different melting curve after PCR amplification. The melting temperature (Tm) analysis of the amplicons identified was as follows: blaIMP type (Tm 82.18°C), blaNDM-1 (Tm 78.8°C). No amplification was detected among the negative samples. The results showed 100% concordance with the genotypes previously identified. Conclusions: The new assay was able to detect the presence of two different carbapenemase gene type by real-time PCR.

Keywords: resistance, b-lactamases, E. coli, real-time PCR

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

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Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Marco Avila Lopez, Hasnae Ait-Douchi, Silvia De Los Santos, Badr Eddine Lebrouhi, Pamela Ramírez Vidal

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In the context of the energy transition, fuel cell technology has emerged as a solution for harnessing hydrogen energy and mitigating greenhouse gas emissions. An in-depth study was conducted on a PEMFC-type fuel cell, with an initiation of an analysis of its operational principles and constituent components. Subsequently, the modelling of the fuel cell was undertaken using the Python programming language, encompassing both steady-state and transient regimes. In the case of the steady-state regime, the physical and electrochemical phenomena occurring within the fuel cell were modelled, with the assumption of uniform temperature throughout all cell compartments. Parametric identification was carried out, resulting in a remarkable mean error of only 1.62% when the model results were compared to experimental data documented in the literature. The dynamic model that was developed enabled the scrutiny of the fuel cell's response in terms of temperature and voltage under varying current conditions.

Keywords: fuel cell, modelling, dynamic, thermal model, PEMFC

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Authors: Chaoyan Huang, Hongxia Zheng

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For deep space exploration and long duration interplanetary manned missions, protection of astronauts from cosmic radiation is an unavoidable problem. However, passive shielding can be little effective for protecting particles which energies are greater than 1GeV/nucleon. In this study, active magnetic protection method is adopted. Taking into account the structure and size of the end-cap, eight shielding magnetic field configurations are designed based on the Hoffman configuration. The shielding effect of shielding magnetic field structure, intensity B and thickness L on H particles with 2GeV energy is compared by test particle simulation. The result shows that the shielding effect is better with the linear type magnetic field structure in the end-cap region. Furthermore, two magnetic field configurations with better shielding effect are investigated through H and He galactic cosmic spectra. And the shielding effect of the linear type configuration adopted in the barrel and end-cap regions is best.

Keywords: galactic cosmic rays, active protection, shielding magnetic field configuration, shielding effect

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Authors: Mokhtar Nikgoo

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Definition of bridge: A bridge is a structure that allows people to pass through the communication road with two points. There are many different types of bridges, each of which is designed to perform a specific function. This article introduces the concept, history, components, uses, types, construction methods, selected factors, damage factors and principles of bridge maintenance. A bridge is a structure to cross a passage such as a water, valley or road without blocking another path underneath. This structure makes it possible to pass obstacles that are difficult or impossible to pass. There are different designs for bridge construction, each of which is used for a particular function and condition. In the old definition, a bridge is an arch over a river, valley, or any type of passage that makes traffic possible. But today, in the topic of urban management, the bridge is considered as a structure to cross physical barriers, so that while using space (not just the surface of the earth), it can facilitate the passage and access to places. The useful life of bridges may be between 30 and 80 years depending on the location and the materials used. But with proper maintenance and improvement, their life may last for hundreds of years.

Keywords: bridge, road construction, surveying, transportation

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Authors: Janusz Bedkowski, Grzegorz Kisala, Michal Wlasiuk, Piotr Pokorski

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Ground-truth data is essential for VO (Visual Odometry) and SLAM (Simultaneous Localization and Mapping) quantitative evaluation using e.g. ATE (Absolute Trajectory Error) and RPE (Relative Pose Error). Many open-access data sets provide raw and ground-truth data for benchmark purposes. The issue appears when one would like to validate Visual Odometry and/or SLAM approaches on data captured using the device for which the algorithm is targeted for example mobile phone and disseminate data for other researchers. For this reason, we propose an open source, open hardware groundtruth system that provides an accurate and precise trajectory with a 3D point cloud. It is based on LiDAR Livox Mid-360 with a non-repetitive scanning pattern, on-board Raspberry Pi 4B computer, battery and software for off-line calculations (camera to LiDAR calibration, LiDAR odometry, SLAM, georeferencing). We show how this system can be used for the evaluation of various the state of the art algorithms (Stella SLAM, ORB SLAM3, DSO) in typical indoor monocular VO/SLAM.

