Search results for: ultra-low frequency waves

Authors: Ashok Sachdeva

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This research paper delves into the application of digital tools, especially Voyant Tools and AntConc version 4.0, for the analysis and interpretation of Seamus Heaney's poems. Scholars and literary aficionados can acquire deeper insights into Heaney's writings by utilising these tools, revealing hidden nuances and improving their knowledge. This paper outlines the methodology used, presents sample analyses and evaluates the merits and limitations of using digital tools in literary analysis. The combination of traditional close reading with digital analysis tools promises to offer new paths for understanding Heaney's vast tapestry of poetry. Seamus Heaney, a Nobel winner known for his vivid poetry, provides a treasure mine of literary discovery. The advent of digital tools gives an exciting opportunity to reveal previously unknown layers of meaning within his works. This paper investigates the use of Voyant Tools and AntConc version 4.0 to analyse and understand Heaney's writings, demonstrating the symbiotic relationship between traditional literary analysis and cutting-edge digital methodologies. Methodology: To demonstrate the efficiency of digital tools in the analysis of Heaney's poetry, a sample of his notable works will be entered into Voyant Tools and AntConc version 4.0. The former provides a graphic representation of word frequency, word clouds, and patterns over numerous poems. The latter, a concordance tool, enables detailed linguistic analysis, revealing patterns, and linguistic subtleties.

Keywords: digital tools, resonance, assonance, alliteration, creative quotient

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Authors: Emmanuel D. Buedi, K. O. Boateng, Griffith S. Klogo

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Electrical distribution networks are prone to power quality disturbances originating from the complexity of the distribution network, mode of distribution (overhead or underground) and types of loads used by customers. Data on the types of disturbances present and frequency of occurrence is needed for economic evaluation and hence finding solution to the problem. Utility companies have resorted to using secondary power quality devices such as smart meters to help gather the required data. Even though this approach is easier to adopt, data gathered from these devices may not serve the required purpose, since the installation of these devices in the electrical network usually does not conform to available PQM placement methods. This paper presents a design of a PQM that is capable of integrating into an existing DAS infrastructure to take advantage of available placement methodologies. The monitoring component of the design is implemented and installed to monitor an existing LV network. Data from the monitor is analyzed and presented. A portion of the LV network of the Electricity Company of Ghana is modeled in MATLAB-Simulink and analyzed under various earth fault conditions. The results presented show the ability of the PQM to detect and analyze PQ disturbance such as voltage sag and overvoltage. By adopting a placement methodology and installing these nodes, utilities are assured of accurate and reliable information with respect to the quality of power delivered to consumers.

Keywords: power quality, remote monitoring, distributed automation system, economic evaluation, LV network

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Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE

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Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.

Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network

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Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

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Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

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Authors: Zety Shakila Binti Mohd Yusof, Muhammad Adib Bin Ishak, Hajah Fatimah Binti Hussein

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The international shipping business is related to numerous controls or regulations of export and import shipments. It is costly and time consuming, and when something goes wrong or when the buyer or seller fails to comply with the regulations, it can result in penalties, delays, and unexpected costs etc. For the focus of this study, the researchers have selected a local forwarder that provides forwarding and clearance services, Nexus Zone Logistics. It was identified that this company currently has many extra costs to be paid including local and detention charges, which negatively impacts the flow of income and reduces overall stability. Two variables have been identified as factors of extra charges; loaded containers entering the port by exceeded closing time and late delivery of empty containers to the container yard. This study is a qualitative in nature and the secondary data collected was analyzed using self-administered observation. The findings of this study were covered by one selected case for each export and import shipment between July and December 2014. The data were analyzed using frequency analysis based on tables and graphs. The researcher recommends Nexus Zone Logistics impose a 1% deposit payment per container for each shipment (export and import) to its customers.

Keywords: international shipping, export and import, detention charges, container shipment

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Authors: Sun Zhe, Ruggero Micheletto

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As discussed extensively in many studies, noise in neural networks have an important role in the functioning and time evolution of the system. The mechanism by which noise induce stochastic resonance enhancing and influencing certain operations is not clarified nor is the mechanism of information storage and coding. With the present research we want to study the role of noise, especially focusing on the frequency peaks in a three variable Hindmarsh−Rose Small−World network. We investigated the behaviour of the network to external noises. We demonstrate that a variation of signal to noise ratio of about 10 dB induces an increase in membrane potential signal of about 15%, averaged over the whole network. We also considered the integral of the whole membrane potential as a paradigm of internal noise, the one generated by the brain network. We showed that this internal noise is attenuated with the size of the network or with the number of random connections. By means of Fourier analysis we found that it has distinct peaks of frequencies, moreover, we showed that increasing the size of the network introducing more neurons, reduced the maximum frequencies generated by the network, whereas the increase in the number of random connections (determined by the small-world probability p) led to a trend toward higher frequencies. This study may give clues on how networks utilize noise to alter the collective behaviour of the system in their operations.