Keywords: SLAM, ground truth, navigation, LiDAR, visual odometry, mapping

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Authors: Zaki Ahmad Khan, Jamshed Siddiqui, Abdus Samad

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The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear type of architectures as well as cube based architectures. Two standard dynamic scheduling schemes namely Minimum Distance Scheduling (MDS) and Two Round Scheduling (TRS) schemes are implemented on the LCQ network. Parallel tasks are mapped and the imbalance of load is evaluated on different set of processors in LCQ network. The simulations results are evaluated and effort is made by means of through analysis of the results to obtain the best solution for the given network in term of load imbalance left and execution time. The other performance matrices like speedup and efficiency are also evaluated with the given dynamic algorithms.

Keywords: dynamic algorithm, load imbalance, mapping, task scheduling

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Authors: Reza Bahboodian

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One of the most important factors in the use of construction machinery is the fuel consumption cost of this equipment. The use of diesel engines in off-road vehicles is an important source of nitrogen oxides and particulate matter. Emissions of nitrogen oxides and particulate matter 10 in off-road vehicles (construction and mining) may be high. Due to the high cost of fuel, it is necessary to minimize fuel consumption. Factors affecting the fuel consumption of these cars are very diverse. Climate changes such as changes in pressure, temperature, humidity, fuel type selection, type of gearbox used in the car are effective in fuel consumption and pollution, and engine efficiency. In this paper, methods for reducing fuel consumption and pollutants by considering valid European and European standards are examined based on new methods such as hybridization, optimal gear change, adding hydrogen to diesel fuel, determining optimal working fluids, and using oxidation catalysts.

Keywords: improve fuel consumption, construction machinery, pollutant reduction, determining the optimal working cycle

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Authors: Ghada S. Moussa

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With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management. This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: appearance attributes, geometric attributes, support vector machine, vehicle classification

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Authors: Neil Erick Q. Madariaga, Noel B. Linsangan

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Body Mass Index (BMI) is one of the different ways to monitor the health of a person. It is based on the height and weight of the person. This study aims to compute for the BMI using an Android tablet by obtaining the height of the person by using a camera and measuring the weight of the person by using a weighing scale or load cell. The height of the person was estimated by applying background subtraction to the image captured and applying different processes such as getting the vanishing point and applying Artificial Neural Network. The weight was measured by using Wheatstone bridge load cell configuration and sending the value to the computer by using Gizduino microcontroller and Bluetooth technology after the amplification using AD620 instrumentation amplifier. The application will process the images and read the measured values and show the BMI of the person. The study met all the objectives needed and further studies will be needed to improve the design project.

Keywords: body mass index, artificial neural network, vanishing point, bluetooth, wheatstone bridge load cell

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Authors: William Elnemer, Nauman Hussain, Samir Al-Ali, Henry Shu, Diane Ghanem, Babar Shafiq