Keywords: neural networks, stochastic processes, small-world networks, discrete Fourier analysis

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Authors: Atena Tazikeh Lemeski, Ismail Ozdamar

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This study presents a detailed analysis of harmonic distortion in a grid-connected photovoltaic (PV) system using real-time data captured from a solar power plant. Harmonics introduced by inverters in PV systems can degrade power quality and lead to increased Total Harmonic Distortion (THD), which poses challenges such as transformer overheating, increased power losses, and potential grid instability. This research addresses these issues by applying Fast Fourier Transform (FFT) to identify significant harmonic components and employing notch filters to target specific frequencies, particularly the 3rd harmonic (150 Hz), which was identified as the largest contributor to THD. Initial analysis of the unfiltered voltage signal revealed a THD of 21.15%, with prominent harmonic peaks at 150 Hz, 250 Hz and 350 Hz, corresponding to the 3rd, 5th, and 7th harmonics, respectively. After implementing the notch filters, the THD was reduced to 5.72%, demonstrating the effectiveness of this approach in mitigating harmonic distortion without affecting the fundamental frequency. This paper provides practical insights into the application of real-time filtering techniques in PV systems and their role in improving overall grid stability and power quality. The results indicate that targeted harmonic mitigation is crucial for the sustainable integration of renewable energy sources into modern electrical grids.

Keywords: grid-connected photovoltaic systems, fast Fourier transform, harmonic filtering, inverter-induced harmonics

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Authors: Parvin Mirmiran, Zahra Bahadoran, Nazanin Moslehi, Fereidoun Azizi

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Background and aim: We aimed to investigate the effects of green fruits and vegetables (green FV) consumption on the 3-year changes of cardiometabolic risk factors. Methods: This longitudinal study was conducted in the framework of Tehran Lipid and Glucose Study, between 2006-2008 and 2009-2011, on 1272 adults. Dietary intake of green FV, including green cabbage, broccoli, lettuce, celery, green beans, green peas, cucumber, leafy vegetables, zucchini, green chili and bell pepper, and kiwi fruit, has been assessed by a validated semi-quantitative food frequency questionnaire at baseline and second examination. Demographics, anthropometrics and biochemical measures were evaluated at baseline and 3 years later. The associations of cardiometabolic risk changes with mean intake of green FV were estimated. Results: The mean age of men and women at baseline was 39.8±12.7 and 37.3±12.1 years, respectively. Mean intake of green FV was 152±77 g/d. More intake from green FV was accompanied to more intake of vitamin A, α and β-carotene, lutein, β-criptoxanthine, potassium, magnesium and fiber. Consumption of green FV was inversely associated with 3-year change of waist circumference (β= -0.07, P=0.01), total cholesterol (β= -0.11, P=0.01) and triglycerides (β= -0.13, P=0.01). Each 25 g/d increase in consumption of green FV decreased the incidence of hyper-triglyceridemia by 12% (OR:0.88, 95%CI:0.71-0.99) in men. In women, no significant association was observed between consumption of green FV with cardiometabolic risk factors. Conclusion: Higher consumption of green FV could have preventive effects against abdominal fat gain and lipid disorders.

Keywords: cardiometabolic risk factors, abdominal obesity, lipid disorders, fruits, vegetables

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Authors: Bharat Kumar, Deepak Kumar, Vijay Chaudhry

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Zirconium alloys are widely used for the core components of a pressurized heavy water reactor (PHWR) or Canada deuterium (CANDU) reactor due to their low neutron absorption cross-section and excellent mechanical properties. The components made of Zirconium alloys are subjected to flow-induced vibrations, resulting in fretting wear at the interface of; pressure tubes and bearing pads, pressure tubes and calandria tubes, and calandria tubes and Liquid injection shutdown system (LISS) nozzles. There is a need to explore the tribological response under such conditions. Present work simulates the contact between calandria tube and LISS nozzle of PHWR/CANDU reactor as cylinder-on-cylinder contact configuration. Reciprocating tribo-tests were conducted on Zircaloy-4 (Zr-4) under the self-mated condition at varying amplitude, frequency, and sliding time. To understand the active wear mechanism, worn surfaces were analyzed using Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS). The change in amplitude severely affects the wear than other factors. The wear mechanism transits from adhesion to abrasion with increasing test amplitude. The dominant wear mechanisms are micro-cutting and micro-plowing followed by delamination in some areas. However, the coefficient of friction has indifferent behaviors.

Keywords: zircaloy-4, tribology, calandria tube, LISS nozzle, PHWR

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Authors: Noor Rizkiyah, Djoko Koestiono, Budi Setiawan, Nuhfil Hanani

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This research aims to identify the factors that affect the production of sugar cane, the level of technical efficiency of farming sugar cane ratooning and factors that affect technical inefficiency. Research carried out in Malang of East Java with sampling in a non random sampling stratified proportioned and obtained 172 household sugar cane farmers who are classified based on the level of ratooning i.e. ratooning I 3-4 times ratoning, ratooning II 5-10 times ratoning as well as ratooning III > 10 times ratoning. The method used is the Stochastic Production Frontier approach MLE (maximum likelihood estimation). From the results obtained by analysis of the factors affecting the production of sugar cane farming land, namely ratooning fertilizer use ZA petroganic, use of fertilizer and seeds of embroidery and labor. While the average level of sugar cane farmers ratooning efficiency of 0.78 and categorized yet efficient technically. For the factors that influence the technical inefficiency i.e. age, number of dependents and the frequency of family ratooning. Though not yet technically efficient but sugar cane farmers cultivate cultivation remains ratooning. But if it is done repeatedly ratooning will result in a decrease in the production of sugar cane. Whereas the results of the analysis of farming level of feasibility or RC ratooning sugar cane ratio of 1.15 so worth trying to accomplish. Thus with increased technology and combining the use of inputs is an attempt to let the technical efficiency can be achieved so that the more worthy to be organised.

Keywords: technical efficiency, production, sugarcane, frontier

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Authors: Oluwole Victor Falobi, Lawrence Olusola Ige

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The cardinal drawing force of this study is to examine the influence of audio-visual resources in teaching business subjects in selected secondary schools in IfakoIjaiye Local Government Area of Lagos State, Nigeria. A descriptive survey research design was employed for the study. By using a quantitative research approach and a sample size of 120 students were randomly selected from four public schools. Three research questions with one hypothesis guided the study. Data collected were analysed using frequency, the mean and standard deviation for the research questions, and Pearson Product Moment Correlation PPMC were used to analysed the inferential statistic. Findings from the study revealed that the Influence of audio-visual resources in teaching business subjects in selected secondary schools in IfakoIjaiye Local Government Area of Lagos State is low. It further revealed data the knowledge of teachers on the use of audio-visual resources is high in Ifako Local Government Area. It was recommended that government should create a timely monitoring system in other to check secondary school laboratories and classrooms to replace outdated facilities and also purchase needed facilities for effective teaching and learning to take place.

Keywords: audio-visual resources, business subjects, school, teaching

Procedia PDF Downloads 99

Authors: Mace Bentley, Zhuojun Duan, Tobias Gerken, Dudley Bonsal, Henry Way, Endre Szakal, Mia Pham, Hunter Donaldson, Chelsea Lang, Hayden Abbott, Leah Wilcynzski

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Air pollution has the potential to modify the lifespan and intensity of thunderstorms and the properties of lightning. Using data mining and geovisualization, we investigate how background climate and weather conditions shape variability in urban air pollution and how this, in turn, shapes thunderstorms as measured by the intensity, distribution, and frequency of cloud-to-ground lightning. A spatiotemporal analysis was conducted in order to identify thunderstorms using high-resolution lightning detection network data. Over seven million lightning flashes were used to identify more than 196,000 thunderstorms that occurred between 2006 - 2020 in the Washington, DC Metropolitan Region. Each lightning flash in the dataset was grouped into thunderstorm events by means of a temporal and spatial clustering algorithm. Once the thunderstorm event database was constructed, hourly wind direction, wind speed, and atmospheric thermodynamic data were added to the initiation and dissipation times and locations for the 196,000 identified thunderstorms. Hourly aerosol and air quality data for the thunderstorm initiation times and locations were also incorporated into the dataset. Developing thunderstorm climatologies using a lightning tracking algorithm and lightning detection network data was found to be useful for visualizing the spatial and temporal distribution of urban augmented thunderstorms in the region.