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Introduction: The incidence of infection in open tibial shaft injuries varies depending on the severity of the injury, with rates ranging from 1.8% for Gustilo-Anderson type I to 42.9% for type IIIB fractures. The timely administration of antibiotics upon presentation to the emergency department (ED) is an essential component of fracture management, and evidence indicates that prompt delivery of antibiotics is associated with improved outcomes. The objective of this study is to identify factors that contribute to the expedient administration of antibiotics. Methods: This is a retrospective study of open tibial shaft fractures at an academic Level I trauma center. Current Procedural Terminology (CPT) codes identified all patients treated for open tibial shaft fractures between 2015 and 2021. Open fractures were identified by reviewing ED and provider notes, and with ballistic fractures were considered open. Chart reviews were performed to extract demographics, fracture characteristics, postoperative outcomes, time to operative room, time to antibiotic order, and delivery. Univariate statistical analysis compared patients who received early antibiotics (EA), which were delivered within one hour of ED presentation, and those who received late antibiotics (LA), which were delivered outside of one hour of ED presentation. A multivariate analysis was performed to investigate patient, fracture, and transport/ED characteristics contributing to faster delivery of antibiotics. The multivariate analysis included the dependent variables: ballistic fracture, activation of Delta Trauma, Gustilo-Andersen (Type III vs. Type I and II), AO-OTA Classification (Type C vs. Type A and B), arrival between 7 am and 11 pm, and arrival via Emergency Medical Services (EMS) or walk-in. Results: Seventy ED patients with open tibial shaft fractures were identified. Of these, 39 patients (55.7%) received EA, while 31 patients (44.3%) received LA. Univariate analysis shows that the arrival via EMS as opposed to walk-in (97.4% vs. 74.2%, respectively, p = 0.01) and activation of Delta Trauma (89.7% vs. 51.6%, respectively, p < 0.001) was significantly higher in the EA group vs. the LA group. Additionally, EA cases had significantly shorter intervals between the antibiotic order and delivery when compared to LA cases (0.02 hours vs. 0.35 hours, p = 0.007). No other significant differences were found in terms of postoperative outcomes or fracture characteristics. Multivariate analysis shows that a Delta Trauma Response, arrival via EMS, and presentation between 7 am and 11 pm were independent predictors of a shorter time to antibiotic administration (Odds Ratio = 11.9, 30.7, and 5.4, p = 0.001, 0.016, and 0.013, respectively). Discussion: Earlier antibiotic delivery is associated with arrival to the ED between 7 am and 11 pm, arrival via EMS, and a coordinated Delta Trauma activation. Our findings indicate that in cases where administering antibiotics is critical to achieving positive outcomes, it is advisable to employ a coordinated Delta Trauma response. Hospital personnel should be attentive to the rapid administration of antibiotics to patients with open fractures who arrive via walk-in or during late-night hours.

Keywords: antibiotics, emergency department, fracture management, open tibial shaft fractures, orthopaedic surgery, time to or, trauma fractures

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Authors: I. Ramalho, S. Campos, M. Dias

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Introduction: Endometriosis may play a role in the pathogenesis of ovarian cancer (OC), however, the risk and prognosis have not been well established. The association between these two pathologies could have an important impact on prevention and early diagnosis of OC. Objective: To analyze the prevalence of endometriosis associated ovarian cancer and related clinical, epidemiological and histopathological issues. Design: We conducted a retrospective case series analysis of patients diagnosed with endometriosis and ovarian cancer in the Gynecology Department of Coimbra University Hospital Center since 2006 to 2015. Methods: We collected data from women diagnosed with ovarian cancer, with anatomopathology records reporting findings of endometriosis in ovarian cancer patients. Patients were retrieved from the pathological records and appropriate medical records were retrospectively reviewed. Statistical analysis was performed using SPSS 22.0. Results: Histological evidence of endometriosis was found in 17 out of 261 patients diagnosed with ovarian cancer (OC) (6.51%). The most usual symptoms were pelvic pain, abdominal distension, asthenia, ascites, weight loss and nausea. Mean age at diagnosis was 61.2 ± 15.1, 41-86 years old, 33.3% were pre-menopausal patients and cancer stage distribution was predominantly stage I (31.3%) and stage III (56.3%). OC occurred unilaterally in 14 patients and 2 patients were diagnosed with a synchronous ovarian and endometrial cancer. Regarding histological type, 10 OC were classified as clear cell carcinoma (CCC), 4 endometrioid carcinomas (EC) and 3 mixed type (clear cell and endometrioid). Four ovarian carcinomas presumably arose from endometriomas: 3 CCC and 1 EC. Conclusions: In accordance with previous studies, clear cell was the most common pathological type in endometriotic patients, followed by endometrioid carcinomas, and two rare synchronous ovarian and endometrial carcinomas were registered. Although endometriosis association to OC is uncommon, endometriosis should be managed with special care in order to early diagnosis.

Keywords: endometriosis, histology, observational study, ovarian cancer

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Authors: K. Badron, A. F. Ismail, A. L. Asnawi, N. F. A. Malik, S. Z. Abidin, S. Dzulkifly

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The occurrences of precipitation, also commonly referred as rain, in the form of "convective" and "stratiform" have been identified to exist worldwide. In this study, the radar return echoes or known as reflectivity values acquired from radar scans have been exploited in the process of classifying the type of rain endured. The investigation use radar data from Malaysian Meteorology Department (MMD). It is possible to discriminate the types of rain experienced in tropical region by observing the vertical characteristics of the rain structure. .Heavy rain in tropical region profoundly affects radiowave signals, causing transmission interference and signal fading. Required wireless system fade margin depends on the type of rain. Information relating to the two mentioned types of rain is critical for the system engineers and researchers in their endeavour to improve the reliability of communication links. This paper highlights the quantification of percentage occurrences over one year period in 2009.

Keywords: stratiform, convective, tropical region, attenuation radar reflectivity

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Authors: Chien-Wan Hun, Shao-Fu Chang, Chien-Chon Chen, Ker-Jer Huang

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This study presents how to use a high-efficiency process for producing cesium iodide (CsI) crystal columns by rapid heating method. In the past, the heating rate of the resistance wire heating furnace was relatively slow and excessive iodine and CsI vapors were therefore generated during heating. Because much iodine and CsI vapors are produced during heating process, the composition of CsI crystal columns is not correct. In order to enhance the heating rate, making CsI material in the heating process can quickly reach the melting point temperature. This study replaced the traditional type of external resistance heating furnace with halogen-type quartz heater, and then, CsI material can quickly reach the melting point. Eventually, CsI melt can solidify in the anodic aluminum template forming CsI crystal columns.

Keywords: cesium iodide, high efficiency, vapor, rapid heating, crystal column

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Authors: Lei Zhang, Tingting Xu, Jun He, Zhenyu Yan

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Email marketing is one of the most important segments of online marketing. It has been proved to be the most effective way to acquire and retain customers. The email content is vital to customers. Different customers may have different familiarity with a product, so a successful marketing strategy must personalize email content based on individual customers’ product affinity. In this study, we build our personalized email marketing strategy with three types of emails: nurture, promotion, and conversion. Each type of email has a different influence on customers. We investigate this difference by analyzing customers’ open rates, click rates and opt-out rates. Feature importance from response models is also analyzed. The goal of the marketing strategy is to improve the click rate on conversion-type emails. To build the personalized strategy, we formulate the problem as a reinforcement learning problem and adopt a Q-learning algorithm with variations. The simulation results show that our model-based strategy outperforms the current marketer’s strategy.

Keywords: email marketing, email content, reinforcement learning, machine learning, Q-learning

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Authors: Lluís Bermúdez, Isabel Morillo

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Road safety involves carrying out a determined and explicit policy to reduce accidents. In the city of Barcelona, through the Local Road Safety Plan 2013-2018, in line with the framework that has been established at the European and state level, a series of preventive, corrective and technical measures are specified, with the priority objective of reducing the number of serious injuries and fatalities. In this work, based on the data from the accidents managed by the local police during the period 2010-2019, an analysis is carried out to verify whether the measures established in the Plan to reduce the accident rate have had an effect or not and to what extent. The analysis focuses on the type of accident and the type of vehicles involved. Different count regression models have been fitted, from which it can be deduced that the number of serious and fatal victims of the accidents that have occurred in the city of Barcelona has been reduced as the measures approved by the authorities.