Keywords: lightning, urbanization, thunderstorms, climatology

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Authors: Chung-Hung Tsai, Ya-Ping Li

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Tourism industry is highly depended on the natural environment and climate. Compared to other industries, it is more susceptible to environment and climate. Taiwan belongs to a sea island country and located in the subtropical monsoon zone. The events of climate variability, frequency of typhoons and rainfalls raged are caused regularly serious disaster. In traditional disaster assessment, it usually focuses on the disaster damage and risk assessment, which is short of the features from different industries to understand the impact of the restoring force in post-disaster resilience and the main factors that constitute resilience. The object of this study is based on disaster recovery experience of tourism area and to understand the main factors affecting the tourist area of disaster resilience. The combinations of literature review and interviews with experts are prepared an early indicator system of the disaster resilience. Then, it is screened through a Fuzzy Delphi Method and Analytic Network Process for weight analysis. Finally, this study will establish the tourism disaster resilience evaluation index system considering the Taiwan's tourism industry characteristics. We hope that be able to enhance disaster resilience after tourist areas and increases the sustainability of industrial development. It is expected to provide government departments the tourism industry as the future owner of the assets in extreme climates responses.

Keywords: resilience, Fuzzy Delphi Method, Analytic Network Process, industrial development

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Authors: Abiodun Ezekiel Adesina, Ijeoma Ginikanwa Akubugwo

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Information and Communication Technology, ICT can heighten pre-service teachers’ attitudes toward learning and metacognitive learning; however, there is a dearth of literature on the perception of the pre-service teachers on heightening their attitude toward learning and metacognitive learning. Thus, this study investigates the perception of pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT. Two research questions and four hypotheses guided the research. A mixed methods research was adopted for the study in concurrent triangulation type of integrating qualitative and quantitative approaches to the study. The cluster random sampling technique was adopted to select 250 pre-service science teachers in Oyo township. Two self-constructed instruments: Heightening Pre-service Science Teachers’ Attitude towards Learning and Metacognitive Learning through Information and Communication Technology Scale (HPALMIS, r=.73), and an unstructured interview were used for data collection. Thematic analysis, frequency counts and percentages, t-tests, and analysis of variance were used for data analysis. The perception level of the pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT is above average, with the majority perceiving that ICT can enhance their thinking about their learning. The perception was significant (mean=92.68, SD=10.86, df=249, t=134.91, p<.05). The perception was significantly differentiated by gender (t=2.10, df= 248, p<.05) in favour of the female pre-service teachers and based on the first time of ICTs use (F(5,244)= 9.586, p<.05). Lecturers of science and science related courses should therefore imbibe the use of ICTs in heightening pre-service teachers’ attitude towards learning and metacognitive learning. Government should organize workshops, seminars, lectures, and symposia along with professional bodies for the science education lecturers to keep abreast of the trending ICT.

Keywords: pre-service teachers’ attitude towards learning, metacognitive learning, ICT, pre-service teachers’ perspectives

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Authors: Abdelfatah Elsenosy, Mahmoud Ebrahim

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Background: Distal radius fractures are commonly encountered in orthopedic practice, especially in elderly patients. A number of clinical papers have supported the idea that anatomic restoration of the distal end of the radius is essential to gain superior results. Aim and objectives: The aim of the study is to systematically review the literature for the management of distal end radius in elderly persons (conservative treatment versus percutaneous wire fixation) as regards radiological and functional outcomes. Subjects and methods: Studies were identified from the Medline, Cochrane, EMBASE, and Google Scholar databases were searched until 2019 using combinations of the following search terms: distal radius fracture, conservative treatment, non-operative treatment, and nonsurgical treatment, surgical treatment, operative, elderly, and older. Reference lists of relevant studies were manually searched. Results: There was no statistical significance difference between CI and PKF groups’ frequency of complication in all of the selected studies. Based on the results, we recommend more analysis regarding every parameter of the radiographic and functional results and specific complications related to each fixation need to be accomplished, which requires more Randomized controlled trials (RCTs) with high quality. Conclusion: Surgical treatment seems to be more effective distal radius fracture compared with conservative treatment when the radiographic outcomes were analyzed, and no significant differences were detected in the functional outcomes and complication rate.