Keywords: accident reduction, count regression models, road safety, urban traffic

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Authors: Parminder Kaur, Chandrajit B. Majumder

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The unrestrained usage of pesticides to meet the burgeoning demand of enhanced crop productivity has led to the serious contamination of both terrestrial and aquatic ecosystem. The remediation of mixture of pesticides is a challenging affair regarding inadvertent mixture of pesticides from agricultural lands treated with various compounds. Global concerns about the excessive use of pesticides have driven the need to develop more effective and safer alternatives for their remediation. We focused our work on the microbial degradation of a mixture of three Type II-pyrethroids, namely Cypermethrin, Cyhalothrin and Deltamethrin commonly applied for both agricultural and domestic purposes. The fungal strains (Fusarium strain 8-11P and Fusarium sp. zzz1124) had previously been isolated from agricultural soils and their ability to biotransform this amalgam was studied. In brief, the experiment was conducted in two growth systems (added carbon and carbon-free) enriched with variable concentrations of pyrethroids between 100 to 300 mgL⁻¹. Parameter optimization (pH, temperature, concentration and time) was done using a central composite design matrix of Response Surface Methodology (RSM). At concentrations below 200 mgL⁻¹, complete removal was observed; however, degradation of 95.6%/97.4 and 92.27%/95.65% (in carbon-free/added carbon) was observed for 250 and 300 mgL⁻¹ respectively. The consortium has been shown to degrade the pyrethroid mixture (300 mg L⁻¹) within 120 h. After 5 day incubation, the residual pyrethroids concentration in unsterilized soil were much lower than in sterilized soil, indicating that microbial degradation predominates in pyrethroids elimination with the half-life (t₁/₂) of 1.6 d and R² ranging from 0.992-0.999. Overall, these results showed that microbial consortia might be more efficient than single degrader strains. The findings will complement our current understanding of the bioremediation of mixture of Type II pyrethroids with microbial consortia and potentially heighten the importance for considering bioremediation as an effective alternative for the remediation of such pollutants.

Keywords: bioremediation, fungi, pyrethroids, soil

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Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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Authors: Edwin Foo, Woei Wen, Lui, Meijun Zhao, Shigeru Kuchii, Chin Sai Wong, Chung Sern Goh, Yi Hao He

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This presentation presents an elderly care and assistive social robot development work. We named this robot JOS and he is restricted to table top operation. JOS is designed to have a maximum volume of 3600 cm3 with its base restricted to 250 mm and his mission is to provide companion, assist and help the elderly. In order for JOS to accomplish his mission, he will be equipped with perception, reaction and cognition capability. His appearance will be not human like but more towards cute and approachable type. JOS will also be designed to be neutral gender. However, the robot will still have eyes, eyelid and a mouth. For his eyes and eyelids, they will be built entirely with Robotis Dynamixel AX18 motor. To realize this complex task, JOS will be also be equipped with micro-phone array, vision camera and Intel i5 NUC computer and a powered by a 12 V lithium battery that will be self-charging. His face is constructed using 1 motor each for the eyelid, 2 motors for the eyeballs, 3 motors for the neck mechanism and 1 motor for the lips movement. The vision senor will be house on JOS forehead and the microphone array will be somewhere below the mouth. For the vision system, Omron latest OKAO vision sensor is used. It is a compact and versatile sensor that is only 60mm by 40mm in size and operates with only 5V supply. In addition, OKAO vision sensor is capable of identifying the user and recognizing the expression of the user. With these functions, JOS is able to track and identify the user. If he cannot recognize the user, JOS will ask the user if he would want him to remember the user. If yes, JOS will store the user information together with the capture face image into a database. This will allow JOS to recognize the user the next time the user is with JOS. In addition, JOS is also able to interpret the mood of the user through the facial expression of the user. This will allow the robot to understand the user mood and behavior and react according. Machine learning will be later incorporated to learn the behavior of the user so as to understand the mood of the user and requirement better. For the speech system, Microsoft speech and grammar engine is used for the speech recognition. In order to use the speech engine, we need to build up a speech grammar database that captures the commonly used words by the elderly. This database is built from research journals and literature on elderly speech and also interviewing elderly what do they want to robot to assist them with. Using the result from the interview and research from journal, we are able to derive a set of common words the elderly frequently used to request for the help. It is from this set that we build up our grammar database. In situation where there is more than one person near JOS, he is able to identify the person who is talking to him through an in-house developed microphone array structure. In order to make the robot more interacting, we have also included the capability for the robot to express his emotion to the user through the facial expressions by changing the position and movement of the eyelids and mouth. All robot emotions will be in response to the user mood and request. Lastly, we are expecting to complete this phase of project and test it with elderly and also delirium patient by Feb 2015.