Keywords: radius, fracture, surgical, RCTs, conservative, radiographic, outcomes, orthopedic

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Authors: Mohhamed El Habib Labdouni

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Introduction: Co-infection with VIH and tuberculosis poses one of the major ongoing challenges for global TB and AIDS prevention and control. The objective of this study is to raise the issue of the resurgence of TB, in People living with VIH supported in a referent center in western Algeria. Its epidemiological, clinical, biological and radiological new trends, and to compare the mortality rate between early and delayed ART. Methods: It was a prospective study, during 36 months from the 01st/01/2012 to 31st/12/2014, by identifying and analyzing cases of TB-VIH co-infection. Our population was devised in two groups/ early ART and delayed ART. The primary and secondary endpoints were analyzed with Kaplan-Meier curves and log-rank test the period of follow up, which was fixed at 300 weeks. Results: Sixty cases of co-infection TB -VIH were enrolled in our study: 78.3% had pulmonary tuberculosis associated with extra-pulmonary, 13.3% had only pulmonary tuberculosis and 08.3% presented strictly extra-pulmonary TB. The clinical particularity of this co-infection is the frequency of serious localization such us: pleural 23.3%, peritoneal 31.7%, and meningeal suffusion 13.3%.y-.biologicaly we notice the predominance both of pancytopenia and leucoanemia, hyponatremia in 38,6% and hypokalemia in 19,3%. By analyzing Kaplan-Meier survival curves, we notice that early ART initiation is associated with a significant reduction of all-cause mortality (p = 0,000), and we have identified several prognostic factors such as hypokalemia hyponatremia, leukocytosis thrombopenemia leucothrombopenia (p = 0,005). Conclusion: Our study confirms most of the results reported in the literature. Early ART initiation reduces the rate of all-cause mortality, despite the probability of the occurrence of TB-IRIS.

Keywords: TB-HIV co-infection, early ART, hyponatremia, extrapulmonary tuberculosis

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Authors: A. Sreedevi, G. Anantaramu

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The present space research organizations are striving towards the development of lighter, smaller, more efficient, low cost, and highly reliable power supply. Switch mode power supplies (SMPS) overcome the demerits of linear power supplies such as low efficiency, difficulties in thermal management, and in boosting the output voltage. Space applications require a constant DC voltage to supply its load. As the load varies, the battery terminal voltage tends to vary accordingly. To avoid this variation in the load terminal voltage, a DC-DC regulator is required. The conventional regulator for space applications is isolated boost topology. The proposed topology uses an interleaved push-pull converter with a current doubler secondary to reduce the EMI issues and increase efficiency. The proposed topology uses a floating technique where the converter derives power from the battery and generates only the voltage that is required to fill the gap between the bus and the battery voltage. The direct voltage sense and current loop provide tight regulation of output and better stability. Converter is designed with 50 kHz switching frequency using UC 1825 PWM controller employing both voltage and peak current mode control. Experimental tests have been carried out on the converter under different input and load conditions to validate the design. The experimental results showed that the efficiency was greater than 91%. Stability analysis is done using venable stability analyzer.

Keywords: push pull converter, current doubler, converter, PWM control

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Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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Authors: S. Mohamed, D. Gonzalez, C. Sayada, P. Halfon

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Drug resistance mutations are routinely detected using standard Sanger sequencing, which does not detect minor variants with a frequency below 20%. The impact of detecting minor variants generated by ultra-deep sequencing (UDS) on HIV drug-resistance (DR) interpretations has not yet been studied. Fifty HIV-1 patients who experienced virological failure were included in this retrospective study. The HIV-1 UDS protocol allowed the detection and quantification of HIV-1 protease and reverse transcriptase variants related to genotypes A, B, C, E, F, and G. DeepChek®-HIV simplified DR interpretation software was used to compare Sanger sequencing and UDS. The total time required for the UDS protocol was found to be approximately three times longer than Sanger sequencing with equivalent reagent costs. UDS detected all of the mutations found by population sequencing and identified additional resistance variants in all patients. An analysis of DR revealed a total of 643 and 224 clinically relevant mutations by UDS and Sanger sequencing, respectively. Three resistance mutations with > 20% prevalence were detected solely by UDS: A98S (23%), E138A (21%) and V179I (25%). A significant difference in the DR interpretations for 19 antiretroviral drugs was observed between the UDS and Sanger sequencing methods. Y181C and T215Y were the most frequent mutations associated with interpretation differences. A combination of UDS and DeepChek® software for the interpretation of DR results would help clinicians provide suitable treatments. A cut-off of 1% allowed a better characterisation of the viral population by identifying additional resistance mutations and improving the DR interpretation.

Keywords: HIV-1, ultra-deep sequencing, Sanger sequencing, drug resistance

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Authors: Lei Xue, Liye Zhao, Jundong Wang, Yu Xue

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A hybrid energy conversion system composed of a floating offshore wind turbine (FOWT) and wave energy converters (WECs) may possibly reduce the levelized cost of energy, improving the platform dynamics and increasing the capacity to harvest energy. This paper investigates the aerodynamic performance and dynamic responses of the combined semi-submersible FOWT and point-absorber WECs in frequency and time domains using synthetic optimizing control under turbulent wind and irregular wave conditions. Individual pitch control is applied to the FOWT part, while spring–damping control is used on the WECs part, as well as the synergistic control effect of both are studied. The effect of the above control optimization is analyzed under several typical working conditions, such as below-rated wind speed, rated wind speed, and above-rated wind speed by OpenFAST and WEC-Sim software. Particularly, the wind-wave misalignment is also comparatively investigated, which has demonstrated the importance of applying proper integrated optimal control in this hybrid energy system. More specifically, the combination of individual pitch control and spring–damping control is able to mitigate the platform pitch motion and improve output power. However, the increase in blade root load needs to be considered which needs further investigations in the future.

Keywords: floating offshore wind turbine, wave energy converters, control optimization, individual pitch control, dynamic response

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Authors: Richard S. Jatau, Kankanala Venkateswarlu, Bulus Kpame

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The purpose of this critical review is to find out what is known and what is unknown about the effects of aging on endurance performance, especially on ultra- triathlon performance. It has been shown that among master’s athlete’s peak levels of performance decreased by 50% by age 50 it has also been clearly revealed that age associated atrophy, weakness and fatigability cannot be halted, although year round athletic training can slow down this age associated decline. Studies have further revealed that 30% to 50% decrease in skeletal muscle mass between ages 40 and 80 years, which is accompanied by an equal or even greater decline in strength and power and an increase in muscle weakness and fatigability. Studies on ultra- triathlon athletes revealed that 30 to 39 year old showed fastest time, with athletes in younger and older age groups were slower. It appears that the length of the endurance performance appears to influence age related endurance performance decline in short distance triathlons. A significant decline seems to start at the age of 40 to 50 years, whereas in long distance triathlons this decline seems to start after the age of 65 years. However, it is not clear whether this decline is related in any way to the training methods used, the duration of training, or the frequency of training. It’s also not clear whether the triathlon athletes experience more injuries due to long hours of training. It’s also not clear whether these athletes used performance enhancing drugs to enhance their performance. It’s not also clear whiles there has been tremendous increase in the number of athletes specializing in triathlon. On the basis of our experience and available research evidence we have provided answers to some of these questions. We concluded that aging associated decline in ultra–endurance performance is inevitable although it can be slowed down.

Keywords: aging, triathlon, atrophy, endurance

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Leticia Souza Guirra, Márcia Eduarda Vieira Ramos, Edlaine Souza Pereira, Leticia Correa Celeste

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Introduction: Studies indicate that equine-assisted therapy enables improvements in several areas of functioning that are impaired in children with autism spectrum disorder (ASD), such as social interaction and communication. Objective: The study proposes to analyze the development of dialogic skills of a verbal child with ASD after participating in the equine-assisted therapy Step By Step in Communication. Method: This is quantitative and qualitative research through a case study. It refers to a 6 years old child diagnosed with ASD belonging to a group of practitioners of the Brazilian National Equine-Assited-Therapy Association. The Behavioral Observation Protocol (PROC) was used to evaluate communicative skills before and after the intervention, which consisted of 24 sessions once a week. Results: All conversational skills increased their frequency, with participation in dialogue and initiation of interaction. The child also increases the habit of waiting for his turn and answering the interlocutor. The emission of topics not related to conversation and echolalia showed a significant decrease after the intervention. Conclusion: The studied child showed improvement in communicative skills after participating in the equine-assisted therapy Step By Step in Communication. Contributions: This study contributes to a greater understanding of the impact of equine-assisted therapy on the communicative abilities of children with ASD.