Keywords: social robot, vision, elderly care, machine learning

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Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin

Abstract:

We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.

Keywords: human action recognition, pose estimation, D-CNN, deep learning

Procedia PDF Downloads 146

Authors: Pajaree Donkhampa, Fuangfa Unob

Abstract:

Ceftazidime is an antibiotic drug commonly used to treat several human and veterinary infections. However, the presence of ceftazidime residues in the environment may induce microbial resistance and cause side effects to humans. Therefore, monitoring the level of ceftazidime in environmental resources is important. In this work, a melamine foam platform was proposed for simultaneous extraction and colorimetric detection of ceftazidime based on the azo dye formation on the surface. The melamine foam was chemically modified with polyethyleneimine (PEI) and characterized by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). Ceftazidime is a sample that was extracted on the PEI-modified melamine foam and further reacted with nitrite in an acidic medium to form an intermediate diazonium ion. The diazotized molecule underwent an azo coupling reaction with chromotropic acid to generate a red-colored compound. The material color changed from pale yellow to pink depending on the ceftazidime concentration. The photo of the obtained material was taken by a smartphone camera and the color intensity was determined by Image J software. The material fabrication and ceftazidime extraction and detection procedures were optimized. The detection of a sub-ppm level of ceftazidime was achieved without using a complex analytical instrument.

Keywords: colorimetric detection, ceftazidime, melamine foam, extraction, azo dye

Procedia PDF Downloads 169

Authors: Djalal Hamed

Abstract:

The aim of this paper is to perform an analytic solution of steady state natural convection in a narrow rectangular channel between two vertical parallel MTR-type fuel plates, imposed under a cosine shape heat flux to determine the margin of the nuclear core power at which the natural convection cooling mode can ensure a safe core cooling, where the cladding temperature should not be reach the specific safety limits (90 °C). For this purpose, a simple computer program is developed to determine the principal parameter related to the nuclear core safety such as the temperature distribution in the fuel plate and in the coolant (light water) as a function of the reactor power. Our results are validated throughout a comparison against the results of another published work, which is considered like a reference of this study.

Keywords: buoyancy force, friction force, natural convection, thermal hydraulic analysis, vertical heated rectangular channel

Procedia PDF Downloads 316

Authors: Phanindra Prasad Thummala, Umran Tezcan Un

Abstract:

In this study, hydrodynamics analysis of two batch type electrocoagulation stirred tank reactors, used for the electrocoagulation treatment of Cr(VI) wastewater, was carried using computational fluid dynamics (CFD). The aim of the study was to evaluate the impact of mixing characteristics on overall performance of electrocoagulation reactor. The CFD simulations were performed using ANSYS FLUENT 14.4 software. The mixing performance of each reactor was evaluated by numerically modelling tracer dispersion in each reactor configuration. The uniformity in tracer dispersion was assumed when 90% of the ratio of the maximum to minimum concentration of the tracer was realized. In parallel, experimental evaluation of both the electrocoagulation reactors for removal of Cr(VI) from wastewater was also carried out. The results of CFD and experimental analysis clearly show that the reactor which can give higher uniformity in lesser time, will perform better as an electrocoagulation reactor for removal of Cr(VI) from wastewater.