Keywords: equine-assisted-therapy, autism spectrum disorder, language, communication, language and hearing sciences

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Sapan Tiwari, Namrata Ghosh

Abstract:

In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.

Keywords: crew scheduling, duty, optimization of cost, urban mass transit

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Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin

Abstract:

In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.

Keywords: cash flow optimization, payment plan, procurement management, subcontracting plan

Procedia PDF Downloads 132

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: K. Ö. Kartal, L. Maul, M. Hägele

Abstract:

With the development of new technologies come additional opportunities for the founding of companies and new markets to be created. The barriers to entry are lowered and technology makes old business models obsolete. Incumbent companies have to be adaptable to this quickly changing environment. They have to start the process of digital maturation and they have to be able to adapt quickly to new and drastic changes that might arise. One of the biggest barriers for organizations in order to do so is their culture. This paper shows the core elements of a corporate culture that supports the process of digital maturation in incumbent organizations. Furthermore, it is explored how ideation and innovation can be used in a strategy in order to facilitate these core elements of culture that promote digital maturity. Focus areas are identified for the design of ideation strategies, with the aim to make the facilitation and incitation process more effective, short to long term. Therefore, one in-depth case study is conducted with data collection from interviews, observation, document review and surveys. The findings indicate that digital maturity is connected to cultural shift and 11 relevant elements of digital culture are identified which have to be considered. Based on these 11 core elements, five focus areas that need to be regarded in the design of a strategy that uses ideation and innovation to facilitate the cultural shift are identified. These are: Focus topics, rewards and communication, structure and frequency, regions and new online formats.

Keywords: digital transformation, innovation management, ideation strategy, creativity culture, change

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Authors: Erjola Reufi, Thomas Beer

Abstract:

Plain, unreinforced concrete is a brittle material, with a low tensile strength, limited ductility and little resistance to cracking. In order to improve the inherent tensile strength of concrete there is a need of multi directional and closely spaced reinforcement, which can be provided in the form of randomly distributed fibers. Fiber reinforced concrete (FRC) is a composite material consisting of cement, sand, coarse aggregate, water and fibers. In this composite material, short discrete fibers are randomly distributed throughout the concrete mass. The behavioral efficiency of this composite material is far superior to that of plain concrete and many other construction materials of equal cost. The present experimental study considers the effect of steel fibers and polypropylene fiber on the modulus of elasticity of concrete. Hook end steel fibers of length 5 cm and 3 cm at volume fraction of 0.25%, 0.5% and 1.% were used. Also polypropylene fiber of length 12, 6, 3 mm at volume fraction 0.1, 0.25, and 0.4 % were used. Fifteen mixtures has been prepared to evaluate the effect of fiber on modulus of elasticity of concrete. Ultrasonic pulse velocity (UPV) and resonant frequency methods which are two non-destructive testing techniques have been used to measure the elastic properties of fiber reinforced concrete. This study found that ultrasonic wave propagation is the most reliable, easy and cost effective testing technique to use in the determination of the elastic properties of the FRC mix used in this study.

Keywords: fiber reinforced concrete(FRC), polypropylene fiber, resonance, ultrasonic pulse velocity, steel fiber

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Authors: Tessy Treesa Jose, Sripathy M. Bhat

Abstract:

Nursing is recognized as a stressful occupation and has indicated a probable high prevalence of distress. It is a helping profession requiring a high degree of commitment and involvement. If stress is intense, continuous and repeated, it becomes a negative phenomenon or "distress," which can lead to physical illness and psychological disorders. The frequency of common psychosomatic symptoms including sleeping problems, tension headache, chronic fatigue, palpitation etc. may be an indicator of nurses’ work-related stress level. Objectives of the study were to determine psychiatric morbidity among nurses and to find its association with selected variables. The study population consisted of 1040 registered nurses working in selected medical college hospitals and government hospitals of Udupi and Mangalore districts. Descriptive survey design was used to conduct the study. Subjects were selected by using purposive sampling. Data were gathered by administering background proforma and General Health questionnaire. Severe distress was experienced by 0.9% of nurses and 5.6% had some evidence of distress. Subjects who did not have any distress were 93.5%. No significant association between psychiatric morbidity in nurses and demographic variables was observed. With regard to work variables significant association is observed between psychiatric morbidity and total years of experience (z=10.67, p=0.03) and experience in current area of work (z=9.43, p=0.02).

Keywords: psychiatric morbidity, nurse, selected hospitals, working

Procedia PDF Downloads 291