Keywords: CFD, stirred tank reactors, electrocoagulation, Cr(VI) wastewater

Procedia PDF Downloads 462

Authors: Miguel A. Orellana, Sonia E. Ruiz, Juan Bojórquez

Abstract:

Optimal load factors (dead, live and seismic) used for the design of buildings may be different, depending of the seismic ground motion characteristics to which they are subjected, which are closely related to the type of soil conditions where the structures are located. The influence of the type of soil on those load factors, is analyzed in the present study. A methodology that is useful for establishing optimal load factors that minimize the cost over the life cycle of the structure is employed; and as a restriction, it is established that the probability of structural failure must be less than or equal to a prescribed value. The life-cycle cost model used here includes different types of costs. The optimization methodology is applied to two groups of reinforced concrete buildings. One set (consisting on 4-, 7-, and 10-story buildings) is located on firm ground (with a dominant period Ts=0.5 s) and the other (consisting on 6-, 12-, and 16-story buildings) on soft soil (Ts=1.5 s) of Mexico City. Each group of buildings is designed using different combinations of load factors. The statistics of the maximums inter-story drifts (associated with the structural capacity) are found by means of incremental dynamic analyses. The buildings located on firm zone are analyzed under the action of 10 strong seismic records, and those on soft zone, under 13 strong ground motions. All the motions correspond to seismic subduction events with magnitudes M=6.9. Then, the structural damage and the expected total costs, corresponding to each group of buildings, are estimated. It is concluded that the optimal load factors combination is different for the design of buildings located on firm ground than that for buildings located on soft soil.

Keywords: life-cycle cost, optimal load factors, reinforced concrete buildings, total costs, type of soil

Procedia PDF Downloads 306

Authors: Evgeny Pokushalov, Claire Garcia, Andrey Ponomarenko, John Smith, Michael Johnson, Inessa Pak, Evgenya Shrainer, Dmitry Kudlay, Leila Kasimova, Richard Miller

Abstract:

This study evaluated the efficacy of an AI-guided dietary supplement regimen compared to a standard physician-guided regimen in managing Type 2 diabetes (T2D). A total of 160 patients were randomly assigned to either the AI-guided group (n=80) or the physician-guided group (n=80) and followed over 90 days. The AI-guided group received 5.3 ± 1.2 supplements per patient, while the physician-guided group received 2.7 ± 0.6 supplements per patient. The AI system personalized supplement types and dosages based on individual genetic and metabolic profiles. The AI-guided group showed a significant reduction in HbA1c levels from 7.5 ± 0.8% to 7.1 ± 0.7%, compared to a reduction from 7.6 ± 0.9% to 7.4 ± 0.8% in the physician-guided group (mean difference: -0.3%, 95% CI: -0.5% to -0.1%; p < 0.01). Secondary outcomes, including fasting plasma glucose, HOMA-IR, and insulin levels, also improved more in the AI-guided group. Subgroup analyses revealed that the AI-guided regimen was particularly effective in patients with specific genetic polymorphisms and elevated metabolic markers. Safety profiles were comparable between both groups, with no serious adverse events reported. In conclusion, the AI-guided dietary supplement regimen significantly improved glycemic control and metabolic health in T2D patients compared to the standard physician-guided approach, demonstrating the potential of personalized AI-driven interventions in diabetes management.

Keywords: Type 2 diabetes, AI-guided supplementation, personalized medicine, glycemic control, metabolic health, genetic polymorphisms, dietary supplements, HbA1c, fasting plasma glucose, HOMA-IR, personalized nutrition

Procedia PDF Downloads 9